From b79a3ecafed64f04681285644bff8825f834ea2b Mon Sep 17 00:00:00 2001 From: Carles Onielfa Date: Wed, 5 Aug 2026 09:35:08 +0200 Subject: [PATCH 1/6] Enable offline tests --- .../test_conditional_context.yaml | 48 +- .../test_conditional_fallback.yaml | 24 +- ...est_conditional_fallback_second_level.yaml | 24 +- .../test_conditional_static.yaml | 32 +- agents/conditional/tests/test_conditional.py | 2 +- .../test_external/test_external.yaml | 12 +- agents/external/tests/test_external.py | 2 +- agents/google/tests/test_google.py | 2 +- .../test_http_static_get.yaml | 12 +- agents/http/tests/test_http_static.py | 2 +- .../cassettes/test_mcp/test_mcp_client.yaml | 48 +- .../test_mcp/test_mcp_client_headers.yaml | 24 +- .../test_mcp/test_mcp_client_no_prompt.yaml | 24 +- .../test_mcp/test_mcp_client_prompt.yaml | 24 +- agents/mcp/tests/test_mcp.py | 2 +- .../test_nucliadb_agent_basic_ask.yaml | 36 +- .../test_nucliadb_agent_simple.yaml | 52 +- ...nt_simple_disable_ai_parameter_search.yaml | 72 +- agents/nucliadb/tests/test_nucliadb.py | 22 +- agents/nucliadb/tests/test_sync.py | 4 +- agents/perplexity/tests/test_perplexity.py | 2 +- .../tests/test_perplexity_search.py | 2 +- .../cassettes/test_remi/test_remi[full].yaml | 1069 ++++++++--------- .../test_remi/test_remi[partial_answers].yaml | 965 +++++++-------- .../test_remi_not_enough_data[full].yaml | 813 ++++++------- ...remi_not_enough_data[partial_answers].yaml | 801 ++++++------ agents/remi/tests/conftest.py | 20 + agents/remi/tests/test_remi.py | 13 +- .../test_rephrase/test_rephrase_agent.yaml | 92 +- .../test_rephrase_agent_only_rephrase.yaml | 52 +- agents/rephrase/tests/test_rephrase.py | 10 +- .../test_smart/test_smart[default].yaml | 80 +- .../test_smart/test_smart[gemini].yaml | 80 +- .../test_smart_calls_correct_agent.yaml | 40 +- .../test_smart/test_smart_parameters.yaml | 128 +- .../test_smart/test_smart_with_history.yaml | 40 +- .../test_smart_with_user_feedback.yaml | 40 +- agents/smart/tests/test_smart.py | 2 +- .../smart/tests/test_smart_mcp_perplexity.py | 2 +- .../test_summarize_answers.yaml | 148 +-- ...e_answers_force_chunk_level_citations.yaml | 76 +- ...test_summarize_answers_with_citations.yaml | 76 +- .../test_summarize_streaming.yaml | 60 +- .../test_summarize/test_summarize_tokens.yaml | 60 +- ...st_summarize_with_funny_system_prompt.yaml | 132 +- agents/summarize/tests/test_summarize.py | 10 +- hyperforge/src/hyperforge/fixtures.py | 38 +- .../tests/api/test_chat_history_workflow.py | 2 +- hyperforge/tests/context/test_validation.py | 2 +- hyperforge/tests/test_mcp_interaction.py | 4 +- hyperforge/tests/test_next.py | 4 +- 51 files changed, 2557 insertions(+), 2774 deletions(-) diff --git a/agents/conditional/tests/cassettes/test_conditional/test_conditional_context.yaml b/agents/conditional/tests/cassettes/test_conditional/test_conditional_context.yaml index 6458d0cb..78dbbd87 100644 --- a/agents/conditional/tests/cassettes/test_conditional/test_conditional_context.yaml +++ b/agents/conditional/tests/cassettes/test_conditional/test_conditional_context.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -102,7 +102,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -112,7 +112,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -197,7 +197,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -207,7 +207,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"rephrased_question":"","needed":false,"reason":"The @@ -275,7 +275,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -291,7 +291,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"yes":true,"reason":"The text explicitly @@ -396,7 +396,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -406,7 +406,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -487,7 +487,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -503,7 +503,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"You"}} @@ -669,13 +669,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -762,7 +762,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -772,7 +772,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -854,7 +854,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -864,7 +864,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"rephrased_question":"What are @@ -932,7 +932,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -948,7 +948,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"yes":false,"reason":"The provided @@ -1053,7 +1053,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -1063,7 +1063,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -1142,7 +1142,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1158,7 +1158,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"Good"}} diff --git a/agents/conditional/tests/cassettes/test_conditional/test_conditional_fallback.yaml b/agents/conditional/tests/cassettes/test_conditional/test_conditional_fallback.yaml index ce7ffd24..e84fbd66 100644 --- a/agents/conditional/tests/cassettes/test_conditional/test_conditional_fallback.yaml +++ b/agents/conditional/tests/cassettes/test_conditional/test_conditional_fallback.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -64,7 +64,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -80,7 +80,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"yes":false,"reason":"The given @@ -184,7 +184,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -194,7 +194,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context does not @@ -297,7 +297,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -307,7 +307,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context does not @@ -414,7 +414,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -424,7 +424,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -499,7 +499,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -515,7 +515,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"You"}} diff --git a/agents/conditional/tests/cassettes/test_conditional/test_conditional_fallback_second_level.yaml b/agents/conditional/tests/cassettes/test_conditional/test_conditional_fallback_second_level.yaml index 6ab2d034..9182e790 100644 --- a/agents/conditional/tests/cassettes/test_conditional/test_conditional_fallback_second_level.yaml +++ b/agents/conditional/tests/cassettes/test_conditional/test_conditional_fallback_second_level.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -64,7 +64,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -80,7 +80,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"yes":false,"reason":"The provided @@ -183,7 +183,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -193,7 +193,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context does not @@ -296,7 +296,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -306,7 +306,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context does not @@ -414,7 +414,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -424,7 +424,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -499,7 +499,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -515,7 +515,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"You"}} diff --git a/agents/conditional/tests/cassettes/test_conditional/test_conditional_static.yaml b/agents/conditional/tests/cassettes/test_conditional/test_conditional_static.yaml index 0f10de70..04f69b8f 100644 --- a/agents/conditional/tests/cassettes/test_conditional/test_conditional_static.yaml +++ b/agents/conditional/tests/cassettes/test_conditional/test_conditional_static.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -63,7 +63,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -79,7 +79,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"yes":true,"reason":"The text ''Who @@ -184,7 +184,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -194,7 +194,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -267,7 +267,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -283,7 +283,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"Atlas"}} @@ -377,13 +377,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -431,7 +431,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -447,7 +447,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"yes":false,"reason":"The provided @@ -551,7 +551,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -561,7 +561,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -634,7 +634,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -650,7 +650,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"RA"}} diff --git a/agents/conditional/tests/test_conditional.py b/agents/conditional/tests/test_conditional.py index 3bfb7654..5838a7a8 100644 --- a/agents/conditional/tests/test_conditional.py +++ b/agents/conditional/tests/test_conditional.py @@ -7,7 +7,7 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") CONFIG = { "drivers": [], diff --git a/agents/external/tests/cassettes/test_external/test_external.yaml b/agents/external/tests/cassettes/test_external/test_external.yaml index 62afdcd1..aa313984 100644 --- a/agents/external/tests/cassettes/test_external/test_external.yaml +++ b/agents/external/tests/cassettes/test_external/test_external.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -101,7 +101,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -111,7 +111,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"reason\":\"The context @@ -168,7 +168,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -184,7 +184,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"brand":""}}} diff --git a/agents/external/tests/test_external.py b/agents/external/tests/test_external.py index be0129dc..adbfdbf4 100644 --- a/agents/external/tests/test_external.py +++ b/agents/external/tests/test_external.py @@ -7,7 +7,7 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") CONFIG = { "drivers": [], diff --git a/agents/google/tests/test_google.py b/agents/google/tests/test_google.py index 724f8ad7..a7c7bd97 100644 --- a/agents/google/tests/test_google.py +++ b/agents/google/tests/test_google.py @@ -15,7 +15,7 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") pytestmark = [ pytest.mark.vcr( diff --git a/agents/http/tests/cassettes/test_http_static/test_http_static_get.yaml b/agents/http/tests/cassettes/test_http_static/test_http_static_get.yaml index cb330e05..441b2291 100644 --- a/agents/http/tests/cassettes/test_http_static/test_http_static_get.yaml +++ b/agents/http/tests/cassettes/test_http_static/test_http_static_get.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -104,7 +104,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -114,7 +114,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -193,7 +193,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -209,7 +209,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"The"}} diff --git a/agents/http/tests/test_http_static.py b/agents/http/tests/test_http_static.py index 853c7c81..78232159 100644 --- a/agents/http/tests/test_http_static.py +++ b/agents/http/tests/test_http_static.py @@ -8,7 +8,7 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") CONFIG = { "drivers": [], diff --git a/agents/mcp/tests/cassettes/test_mcp/test_mcp_client.yaml b/agents/mcp/tests/cassettes/test_mcp/test_mcp_client.yaml index c8b8522c..a56aa91f 100644 --- a/agents/mcp/tests/cassettes/test_mcp/test_mcp_client.yaml +++ b/agents/mcp/tests/cassettes/test_mcp/test_mcp_client.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -59,7 +59,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -75,7 +75,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"prompt_id":""}}} @@ -175,7 +175,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -191,7 +191,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"add":[{"function":{"name":"add","arguments":{"a":2,"b":2}}}]}}} @@ -295,7 +295,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -311,7 +311,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"task_complete":[{"function":{"name":"task_complete","arguments":{}}}]}}} @@ -412,7 +412,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -422,7 +422,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -492,7 +492,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -508,7 +508,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"2"}} @@ -572,13 +572,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -622,7 +622,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -638,7 +638,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"prompt_id":""}}} @@ -739,7 +739,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -755,7 +755,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"add":[{"function":{"name":"add","arguments":{"a":2,"b":2}}}],"divide":[{"function":{"name":"divide","arguments":{"a":6,"b":3}}}]}}} @@ -860,7 +860,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -876,7 +876,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"task_complete":[{"function":{"name":"task_complete","arguments":{}}}]}}} @@ -979,7 +979,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -989,7 +989,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -1061,7 +1061,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1077,7 +1077,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"2"}} diff --git a/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_headers.yaml b/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_headers.yaml index 72d7f861..7ccb73da 100644 --- a/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_headers.yaml +++ b/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_headers.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -59,7 +59,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -75,7 +75,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"prompt_id":"none"}}} @@ -171,7 +171,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -187,7 +187,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"add":[{"function":{"name":"add","arguments":{"a":2,"b":2}}}]}}} @@ -286,7 +286,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -302,7 +302,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"task_complete":[{"function":{"name":"task_complete","arguments":{}}}]}}} @@ -403,7 +403,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -413,7 +413,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -483,7 +483,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -499,7 +499,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"2"}} diff --git a/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_no_prompt.yaml b/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_no_prompt.yaml index c414a893..007cc4cb 100644 --- a/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_no_prompt.yaml +++ b/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_no_prompt.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -59,7 +59,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -75,7 +75,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"prompt_id":""}}} @@ -175,7 +175,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -191,7 +191,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"multiply":[{"function":{"name":"multiply","arguments":{"a":2,"b":5}}}]}}} @@ -295,7 +295,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -311,7 +311,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"task_complete":[{"function":{"name":"task_complete","arguments":{}}}]}}} @@ -413,7 +413,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -423,7 +423,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -494,7 +494,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -510,7 +510,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"The"}} diff --git a/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_prompt.yaml b/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_prompt.yaml index bcb977bb..8d515fa1 100644 --- a/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_prompt.yaml +++ b/agents/mcp/tests/cassettes/test_mcp/test_mcp_client_prompt.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -64,7 +64,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -80,7 +80,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"prompt_id":"multiplication_tool_advice"}}} @@ -185,7 +185,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -201,7 +201,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"multiply":[{"function":{"name":"multiply","arguments":{"a":2,"b":5}}}]}}} @@ -309,7 +309,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -325,7 +325,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"task_complete":[{"function":{"name":"task_complete","arguments":{}}}]}}} @@ -439,7 +439,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -449,7 +449,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -536,7 +536,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -552,7 +552,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"The"}} diff --git a/agents/mcp/tests/test_mcp.py b/agents/mcp/tests/test_mcp.py index 00406518..dcabd617 100644 --- a/agents/mcp/tests/test_mcp.py +++ b/agents/mcp/tests/test_mcp.py @@ -18,7 +18,7 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") pytestmark = [pytest.mark.vcr(ignore_localhost=True), pytest.mark.asyncio] diff --git a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml index 26812c1d..be8c430e 100644 --- a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml +++ b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml @@ -11,7 +11,7 @@ interactions: Content-Length: - '32' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -19,7 +19,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/n/i":986,"/n/i/application":1,"/n/i/application/json":1,"/n/i/text":985,"/n/i/text/markdown":985}}' @@ -53,7 +53,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -61,7 +61,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b response: body: string: '{"slug":"nuclia-docs","uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","config":{"uuid":null,"slug":"4f9285c7-7151-4431-94e6-3f1fb0d66aca:nuclia-docs","title":"Nuclia @@ -98,7 +98,7 @@ interactions: Content-Length: - '32' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -106,7 +106,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/s/p":986,"/s/p/ca":3,"/s/p/cy":1,"/s/p/da":1,"/s/p/en":967,"/s/p/eo":4,"/s/p/la":7,"/s/p/nb":1,"/s/p/tl":1,"/s/p/yo":1}}' @@ -140,7 +140,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -148,7 +148,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration response: body: string: '{"resource_labelers_models":null,"paragraph_labelers_models":null,"intent_models":null,"visual_labeling":"disabled","ner_model":"multilingual","relation_model":"base","anonymization_model":"disabled","semantic_model":"multilingual-2024-05-06","semantic_models":["multilingual-2024-05-06"],"default_semantic_model":"multilingual-2024-05-06","semantic_graph_node_models":[],"default_semantic_graph_node_model":null,"semantic_graph_edge_models":[],"default_semantic_graph_edge_model":null,"semantic_vector_similarity":"DOT","semantic_vector_size":1024,"semantic_matryoshka_dims":[],"semantic_threshold":0.4,"generative_model":"chatgpt-azure-4o","user_keys":{"openai":null,"azure_openai":null,"mistral":null,"palm":null,"anthropic":null,"claude3":null,"anthropic_vertex":null,"anthropic_bedrock":null,"azure_mistral":null,"hf_llm":null,"hf_embedding":null,"azure_aii":null,"openai_compat":null},"user_prompts":{"openai":null,"azure_openai":{"system":"You @@ -187,7 +187,7 @@ interactions: Content-Length: - '61' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -195,7 +195,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"007b445866574d7ca69891d388663cc6\":{\"id\":\"007b445866574d7ca69891d388663cc6\",\"slug\":\"docs-management-security-5-public-ips-md\",\"title\":\"docs @@ -326,7 +326,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -334,7 +334,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets response: body: string: '{"uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","labelsets":{"pmm":{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -372,7 +372,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -380,7 +380,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm response: body: string: '{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -420,7 +420,7 @@ interactions: Content-Length: - '18' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -428,7 +428,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs @@ -565,7 +565,7 @@ interactions: Content-Length: - '198' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -573,7 +573,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/ask + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/ask response: body: string: "{\"item\":{\"type\":\"answer\",\"text\":\"El\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" diff --git a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple.yaml b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple.yaml index d5d21bf3..b687babd 100644 --- a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple.yaml +++ b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple.yaml @@ -9,7 +9,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -17,7 +17,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b response: body: string: '{"slug":"nuclia-docs","uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","config":{"uuid":null,"slug":"4f9285c7-7151-4431-94e6-3f1fb0d66aca:nuclia-docs","title":"Nuclia @@ -54,7 +54,7 @@ interactions: Content-Length: - '32' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -62,7 +62,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/s/p":986,"/s/p/ca":3,"/s/p/cy":1,"/s/p/da":1,"/s/p/en":967,"/s/p/eo":4,"/s/p/la":7,"/s/p/nb":1,"/s/p/tl":1,"/s/p/yo":1}}' @@ -96,7 +96,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -104,7 +104,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets response: body: string: '{"uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","labelsets":{"pmm":{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -142,7 +142,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -150,7 +150,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration response: body: string: '{"resource_labelers_models":null,"paragraph_labelers_models":null,"intent_models":null,"visual_labeling":"disabled","ner_model":"multilingual","relation_model":"base","anonymization_model":"disabled","semantic_model":"multilingual-2024-05-06","semantic_models":["multilingual-2024-05-06"],"default_semantic_model":"multilingual-2024-05-06","semantic_graph_node_models":[],"default_semantic_graph_node_model":null,"semantic_graph_edge_models":[],"default_semantic_graph_edge_model":null,"semantic_vector_similarity":"DOT","semantic_vector_size":1024,"semantic_matryoshka_dims":[],"semantic_threshold":0.4,"generative_model":"chatgpt-azure-4o","user_keys":{"openai":null,"azure_openai":null,"mistral":null,"palm":null,"anthropic":null,"claude3":null,"anthropic_vertex":null,"anthropic_bedrock":null,"azure_mistral":null,"hf_llm":null,"hf_embedding":null,"azure_aii":null,"openai_compat":null},"user_prompts":{"openai":null,"azure_openai":{"system":"You @@ -189,7 +189,7 @@ interactions: Content-Length: - '32' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -197,7 +197,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/n/i":986,"/n/i/application":1,"/n/i/application/json":1,"/n/i/text":985,"/n/i/text/markdown":985}}' @@ -233,7 +233,7 @@ interactions: Content-Length: - '61' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -241,7 +241,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"007b445866574d7ca69891d388663cc6\":{\"id\":\"007b445866574d7ca69891d388663cc6\",\"slug\":\"docs-management-security-5-public-ips-md\",\"title\":\"docs @@ -372,7 +372,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -380,7 +380,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm response: body: string: '{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -420,7 +420,7 @@ interactions: Content-Length: - '18' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -428,7 +428,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs @@ -565,7 +565,7 @@ interactions: Content-Length: - '180' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -573,7 +573,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/predict/run-agents-text + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/predict/run-agents-text response: body: string: '{"results":[{"input_nuclia_tokens":0.0,"output_nuclia_tokens":0.0,"time":0.0001347064971923828,"payloads":[]}]}' @@ -613,7 +613,7 @@ interactions: Content-Length: - '361' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -621,7 +621,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: '{"resources":{},"relations":{"entities":{}},"query":"Esboniwch sut @@ -664,7 +664,7 @@ interactions: Content-Length: - '385' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -672,7 +672,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"6e8250e6b5264156988657a221fd5e94\":{\"id\":\"6e8250e6b5264156988657a221fd5e94\",\"slug\":\"docs-develop-js-sdk-namespaces-Ask-interfaces-ConsumptionAskResponseItem-md\",\"title\":\"docs @@ -2322,7 +2322,7 @@ interactions: Content-Length: - '361' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -2330,7 +2330,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: '{"resources":{},"relations":{"entities":{}},"query":"Esboniwch sut @@ -2386,13 +2386,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"4039d76b0fff4962900836ab3fdec9f7":{"id":"4039d76b0fff4962900836ab3fdec9f7","slug":"docs-rag-advanced-consumption-mdx","title":"docs diff --git a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple_disable_ai_parameter_search.yaml b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple_disable_ai_parameter_search.yaml index 1553c9b2..c1deb468 100644 --- a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple_disable_ai_parameter_search.yaml +++ b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple_disable_ai_parameter_search.yaml @@ -11,7 +11,7 @@ interactions: Content-Length: - '32' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -19,7 +19,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/n/i":986,"/n/i/application":1,"/n/i/application/json":1,"/n/i/text":985,"/n/i/text/markdown":985}}' @@ -53,7 +53,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -61,7 +61,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets response: body: string: '{"uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","labelsets":{"pmm":{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -101,7 +101,7 @@ interactions: Content-Length: - '32' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -109,7 +109,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/s/p":986,"/s/p/ca":3,"/s/p/cy":1,"/s/p/da":1,"/s/p/en":967,"/s/p/eo":4,"/s/p/la":7,"/s/p/nb":1,"/s/p/tl":1,"/s/p/yo":1}}' @@ -143,7 +143,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -151,7 +151,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b response: body: string: '{"slug":"nuclia-docs","uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","config":{"uuid":null,"slug":"4f9285c7-7151-4431-94e6-3f1fb0d66aca:nuclia-docs","title":"Nuclia @@ -186,7 +186,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -194,7 +194,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration response: body: string: '{"resource_labelers_models":null,"paragraph_labelers_models":null,"intent_models":null,"visual_labeling":"disabled","ner_model":"multilingual","relation_model":"base","anonymization_model":"disabled","semantic_model":"multilingual-2024-05-06","semantic_models":["multilingual-2024-05-06"],"default_semantic_model":"multilingual-2024-05-06","semantic_graph_node_models":[],"default_semantic_graph_node_model":null,"semantic_graph_edge_models":[],"default_semantic_graph_edge_model":null,"semantic_vector_similarity":"DOT","semantic_vector_size":1024,"semantic_matryoshka_dims":[],"semantic_threshold":0.4,"generative_model":"chatgpt-azure-4o","user_keys":{"openai":null,"azure_openai":null,"mistral":null,"palm":null,"anthropic":null,"claude3":null,"anthropic_vertex":null,"anthropic_bedrock":null,"azure_mistral":null,"hf_llm":null,"hf_embedding":null,"azure_aii":null,"openai_compat":null},"user_prompts":{"openai":null,"azure_openai":{"system":"You @@ -233,7 +233,7 @@ interactions: Content-Length: - '61' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -241,7 +241,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs @@ -372,7 +372,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -380,7 +380,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm response: body: string: '{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -420,7 +420,7 @@ interactions: Content-Length: - '18' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -428,7 +428,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs @@ -565,7 +565,7 @@ interactions: Content-Length: - '145' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -573,7 +573,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/predict/run-agents-text + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/predict/run-agents-text response: body: string: '{"results":[{"input_nuclia_tokens":0.0,"output_nuclia_tokens":0.0,"time":0.00010657310485839844,"payloads":[]}]}' @@ -613,7 +613,7 @@ interactions: Content-Length: - '347' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -621,7 +621,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: '{"resources":{},"relations":{"entities":{}},"query":"Esboniwch sut @@ -663,7 +663,7 @@ interactions: Content-Length: - '352' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -671,7 +671,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs @@ -2296,7 +2296,7 @@ interactions: Content-Length: - '347' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -2304,7 +2304,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: '{"resources":{},"relations":{"entities":{}},"query":"Esboniwch sut @@ -2360,13 +2360,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"f02da6c4bdf34596a89a8106f4b0ea9f":{"id":"f02da6c4bdf34596a89a8106f4b0ea9f","slug":"docs-develop-js-sdk-interfaces-PageToken-md","title":"docs @@ -2421,7 +2421,7 @@ interactions: Content-Length: - '145' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -2429,7 +2429,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/predict/run-agents-text + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/predict/run-agents-text response: body: string: '{"results":[{"input_nuclia_tokens":0.0,"output_nuclia_tokens":0.0,"time":0.0001285076141357422,"payloads":[]}]}' @@ -2469,7 +2469,7 @@ interactions: Content-Length: - '354' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -2477,7 +2477,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: '{"resources":{},"relations":{"entities":{}},"query":"Sut mae defnyddio''r @@ -2519,7 +2519,7 @@ interactions: Content-Length: - '352' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -2527,7 +2527,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"6e8250e6b5264156988657a221fd5e94\":{\"id\":\"6e8250e6b5264156988657a221fd5e94\",\"slug\":\"docs-develop-js-sdk-namespaces-Ask-interfaces-ConsumptionAskResponseItem-md\",\"title\":\"docs @@ -4149,7 +4149,7 @@ interactions: Content-Length: - '354' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -4157,7 +4157,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: '{"resources":{},"relations":{"entities":{}},"query":"Sut mae defnyddio''r @@ -4213,13 +4213,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"b14cf452a3434839a04c111f2ea4dc51":{"id":"b14cf452a3434839a04c111f2ea4dc51","slug":"docs-develop-js-sdk-enums-UsageType-md","title":"docs diff --git a/agents/nucliadb/tests/test_nucliadb.py b/agents/nucliadb/tests/test_nucliadb.py index eb9d4f95..4806d94f 100644 --- a/agents/nucliadb/tests/test_nucliadb.py +++ b/agents/nucliadb/tests/test_nucliadb.py @@ -28,17 +28,17 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") KB_DE48CFAA_3209_4041_BB64_8604AFF061FB = os.environ.get( "KB_DE48CFAA_3209_4041_BB64_8604AFF061FB" -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") KB_DF8B4C24_2807_4888_AD6C_AE97357A638B = os.environ.get( "KB_DF8B4C24_2807_4888_AD6C_AE97357A638B" -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") KB_F718BA84_2973_462F_9B15_F300BD260134 = os.environ.get( "KB_F718BA84_2973_462F_9B15_F300BD260134" -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") CONFIG = { @@ -61,8 +61,8 @@ "provider": "nucliadb", "identifier": "nuclia-docs", "config": { - "url": "https://europe-1.nuclia.cloud/api", - "manager": "https://europe-1.nuclia.cloud/api", + "url": "https://europe-1.dp.progress.cloud/api", + "manager": "https://europe-1.dp.progress.cloud/api", "kbid": "df8b4c24-2807-4888-ad6c-ae97357a638b", "key": KB_DF8B4C24_2807_4888_AD6C_AE97357A638B, "filters": [], @@ -74,8 +74,8 @@ "provider": "nucliadb", "identifier": "nuclia-web", "config": { - "url": "https://europe-1.nuclia.cloud/api", - "manager": "https://europe-1.nuclia.cloud/api", + "url": "https://europe-1.dp.progress.cloud/api", + "manager": "https://europe-1.dp.progress.cloud/api", "kbid": "f718ba84-2973-462f-9b15-f300bd260134", "key": KB_F718BA84_2973_462F_9B15_F300BD260134, "filters": [], @@ -137,8 +137,8 @@ "provider": "nucliadb", "identifier": "nuclia-docs", "config": { - "url": "https://europe-1.nuclia.cloud/api", - "manager": "https://europe-1.nuclia.cloud/api", + "url": "https://europe-1.dp.progress.cloud/api", + "manager": "https://europe-1.dp.progress.cloud/api", "kbid": "df8b4c24-2807-4888-ad6c-ae97357a638b", "key": KB_DF8B4C24_2807_4888_AD6C_AE97357A638B, "filters": [], @@ -442,7 +442,7 @@ def test_build_ask_request(): search_configuration="foobar", ) driver = NucliaDBConnection( - url="https://europe-1.nuclia.cloud/api", + url="https://europe-1.dp.progress.cloud/api", manager="foo", kbid="df8b4c24-2807-4888-ad6c-ae97357a638b", description="foo", diff --git a/agents/nucliadb/tests/test_sync.py b/agents/nucliadb/tests/test_sync.py index 225f5a23..334be20c 100644 --- a/agents/nucliadb/tests/test_sync.py +++ b/agents/nucliadb/tests/test_sync.py @@ -15,12 +15,12 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") KB_E103CAF3_F8CB_4161_A57C_AAD1192D0666 = os.environ.get( "KB_E103CAF3_F8CB_4161_A57C_AAD1192D0666" -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") pytestmark = [ pytest.mark.vcr(ignore_localhost=True, ignore_hosts=["europe-1.dp.progress.cloud"]), diff --git a/agents/perplexity/tests/test_perplexity.py b/agents/perplexity/tests/test_perplexity.py index 83d285b0..81250769 100644 --- a/agents/perplexity/tests/test_perplexity.py +++ b/agents/perplexity/tests/test_perplexity.py @@ -15,7 +15,7 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") PERPLEXITY_KEY = os.environ.get("PERPLEXITY_API_KEY", "DUMMY_PERPLEXITY_KEY") diff --git a/agents/perplexity_search/tests/test_perplexity_search.py b/agents/perplexity_search/tests/test_perplexity_search.py index 76bae8c7..2a5b51a2 100644 --- a/agents/perplexity_search/tests/test_perplexity_search.py +++ b/agents/perplexity_search/tests/test_perplexity_search.py @@ -15,7 +15,7 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") PERPLEXITY_KEY = os.environ.get("PERPLEXITY_API_KEY", "DUMMY_PERPLEXITY_KEY") diff --git a/agents/remi/tests/cassettes/test_remi/test_remi[full].yaml b/agents/remi/tests/cassettes/test_remi/test_remi[full].yaml index cbe09f5e..45a410ce 100644 --- a/agents/remi/tests/cassettes/test_remi/test_remi[full].yaml +++ b/agents/remi/tests/cassettes/test_remi/test_remi[full].yaml @@ -18,7 +18,7 @@ interactions: uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: - string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"7fe77405-a6de-43cf-ac27-ac09f80b66c6","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' + string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"da1740fa-ab3e-4971-b374-7bb31b5dd325","account_id":"39f5fa6e-680a-475e-a757-812597e86d06","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' headers: Alt-Svc: - h3=":443"; ma=2592000 @@ -27,11 +27,11 @@ interactions: content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:35 GMT + - Wed, 05 Aug 2026 07:25:13 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '5' + - '6' status: code: 200 message: OK @@ -45,7 +45,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -53,14 +53,14 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - 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string: '{"facets":{"/n/i":986,"/n/i/application":1,"/n/i/application/json":1,"/n/i/text":985,"/n/i/text/markdown":985}}' + string: '{"facets":{"/s/p":994,"/s/p/ca":4,"/s/p/cy":1,"/s/p/da":1,"/s/p/en":974,"/s/p/eo":4,"/s/p/la":7,"/s/p/nb":1,"/s/p/tl":1,"/s/p/yo":1}}' headers: Alt-Svc: - h3=":443"; ma=2592000 Content-Length: - - '111' + - '133' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:36 GMT + - Wed, 05 Aug 2026 07:25:13 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '24' + - '19' x-nuclia-trace-id: - - 51b32ce0d6e2ec6275b9032c3d841a51 + - d8c236ce79ff2ac19c1c3efd14536dc8 status: code: 200 message: OK - request: - body: '{"prefixes": [{"prefix": "/s/p"}]}' + body: '' headers: Accept: - '*/*' @@ -177,38 +131,40 @@ interactions: - gzip, deflate Connection: - keep-alive - Content-Length: - - '32' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: - application/json x-stf-serviceaccount: - DUMMY - method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + method: GET + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets response: body: - string: '{"facets":{"/s/p":986,"/s/p/ca":3,"/s/p/cy":1,"/s/p/da":1,"/s/p/en":967,"/s/p/eo":4,"/s/p/la":7,"/s/p/nb":1,"/s/p/tl":1,"/s/p/yo":1}}' + string: '{"uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","labelsets":{"pmm":{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner + Content","related":"","text":"","uri":""},{"title":"Softcat","related":"","text":"","uri":""},{"title":"Sales + Enablement Assets","related":"","text":"","uri":""},{"title":"KO 26","related":"","text":"","uri":""},{"title":"Data + Sheets","related":"","text":"","uri":""},{"title":"Progress Agentic RAG Training + Materials 2026","related":"","text":"","uri":""}]}}}' headers: Alt-Svc: - 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Allowlist these if you restrict inbound traffic to your infrastructure. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n :::note \\n The current list of IP addresses is also available in machine-readable - format: JSON | YAML. These lists may change over time, so we recommend periodically - fetching and applying updates to your firewall rules to ensure uninterrupted - service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall - restricts network traffic, you may need to allowlist the following IP addresses. - They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | - --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 - | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 - | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- - | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n - | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 - | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | - 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 - | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 - | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United - States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- - | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 - | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS - PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately - through an AWS endpoint service (AWS PrivateLink) instead of over the public - internet, allowing connections to be established from your VPC without traversing - public IP addresses. This option is not available through self-service configuration. - Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests - on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent - \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful - tool that enhances the capabilities of traditional retrieval-augmented generation - (RAG) systems. Regular RAG's fixed search-then-generate process is limiting - for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Different models can be chosen for different tasks: \\n \\n Context validation - happens when the Prune context option is enabled (recommended), we recommend - using a fast model - planning or the execution model (depending on the planning - mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Note: the rephrasing model is only used in more complex workflow, it can - be ignored in the present case. \\n Finally, add a Summarize agent in the - Generation step to generate a final answer from the retrieved information. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - The Smart Agent plans the answer: picks the most appropriate sources, splits - the question into sub-questions, evaluates relevancy, and iterates autonomously - until the information is sufficient. \\n Basic usage \\n To set up a Smart - Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, - etc.) in the Sources section of the left menu. Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. It will be slower but more accurate when processing - complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Also select the proper function for each registered agent, depending on the - type of source (MCP agents will not need one, the functions are provided dynamically - by the MCP server). \\n In the Smart Agent configuration, you can select the - planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - In the Summarize Agent, enable the Conversational mode. This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. You can embed it in - your website or application, and it will provide a chat user interface for - interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Go to the Widgets section in the left menu, and click on Create widget to - create a new widget. You can customize its appearance, and then copy the generated - code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" + string: "{\"resources\":{\"7c9e318a8fcc4c9485b8639fdbe93b38\":{\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"slug\":\"docs-develop-nua-md\",\"title\":\"docs + > develop > nua\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-29T07:32:38.792855\",\"modified\":\"2026-07-29T07:32:38.792869\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Processing \\n Push a file \\n Processing data works in 2 steps: \\n + \\n First you will upload the file with /processing/upload, which returns + an upload token. \\n Then you will put this token in the processing queue + with /processing/push so the file is processed. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1627,\"end\":1890},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + json \\n { \\n webhook_config : { \\n uri : http://some.where/my-custom-webhook + , \\n headers : { \\n api-key : xxxxxxxxxx \\n } \\n } \\n } \\n Also, you + can choose to use a fixed uri on your token, and provide the headers in the + /push calls. In this case you don't need to provide the uri parameter. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":23,\"start\":9053,\"end\":9339},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Get a NUA key \\n In order to use the Nuclia Understanding API (NUA), you + first need to generate an API key. \\n There are two options to create an + API key: \\n \\n Using the Agentic RAG dashboard top-right menu: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":496,\"end\":703},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Note: If you have a Knowledge Box and want to use the predict endpoints, they + are proxied through the /api/v1/kb//predict endpoint. You will need to provide + a KB's regular authentication, a NUA API key will not be necessary.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":28,\"start\":10377,\"end\":10603},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The payload received from /requests is based on the fdbwriter.BrokerMessage + provided by writer.proto. \\n Streamed results \\n The /processing/requests//results + endpoint is similar but it returns directly the decoded results as a stream. + You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":18,\"start\":7453,\"end\":7716},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Processing happens asynchronously, so you will need to regularly check the + queue output using one of the two endpoints available to retrieve the results. + \\n Protobuffer results \\n The /processing/requests/ endpoint returns a protobuffer + payload with the processing results. You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":12,\"start\":5098,\"end\":5399},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: nua \\n title: Nuclia Understanding API \\n \\n Using the Nuclia Understanding + API \\n The Nuclia Understanding API (NUA) allows you to process data outside + of a Knowledge Box. It is a set of endpoints that allow you to send data to + the Progress Agentic RAG platform for processing, or to make calls to models + to generate text, summaries, or other outputs. The information is stored temporarily + for the duration of the processing, nothing remains in the ProgressAgentic + RAG cloud infrastructure. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":496},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests/' \\\\ + \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n The response is a JSON object containing + completed indicating if the processing is complete or not, and in case it + is,a response string. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":13,\"start\":5399,\"end\":5644},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n In Python, you can use nucliadb_protos to decode the results: \\n + ```python \\n import base64 \\n import requests \\n from nucliadb_protos.writer_pb2 + import BrokerMessage \\n processing_id = THE_PROCESSING_ID_YOU_RECEIVED_FROM_PUSH + \\n res = requests.get(f'https://europe-1.nuclia.cloud/api/v1/processing/requests/{processing_id}',headers={ + \\n X-NUCLIA-NUAKEY : Bearer YOUR_NUA_KEY , \\n }).json() \\n if payload in + res: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":16,\"start\":6812,\"end\":7224},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/push' \\\\ \\n + -X POST \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\\\ \\n -H 'Content-Type: + application/json' \\\\ \\n --data-raw '{ filefield :{ my_file_1 : eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.W8wfVj04aYicREYXRatCTb8F8-PD4Ph7MmiTliHi6DI + }}' \\n Push text \\n Instead of uploading a file and then pushing it to the + queue, you can also push some text directly to the queue. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":9,\"start\":2730,\"end\":3646},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + It may also be used to create (or delete) Knowledge Boxes via the API \u2013 + for example, if you need to automate Knowledge Box creation. In that case + you will need to select the Allow management of Knowledge Boxes checkbox during + the NUA key creation. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1170,\"end\":1420},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + /predict/rerank reranks a list of results to improve the relevance of the + top results. \\n /predict/sentence computes the embedding of a sentence. \\n + /predict/summarize summarizes a text. \\n \\n The calls must provides the + X-NUCLIA-NUAKEY header with your NUA key: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":26,\"start\":9847,\"end\":10108},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests//results' + \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n Moreover the data_types parameter + allows you to filter the results by data type. For example: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":19,\"start\":7716,\"end\":7926},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Here is a typical example: \\n shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/upload' + \\\\ \\n -X POST \\\\ \\n -H X-NUCLIA-NUAKEY: Bearer \\\\ \\n -H 'content-type: + ' \\\\ \\n -T /path/to/file \\n Will return something like: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":1890,\"end\":2109},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + :::note \\n If an error occurs when posting the result to the webhook URL, + the result is stored in the queue and can be retrieved by calling the /pull + endpoint (see previous section). The error message is appended to the result. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":24,\"start\":9339,\"end\":9568},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + pb = BrokerMessage() \\n pb.ParseFromString( \\n base64.b64decode(res[ payload + ]) \\n ) \\n print(pb) \\n else: \\n print('No payload') \\n ``` \\n For other + languages, Nuclia protobuffer models can be found on the NucliaDB GitHub repository. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":17,\"start\":7224,\"end\":7453},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Model calls \\n The predict endpoints offer various services: \\n + \\n /predict/chat makes a direct call to an LLM. \\n /predict/remi calls the + REMi model to measure the quality of a RAG response. \\n /predict/rephrase + rephrases a question to make it more suitable for a RAG query. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":25,\"start\":9568,\"end\":9847},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJ1cm46cHJveHkiLCJzdWIiOiJmaWxlIiwiYXVkIjoidXJuOnByb3h5IiwiZXhwIjoxNjU1ODkyMDgwLCJpYXQiOjE2NTU4ODg0ODAsImp0aSI6ImFmN2ZmYjU1ZjAxMjRlMzM5MmRjMDY5MmM2NWI5NzY3Iiwic2l6ZSI6ODk3LCJidWNrZXRfbmFtZSI6ImV1cm9wZS0xLXN0b3JhZ2UtcHJveHkiLCJ1cmkiOiIwZDg2YTFmYTcxN2Q0NDUxYTAwM2Q1NGIyNzM2YTA0ZSIsImRyaXZlciI6MCwiY29udGVudF90eXBlIjoiYXBwbGljYXRpb24vb2N0ZXQtc3RyZWFtIiwiZmlsZW5hbWUiOiIiLCJwYXNzd29yZCI6bnVsbCwibGFuZ3VhZ2UiOm51bGwsInNvdXJjZSI6MCwibWQ1IjpudWxsfQ.VItLa_fUen2Pt5W2440Bjwc7Zx64rv6mJnRMFIdao5o + \\n That is your upload token. Now you can push this token to the processing + queue with: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2109,\"end\":2730},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also at any level, if an attribute exceeds a certain size, it will be put + in a downloadable file and will be replaced in the document by a file pointer. + This will consist of { file : { uri : JWT_TOKEN }}. The rule is that if the + size of the message is greater than 1000000 characters, the biggest parts + will be moved to downloadable files. First, the compression process will target + vectors. If that is not enough, it will target large field metadata, and finally + it will target extracted text. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":15,\"start\":6315,\"end\":6812},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In this case, any time a new result is available Nuclia will post it (i.e. + make an actual POST call) to this URL, sending the protobuffer result as payload. + \\n To use a webhook, you will need to fill in the Webhook URL field in the + NUA key creation form when you create your key. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":21,\"start\":8236,\"end\":8517},\"fuzzy_result\":false}],\"facets\":{},\"query\":\"\",\"total\":5358,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - 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Allowlist these if you restrict inbound traffic to your infrastructure. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n :::note \\n The current list of IP addresses is also available in machine-readable - format: JSON | YAML. These lists may change over time, so we recommend periodically - fetching and applying updates to your firewall rules to ensure uninterrupted - service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall - restricts network traffic, you may need to allowlist the following IP addresses. - They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | - --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 - | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 - | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- - | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n - | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 - | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | - 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 - | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 - | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United - States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- - | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 - | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS - PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately - through an AWS endpoint service (AWS PrivateLink) instead of over the public - internet, allowing connections to be established from your VPC without traversing - public IP addresses. This option is not available through self-service configuration. - Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests - on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent - \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful - tool that enhances the capabilities of traditional retrieval-augmented generation - (RAG) systems. Regular RAG's fixed search-then-generate process is limiting - for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Different models can be chosen for different tasks: \\n \\n Context validation - happens when the Prune context option is enabled (recommended), we recommend - using a fast model - planning or the execution model (depending on the planning - mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Note: the rephrasing model is only used in more complex workflow, it can - be ignored in the present case. \\n Finally, add a Summarize agent in the - Generation step to generate a final answer from the retrieved information. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - The Smart Agent plans the answer: picks the most appropriate sources, splits - the question into sub-questions, evaluates relevancy, and iterates autonomously - until the information is sufficient. \\n Basic usage \\n To set up a Smart - Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, - etc.) in the Sources section of the left menu. Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. 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This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. You can embed it in - your website or application, and it will provide a chat user interface for - interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Go to the Widgets section in the left menu, and click on Create widget to - create a new widget. You can customize its appearance, and then copy the generated - code snippet to embed it in your website or application. 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+ string: "{\"resources\":{\"09305118c7314e1483068fb9a588578f\":{\"id\":\"09305118c7314e1483068fb9a588578f\",\"slug\":\"docs-develop-js-sdk-interfaces-KeyValueRangeFilter-md\",\"title\":\"docs + > develop > js sdk > interfaces > KeyValueRangeFilter\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-17T09:12:59.683605\",\"modified\":\"2026-08-03T13:15:39.704705\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"7c9e318a8fcc4c9485b8639fdbe93b38\":{\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"slug\":\"docs-develop-nua-md\",\"title\":\"docs + > develop > 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file_storage\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-16T08:13:35.152238\",\"modified\":\"2026-07-16T08:13:35.152248\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"b5eec709afcf4068a4211a16f1a79576\":{\"id\":\"b5eec709afcf4068a4211a16f1a79576\",\"slug\":\"docs-develop-js-sdk-type-aliases-KeyValueFilterExpression-md\",\"title\":\"docs + > develop > js sdk > type aliases > KeyValueFilterExpression\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-17T09:16:41.330227\",\"modified\":\"2026-08-03T13:19:49.747344\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"5c4166eea30d4b329fb3f141e395781a\":{\"id\":\"5c4166eea30d4b329fb3f141e395781a\",\"slug\":\"docs-develop-js-sdk-interfaces-KeyValueContainsFilter-md\",\"title\":\"docs + > develop > js sdk > interfaces > KeyValueContainsFilter\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"fr\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-17T09:13:32.136172\",\"modified\":\"2026-08-03T13:14:39.313725\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"14b3bd967e2b44ba98372a8d9a0716b6\":{\"id\":\"14b3bd967e2b44ba98372a8d9a0716b6\",\"slug\":\"docs-develop-js-sdk-interfaces-NUAClientEditPayload-md\",\"title\":\"docs + > develop > js sdk > interfaces > NUAClientEditPayload\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"eo\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-28T13:27:28.455426\",\"modified\":\"2026-08-03T13:14:53.788626\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"831a4c9bcc2e49d6a1f2a84c811f4fb6\":{\"id\":\"831a4c9bcc2e49d6a1f2a84c811f4fb6\",\"slug\":\"docs-management-nucliadb-deploy-01-basics-md\",\"title\":\"docs + > management > nucliadb > deploy > 01 basics\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-16T08:13:36.319511\",\"modified\":\"2026-07-16T08:13:36.319522\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"9ae2d3a90d0d452db50f170c535905d4\":{\"id\":\"9ae2d3a90d0d452db50f170c535905d4\",\"slug\":\"docs-develop-js-sdk-interfaces-KeyValueEqualFilter-md\",\"title\":\"docs + > develop > js sdk > interfaces > KeyValueEqualFilter\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-17T09:11:44.148330\",\"modified\":\"2026-08-03T13:16:53.789716\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"d97695fece7948c59cb9b95404b3a5f9\":{\"id\":\"d97695fece7948c59cb9b95404b3a5f9\",\"slug\":\"docs-management-nucliadb-deploy-05-access-md\",\"title\":\"docs + > management > nucliadb > deploy > 05 access\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-16T08:13:36.926639\",\"modified\":\"2026-07-16T08:13:36.926650\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"78943baafe6a49848b4b29e683eaa983\":{\"id\":\"78943baafe6a49848b4b29e683eaa983\",\"slug\":\"docs-develop-js-sdk-interfaces-NUAClientResponse-md\",\"title\":\"docs + > develop > js sdk > interfaces > NUAClientResponse\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"ca\",\"languages\":[\"eo\",\"ca\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-28T13:26:37.201678\",\"modified\":\"2026-08-03T13:16:09.581726\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Processing \\n Push a file \\n Processing data works in 2 steps: \\n + \\n First you will upload the file with /processing/upload, which returns + an upload token. \\n Then you will put this token in the processing queue + with /processing/push so the file is processed. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1627,\"end\":1890},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + json \\n { \\n webhook_config : { \\n uri : http://some.where/my-custom-webhook + , \\n headers : { \\n api-key : xxxxxxxxxx \\n } \\n } \\n } \\n Also, you + can choose to use a fixed uri on your token, and provide the headers in the + /push calls. In this case you don't need to provide the uri parameter. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":23,\"start\":9053,\"end\":9339},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Get a NUA key \\n In order to use the Nuclia Understanding API (NUA), you + first need to generate an API key. \\n There are two options to create an + API key: \\n \\n Using the Agentic RAG dashboard top-right menu: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":496,\"end\":703},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Note: If you have a Knowledge Box and want to use the predict endpoints, they + are proxied through the /api/v1/kb//predict endpoint. You will need to provide + a KB's regular authentication, a NUA API key will not be necessary.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":28,\"start\":10377,\"end\":10603},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The payload received from /requests is based on the fdbwriter.BrokerMessage + provided by writer.proto. \\n Streamed results \\n The /processing/requests//results + endpoint is similar but it returns directly the decoded results as a stream. + You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":18,\"start\":7453,\"end\":7716},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Processing happens asynchronously, so you will need to regularly check the + queue output using one of the two endpoints available to retrieve the results. + \\n Protobuffer results \\n The /processing/requests/ endpoint returns a protobuffer + payload with the processing results. You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":12,\"start\":5098,\"end\":5399},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: nua \\n title: Nuclia Understanding API \\n \\n Using the Nuclia Understanding + API \\n The Nuclia Understanding API (NUA) allows you to process data outside + of a Knowledge Box. It is a set of endpoints that allow you to send data to + the Progress Agentic RAG platform for processing, or to make calls to models + to generate text, summaries, or other outputs. The information is stored temporarily + for the duration of the processing, nothing remains in the ProgressAgentic + RAG cloud infrastructure. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":496},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests/' \\\\ + \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n The response is a JSON object containing + completed indicating if the processing is complete or not, and in case it + is,a response string. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":13,\"start\":5399,\"end\":5644},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n In Python, you can use nucliadb_protos to decode the results: \\n + ```python \\n import base64 \\n import requests \\n from nucliadb_protos.writer_pb2 + import BrokerMessage \\n processing_id = THE_PROCESSING_ID_YOU_RECEIVED_FROM_PUSH + \\n res = requests.get(f'https://europe-1.nuclia.cloud/api/v1/processing/requests/{processing_id}',headers={ + \\n X-NUCLIA-NUAKEY : Bearer YOUR_NUA_KEY , \\n }).json() \\n if payload in + res: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":16,\"start\":6812,\"end\":7224},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/push' \\\\ \\n + -X POST \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\\\ \\n -H 'Content-Type: + application/json' \\\\ \\n --data-raw '{ filefield :{ my_file_1 : eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.W8wfVj04aYicREYXRatCTb8F8-PD4Ph7MmiTliHi6DI + }}' \\n Push text \\n Instead of uploading a file and then pushing it to the + queue, you can also push some text directly to the queue. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":9,\"start\":2730,\"end\":3646},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + It may also be used to create (or delete) Knowledge Boxes via the API \u2013 + for example, if you need to automate Knowledge Box creation. In that case + you will need to select the Allow management of Knowledge Boxes checkbox during + the NUA key creation. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1170,\"end\":1420},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + /predict/rerank reranks a list of results to improve the relevance of the + top results. \\n /predict/sentence computes the embedding of a sentence. \\n + /predict/summarize summarizes a text. \\n \\n The calls must provides the + X-NUCLIA-NUAKEY header with your NUA key: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":26,\"start\":9847,\"end\":10108},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests//results' + \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n Moreover the data_types parameter + allows you to filter the results by data type. For example: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":19,\"start\":7716,\"end\":7926},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Here is a typical example: \\n shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/upload' + \\\\ \\n -X POST \\\\ \\n -H X-NUCLIA-NUAKEY: Bearer \\\\ \\n -H 'content-type: + ' \\\\ \\n -T /path/to/file \\n Will return something like: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":1890,\"end\":2109},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + :::note \\n If an error occurs when posting the result to the webhook URL, + the result is stored in the queue and can be retrieved by calling the /pull + endpoint (see previous section). The error message is appended to the result. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":24,\"start\":9339,\"end\":9568},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + pb = BrokerMessage() \\n pb.ParseFromString( \\n base64.b64decode(res[ payload + ]) \\n ) \\n print(pb) \\n else: \\n print('No payload') \\n ``` \\n For other + languages, Nuclia protobuffer models can be found on the NucliaDB GitHub repository. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":17,\"start\":7224,\"end\":7453},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Model calls \\n The predict endpoints offer various services: \\n + \\n /predict/chat makes a direct call to an LLM. \\n /predict/remi calls the + REMi model to measure the quality of a RAG response. \\n /predict/rephrase + rephrases a question to make it more suitable for a RAG query. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":25,\"start\":9568,\"end\":9847},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJ1cm46cHJveHkiLCJzdWIiOiJmaWxlIiwiYXVkIjoidXJuOnByb3h5IiwiZXhwIjoxNjU1ODkyMDgwLCJpYXQiOjE2NTU4ODg0ODAsImp0aSI6ImFmN2ZmYjU1ZjAxMjRlMzM5MmRjMDY5MmM2NWI5NzY3Iiwic2l6ZSI6ODk3LCJidWNrZXRfbmFtZSI6ImV1cm9wZS0xLXN0b3JhZ2UtcHJveHkiLCJ1cmkiOiIwZDg2YTFmYTcxN2Q0NDUxYTAwM2Q1NGIyNzM2YTA0ZSIsImRyaXZlciI6MCwiY29udGVudF90eXBlIjoiYXBwbGljYXRpb24vb2N0ZXQtc3RyZWFtIiwiZmlsZW5hbWUiOiIiLCJwYXNzd29yZCI6bnVsbCwibGFuZ3VhZ2UiOm51bGwsInNvdXJjZSI6MCwibWQ1IjpudWxsfQ.VItLa_fUen2Pt5W2440Bjwc7Zx64rv6mJnRMFIdao5o + \\n That is your upload token. Now you can push this token to the processing + queue with: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2109,\"end\":2730},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also at any level, if an attribute exceeds a certain size, it will be put + in a downloadable file and will be replaced in the document by a file pointer. + This will consist of { file : { uri : JWT_TOKEN }}. The rule is that if the + size of the message is greater than 1000000 characters, the biggest parts + will be moved to downloadable files. First, the compression process will target + vectors. If that is not enough, it will target large field metadata, and finally + it will target extracted text. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":15,\"start\":6315,\"end\":6812},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In this case, any time a new result is available Nuclia will post it (i.e. + make an actual POST call) to this URL, sending the protobuffer result as payload. + \\n To use a webhook, you will need to fill in the Webhook URL field in the + NUA key creation form when you create your key. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":21,\"start\":8236,\"end\":8517},\"fuzzy_result\":false}],\"facets\":{\"/k\":{\"/k/text\":5358}},\"query\":\"\",\"total\":5358,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"fulltext\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"14b3bd967e2b44ba98372a8d9a0716b6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"14b3bd967e2b44ba98372a8d9a0716b6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"78943baafe6a49848b4b29e683eaa983\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"78943baafe6a49848b4b29e683eaa983\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b5eec709afcf4068a4211a16f1a79576\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b5eec709afcf4068a4211a16f1a79576\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5c4166eea30d4b329fb3f141e395781a\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5c4166eea30d4b329fb3f141e395781a\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"09305118c7314e1483068fb9a588578f\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"09305118c7314e1483068fb9a588578f\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"9ae2d3a90d0d452db50f170c535905d4\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"9ae2d3a90d0d452db50f170c535905d4\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"831a4c9bcc2e49d6a1f2a84c811f4fb6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"831a4c9bcc2e49d6a1f2a84c811f4fb6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"d97695fece7948c59cb9b95404b3a5f9\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"d97695fece7948c59cb9b95404b3a5f9\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5ae74950b55c4d60b754fa706314b24a\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5ae74950b55c4d60b754fa706314b24a\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]}],\"facets\":{},\"query\":\"\",\"total\":2029,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - - '16898' + - '19708' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:37 GMT + - Wed, 05 Aug 2026 07:25:13 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '55' + - '70' x-nuclia-trace-id: - - 1c1c1b07f9b633fad8eedd1295e01a45 + - fc471b66d4811ab86036e0029d70055c status: code: 200 message: OK @@ -600,7 +537,7 @@ interactions: Content-Length: - '114' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -608,7 +545,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/ask + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/ask response: body: string: "{\"item\":{\"type\":\"answer\",\"text\":\"Progress\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" @@ -616,150 +553,150 @@ interactions: R\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\"AG\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" is\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" an\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" API\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" that\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - indexes\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - processes\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" various\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - types\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" of\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\",\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + enhances\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" applications\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + with\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" powerful\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + search\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" capabilities\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + by\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" indexing\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" processing\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + various\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" types\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + of\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\",\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" including\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" audio\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" video\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - files\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\",\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - to\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" enhance\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - applications\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" with\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - advanced\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" search\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - capabilities\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + files\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" It\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" utilizes\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" natural\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" language\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" processing\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" machine\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" learning\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" to\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" understand\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - user\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" intent\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" deliver\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - relevant\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" search\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + the\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" search\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\"er's\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + intent\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + deliver\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" relevant\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" results\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" Additionally\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\",\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - it\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" provides\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - AI\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" search\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" gener\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\"ative\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - answers\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" on\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - un\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\"structured\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\",\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - supporting\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" multiple\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - languages\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" sources\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"retrieval\",\"results\":{\"resources\":{\"399b7a3a66a0468580fb0fd752fc40cd\":{\"id\":\"399b7a3a66a0468580fb0fd752fc40cd\",\"slug\":\"docs-rag-advanced-connect-gemini-keys-md\",\"title\":\"docs - > rag > advanced > connect gemini keys\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-04T13:46:30.392047\",\"modified\":\"2026-06-09T08:07:41.267808\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"399b7a3a66a0468580fb0fd752fc40cd/t/page/846-1053\":{\"score\":0.5691343545913696,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\" - \\n Finalize Connection \\n \\n Navigate to the Progress Agentic RAG dashboard. - \\n When selecting an LLM in AI models or Agent , toggle on Use your Google - Gemini Key . \\n Enter your API key. \\n Save configuration. \\n\",\"id\":\"399b7a3a66a0468580fb0fd752fc40cd/t/page/846-1053\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":846,\"end\":1053,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"399b7a3a66a0468580fb0fd752fc40cd/t/page/301-618\":{\"score\":0.3698839247226715,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" - Prerequisites \\n \\n You have an active Google account with access to Google - AI Studio (https://aistudio.google.com/) \\n You have access to Progress Agentic - RAG. \\n \\n Generate & Locate Your API Key \\n \\n Navigate to Google AI - Studio (https://aistudio.google.com/) \\n Click on Get API key in the left - sidebar at the bottom. \\n\",\"id\":\"399b7a3a66a0468580fb0fd752fc40cd/t/page/301-618\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":301,\"end\":618,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"fd64185262eb403c82456d7111ed3345\":{\"id\":\"fd64185262eb403c82456d7111ed3345\",\"slug\":\"docs-rag-advanced-byok-aws-berock-assume-role-md\",\"title\":\"docs - > rag > advanced > byok aws berock assume role\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-18T13:54:44.059147\",\"modified\":\"2026-06-09T08:07:40.547430\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"fd64185262eb403c82456d7111ed3345/t/page/2483-2747\":{\"score\":0.38242971897125244,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" - For more details on these requirements, please refer to the official AWS Bedrock - Model Access Documentation. \\n Generate Configuration in Progress Agentic - RAG \\n \\n \\n Log in to Progress Agentic RAG and navigate to Manage Account - > Models > AWS Bedrock Integration. \\n\",\"id\":\"fd64185262eb403c82456d7111ed3345/t/page/2483-2747\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2483,\"end\":2747,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"22f855bc36c34e6c82182ebd33d3dbc4\":{\"id\":\"22f855bc36c34e6c82182ebd33d3dbc4\",\"slug\":\"docs-ingestion-how-to-integrate-strapi-md\",\"title\":\"docs + it\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" offers\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + features\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" like\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + automatic\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" indexing\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + of\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" page\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + contents\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + integration\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" with\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + various\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" AI\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + models\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" for\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + generating\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" answers\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" insights\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + from\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" un\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\"structured\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"retrieval\",\"results\":{\"resources\":{\"22f855bc36c34e6c82182ebd33d3dbc4\":{\"id\":\"22f855bc36c34e6c82182ebd33d3dbc4\",\"slug\":\"docs-ingestion-how-to-integrate-strapi-md\",\"title\":\"docs > ingestion > how to > integrate strapi\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:04.222223\",\"modified\":\"2026-06-26T08:59:45.897854\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"22f855bc36c34e6c82182ebd33d3dbc4/t/page/300-661\":{\"score\":0.974821150302887,\"score_type\":\"RERANKER\",\"order\":0,\"text\":\" Agentic RAG is the best search API to do it! \\n Agentic RAG is an API able to index and process any kind of data, including audio and video files, to boost applications with powerful search capability, using natural language processing and machine learning to understand the searcher's intent and return - results that are more relevant to the searcher's needs. \\n\",\"id\":\"22f855bc36c34e6c82182ebd33d3dbc4/t/page/300-661\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":300,\"end\":661,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"252561e259d84800889a576b1e8a35c9\":{\"id\":\"252561e259d84800889a576b1e8a35c9\",\"slug\":\"docs-rag-advanced-connect-vertex-ai-acct-md\",\"title\":\"docs - > rag > advanced > connect vertex ai acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-26T08:02:00.906568\",\"modified\":\"2026-06-09T08:07:44.679374\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"252561e259d84800889a576b1e8a35c9/t/page/0-328\":{\"score\":0.7316341996192932,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\" - \\n id: connect-vertex-ai-acct \\n title: Connect your own Google Vertex AI - \\n \\n Integrating Google Vertex AI with Progress Agentic RAG \\n This guide - provides step-by-step instructions for deploying Google Vertex AI and integrating - it with Progress Agentic RAG to enable AI-powered search capabilities using - Google's Gemini models. \\n\",\"id\":\"252561e259d84800889a576b1e8a35c9/t/page/0-328\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":328,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"252561e259d84800889a576b1e8a35c9/t/page/3243-3725\":{\"score\":0.3472050130367279,\"score_type\":\"RERANKER\",\"order\":15,\"text\":\" - Troubleshooting \\n If you encounter issues during the integration process: - \\n \\n Authentication errors: Verify that the JSON credentials file is correctly - formatted and contains valid credentials \\n Permission errors: Ensure the - service account has the necessary Vertex AI permissions \\n Region errors: - Confirm that the region specified in Progress Agentic RAG matches your Vertex - AI configuration \\n No response: Check your Google Cloud billing account - status and API quota limits \\n \\n \\n\",\"id\":\"252561e259d84800889a576b1e8a35c9/t/page/3243-3725\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":3243,\"end\":3725,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"36489cbab30247fea4edcbe8ba6d93d6\":{\"id\":\"36489cbab30247fea4edcbe8ba6d93d6\",\"slug\":\"docs-management-authentication-mdx\",\"title\":\"docs - > management > authentication.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:46.369763\",\"modified\":\"2026-06-26T08:59:51.921782\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"36489cbab30247fea4edcbe8ba6d93d6/t/page/4972-5293\":{\"score\":0.3301471471786499,\"score_type\":\"RERANKER\",\"order\":16,\"text\":\" - Generate and Use User Key \\n \\n \\n This method is meant to be used from - the Agentic RAG frontend applications but if you need it for testing purpose, - you can obtain a token by going to [https://rag.progress.cloud/redirect?display=token] - \\n Then in the API calls, include it in the `Authorization` header as a Bearer - token: \\n\",\"id\":\"36489cbab30247fea4edcbe8ba6d93d6/t/page/4972-5293\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":4972,\"end\":5293,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"bef9fbb057dc46fa9c2bf121a7967efa\":{\"id\":\"bef9fbb057dc46fa9c2bf121a7967efa\",\"slug\":\"docs-rag-how-to-remi-md\",\"title\":\"docs - > rag > how to > remi\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:59.392903\",\"modified\":\"2026-06-26T08:59:41.701319\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"bef9fbb057dc46fa9c2bf121a7967efa/t/page/1594-1930\":{\"score\":0.32713067531585693,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\" + results that are more relevant to the searcher's needs. \\n\",\"id\":\"22f855bc36c34e6c82182ebd33d3dbc4/t/page/300-661\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":300,\"end\":661,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"c1d73c95e26d44eea84e63919a836289\":{\"id\":\"c1d73c95e26d44eea84e63919a836289\",\"slug\":\"docs-ingestion-how-to-integrate-nextjs-md\",\"title\":\"docs + > ingestion > how to > integrate nextjs\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"de\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:04.780909\",\"modified\":\"2026-06-26T08:59:44.635729\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"c1d73c95e26d44eea84e63919a836289/t/page/837-1226\":{\"score\":0.9353464841842651,\"score_type\":\"RERANKER\",\"order\":1,\"text\":\" + Agentic RAG is an API able to index and process any kind of data, including + audio and video files, to boost applications with powerful search & RAG capability. + \\n Indexing page contents automatically \\n The Agentic RAG Dashboard is + an easy way to index files or web pages by yourself. That's nice for testing + purpose, but it is definitely better to index your Next.js pages automatically. + \\n\",\"id\":\"c1d73c95e26d44eea84e63919a836289/t/page/837-1226\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":837,\"end\":1226,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"c1d73c95e26d44eea84e63919a836289/t/page/1666-2203\":{\"score\":0.5552845597267151,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" + ```js \\n const { Nuclia } = require( @nuclia/core ); \\n require( localstorage-polyfill + ); \\n require( isomorphic-unfetch ); \\n const nuclia = new Nuclia({ \\n + backend: https://accounts.progress.cloud/api , \\n zone: europe-1 , \\n knowledgeBox: + , \\n apiKey: , \\n }); \\n // code to push data to Agentic RAG (detailed + later) \\n ``` \\n As you can see, you need to provide a Agentic RAG API key. + An API key is necessary when adding or modifying contents in a knowledge box. + You can get your API key in the Agentic RAG Dashboard, in the API keys section: + \\n\",\"id\":\"c1d73c95e26d44eea84e63919a836289/t/page/1666-2203\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1666,\"end\":2203,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"fd64185262eb403c82456d7111ed3345\":{\"id\":\"fd64185262eb403c82456d7111ed3345\",\"slug\":\"docs-rag-advanced-byok-aws-berock-assume-role-md\",\"title\":\"docs + > rag > advanced > byok aws berock assume role\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-18T13:54:44.059147\",\"modified\":\"2026-06-09T08:07:40.547430\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"fd64185262eb403c82456d7111ed3345/t/page/2483-2747\":{\"score\":0.38242971897125244,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" + For more details on these requirements, please refer to the official AWS Bedrock + Model Access Documentation. \\n Generate Configuration in Progress Agentic + RAG \\n \\n \\n Log in to Progress Agentic RAG and navigate to Manage Account + > Models > AWS Bedrock Integration. \\n\",\"id\":\"fd64185262eb403c82456d7111ed3345/t/page/2483-2747\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2483,\"end\":2747,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"bef9fbb057dc46fa9c2bf121a7967efa\":{\"id\":\"bef9fbb057dc46fa9c2bf121a7967efa\",\"slug\":\"docs-rag-how-to-remi-md\",\"title\":\"docs + > rag > how to > remi\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:59.392903\",\"modified\":\"2026-06-26T08:59:41.701319\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"bef9fbb057dc46fa9c2bf121a7967efa/t/page/1594-1930\":{\"score\":0.32713067531585693,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\" \\n https://.dp.progress.cloud/api/v1/kb/ \\n \\n \\n Knowledge Box API Key: The This key is used to interact with the Knowledge Box API. To obtain this key, you can follow the instructions here. \\n \\n \\n NUA API Key: This key is used to interact with the Agentic RAG Understanding API. To obtain this - key, you can follow the instructions here. \\n\",\"id\":\"bef9fbb057dc46fa9c2bf121a7967efa/t/page/1594-1930\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1594,\"end\":1930,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"007b445866574d7ca69891d388663cc6\":{\"id\":\"007b445866574d7ca69891d388663cc6\",\"slug\":\"docs-management-security-5-public-ips-md\",\"title\":\"docs - > management > security > 5 public ips\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-03T09:28:57.937064\",\"modified\":\"2026-07-03T09:28:57.937076\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"007b445866574d7ca69891d388663cc6/t/page/418-652\":{\"score\":0.8682692646980286,\"score_type\":\"RERANKER\",\"order\":2,\"text\":\" + key, you can follow the instructions here. \\n\",\"id\":\"bef9fbb057dc46fa9c2bf121a7967efa/t/page/1594-1930\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1594,\"end\":1930,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e6605960cc46412da0e5e5404f511d53\":{\"id\":\"e6605960cc46412da0e5e5404f511d53\",\"slug\":\"docs-intro-md\",\"title\":\"docs + > intro\",\"summary\":\"When teams knit together vector databases, machine + learning pipelines, large language models, ranking algorithms, and interfaces + into specific products, they are only providing one or two of these capabilities.\\nNuclea + delivers all four out of the box.\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"sr\",\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2023-08-03T08:57:16.630817\",\"modified\":\"2026-06-09T08:07:20.822319\",\"last_seqid\":1741334,\"last_account_seq\":67150,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"e6605960cc46412da0e5e5404f511d53/t/page/0-301\":{\"score\":0.689723789691925,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" + \\n id: intro \\n slug: / \\n title: Agentic RAG documentation \\n \\n Agentic + RAG, the RAG-as-a-Service platform \\n Agentic RAG automatically delivers + AI search and Generative Answers on top of your unstructured data, and provides + knowledge in the form of trusted answers, in any language, and from any data. + \\n\",\"id\":\"e6605960cc46412da0e5e5404f511d53/t/page/0-301\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":301,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"46477109e5db4b198b08d39cce0d363c\":{\"id\":\"46477109e5db4b198b08d39cce0d363c\",\"slug\":\"docs-management-security-05-public-ips-md\",\"title\":\"docs + > management > security > 05 public ips\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-16T08:13:28.912083\",\"modified\":\"2026-07-16T08:13:28.912097\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"46477109e5db4b198b08d39cce0d363c/t/page/418-652\":{\"score\":0.8682692646980286,\"score_type\":\"RERANKER\",\"order\":2,\"text\":\" Outbound \u2014 the source IP addresses that Progress Agentic RAG uses when making connections to your systems (e.g., webhooks, sync agents, or other integrations). Allowlist these if you restrict inbound traffic to your infrastructure. - \\n\",\"id\":\"007b445866574d7ca69891d388663cc6/t/page/418-652\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":418,\"end\":652,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"007b445866574d7ca69891d388663cc6/t/page/208-418\":{\"score\":0.6285214424133301,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\" + \\n\",\"id\":\"46477109e5db4b198b08d39cce0d363c/t/page/418-652\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":418,\"end\":652,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"46477109e5db4b198b08d39cce0d363c/t/page/208-418\":{\"score\":0.6285214424133301,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"id\":\"007b445866574d7ca69891d388663cc6/t/page/208-418\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":208,\"end\":418,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"73c3dde3c4cc45c7a9aabaf19d1578a1\":{\"id\":\"73c3dde3c4cc45c7a9aabaf19d1578a1\",\"slug\":\"docs-rag-advanced-bring-your-own-anthropic-acct-md\",\"title\":\"docs - > rag > advanced > bring your own anthropic acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-20T14:58:49.310838\",\"modified\":\"2026-06-09T08:07:46.863851\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"73c3dde3c4cc45c7a9aabaf19d1578a1/t/page/292-560\":{\"score\":0.503440797328949,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\" + and need to reach our services (e.g., calling our APIs). \\n\",\"id\":\"46477109e5db4b198b08d39cce0d363c/t/page/208-418\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":208,\"end\":418,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"399b7a3a66a0468580fb0fd752fc40cd\":{\"id\":\"399b7a3a66a0468580fb0fd752fc40cd\",\"slug\":\"docs-rag-advanced-connect-gemini-keys-md\",\"title\":\"docs + > rag > advanced > connect gemini keys\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-04T13:46:30.392047\",\"modified\":\"2026-06-09T08:07:41.267808\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"399b7a3a66a0468580fb0fd752fc40cd/t/page/846-1053\":{\"score\":0.5691343545913696,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\" + \\n Finalize Connection \\n \\n Navigate to the Progress Agentic RAG dashboard. + \\n When selecting an LLM in AI models or Agent , toggle on Use your Google + Gemini Key . \\n Enter your API key. \\n Save configuration. \\n\",\"id\":\"399b7a3a66a0468580fb0fd752fc40cd/t/page/846-1053\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":846,\"end\":1053,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"399b7a3a66a0468580fb0fd752fc40cd/t/page/301-618\":{\"score\":0.3698839247226715,\"score_type\":\"RERANKER\",\"order\":15,\"text\":\" + Prerequisites \\n \\n You have an active Google account with access to Google + AI Studio (https://aistudio.google.com/) \\n You have access to Progress Agentic + RAG. \\n \\n Generate & Locate Your API Key \\n \\n Navigate to Google AI + Studio (https://aistudio.google.com/) \\n Click on Get API key in the left + sidebar at the bottom. \\n\",\"id\":\"399b7a3a66a0468580fb0fd752fc40cd/t/page/301-618\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":301,\"end\":618,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"73c3dde3c4cc45c7a9aabaf19d1578a1\":{\"id\":\"73c3dde3c4cc45c7a9aabaf19d1578a1\",\"slug\":\"docs-rag-advanced-bring-your-own-anthropic-acct-md\",\"title\":\"docs + > rag > advanced > bring your own anthropic acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-20T14:58:49.310838\",\"modified\":\"2026-06-09T08:07:46.863851\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"73c3dde3c4cc45c7a9aabaf19d1578a1/t/page/292-560\":{\"score\":0.5028190016746521,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" Prerequisites \\n \\n You have an active Anthropic account (https://console.anthropic.com/) \\n Billing is enabled in your Anthropic console. \\n You have access to Progress Agentic RAG. \\n \\n Generate & Locate Your API Key \\n \\n Expand the sidebar - on the top left hand corner. \\n\",\"id\":\"73c3dde3c4cc45c7a9aabaf19d1578a1/t/page/292-560\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":292,\"end\":560,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e6605960cc46412da0e5e5404f511d53\":{\"id\":\"e6605960cc46412da0e5e5404f511d53\",\"slug\":\"docs-intro-md\",\"title\":\"docs - > intro\",\"summary\":\"When teams knit together vector databases, machine - learning pipelines, large language models, ranking algorithms, and interfaces - into specific products, they are only providing one or two of these capabilities.\\nNuclea - delivers all four out of the box.\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"sr\",\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2023-08-03T08:57:16.630817\",\"modified\":\"2026-06-09T08:07:20.822319\",\"last_seqid\":1741334,\"last_account_seq\":67150,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"e6605960cc46412da0e5e5404f511d53/t/page/0-301\":{\"score\":0.689723789691925,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" - \\n id: intro \\n slug: / \\n title: Agentic RAG documentation \\n \\n Agentic - RAG, the RAG-as-a-Service platform \\n Agentic RAG automatically delivers - AI search and Generative Answers on top of your unstructured data, and provides - knowledge in the form of trusted answers, in any language, and from any data. - \\n\",\"id\":\"e6605960cc46412da0e5e5404f511d53/t/page/0-301\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":301,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"2a9e55371d8f4461993ef6b6ae3bb3e6\":{\"id\":\"2a9e55371d8f4461993ef6b6ae3bb3e6\",\"slug\":\"docs-rag-advanced-performances-md\",\"title\":\"docs - > rag > advanced > performances\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-10-02T15:19:15.263181\",\"modified\":\"2026-06-09T08:07:44.014121\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"2a9e55371d8f4461993ef6b6ae3bb3e6/t/page/2716-2929\":{\"score\":0.30331891775131226,\"score_type\":\"RERANKER\",\"order\":19,\"text\":\" - \\n How to use REMi \\n Agentic RAG runs REMi on a regular basis to monitor - the quality of the RAG pipeline. The results are displayed in the Agentic - RAG dashboard that shows the evolution of the metrics over time. \\n\",\"id\":\"2a9e55371d8f4461993ef6b6ae3bb3e6/t/page/2716-2929\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":2716,\"end\":2929,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"9e6238e3377d41699643ba954dd500fa\":{\"id\":\"9e6238e3377d41699643ba954dd500fa\",\"slug\":\"docs-ingestion-how-to-extract-strategies-md\",\"title\":\"docs - > ingestion > how to > extract strategies\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-06-13T08:13:07.100304\",\"modified\":\"2026-06-09T08:18:12.970227\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"9e6238e3377d41699643ba954dd500fa/t/page/2317-2576\":{\"score\":0.5746932029724121,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" - Apart from cutting-edge table and text extraction capabilities, \U0001F415 - pagehound-v1 is capable of extracting embedded images from full page scans, - making it possible to apply Progress' Agentic RAG image processing pipeline - to them, enabling search capabilities. \\n\",\"id\":\"9e6238e3377d41699643ba954dd500fa/t/page/2317-2576\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2317,\"end\":2576,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"0d4445df40ee4daeb4bb6d609f2b64b1\":{\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1\",\"slug\":\"docs-rag-advanced-connect-your-own-azure-openai-acct-md\",\"title\":\"docs + on the top left hand corner. \\n\",\"id\":\"73c3dde3c4cc45c7a9aabaf19d1578a1/t/page/292-560\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":292,\"end\":560,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"0d4445df40ee4daeb4bb6d609f2b64b1\":{\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1\",\"slug\":\"docs-rag-advanced-connect-your-own-azure-openai-acct-md\",\"title\":\"docs > rag > advanced > connect your own azure openai acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-15T14:36:48.862567\",\"modified\":\"2026-06-09T08:07:50.247127\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/3184-3468\":{\"score\":0.8507168292999268,\"score_type\":\"RERANKER\",\"order\":3,\"text\":\" Select Azure OpenAI as the LLM provider \\n Enable Use your own Azure OpenAI key \\n Enter: \\n API Key \\n Endpoint URL \\n Deployment Name \\n Model Name \\n Save the configuration \\n Test answer generation \\n \\n Outcome \\n \\n Progress Agentic RAG uses your Azure-hosted LLM for answer generation - \\n \",\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/3184-3468\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":3184,\"end\":3468,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/2859-3184\":{\"score\":0.36161547899246216,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" + \\n \",\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/3184-3468\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":3184,\"end\":3468,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/2859-3184\":{\"score\":0.36161547899246216,\"score_type\":\"RERANKER\",\"order\":16,\"text\":\" 6. Configure Azure OpenAI in Progress Agentic RAG \\n This step connects your deployed model to Progress Agentic RAG. \\n Required Configuration Values \\n | Field | Source | \\n | --------------- | ------- | \\n | API Key | Foundry | \\n | Endpoint URL | Foundry | \\n | Deployment Name | Foundry | \\n | Model - Name | Foundry | \\n Steps \\n \\n\",\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/2859-3184\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2859,\"end\":3184,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/0-446\":{\"score\":0.30466195940971375,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\" - \\n id: connect-your-own-azure-openai-acct \\n title: Connect your own Azure - OpenAI Model \\n \\n Deploying an Azure OpenAI Model and Connecting It to - Progress Agentic RAG \\n Summary Flow \\n \\n Create Azure account and subscription - \\n Create Azure OpenAI resource \\n Open Microsoft Foundry from the resource - overview \\n Deploy a model via the Model Catalog \\n Retrieve API key and - endpoint from Foundry UI \\n Configure Azure OpenAI in Progress Agentic RAG - \\n \\n \\n\",\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/0-446\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":446,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"c1d73c95e26d44eea84e63919a836289\":{\"id\":\"c1d73c95e26d44eea84e63919a836289\",\"slug\":\"docs-ingestion-how-to-integrate-nextjs-md\",\"title\":\"docs - > ingestion > how to > integrate nextjs\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"de\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:04.780909\",\"modified\":\"2026-06-26T08:59:44.635729\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"c1d73c95e26d44eea84e63919a836289/t/page/837-1226\":{\"score\":0.9353464841842651,\"score_type\":\"RERANKER\",\"order\":1,\"text\":\" - Agentic RAG is an API able to index and process any kind of data, including - audio and video files, to boost applications with powerful search & RAG capability. - \\n Indexing page contents automatically \\n The Agentic RAG Dashboard is - an easy way to index files or web pages by yourself. That's nice for testing - purpose, but it is definitely better to index your Next.js pages automatically. - \\n\",\"id\":\"c1d73c95e26d44eea84e63919a836289/t/page/837-1226\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":837,\"end\":1226,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"c1d73c95e26d44eea84e63919a836289/t/page/1666-2203\":{\"score\":0.5552845597267151,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" - ```js \\n const { Nuclia } = require( @nuclia/core ); \\n require( localstorage-polyfill - ); \\n require( isomorphic-unfetch ); \\n const nuclia = new Nuclia({ \\n - backend: https://accounts.progress.cloud/api , \\n zone: europe-1 , \\n knowledgeBox: - , \\n apiKey: , \\n }); \\n // code to push data to Agentic RAG (detailed - later) \\n ``` \\n As you can see, you need to provide a Agentic RAG API key. - An API key is necessary when adding or modifying contents in a knowledge box. - You can get your API key in the Agentic RAG Dashboard, in the API keys section: - \\n\",\"id\":\"c1d73c95e26d44eea84e63919a836289/t/page/1666-2203\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1666,\"end\":2203,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"7a58f44f10fc423f83239c0b733057c1\":{\"id\":\"7a58f44f10fc423f83239c0b733057c1\",\"slug\":\"docs-develop-dotnet-sdk-index-md\",\"title\":\"docs - > develop > dotnet sdk > 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\\n\",\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/2859-3184\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2859,\"end\":3184,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"7a58f44f10fc423f83239c0b733057c1\":{\"id\":\"7a58f44f10fc423f83239c0b733057c1\",\"slug\":\"docs-develop-dotnet-sdk-index-md\",\"title\":\"docs + > develop > dotnet sdk > index\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"sk\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-24T16:03:48.411403\",\"modified\":\"2026-06-09T08:17:38.462625\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"7a58f44f10fc423f83239c0b733057c1/t/page/0-226\":{\"score\":0.6728693246841431,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\"Progress.Nuclia .NET SDK \\n A comprehensive .NET SDK for Progress Agentic RAG's NucliaDb, providing RAG (Retrieval-Augmented Generation) capabilities with knowledge - base management, AI-powered search, and resource operations. 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+ base management, AI-powered search, and resource operations. \\n\",\"id\":\"7a58f44f10fc423f83239c0b733057c1/t/page/0-226\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":226,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"9e6238e3377d41699643ba954dd500fa\":{\"id\":\"9e6238e3377d41699643ba954dd500fa\",\"slug\":\"docs-ingestion-how-to-extract-strategies-md\",\"title\":\"docs + > ingestion > how to > extract strategies\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-06-13T08:13:07.100304\",\"modified\":\"2026-06-09T08:18:12.970227\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"9e6238e3377d41699643ba954dd500fa/t/page/2317-2576\":{\"score\":0.5746932029724121,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" + Apart from cutting-edge table and text extraction capabilities, \U0001F415 + pagehound-v1 is capable of extracting embedded images from full page scans, + making it possible to apply Progress' Agentic RAG image processing pipeline + to them, enabling search capabilities. \\n\",\"id\":\"9e6238e3377d41699643ba954dd500fa/t/page/2317-2576\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2317,\"end\":2576,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"36489cbab30247fea4edcbe8ba6d93d6\":{\"id\":\"36489cbab30247fea4edcbe8ba6d93d6\",\"slug\":\"docs-management-authentication-mdx\",\"title\":\"docs + > management > authentication.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:46.369763\",\"modified\":\"2026-06-26T08:59:51.921782\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"36489cbab30247fea4edcbe8ba6d93d6/t/page/4972-5293\":{\"score\":0.3301471471786499,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\" + Generate and Use User Key \\n \\n \\n This method is meant to be used from + the Agentic RAG frontend applications but if you need it for testing purpose, + you can obtain a token by going to [https://rag.progress.cloud/redirect?display=token] + \\n Then in the API calls, include it in the `Authorization` header as a Bearer + token: \\n\",\"id\":\"36489cbab30247fea4edcbe8ba6d93d6/t/page/4972-5293\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":4972,\"end\":5293,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"7c9e318a8fcc4c9485b8639fdbe93b38\":{\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"slug\":\"docs-develop-nua-md\",\"title\":\"docs + > develop > nua\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-29T07:32:38.792855\",\"modified\":\"2026-07-29T07:32:38.792869\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"7c9e318a8fcc4c9485b8639fdbe93b38/t/page/0-496\":{\"score\":0.8438951373100281,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\" + \\n id: nua \\n title: Nuclia Understanding API \\n \\n Using the Nuclia Understanding + API \\n The Nuclia Understanding API (NUA) allows you to process data outside + of a Knowledge Box. It is a set of endpoints that allow you to send data to + the Progress Agentic RAG platform for processing, or to make calls to models + to generate text, summaries, or other outputs. The information is stored temporarily + for the duration of the processing, nothing remains in the ProgressAgentic + RAG cloud infrastructure. \\n\",\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38/t/page/0-496\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":496,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"7c9e318a8fcc4c9485b8639fdbe93b38/t/page/934-1170\":{\"score\":0.5865820646286011,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\" + \\n \\n Once you have the API key, you can use it in the NUA endpoints by + setting the header X-NUCLIA-NUAKEY in each request. \\n The primary usage + of a NUA key is to allow running data processing jobs on the Progress Agentic + RAG platform. \\n\",\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38/t/page/934-1170\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":934,\"end\":1170,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"7c9e318a8fcc4c9485b8639fdbe93b38/t/page/703-934\":{\"score\":0.31205546855926514,\"score_type\":\"RERANKER\",\"order\":19,\"text\":\" + Click on NUA keys . \\n Click on the Create new Progress Agentic RAG Understanding + API key button. \\n \\n Fill out the form and submit it. \\n \\n \\n Using + the Nuclia API /api/v1/account/{your_account}/nua_client endpoint (see Reference). + \\n\",\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38/t/page/703-934\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":703,\"end\":934,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"252561e259d84800889a576b1e8a35c9\":{\"id\":\"252561e259d84800889a576b1e8a35c9\",\"slug\":\"docs-rag-advanced-connect-vertex-ai-acct-md\",\"title\":\"docs + > rag > advanced > connect vertex ai acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-26T08:02:00.906568\",\"modified\":\"2026-06-09T08:07:44.679374\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"252561e259d84800889a576b1e8a35c9/t/page/0-328\":{\"score\":0.7316341996192932,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" + \\n id: connect-vertex-ai-acct \\n title: Connect your own Google Vertex AI + \\n \\n Integrating Google Vertex AI with Progress Agentic RAG \\n This guide + provides step-by-step instructions for deploying Google Vertex AI and integrating + it with Progress Agentic RAG to enable AI-powered search capabilities using + Google's Gemini models. 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headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 @@ -770,15 +707,13 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 15 Jul 2026 07:54:36 GMT + - Wed, 05 Aug 2026 07:25:13 GMT nuclia-learning-id: - - 86564862880e41b6bee1fabe31259f99 + - ac6502c11c4e41a882aa10e76c07f3b5 via: - 1.1 google x-envoy-upstream-service-time: - - '1105' - x-nuclia-trace-id: - - e0a282121573d3e2abb89ab18feabd35 + - '824' status: code: 200 message: OK @@ -794,20 +729,28 @@ interactions: {}, "query_context_order": {}, "truncate": true, "user_prompt": {"prompt": "\n## Question\nWhat is Progress Agentic RAG?\n\n## Provided Context\n[START OF CONTEXT]\n## Nuclia Docs Retrieval Agent\n\n# What is Progress Agentic RAG?\n\n Progress - Agentic RAG is an API that indexes and processes various types of data, including - audio and video files, to enhance applications with advanced search capabilities. - It utilizes natural language processing and machine learning to understand user - intent and deliver relevant search results. Additionally, it provides AI search - and generative answers on unstructured data, supporting multiple languages and - data sources.\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read - all context; it may be lengthy or detailed\n- Do not omit or overlook any relevant - information\n- If the context is incomplete or insufficient, state: \"Not enough - data to answer this.\"\n- Read carefully any extra instructions below if provided - and use them to answer\n\nNow provide your answer to the question: What is Progress - Agentic RAG?"}, "citations": null, "citation_threshold": null, "generative_model": - "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": - null, "json_schema": null, "format_prompt": false, "rerank_context": false, - "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": null}' + Agentic RAG is an API that enhances applications with powerful search capabilities + by indexing and processing various types of data, including audio and video + files. It utilizes natural language processing and machine learning to understand + the searcher''s intent and deliver relevant results. Additionally, it offers + features like automatic indexing of page contents and integration with various + AI models for generating answers and insights from unstructured data.\n[END + OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all context; it may + be lengthy or detailed\n- Do not omit or overlook any relevant information\n- + Existing context summaries are answer attempts produced by retrieval agents. + Treat them as first-class evidence and preserve their supported facts.\n- Combine + complementary summaries from multiple contexts when the question has multiple + parts. Do not require every context to answer the whole question by itself.\n- + If a context summary directly answers the question, do not replace it with an + insufficient-data answer merely because one retrieved chunk is incomplete; use + the chunks for supporting citations.\n- If the context is incomplete or insufficient, + state: \"Not enough data to answer this.\"\n- Read carefully any extra instructions + below if provided and use them to answer\n\nNow provide your answer to the question: + What is Progress Agentic RAG?"}, "citations": null, "citation_threshold": null, + "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": + {}, "prefer_markdown": null, "json_schema": null, "format_prompt": false, "rerank_context": + false, "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": + null}' headers: Accept: - application/x-ndjson @@ -816,7 +759,7 @@ interactions: Connection: - keep-alive Content-Length: - - '1998' + - '2560' Content-Type: - application/json Host: @@ -826,7 +769,7 @@ interactions: x-client-ident: - default x-message: - - 143abdb5824d475ab314e138c99b8ee5 + - 22294f46813144ee8ea25c21d78c37a7 x-origin: - RAO x-session: @@ -855,13 +798,29 @@ interactions: {"chunk":{"type":"text","text":" API"}} - {"chunk":{"type":"text","text":" that"}} + {"chunk":{"type":"text","text":" designed"}} + + {"chunk":{"type":"text","text":" to"}} + + {"chunk":{"type":"text","text":" enhance"}} + + {"chunk":{"type":"text","text":" applications"}} + + {"chunk":{"type":"text","text":" with"}} + + {"chunk":{"type":"text","text":" advanced"}} - {"chunk":{"type":"text","text":" indexes"}} + {"chunk":{"type":"text","text":" search"}} + + {"chunk":{"type":"text","text":" capabilities"}} + + {"chunk":{"type":"text","text":" by"}} + + {"chunk":{"type":"text","text":" indexing"}} {"chunk":{"type":"text","text":" and"}} - {"chunk":{"type":"text","text":" processes"}} + {"chunk":{"type":"text","text":" processing"}} {"chunk":{"type":"text","text":" various"}} @@ -883,27 +842,11 @@ interactions: {"chunk":{"type":"text","text":" files"}} - 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{"chunk":{"type":"text","text":" search"}} - {"chunk":{"type":"text","text":" results"}} {"chunk":{"type":"text","text":"."}} - {"chunk":{"type":"text","text":" Additionally"}} + {"chunk":{"type":"text","text":" Key"}} - {"chunk":{"type":"text","text":","}} + {"chunk":{"type":"text","text":" features"}} - {"chunk":{"type":"text","text":" it"}} + {"chunk":{"type":"text","text":" include"}} - {"chunk":{"type":"text","text":" provides"}} + {"chunk":{"type":"text","text":" automatic"}} - {"chunk":{"type":"text","text":" AI"}} + {"chunk":{"type":"text","text":" indexing"}} - {"chunk":{"type":"text","text":" search"}} + {"chunk":{"type":"text","text":" of"}} + + {"chunk":{"type":"text","text":" page"}} + + {"chunk":{"type":"text","text":" contents"}} {"chunk":{"type":"text","text":" and"}} - {"chunk":{"type":"text","text":" gener"}} + {"chunk":{"type":"text","text":" integration"}} - {"chunk":{"type":"text","text":"ative"}} + {"chunk":{"type":"text","text":" with"}} - {"chunk":{"type":"text","text":" answers"}} + {"chunk":{"type":"text","text":" various"}} - {"chunk":{"type":"text","text":" on"}} + {"chunk":{"type":"text","text":" AI"}} - {"chunk":{"type":"text","text":" un"}} + {"chunk":{"type":"text","text":" models"}} - {"chunk":{"type":"text","text":"structured"}} + {"chunk":{"type":"text","text":" to"}} - {"chunk":{"type":"text","text":" data"}} + {"chunk":{"type":"text","text":" generate"}} - {"chunk":{"type":"text","text":","}} + {"chunk":{"type":"text","text":" answers"}} - {"chunk":{"type":"text","text":" supporting"}} + {"chunk":{"type":"text","text":" and"}} - {"chunk":{"type":"text","text":" multiple"}} + {"chunk":{"type":"text","text":" insights"}} - {"chunk":{"type":"text","text":" languages"}} + {"chunk":{"type":"text","text":" from"}} - {"chunk":{"type":"text","text":" and"}} + {"chunk":{"type":"text","text":" un"}} - {"chunk":{"type":"text","text":" data"}} + {"chunk":{"type":"text","text":"structured"}} - {"chunk":{"type":"text","text":" sources"}} + {"chunk":{"type":"text","text":" data"}} {"chunk":{"type":"text","text":"."}} {"chunk":{"type":"status","code":"0"}} - {"chunk":{"type":"meta","input_tokens":9,"output_tokens":9,"timings":{"generative_first_chunk":0.46801990098902024,"generative":1.3842634939937852},"input_nuclia_tokens":0.009,"output_nuclia_tokens":0.009}} + {"chunk":{"type":"meta","input_tokens":12,"output_tokens":9,"timings":{"generative_first_chunk":0.6119108589991811,"generative":1.84506226600206},"input_nuclia_tokens":0.012,"output_nuclia_tokens":0.009}} - {"chunk":{"normalized_tokens":{"input":0.00906,"output":0.00864,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} + {"chunk":{"normalized_tokens":{"input":0.01176,"output":0.009,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} ' headers: @@ -998,85 +947,82 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 15 Jul 2026 07:54:39 GMT + - Wed, 05 Aug 2026 07:25:16 GMT nuclia-learning-id: - - 25eb7445c64e4726a50cd1215b270923 + - 87774b36141d446abb22189b9856a523 nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '475' + - '619' x-nuclia-trace-id: - - 03610131d50c3d96279e90d11cde26e9 + - cd8c8309cedaf33b6abc3f110f8f3adb status: code: 200 message: OK - request: body: '{"user_id": "arag_evaluate", "question": null, "answer": "Progress Agentic - RAG is an API that indexes and processes various types of data, including audio - and video files, to enhance applications with advanced search capabilities. - It utilizes natural language processing and machine learning to understand user - intent and deliver relevant search results. Additionally, it provides AI search - and generative answers on unstructured data, supporting multiple languages and - data sources.", "contexts": ["## docs > ingestion > how to > integrate nextjs\n\n - Agentic RAG is an API able to index and process any kind of data, including - audio and video files, to boost applications with powerful search & RAG capability. - \n Indexing page contents automatically \n The Agentic RAG Dashboard is an easy - way to index files or web pages by yourself. That''s nice for testing purpose, - but it is definitely better to index your Next.js pages automatically. \n\n\n", - "## docs > ingestion > how to > integrate strapi\n\n Agentic RAG is the best - search API to do it! \n Agentic RAG is an API able to index and process any - kind of data, including audio and video files, to boost applications with powerful - search capability, using natural language processing and machine learning to - understand the searcher''s intent and return results that are more relevant - to the searcher''s needs. \n\n\n", "## docs > rag > advanced > connect your - own azure openai acct\n\n \n id: connect-your-own-azure-openai-acct \n title: - Connect your own Azure OpenAI Model \n \n Deploying an Azure OpenAI Model and - Connecting It to Progress Agentic RAG \n Summary Flow \n \n Create Azure account - and subscription \n Create Azure OpenAI resource \n Open Microsoft Foundry from - the resource overview \n Deploy a model via the Model Catalog \n Retrieve API - key and endpoint from Foundry UI \n Configure Azure OpenAI in Progress Agentic - RAG \n \n \n\n\n", "## docs > rag > advanced > connect vertex ai acct\n\n Troubleshooting - \n If you encounter issues during the integration process: \n \n Authentication - errors: Verify that the JSON credentials file is correctly formatted and contains - valid credentials \n Permission errors: Ensure the service account has the necessary - Vertex AI permissions \n Region errors: Confirm that the region specified in - Progress Agentic RAG matches your Vertex AI configuration \n No response: Check - your Google Cloud billing account status and API quota limits \n \n \n\n\n", - "## docs > develop > dotnet sdk > index\n\nProgress.Nuclia .NET SDK \n A comprehensive - .NET SDK for Progress Agentic RAG''s NucliaDb, providing RAG (Retrieval-Augmented - Generation) capabilities with knowledge base management, AI-powered search, - and resource operations. \n\n\n", "## docs > rag > advanced > connect gemini - keys\n\n Prerequisites \n \n You have an active Google account with access to - Google AI Studio (https://aistudio.google.com/) \n You have access to Progress - Agentic RAG. \n \n Generate & Locate Your API Key \n \n Navigate to Google AI - Studio (https://aistudio.google.com/) \n Click on Get API key in the left sidebar - at the bottom. \n\n\n", "## docs > rag > advanced > bring your own anthropic - acct\n\n Prerequisites \n \n You have an active Anthropic account (https://console.anthropic.com/) - \n Billing is enabled in your Anthropic console. \n You have access to Progress - Agentic RAG. \n \n Generate & Locate Your API Key \n \n Expand the sidebar on - the top left hand corner. \n\n\n", "## docs > rag > advanced > connect your - own azure openai acct\n\n 6. Configure Azure OpenAI in Progress Agentic RAG - \n This step connects your deployed model to Progress Agentic RAG. \n Required - Configuration Values \n | Field | Source | \n | --------------- | ------- | - \n | API Key | Foundry | \n | Endpoint URL | Foundry | \n | Deployment Name - | Foundry | \n | Model Name | Foundry | \n Steps \n \n\n\n", "## docs > ingestion + RAG is an API designed to enhance applications with advanced search capabilities + by indexing and processing various types of data, including audio and video + files. It employs natural language processing and machine learning to comprehend + the searcher''s intent and deliver relevant results. Key features include automatic + indexing of page contents and integration with various AI models to generate + answers and insights from unstructured data.", "contexts": ["## docs > ingestion + > how to > integrate strapi\n\n Agentic RAG is the best search API to do it! + \n Agentic RAG is an API able to index and process any kind of data, including + audio and video files, to boost applications with powerful search capability, + using natural language processing and machine learning to understand the searcher''s + intent and return results that are more relevant to the searcher''s needs. \n\n\n", + "## docs > ingestion > how to > integrate nextjs\n\n Agentic RAG is an API able + to index and process any kind of data, including audio and video files, to boost + applications with powerful search & RAG capability. \n Indexing page contents + automatically \n The Agentic RAG Dashboard is an easy way to index files or + web pages by yourself. That''s nice for testing purpose, but it is definitely + better to index your Next.js pages automatically. \n\n\n", "## docs > develop + > dotnet sdk > index\n\nProgress.Nuclia .NET SDK \n A comprehensive .NET SDK + for Progress Agentic RAG''s NucliaDb, providing RAG (Retrieval-Augmented Generation) + capabilities with knowledge base management, AI-powered search, and resource + operations. \n\n\n", "## docs > rag > advanced > connect gemini keys\n\n Prerequisites + \n \n You have an active Google account with access to Google AI Studio (https://aistudio.google.com/) + \n You have access to Progress Agentic RAG. \n \n Generate & Locate Your API + Key \n \n Navigate to Google AI Studio (https://aistudio.google.com/) \n Click + on Get API key in the left sidebar at the bottom. \n\n\n", "## docs > ingestion > how to > extract strategies\n\n Apart from cutting-edge table and text extraction capabilities, \ud83d\udc15 pagehound-v1 is capable of extracting embedded images from full page scans, making it possible to apply Progress'' Agentic RAG image processing pipeline to them, enabling search capabilities. \n\n\n", "## docs - > ingestion > how to > integrate nextjs\n\n ```js \n const { Nuclia } = require( - @nuclia/core ); \n require( localstorage-polyfill ); \n require( isomorphic-unfetch - ); \n const nuclia = new Nuclia({ \n backend: https://accounts.progress.cloud/api - , \n zone: europe-1 , \n knowledgeBox: , \n apiKey: , \n }); \n // code to push - data to Agentic RAG (detailed later) \n ``` \n As you can see, you need to provide - a Agentic RAG API key. An API key is necessary when adding or modifying contents - in a knowledge box. You can get your API key in the Agentic RAG Dashboard, in - the API keys section: \n\n\n", "## docs > rag > advanced > connect gemini keys\n\n - \n Finalize Connection \n \n Navigate to the Progress Agentic RAG dashboard. - \n When selecting an LLM in AI models or Agent , toggle on Use your Google Gemini - Key . \n Enter your API key. \n Save configuration. \n\n\n"]}' + > rag > advanced > bring your own anthropic acct\n\n Prerequisites \n \n You + have an active Anthropic account (https://console.anthropic.com/) \n Billing + is enabled in your Anthropic console. \n You have access to Progress Agentic + RAG. \n \n Generate & Locate Your API Key \n \n Expand the sidebar on the top + left hand corner. \n\n\n", "## docs > ingestion > how to > integrate nextjs\n\n + ```js \n const { Nuclia } = require( @nuclia/core ); \n require( localstorage-polyfill + ); \n require( isomorphic-unfetch ); \n const nuclia = new Nuclia({ \n backend: + https://accounts.progress.cloud/api , \n zone: europe-1 , \n knowledgeBox: , + \n apiKey: , \n }); \n // code to push data to Agentic RAG (detailed later) + \n ``` \n As you can see, you need to provide a Agentic RAG API key. An API + key is necessary when adding or modifying contents in a knowledge box. You can + get your API key in the Agentic RAG Dashboard, in the API keys section: \n\n\n", + "## docs > develop > nua\n\n \n id: nua \n title: Nuclia Understanding API \n + \n Using the Nuclia Understanding API \n The Nuclia Understanding API (NUA) + allows you to process data outside of a Knowledge Box. It is a set of endpoints + that allow you to send data to the Progress Agentic RAG platform for processing, + or to make calls to models to generate text, summaries, or other outputs. The + information is stored temporarily for the duration of the processing, nothing + remains in the ProgressAgentic RAG cloud infrastructure. \n\n\n", "## docs > + rag > advanced > connect your own azure openai acct\n\n 6. Configure Azure OpenAI + in Progress Agentic RAG \n This step connects your deployed model to Progress + Agentic RAG. \n Required Configuration Values \n | Field | Source | \n | --------------- + | ------- | \n | API Key | Foundry | \n | Endpoint URL | Foundry | \n | Deployment + Name | Foundry | \n | Model Name | Foundry | \n Steps \n \n\n\n", "## docs > + rag > advanced > connect gemini keys\n\n \n Finalize Connection \n \n Navigate + to the Progress Agentic RAG dashboard. \n When selecting an LLM in AI models + or Agent , toggle on Use your Google Gemini Key . \n Enter your API key. \n + Save configuration. \n\n\n", "## docs > develop > nua\n\n Click on NUA keys + . \n Click on the Create new Progress Agentic RAG Understanding API key button. + \n \n Fill out the form and submit it. \n \n \n Using the Nuclia API /api/v1/account/{your_account}/nua_client + endpoint (see Reference). \n\n\n"]}' headers: Accept: - '*/*' @@ -1085,7 +1031,7 @@ interactions: Connection: - keep-alive Content-Length: - - '5062' + - '4820' Content-Type: - application/json Host: @@ -1098,7 +1044,7 @@ interactions: uri: https://europe-1.dp.progress.cloud/api/v1/predict/remi response: body: - string: '{"time":2.1646599769592285,"answer_relevance":null,"context_relevance":[],"groundedness":[2,4,0,0,0,0,0,0,0,0,0]}' + string: '{"time":0.4446592330932617,"answer_relevance":null,"context_relevance":[],"groundedness":[5,2,0,0,0,0,0,0,0,0,0]}' headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 @@ -1109,26 +1055,27 @@ interactions: content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:40 GMT + - Wed, 05 Aug 2026 07:25:18 GMT nuclia-learning-model: - Llama-REMi-v1 via: - 1.1 google x-envoy-upstream-service-time: - - '2170' + - '454' x-nuclia-trace-id: - - 4f866411a0467e15aa654bca62c614a2 + - ed4f312ee47151398f4b748e3bf1eb8a status: code: 200 message: OK - request: body: '{"user_id": "arag_evaluate", "question": "What is Progress Agentic RAG?", - "answer": "Progress Agentic RAG is an API that indexes and processes various - types of data, including audio and video files, to enhance applications with - advanced search capabilities. It utilizes natural language processing and machine - learning to understand user intent and deliver relevant search results. Additionally, - it provides AI search and generative answers on unstructured data, supporting - multiple languages and data sources.", "contexts": null}' + "answer": "Progress Agentic RAG is an API designed to enhance applications with + advanced search capabilities by indexing and processing various types of data, + including audio and video files. It employs natural language processing and + machine learning to comprehend the searcher''s intent and deliver relevant results. + Key features include automatic indexing of page contents and integration with + various AI models to generate answers and insights from unstructured data.", + "contexts": null}' headers: Accept: - '*/*' @@ -1137,7 +1084,7 @@ interactions: Connection: - keep-alive Content-Length: - - '523' + - '557' Content-Type: - application/json Host: @@ -1150,26 +1097,26 @@ interactions: uri: https://europe-1.dp.progress.cloud/api/v1/predict/remi response: body: - string: '{"time":2.300419330596924,"answer_relevance":{"score":4,"reason":""},"context_relevance":[],"groundedness":[]}' + string: '{"time":0.7433090209960938,"answer_relevance":{"score":5,"reason":""},"context_relevance":[],"groundedness":[]}' headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Content-Length: - - '110' + - '111' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:40 GMT + - Wed, 05 Aug 2026 07:25:18 GMT nuclia-learning-model: - Llama-REMi-v1 via: - 1.1 google x-envoy-upstream-service-time: - - '2306' + - '749' x-nuclia-trace-id: - - 03610131d50c3d96279e90d11cde26e9 + - a69032f75b09611d823f3108210f9a24 status: code: 200 message: OK diff --git a/agents/remi/tests/cassettes/test_remi/test_remi[partial_answers].yaml b/agents/remi/tests/cassettes/test_remi/test_remi[partial_answers].yaml index 55b4ee72..dfffc513 100644 --- a/agents/remi/tests/cassettes/test_remi/test_remi[partial_answers].yaml +++ b/agents/remi/tests/cassettes/test_remi/test_remi[partial_answers].yaml @@ -18,7 +18,7 @@ interactions: uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: - string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"7fe77405-a6de-43cf-ac27-ac09f80b66c6","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' + string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"da1740fa-ab3e-4971-b374-7bb31b5dd325","account_id":"39f5fa6e-680a-475e-a757-812597e86d06","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' headers: Alt-Svc: - h3=":443"; 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Allowlist these if you restrict inbound traffic to your infrastructure. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n :::note \\n The current list of IP addresses is also available in machine-readable - format: JSON | YAML. These lists may change over time, so we recommend periodically - fetching and applying updates to your firewall rules to ensure uninterrupted - service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall - restricts network traffic, you may need to allowlist the following IP addresses. - They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | - --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 - | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 - | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- - | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n - | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 - | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | - 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 - | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 - | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United - States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- - | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 - | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS - PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately - through an AWS endpoint service (AWS PrivateLink) instead of over the public - internet, allowing connections to be established from your VPC without traversing - public IP addresses. This option is not available through self-service configuration. - Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests - on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent - \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful - tool that enhances the capabilities of traditional retrieval-augmented generation - (RAG) systems. Regular RAG's fixed search-then-generate process is limiting - for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Different models can be chosen for different tasks: \\n \\n Context validation - happens when the Prune context option is enabled (recommended), we recommend - using a fast model - planning or the execution model (depending on the planning - mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Note: the rephrasing model is only used in more complex workflow, it can - be ignored in the present case. \\n Finally, add a Summarize agent in the - Generation step to generate a final answer from the retrieved information. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - The Smart Agent plans the answer: picks the most appropriate sources, splits - the question into sub-questions, evaluates relevancy, and iterates autonomously - until the information is sufficient. \\n Basic usage \\n To set up a Smart - Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, - etc.) in the Sources section of the left menu. Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. It will be slower but more accurate when processing - complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Also select the proper function for each registered agent, depending on the - type of source (MCP agents will not need one, the functions are provided dynamically - by the MCP server). \\n In the Smart Agent configuration, you can select the - planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - In the Summarize Agent, enable the Conversational mode. This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. You can embed it in - your website or application, and it will provide a chat user interface for - interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Go to the Widgets section in the left menu, and click on Create widget to - create a new widget. You can customize its appearance, and then copy the generated - code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" + string: "{\"resources\":{\"7c9e318a8fcc4c9485b8639fdbe93b38\":{\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"slug\":\"docs-develop-nua-md\",\"title\":\"docs + > develop > nua\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-29T07:32:38.792855\",\"modified\":\"2026-07-29T07:32:38.792869\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Processing \\n Push a file \\n Processing data works in 2 steps: \\n + \\n First you will upload the file with /processing/upload, which returns + an upload token. \\n Then you will put this token in the processing queue + with /processing/push so the file is processed. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1627,\"end\":1890},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + json \\n { \\n webhook_config : { \\n uri : http://some.where/my-custom-webhook + , \\n headers : { \\n api-key : xxxxxxxxxx \\n } \\n } \\n } \\n Also, you + can choose to use a fixed uri on your token, and provide the headers in the + /push calls. In this case you don't need to provide the uri parameter. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":23,\"start\":9053,\"end\":9339},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Get a NUA key \\n In order to use the Nuclia Understanding API (NUA), you + first need to generate an API key. \\n There are two options to create an + API key: \\n \\n Using the Agentic RAG dashboard top-right menu: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":496,\"end\":703},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Note: If you have a Knowledge Box and want to use the predict endpoints, they + are proxied through the /api/v1/kb//predict endpoint. You will need to provide + a KB's regular authentication, a NUA API key will not be necessary.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":28,\"start\":10377,\"end\":10603},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The payload received from /requests is based on the fdbwriter.BrokerMessage + provided by writer.proto. \\n Streamed results \\n The /processing/requests//results + endpoint is similar but it returns directly the decoded results as a stream. + You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":18,\"start\":7453,\"end\":7716},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Processing happens asynchronously, so you will need to regularly check the + queue output using one of the two endpoints available to retrieve the results. + \\n Protobuffer results \\n The /processing/requests/ endpoint returns a protobuffer + payload with the processing results. You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":12,\"start\":5098,\"end\":5399},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: nua \\n title: Nuclia Understanding API \\n \\n Using the Nuclia Understanding + API \\n The Nuclia Understanding API (NUA) allows you to process data outside + of a Knowledge Box. It is a set of endpoints that allow you to send data to + the Progress Agentic RAG platform for processing, or to make calls to models + to generate text, summaries, or other outputs. The information is stored temporarily + for the duration of the processing, nothing remains in the ProgressAgentic + RAG cloud infrastructure. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":496},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests/' \\\\ + \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n The response is a JSON object containing + completed indicating if the processing is complete or not, and in case it + is,a response string. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":13,\"start\":5399,\"end\":5644},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n In Python, you can use nucliadb_protos to decode the results: \\n + ```python \\n import base64 \\n import requests \\n from nucliadb_protos.writer_pb2 + import BrokerMessage \\n processing_id = THE_PROCESSING_ID_YOU_RECEIVED_FROM_PUSH + \\n res = requests.get(f'https://europe-1.nuclia.cloud/api/v1/processing/requests/{processing_id}',headers={ + \\n X-NUCLIA-NUAKEY : Bearer YOUR_NUA_KEY , \\n }).json() \\n if payload in + res: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":16,\"start\":6812,\"end\":7224},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/push' \\\\ \\n + -X POST \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\\\ \\n -H 'Content-Type: + application/json' \\\\ \\n --data-raw '{ filefield :{ my_file_1 : eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.W8wfVj04aYicREYXRatCTb8F8-PD4Ph7MmiTliHi6DI + }}' \\n Push text \\n Instead of uploading a file and then pushing it to the + queue, you can also push some text directly to the queue. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":9,\"start\":2730,\"end\":3646},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + It may also be used to create (or delete) Knowledge Boxes via the API \u2013 + for example, if you need to automate Knowledge Box creation. In that case + you will need to select the Allow management of Knowledge Boxes checkbox during + the NUA key creation. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1170,\"end\":1420},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + /predict/rerank reranks a list of results to improve the relevance of the + top results. \\n /predict/sentence computes the embedding of a sentence. \\n + /predict/summarize summarizes a text. \\n \\n The calls must provides the + X-NUCLIA-NUAKEY header with your NUA key: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":26,\"start\":9847,\"end\":10108},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests//results' + \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n Moreover the data_types parameter + allows you to filter the results by data type. For example: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":19,\"start\":7716,\"end\":7926},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Here is a typical example: \\n shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/upload' + \\\\ \\n -X POST \\\\ \\n -H X-NUCLIA-NUAKEY: Bearer \\\\ \\n -H 'content-type: + ' \\\\ \\n -T /path/to/file \\n Will return something like: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":1890,\"end\":2109},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + :::note \\n If an error occurs when posting the result to the webhook URL, + the result is stored in the queue and can be retrieved by calling the /pull + endpoint (see previous section). The error message is appended to the result. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":24,\"start\":9339,\"end\":9568},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + pb = BrokerMessage() \\n pb.ParseFromString( \\n base64.b64decode(res[ payload + ]) \\n ) \\n print(pb) \\n else: \\n print('No payload') \\n ``` \\n For other + languages, Nuclia protobuffer models can be found on the NucliaDB GitHub repository. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":17,\"start\":7224,\"end\":7453},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Model calls \\n The predict endpoints offer various services: \\n + \\n /predict/chat makes a direct call to an LLM. \\n /predict/remi calls the + REMi model to measure the quality of a RAG response. \\n /predict/rephrase + rephrases a question to make it more suitable for a RAG query. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":25,\"start\":9568,\"end\":9847},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJ1cm46cHJveHkiLCJzdWIiOiJmaWxlIiwiYXVkIjoidXJuOnByb3h5IiwiZXhwIjoxNjU1ODkyMDgwLCJpYXQiOjE2NTU4ODg0ODAsImp0aSI6ImFmN2ZmYjU1ZjAxMjRlMzM5MmRjMDY5MmM2NWI5NzY3Iiwic2l6ZSI6ODk3LCJidWNrZXRfbmFtZSI6ImV1cm9wZS0xLXN0b3JhZ2UtcHJveHkiLCJ1cmkiOiIwZDg2YTFmYTcxN2Q0NDUxYTAwM2Q1NGIyNzM2YTA0ZSIsImRyaXZlciI6MCwiY29udGVudF90eXBlIjoiYXBwbGljYXRpb24vb2N0ZXQtc3RyZWFtIiwiZmlsZW5hbWUiOiIiLCJwYXNzd29yZCI6bnVsbCwibGFuZ3VhZ2UiOm51bGwsInNvdXJjZSI6MCwibWQ1IjpudWxsfQ.VItLa_fUen2Pt5W2440Bjwc7Zx64rv6mJnRMFIdao5o + \\n That is your upload token. Now you can push this token to the processing + queue with: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2109,\"end\":2730},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also at any level, if an attribute exceeds a certain size, it will be put + in a downloadable file and will be replaced in the document by a file pointer. + This will consist of { file : { uri : JWT_TOKEN }}. The rule is that if the + size of the message is greater than 1000000 characters, the biggest parts + will be moved to downloadable files. First, the compression process will target + vectors. If that is not enough, it will target large field metadata, and finally + it will target extracted text. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":15,\"start\":6315,\"end\":6812},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In this case, any time a new result is available Nuclia will post it (i.e. + make an actual POST call) to this URL, sending the protobuffer result as payload. + \\n To use a webhook, you will need to fill in the Webhook URL field in the + NUA key creation form when you create your key. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":21,\"start\":8236,\"end\":8517},\"fuzzy_result\":false}],\"facets\":{},\"query\":\"\",\"total\":5358,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - - h3=":443"; ma=2592000 + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - - '12993' + - '12190' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:28 GMT + - Wed, 05 Aug 2026 07:25:07 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '55' + - '51' x-nuclia-trace-id: - - 5761735d16d31f73be074f1acfe07daf + - 2ea9d8408bc51f8e84f136ddcbe7d60f status: code: 200 message: OK @@ -408,7 +351,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -416,31 +359,30 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration response: body: - string: '{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner - Content","related":"","text":"","uri":""},{"title":"Softcat","related":"","text":"","uri":""},{"title":"Sales - Enablement Assets","related":"","text":"","uri":""},{"title":"KO 26","related":"","text":"","uri":""},{"title":"Data - Sheets","related":"","text":"","uri":""},{"title":"Progress Agentic RAG Training - Materials 2026","related":"","text":"","uri":""}]}' + string: '{"resource_labelers_models":null,"paragraph_labelers_models":null,"intent_models":null,"visual_labeling":"disabled","ner_model":"multilingual","relation_model":"base","anonymization_model":"disabled","semantic_model":"multilingual-2024-05-06","semantic_models":["multilingual-2024-05-06"],"default_semantic_model":"multilingual-2024-05-06","semantic_graph_node_models":[],"default_semantic_graph_node_model":null,"semantic_graph_edge_models":[],"default_semantic_graph_edge_model":null,"semantic_vector_similarity":"DOT","semantic_vector_size":1024,"semantic_matryoshka_dims":[],"semantic_threshold":0.4,"generative_model":"chatgpt-azure-4o","user_keys":{"openai":null,"azure_openai":null,"mistral":null,"palm":null,"anthropic":null,"claude3":null,"anthropic_vertex":null,"anthropic_bedrock":null,"azure_mistral":null,"hf_llm":null,"hf_embedding":null,"azure_aii":null,"openai_compat":null},"user_prompts":{"openai":null,"azure_openai":{"system":"You + are an IT expert, express yourself like one. If you do not find an answer + in the context, please say \"Right now I don''t have enough context to answer + your question. Please contact us at support@nuclia.com\". 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Allowlist these if you restrict inbound traffic to your infrastructure. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n :::note \\n The current list of IP addresses is also available in machine-readable - format: JSON | YAML. These lists may change over time, so we recommend periodically - fetching and applying updates to your firewall rules to ensure uninterrupted - service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall - restricts network traffic, you may need to allowlist the following IP addresses. - They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | - --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 - | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 - | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- - | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n - | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 - | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | - 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 - | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 - | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United - States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- - | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 - | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS - PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately - through an AWS endpoint service (AWS PrivateLink) instead of over the public - internet, allowing connections to be established from your VPC without traversing - public IP addresses. This option is not available through self-service configuration. - Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests - on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent - \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful - tool that enhances the capabilities of traditional retrieval-augmented generation - (RAG) systems. Regular RAG's fixed search-then-generate process is limiting - for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Different models can be chosen for different tasks: \\n \\n Context validation - happens when the Prune context option is enabled (recommended), we recommend - using a fast model - planning or the execution model (depending on the planning - mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Note: the rephrasing model is only used in more complex workflow, it can - be ignored in the present case. \\n Finally, add a Summarize agent in the - Generation step to generate a final answer from the retrieved information. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - The Smart Agent plans the answer: picks the most appropriate sources, splits - the question into sub-questions, evaluates relevancy, and iterates autonomously - until the information is sufficient. \\n Basic usage \\n To set up a Smart - Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, - etc.) in the Sources section of the left menu. Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. It will be slower but more accurate when processing - complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Also select the proper function for each registered agent, depending on the - type of source (MCP agents will not need one, the functions are provided dynamically - by the MCP server). \\n In the Smart Agent configuration, you can select the - planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - In the Summarize Agent, enable the Conversational mode. This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. You can embed it in - your website or application, and it will provide a chat user interface for - interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Go to the Widgets section in the left menu, and click on Create widget to - create a new widget. You can customize its appearance, and then copy the generated - code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{\"/k\":{\"/k/text\":5294}},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"fulltext\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-resources\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-search\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-rag-lab\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"account-arag\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-kv-schemas\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"user-profile\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-users\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-widgets\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-remi-analytics\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"agent-users\",\"labels\":[]}],\"facets\":{},\"query\":\"\",\"total\":2013,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" 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NUAClientEditPayload\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"eo\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-28T13:27:28.455426\",\"modified\":\"2026-08-03T13:14:53.788626\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"d97695fece7948c59cb9b95404b3a5f9\":{\"id\":\"d97695fece7948c59cb9b95404b3a5f9\",\"slug\":\"docs-management-nucliadb-deploy-05-access-md\",\"title\":\"docs + > management > nucliadb > deploy > 05 access\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-16T08:13:36.926639\",\"modified\":\"2026-07-16T08:13:36.926650\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Processing \\n Push a file \\n Processing data works in 2 steps: \\n + \\n First you will upload the file with /processing/upload, which returns + an upload token. \\n Then you will put this token in the processing queue + with /processing/push so the file is processed. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1627,\"end\":1890},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + json \\n { \\n webhook_config : { \\n uri : http://some.where/my-custom-webhook + , \\n headers : { \\n api-key : xxxxxxxxxx \\n } \\n } \\n } \\n Also, you + can choose to use a fixed uri on your token, and provide the headers in the + /push calls. In this case you don't need to provide the uri parameter. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":23,\"start\":9053,\"end\":9339},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Get a NUA key \\n In order to use the Nuclia Understanding API (NUA), you + first need to generate an API key. \\n There are two options to create an + API key: \\n \\n Using the Agentic RAG dashboard top-right menu: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":496,\"end\":703},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Note: If you have a Knowledge Box and want to use the predict endpoints, they + are proxied through the /api/v1/kb//predict endpoint. You will need to provide + a KB's regular authentication, a NUA API key will not be necessary.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":28,\"start\":10377,\"end\":10603},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The payload received from /requests is based on the fdbwriter.BrokerMessage + provided by writer.proto. \\n Streamed results \\n The /processing/requests//results + endpoint is similar but it returns directly the decoded results as a stream. + You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":18,\"start\":7453,\"end\":7716},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Processing happens asynchronously, so you will need to regularly check the + queue output using one of the two endpoints available to retrieve the results. + \\n Protobuffer results \\n The /processing/requests/ endpoint returns a protobuffer + payload with the processing results. You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":12,\"start\":5098,\"end\":5399},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: nua \\n title: Nuclia Understanding API \\n \\n Using the Nuclia Understanding + API \\n The Nuclia Understanding API (NUA) allows you to process data outside + of a Knowledge Box. It is a set of endpoints that allow you to send data to + the Progress Agentic RAG platform for processing, or to make calls to models + to generate text, summaries, or other outputs. The information is stored temporarily + for the duration of the processing, nothing remains in the ProgressAgentic + RAG cloud infrastructure. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":496},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests/' \\\\ + \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n The response is a JSON object containing + completed indicating if the processing is complete or not, and in case it + is,a response string. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":13,\"start\":5399,\"end\":5644},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n In Python, you can use nucliadb_protos to decode the results: \\n + ```python \\n import base64 \\n import requests \\n from nucliadb_protos.writer_pb2 + import BrokerMessage \\n processing_id = THE_PROCESSING_ID_YOU_RECEIVED_FROM_PUSH + \\n res = requests.get(f'https://europe-1.nuclia.cloud/api/v1/processing/requests/{processing_id}',headers={ + \\n X-NUCLIA-NUAKEY : Bearer YOUR_NUA_KEY , \\n }).json() \\n if payload in + res: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":16,\"start\":6812,\"end\":7224},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/push' \\\\ \\n + -X POST \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\\\ \\n -H 'Content-Type: + application/json' \\\\ \\n --data-raw '{ filefield :{ my_file_1 : eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.W8wfVj04aYicREYXRatCTb8F8-PD4Ph7MmiTliHi6DI + }}' \\n Push text \\n Instead of uploading a file and then pushing it to the + queue, you can also push some text directly to the queue. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":9,\"start\":2730,\"end\":3646},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + It may also be used to create (or delete) Knowledge Boxes via the API \u2013 + for example, if you need to automate Knowledge Box creation. In that case + you will need to select the Allow management of Knowledge Boxes checkbox during + the NUA key creation. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1170,\"end\":1420},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + /predict/rerank reranks a list of results to improve the relevance of the + top results. \\n /predict/sentence computes the embedding of a sentence. \\n + /predict/summarize summarizes a text. \\n \\n The calls must provides the + X-NUCLIA-NUAKEY header with your NUA key: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":26,\"start\":9847,\"end\":10108},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests//results' + \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n Moreover the data_types parameter + allows you to filter the results by data type. For example: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":19,\"start\":7716,\"end\":7926},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Here is a typical example: \\n shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/upload' + \\\\ \\n -X POST \\\\ \\n -H X-NUCLIA-NUAKEY: Bearer \\\\ \\n -H 'content-type: + ' \\\\ \\n -T /path/to/file \\n Will return something like: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":1890,\"end\":2109},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + :::note \\n If an error occurs when posting the result to the webhook URL, + the result is stored in the queue and can be retrieved by calling the /pull + endpoint (see previous section). The error message is appended to the result. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":24,\"start\":9339,\"end\":9568},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + pb = BrokerMessage() \\n pb.ParseFromString( \\n base64.b64decode(res[ payload + ]) \\n ) \\n print(pb) \\n else: \\n print('No payload') \\n ``` \\n For other + languages, Nuclia protobuffer models can be found on the NucliaDB GitHub repository. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":17,\"start\":7224,\"end\":7453},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Model calls \\n The predict endpoints offer various services: \\n + \\n /predict/chat makes a direct call to an LLM. \\n /predict/remi calls the + REMi model to measure the quality of a RAG response. \\n /predict/rephrase + rephrases a question to make it more suitable for a RAG query. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":25,\"start\":9568,\"end\":9847},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJ1cm46cHJveHkiLCJzdWIiOiJmaWxlIiwiYXVkIjoidXJuOnByb3h5IiwiZXhwIjoxNjU1ODkyMDgwLCJpYXQiOjE2NTU4ODg0ODAsImp0aSI6ImFmN2ZmYjU1ZjAxMjRlMzM5MmRjMDY5MmM2NWI5NzY3Iiwic2l6ZSI6ODk3LCJidWNrZXRfbmFtZSI6ImV1cm9wZS0xLXN0b3JhZ2UtcHJveHkiLCJ1cmkiOiIwZDg2YTFmYTcxN2Q0NDUxYTAwM2Q1NGIyNzM2YTA0ZSIsImRyaXZlciI6MCwiY29udGVudF90eXBlIjoiYXBwbGljYXRpb24vb2N0ZXQtc3RyZWFtIiwiZmlsZW5hbWUiOiIiLCJwYXNzd29yZCI6bnVsbCwibGFuZ3VhZ2UiOm51bGwsInNvdXJjZSI6MCwibWQ1IjpudWxsfQ.VItLa_fUen2Pt5W2440Bjwc7Zx64rv6mJnRMFIdao5o + \\n That is your upload token. Now you can push this token to the processing + queue with: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2109,\"end\":2730},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also at any level, if an attribute exceeds a certain size, it will be put + in a downloadable file and will be replaced in the document by a file pointer. + This will consist of { file : { uri : JWT_TOKEN }}. The rule is that if the + size of the message is greater than 1000000 characters, the biggest parts + will be moved to downloadable files. First, the compression process will target + vectors. If that is not enough, it will target large field metadata, and finally + it will target extracted text. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":15,\"start\":6315,\"end\":6812},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In this case, any time a new result is available Nuclia will post it (i.e. + make an actual POST call) to this URL, sending the protobuffer result as payload. + \\n To use a webhook, you will need to fill in the Webhook URL field in the + NUA key creation form when you create your key. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":21,\"start\":8236,\"end\":8517},\"fuzzy_result\":false}],\"facets\":{\"/k\":{\"/k/text\":5358}},\"query\":\"\",\"total\":5358,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"fulltext\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"14b3bd967e2b44ba98372a8d9a0716b6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"14b3bd967e2b44ba98372a8d9a0716b6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"78943baafe6a49848b4b29e683eaa983\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"78943baafe6a49848b4b29e683eaa983\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b5eec709afcf4068a4211a16f1a79576\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b5eec709afcf4068a4211a16f1a79576\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5c4166eea30d4b329fb3f141e395781a\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5c4166eea30d4b329fb3f141e395781a\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"09305118c7314e1483068fb9a588578f\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"09305118c7314e1483068fb9a588578f\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"9ae2d3a90d0d452db50f170c535905d4\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"9ae2d3a90d0d452db50f170c535905d4\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"831a4c9bcc2e49d6a1f2a84c811f4fb6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"831a4c9bcc2e49d6a1f2a84c811f4fb6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"d97695fece7948c59cb9b95404b3a5f9\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"d97695fece7948c59cb9b95404b3a5f9\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5ae74950b55c4d60b754fa706314b24a\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5ae74950b55c4d60b754fa706314b24a\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]}],\"facets\":{},\"query\":\"\",\"total\":2029,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - h3=":443"; ma=2592000 Content-Length: - - '16898' + - '19708' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:28 GMT + - Wed, 05 Aug 2026 07:25:08 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '55' + - '63' x-nuclia-trace-id: - - 7ac47bac47993c16630f51e1c16ed3ba + - 33c8f2bcfd28b1d84522dcef25da6097 status: code: 200 message: OK @@ -600,7 +537,7 @@ interactions: Content-Length: - '114' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -608,7 +545,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/ask + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/ask response: body: string: "{\"item\":{\"type\":\"answer\",\"text\":\"Progress\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" @@ -616,137 +553,118 @@ interactions: R\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\"AG\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" is\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" an\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" API\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" that\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - indexes\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - processes\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" various\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - types\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" of\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\",\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + enhances\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" applications\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + with\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" powerful\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + search\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" capabilities\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + by\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" indexing\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" processing\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + various\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" types\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + of\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\",\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" including\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" audio\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" video\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - files\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\",\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - to\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" enhance\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - applications\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" with\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - advanced\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" search\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - capabilities\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + files\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" It\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" utilizes\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" natural\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" language\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" processing\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" machine\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" learning\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" to\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" understand\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - user\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" intent\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" deliver\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - relevant\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" search\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + the\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" search\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\"er's\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + intent\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + deliver\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" relevant\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" results\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" Additionally\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\",\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - it\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" provides\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - AI\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" search\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" gener\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\"ative\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - answers\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" on\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - un\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\"structured\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\",\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - supporting\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" multiple\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - languages\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" sources\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"retrieval\",\"results\":{\"resources\":{\"399b7a3a66a0468580fb0fd752fc40cd\":{\"id\":\"399b7a3a66a0468580fb0fd752fc40cd\",\"slug\":\"docs-rag-advanced-connect-gemini-keys-md\",\"title\":\"docs - > rag > advanced > connect gemini keys\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-04T13:46:30.392047\",\"modified\":\"2026-06-09T08:07:41.267808\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"399b7a3a66a0468580fb0fd752fc40cd/t/page/846-1053\":{\"score\":0.5691343545913696,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\" - \\n Finalize Connection \\n \\n Navigate to the Progress Agentic RAG dashboard. - \\n When selecting an LLM in AI models or Agent , toggle on Use your Google - Gemini Key . \\n Enter your API key. \\n Save configuration. \\n\",\"id\":\"399b7a3a66a0468580fb0fd752fc40cd/t/page/846-1053\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":846,\"end\":1053,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"399b7a3a66a0468580fb0fd752fc40cd/t/page/301-618\":{\"score\":0.3698839247226715,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" - Prerequisites \\n \\n You have an active Google account with access to Google - AI Studio (https://aistudio.google.com/) \\n You have access to Progress Agentic - RAG. \\n \\n Generate & Locate Your API Key \\n \\n Navigate to Google AI - Studio (https://aistudio.google.com/) \\n Click on Get API key in the left - sidebar at the bottom. \\n\",\"id\":\"399b7a3a66a0468580fb0fd752fc40cd/t/page/301-618\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":301,\"end\":618,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"fd64185262eb403c82456d7111ed3345\":{\"id\":\"fd64185262eb403c82456d7111ed3345\",\"slug\":\"docs-rag-advanced-byok-aws-berock-assume-role-md\",\"title\":\"docs - > rag > advanced > byok aws berock assume role\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-18T13:54:44.059147\",\"modified\":\"2026-06-09T08:07:40.547430\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"fd64185262eb403c82456d7111ed3345/t/page/2483-2747\":{\"score\":0.38242971897125244,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" - For more details on these requirements, please refer to the official AWS Bedrock - Model Access Documentation. \\n Generate Configuration in Progress Agentic - RAG \\n \\n \\n Log in to Progress Agentic RAG and navigate to Manage Account - > Models > AWS Bedrock Integration. \\n\",\"id\":\"fd64185262eb403c82456d7111ed3345/t/page/2483-2747\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2483,\"end\":2747,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"22f855bc36c34e6c82182ebd33d3dbc4\":{\"id\":\"22f855bc36c34e6c82182ebd33d3dbc4\",\"slug\":\"docs-ingestion-how-to-integrate-strapi-md\",\"title\":\"docs - > ingestion > how to > integrate strapi\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:04.222223\",\"modified\":\"2026-06-26T08:59:45.897854\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"22f855bc36c34e6c82182ebd33d3dbc4/t/page/300-661\":{\"score\":0.974821150302887,\"score_type\":\"RERANKER\",\"order\":0,\"text\":\" - Agentic RAG is the best search API to do it! \\n Agentic RAG is an API able - to index and process any kind of data, including audio and video files, to - boost applications with powerful search capability, using natural language - processing and machine learning to understand the searcher's intent and return - results that are more relevant to the searcher's needs. \\n\",\"id\":\"22f855bc36c34e6c82182ebd33d3dbc4/t/page/300-661\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":300,\"end\":661,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"252561e259d84800889a576b1e8a35c9\":{\"id\":\"252561e259d84800889a576b1e8a35c9\",\"slug\":\"docs-rag-advanced-connect-vertex-ai-acct-md\",\"title\":\"docs - > rag > advanced > connect vertex ai acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-26T08:02:00.906568\",\"modified\":\"2026-06-09T08:07:44.679374\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"252561e259d84800889a576b1e8a35c9/t/page/0-328\":{\"score\":0.7316341996192932,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\" + it\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" offers\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + features\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" like\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + automatic\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" indexing\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + of\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" page\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + contents\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + integration\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" with\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + various\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" AI\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + models\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" for\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + generating\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" answers\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + and\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" processing\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" + data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"retrieval\",\"results\":{\"resources\":{\"0d4445df40ee4daeb4bb6d609f2b64b1\":{\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1\",\"slug\":\"docs-rag-advanced-connect-your-own-azure-openai-acct-md\",\"title\":\"docs + > rag > advanced > connect your own azure openai acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-15T14:36:48.862567\",\"modified\":\"2026-06-09T08:07:50.247127\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/3184-3468\":{\"score\":0.8507168292999268,\"score_type\":\"RERANKER\",\"order\":3,\"text\":\" + Select Azure OpenAI as the LLM provider \\n Enable Use your own Azure OpenAI + key \\n Enter: \\n API Key \\n Endpoint URL \\n Deployment Name \\n Model + Name \\n Save the configuration \\n Test answer generation \\n \\n Outcome + \\n \\n Progress Agentic RAG uses your Azure-hosted LLM for answer generation + \\n \",\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/3184-3468\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":3184,\"end\":3468,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/2859-3184\":{\"score\":0.36161547899246216,\"score_type\":\"RERANKER\",\"order\":16,\"text\":\" + 6. Configure Azure OpenAI in Progress Agentic RAG \\n This step connects your + deployed model to Progress Agentic RAG. \\n Required Configuration Values + \\n | Field | Source | \\n | --------------- | ------- | \\n | API Key | Foundry + | \\n | Endpoint URL | Foundry | \\n | Deployment Name | Foundry | \\n | Model + Name | Foundry | \\n Steps \\n \\n\",\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/2859-3184\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2859,\"end\":3184,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"9e6238e3377d41699643ba954dd500fa\":{\"id\":\"9e6238e3377d41699643ba954dd500fa\",\"slug\":\"docs-ingestion-how-to-extract-strategies-md\",\"title\":\"docs + > ingestion > how to > extract strategies\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-06-13T08:13:07.100304\",\"modified\":\"2026-06-09T08:18:12.970227\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"9e6238e3377d41699643ba954dd500fa/t/page/2317-2576\":{\"score\":0.5746932029724121,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" + Apart from cutting-edge table and text extraction capabilities, \U0001F415 + pagehound-v1 is capable of extracting embedded images from full page scans, + making it possible to apply Progress' Agentic RAG image processing pipeline + to them, enabling search capabilities. \\n\",\"id\":\"9e6238e3377d41699643ba954dd500fa/t/page/2317-2576\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2317,\"end\":2576,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"7a58f44f10fc423f83239c0b733057c1\":{\"id\":\"7a58f44f10fc423f83239c0b733057c1\",\"slug\":\"docs-develop-dotnet-sdk-index-md\",\"title\":\"docs + > develop > dotnet sdk > index\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"sk\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-24T16:03:48.411403\",\"modified\":\"2026-06-09T08:17:38.462625\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"7a58f44f10fc423f83239c0b733057c1/t/page/0-226\":{\"score\":0.6728693246841431,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\"Progress.Nuclia + .NET SDK \\n A comprehensive .NET SDK for Progress Agentic RAG's NucliaDb, + providing RAG (Retrieval-Augmented Generation) capabilities with knowledge + base management, AI-powered search, and resource operations. \\n\",\"id\":\"7a58f44f10fc423f83239c0b733057c1/t/page/0-226\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":226,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e6605960cc46412da0e5e5404f511d53\":{\"id\":\"e6605960cc46412da0e5e5404f511d53\",\"slug\":\"docs-intro-md\",\"title\":\"docs + > intro\",\"summary\":\"When teams knit together vector databases, machine + learning pipelines, large language models, ranking algorithms, and interfaces + into specific products, they are only providing one or two of these capabilities.\\nNuclea + delivers all four out of the box.\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"sr\",\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2023-08-03T08:57:16.630817\",\"modified\":\"2026-06-09T08:07:20.822319\",\"last_seqid\":1741334,\"last_account_seq\":67150,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"e6605960cc46412da0e5e5404f511d53/t/page/0-301\":{\"score\":0.689723789691925,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" + \\n id: intro \\n slug: / \\n title: Agentic RAG documentation \\n \\n Agentic + RAG, the RAG-as-a-Service platform \\n Agentic RAG automatically delivers + AI search and Generative Answers on top of your unstructured data, and provides + knowledge in the form of trusted answers, in any language, and from any data. + \\n\",\"id\":\"e6605960cc46412da0e5e5404f511d53/t/page/0-301\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":301,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"252561e259d84800889a576b1e8a35c9\":{\"id\":\"252561e259d84800889a576b1e8a35c9\",\"slug\":\"docs-rag-advanced-connect-vertex-ai-acct-md\",\"title\":\"docs + > rag > advanced > connect vertex ai acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-26T08:02:00.906568\",\"modified\":\"2026-06-09T08:07:44.679374\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"252561e259d84800889a576b1e8a35c9/t/page/0-328\":{\"score\":0.7316341996192932,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" \\n id: connect-vertex-ai-acct \\n title: Connect your own Google Vertex AI \\n \\n Integrating Google Vertex AI with Progress Agentic RAG \\n This guide provides step-by-step instructions for deploying Google Vertex AI and integrating it with Progress Agentic RAG to enable AI-powered search capabilities using - Google's Gemini models. \\n\",\"id\":\"252561e259d84800889a576b1e8a35c9/t/page/0-328\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":328,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"252561e259d84800889a576b1e8a35c9/t/page/3243-3725\":{\"score\":0.3472050130367279,\"score_type\":\"RERANKER\",\"order\":15,\"text\":\" - Troubleshooting \\n If you encounter issues during the integration process: - \\n \\n Authentication errors: Verify that the JSON credentials file is correctly - formatted and contains valid credentials \\n Permission errors: Ensure the - service account has the necessary Vertex AI permissions \\n Region errors: - Confirm that the region specified in Progress Agentic RAG matches your Vertex - AI configuration \\n No response: Check your Google Cloud billing account - status and API quota limits \\n \\n \\n\",\"id\":\"252561e259d84800889a576b1e8a35c9/t/page/3243-3725\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":3243,\"end\":3725,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"36489cbab30247fea4edcbe8ba6d93d6\":{\"id\":\"36489cbab30247fea4edcbe8ba6d93d6\",\"slug\":\"docs-management-authentication-mdx\",\"title\":\"docs - > management > authentication.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:46.369763\",\"modified\":\"2026-06-26T08:59:51.921782\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"36489cbab30247fea4edcbe8ba6d93d6/t/page/4972-5293\":{\"score\":0.3301471471786499,\"score_type\":\"RERANKER\",\"order\":16,\"text\":\" - Generate and Use User Key \\n \\n \\n This method is meant to be used from - the Agentic RAG frontend applications but if you need it for testing purpose, - you can obtain a token by going to [https://rag.progress.cloud/redirect?display=token] - \\n Then in the API calls, include it in the `Authorization` header as a Bearer - token: \\n\",\"id\":\"36489cbab30247fea4edcbe8ba6d93d6/t/page/4972-5293\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":4972,\"end\":5293,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"bef9fbb057dc46fa9c2bf121a7967efa\":{\"id\":\"bef9fbb057dc46fa9c2bf121a7967efa\",\"slug\":\"docs-rag-how-to-remi-md\",\"title\":\"docs - > rag > how to > remi\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:59.392903\",\"modified\":\"2026-06-26T08:59:41.701319\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"bef9fbb057dc46fa9c2bf121a7967efa/t/page/1594-1930\":{\"score\":0.32713067531585693,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\" + Google's Gemini models. \\n\",\"id\":\"252561e259d84800889a576b1e8a35c9/t/page/0-328\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":328,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"fd64185262eb403c82456d7111ed3345\":{\"id\":\"fd64185262eb403c82456d7111ed3345\",\"slug\":\"docs-rag-advanced-byok-aws-berock-assume-role-md\",\"title\":\"docs + > rag > advanced > byok aws berock assume role\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-18T13:54:44.059147\",\"modified\":\"2026-06-09T08:07:40.547430\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"fd64185262eb403c82456d7111ed3345/t/page/2483-2747\":{\"score\":0.38242971897125244,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" + For more details on these requirements, please refer to the official AWS Bedrock + Model Access Documentation. \\n Generate Configuration in Progress Agentic + RAG \\n \\n \\n Log in to Progress Agentic RAG and navigate to Manage Account + > Models > AWS Bedrock Integration. \\n\",\"id\":\"fd64185262eb403c82456d7111ed3345/t/page/2483-2747\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2483,\"end\":2747,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"bef9fbb057dc46fa9c2bf121a7967efa\":{\"id\":\"bef9fbb057dc46fa9c2bf121a7967efa\",\"slug\":\"docs-rag-how-to-remi-md\",\"title\":\"docs + > rag > how to > remi\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:59.392903\",\"modified\":\"2026-06-26T08:59:41.701319\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"bef9fbb057dc46fa9c2bf121a7967efa/t/page/1594-1930\":{\"score\":0.32713067531585693,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\" \\n https://.dp.progress.cloud/api/v1/kb/ \\n \\n \\n Knowledge Box API Key: The This key is used to interact with the Knowledge Box API. To obtain this key, you can follow the instructions here. \\n \\n \\n NUA API Key: This key is used to interact with the Agentic RAG Understanding API. To obtain this - key, you can follow the instructions here. \\n\",\"id\":\"bef9fbb057dc46fa9c2bf121a7967efa/t/page/1594-1930\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1594,\"end\":1930,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"007b445866574d7ca69891d388663cc6\":{\"id\":\"007b445866574d7ca69891d388663cc6\",\"slug\":\"docs-management-security-5-public-ips-md\",\"title\":\"docs - > management > security > 5 public ips\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-03T09:28:57.937064\",\"modified\":\"2026-07-03T09:28:57.937076\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"007b445866574d7ca69891d388663cc6/t/page/418-652\":{\"score\":0.8682692646980286,\"score_type\":\"RERANKER\",\"order\":2,\"text\":\" + key, you can follow the instructions here. \\n\",\"id\":\"bef9fbb057dc46fa9c2bf121a7967efa/t/page/1594-1930\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1594,\"end\":1930,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"399b7a3a66a0468580fb0fd752fc40cd\":{\"id\":\"399b7a3a66a0468580fb0fd752fc40cd\",\"slug\":\"docs-rag-advanced-connect-gemini-keys-md\",\"title\":\"docs + > rag > advanced > connect gemini keys\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-04T13:46:30.392047\",\"modified\":\"2026-06-09T08:07:41.267808\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"399b7a3a66a0468580fb0fd752fc40cd/t/page/846-1053\":{\"score\":0.5691343545913696,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\" + \\n Finalize Connection \\n \\n Navigate to the Progress Agentic RAG dashboard. + \\n When selecting an LLM in AI models or Agent , toggle on Use your Google + Gemini Key . \\n Enter your API key. \\n Save configuration. \\n\",\"id\":\"399b7a3a66a0468580fb0fd752fc40cd/t/page/846-1053\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":846,\"end\":1053,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"399b7a3a66a0468580fb0fd752fc40cd/t/page/301-618\":{\"score\":0.3698839247226715,\"score_type\":\"RERANKER\",\"order\":15,\"text\":\" + Prerequisites \\n \\n You have an active Google account with access to Google + AI Studio (https://aistudio.google.com/) \\n You have access to Progress Agentic + RAG. \\n \\n Generate & Locate Your API Key \\n \\n Navigate to Google AI + Studio (https://aistudio.google.com/) \\n Click on Get API key in the left + sidebar at the bottom. \\n\",\"id\":\"399b7a3a66a0468580fb0fd752fc40cd/t/page/301-618\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":301,\"end\":618,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"46477109e5db4b198b08d39cce0d363c\":{\"id\":\"46477109e5db4b198b08d39cce0d363c\",\"slug\":\"docs-management-security-05-public-ips-md\",\"title\":\"docs + > management > security > 05 public ips\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-16T08:13:28.912083\",\"modified\":\"2026-07-16T08:13:28.912097\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"46477109e5db4b198b08d39cce0d363c/t/page/418-652\":{\"score\":0.8682692646980286,\"score_type\":\"RERANKER\",\"order\":2,\"text\":\" Outbound \u2014 the source IP addresses that Progress Agentic RAG uses when making connections to your systems (e.g., webhooks, sync agents, or other integrations). Allowlist these if you restrict inbound traffic to your infrastructure. - \\n\",\"id\":\"007b445866574d7ca69891d388663cc6/t/page/418-652\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":418,\"end\":652,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"007b445866574d7ca69891d388663cc6/t/page/208-418\":{\"score\":0.6285214424133301,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\" + \\n\",\"id\":\"46477109e5db4b198b08d39cce0d363c/t/page/418-652\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":418,\"end\":652,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"46477109e5db4b198b08d39cce0d363c/t/page/208-418\":{\"score\":0.6285214424133301,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"id\":\"007b445866574d7ca69891d388663cc6/t/page/208-418\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":208,\"end\":418,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"73c3dde3c4cc45c7a9aabaf19d1578a1\":{\"id\":\"73c3dde3c4cc45c7a9aabaf19d1578a1\",\"slug\":\"docs-rag-advanced-bring-your-own-anthropic-acct-md\",\"title\":\"docs - > rag > advanced > bring your own anthropic acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-20T14:58:49.310838\",\"modified\":\"2026-06-09T08:07:46.863851\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"73c3dde3c4cc45c7a9aabaf19d1578a1/t/page/292-560\":{\"score\":0.503440797328949,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\" + and need to reach our services (e.g., calling our APIs). \\n\",\"id\":\"46477109e5db4b198b08d39cce0d363c/t/page/208-418\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":208,\"end\":418,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"36489cbab30247fea4edcbe8ba6d93d6\":{\"id\":\"36489cbab30247fea4edcbe8ba6d93d6\",\"slug\":\"docs-management-authentication-mdx\",\"title\":\"docs + > management > authentication.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:46.369763\",\"modified\":\"2026-06-26T08:59:51.921782\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"36489cbab30247fea4edcbe8ba6d93d6/t/page/4972-5293\":{\"score\":0.3301471471786499,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\" + Generate and Use User Key \\n \\n \\n This method is meant to be used from + the Agentic RAG frontend applications but if you need it for testing purpose, + you can obtain a token by going to [https://rag.progress.cloud/redirect?display=token] + \\n Then in the API calls, include it in the `Authorization` header as a Bearer + token: \\n\",\"id\":\"36489cbab30247fea4edcbe8ba6d93d6/t/page/4972-5293\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":4972,\"end\":5293,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"73c3dde3c4cc45c7a9aabaf19d1578a1\":{\"id\":\"73c3dde3c4cc45c7a9aabaf19d1578a1\",\"slug\":\"docs-rag-advanced-bring-your-own-anthropic-acct-md\",\"title\":\"docs + > rag > advanced > bring your own anthropic acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-20T14:58:49.310838\",\"modified\":\"2026-06-09T08:07:46.863851\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"73c3dde3c4cc45c7a9aabaf19d1578a1/t/page/292-560\":{\"score\":0.5028190016746521,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" Prerequisites \\n \\n You have an active Anthropic account (https://console.anthropic.com/) \\n Billing is enabled in your Anthropic console. \\n You have access to Progress Agentic RAG. \\n \\n Generate & Locate Your API Key \\n \\n Expand the sidebar - on the top left hand corner. \\n\",\"id\":\"73c3dde3c4cc45c7a9aabaf19d1578a1/t/page/292-560\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":292,\"end\":560,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e6605960cc46412da0e5e5404f511d53\":{\"id\":\"e6605960cc46412da0e5e5404f511d53\",\"slug\":\"docs-intro-md\",\"title\":\"docs - > intro\",\"summary\":\"When teams knit together vector databases, machine - learning pipelines, large language models, ranking algorithms, and interfaces - into specific products, they are only providing one or two of these capabilities.\\nNuclea - delivers all four out of the box.\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"sr\",\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2023-08-03T08:57:16.630817\",\"modified\":\"2026-06-09T08:07:20.822319\",\"last_seqid\":1741334,\"last_account_seq\":67150,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"e6605960cc46412da0e5e5404f511d53/t/page/0-301\":{\"score\":0.689723789691925,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" - \\n id: intro \\n slug: / \\n title: Agentic RAG documentation \\n \\n Agentic - RAG, the RAG-as-a-Service platform \\n Agentic RAG automatically delivers - AI search and Generative Answers on top of your unstructured data, and provides - knowledge in the form of trusted answers, in any language, and from any data. - \\n\",\"id\":\"e6605960cc46412da0e5e5404f511d53/t/page/0-301\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":301,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"2a9e55371d8f4461993ef6b6ae3bb3e6\":{\"id\":\"2a9e55371d8f4461993ef6b6ae3bb3e6\",\"slug\":\"docs-rag-advanced-performances-md\",\"title\":\"docs - > rag > advanced > performances\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-10-02T15:19:15.263181\",\"modified\":\"2026-06-09T08:07:44.014121\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"2a9e55371d8f4461993ef6b6ae3bb3e6/t/page/2716-2929\":{\"score\":0.30331891775131226,\"score_type\":\"RERANKER\",\"order\":19,\"text\":\" - \\n How to use REMi \\n Agentic RAG runs REMi on a regular basis to monitor - the quality of the RAG pipeline. The results are displayed in the Agentic - RAG dashboard that shows the evolution of the metrics over time. \\n\",\"id\":\"2a9e55371d8f4461993ef6b6ae3bb3e6/t/page/2716-2929\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":2716,\"end\":2929,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"9e6238e3377d41699643ba954dd500fa\":{\"id\":\"9e6238e3377d41699643ba954dd500fa\",\"slug\":\"docs-ingestion-how-to-extract-strategies-md\",\"title\":\"docs - > ingestion > how to > extract strategies\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-06-13T08:13:07.100304\",\"modified\":\"2026-06-09T08:18:12.970227\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"9e6238e3377d41699643ba954dd500fa/t/page/2317-2576\":{\"score\":0.5746932029724121,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" - Apart from cutting-edge table and text extraction capabilities, \U0001F415 - pagehound-v1 is capable of extracting embedded images from full page scans, - making it possible to apply Progress' Agentic RAG image processing pipeline - to them, enabling search capabilities. \\n\",\"id\":\"9e6238e3377d41699643ba954dd500fa/t/page/2317-2576\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2317,\"end\":2576,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"0d4445df40ee4daeb4bb6d609f2b64b1\":{\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1\",\"slug\":\"docs-rag-advanced-connect-your-own-azure-openai-acct-md\",\"title\":\"docs - > rag > advanced > connect your own azure openai acct\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-15T14:36:48.862567\",\"modified\":\"2026-06-09T08:07:50.247127\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/3184-3468\":{\"score\":0.8507168292999268,\"score_type\":\"RERANKER\",\"order\":3,\"text\":\" - Select Azure OpenAI as the LLM provider \\n Enable Use your own Azure OpenAI - key \\n Enter: \\n API Key \\n Endpoint URL \\n Deployment Name \\n Model - Name \\n Save the configuration \\n Test answer generation \\n \\n Outcome - \\n \\n Progress Agentic RAG uses your Azure-hosted LLM for answer generation - \\n \",\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/3184-3468\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":3184,\"end\":3468,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/2859-3184\":{\"score\":0.36161547899246216,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" - 6. Configure Azure OpenAI in Progress Agentic RAG \\n This step connects your - deployed model to Progress Agentic RAG. \\n Required Configuration Values - \\n | Field | Source | \\n | --------------- | ------- | \\n | API Key | Foundry - | \\n | Endpoint URL | Foundry | \\n | Deployment Name | Foundry | \\n | Model - Name | Foundry | \\n Steps \\n \\n\",\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/2859-3184\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2859,\"end\":3184,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/0-446\":{\"score\":0.30466195940971375,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\" - \\n id: connect-your-own-azure-openai-acct \\n title: Connect your own Azure - OpenAI Model \\n \\n Deploying an Azure OpenAI Model and Connecting It to - Progress Agentic RAG \\n Summary Flow \\n \\n Create Azure account and subscription - \\n Create Azure OpenAI resource \\n Open Microsoft Foundry from the resource - overview \\n Deploy a model via the Model Catalog \\n Retrieve API key and - endpoint from Foundry UI \\n Configure Azure OpenAI in Progress Agentic RAG - \\n \\n \\n\",\"id\":\"0d4445df40ee4daeb4bb6d609f2b64b1/t/page/0-446\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":446,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"c1d73c95e26d44eea84e63919a836289\":{\"id\":\"c1d73c95e26d44eea84e63919a836289\",\"slug\":\"docs-ingestion-how-to-integrate-nextjs-md\",\"title\":\"docs + on the top left hand corner. \\n\",\"id\":\"73c3dde3c4cc45c7a9aabaf19d1578a1/t/page/292-560\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":292,\"end\":560,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"c1d73c95e26d44eea84e63919a836289\":{\"id\":\"c1d73c95e26d44eea84e63919a836289\",\"slug\":\"docs-ingestion-how-to-integrate-nextjs-md\",\"title\":\"docs > ingestion > how to > integrate nextjs\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"de\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:04.780909\",\"modified\":\"2026-06-26T08:59:44.635729\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"c1d73c95e26d44eea84e63919a836289/t/page/837-1226\":{\"score\":0.9353464841842651,\"score_type\":\"RERANKER\",\"order\":1,\"text\":\" Agentic RAG is an API able to index and process any kind of data, including audio and video files, to boost applications with powerful search & RAG capability. \\n Indexing page contents automatically \\n The Agentic RAG Dashboard is an easy way to index files or web pages by yourself. That's nice for testing purpose, but it is definitely better to index your Next.js pages automatically. - \\n\",\"id\":\"c1d73c95e26d44eea84e63919a836289/t/page/837-1226\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":837,\"end\":1226,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"c1d73c95e26d44eea84e63919a836289/t/page/1666-2203\":{\"score\":0.5552845597267151,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" + \\n\",\"id\":\"c1d73c95e26d44eea84e63919a836289/t/page/837-1226\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":837,\"end\":1226,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"c1d73c95e26d44eea84e63919a836289/t/page/1666-2203\":{\"score\":0.5552845597267151,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" ```js \\n const { Nuclia } = require( @nuclia/core ); \\n require( localstorage-polyfill ); \\n require( isomorphic-unfetch ); \\n const nuclia = new Nuclia({ \\n backend: https://accounts.progress.cloud/api , \\n zone: europe-1 , \\n knowledgeBox: @@ -754,15 +672,33 @@ interactions: later) \\n ``` \\n As you can see, you need to provide a Agentic RAG API key. An API key is necessary when adding or modifying contents in a knowledge box. You can get your API key in the Agentic RAG Dashboard, in the API keys section: - \\n\",\"id\":\"c1d73c95e26d44eea84e63919a836289/t/page/1666-2203\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1666,\"end\":2203,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"7a58f44f10fc423f83239c0b733057c1\":{\"id\":\"7a58f44f10fc423f83239c0b733057c1\",\"slug\":\"docs-develop-dotnet-sdk-index-md\",\"title\":\"docs - > develop > dotnet sdk > index\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"sk\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-24T16:03:48.411403\",\"modified\":\"2026-06-09T08:17:38.462625\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"7a58f44f10fc423f83239c0b733057c1/t/page/0-226\":{\"score\":0.6728693246841431,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\"Progress.Nuclia - .NET SDK \\n A comprehensive .NET SDK for Progress Agentic RAG's NucliaDb, - providing RAG (Retrieval-Augmented Generation) capabilities with knowledge - base management, AI-powered search, and resource operations. 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strapi\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:04.222223\",\"modified\":\"2026-06-26T08:59:45.897854\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"22f855bc36c34e6c82182ebd33d3dbc4/t/page/300-661\":{\"score\":0.974821150302887,\"score_type\":\"RERANKER\",\"order\":0,\"text\":\" + Agentic RAG is the best search API to do it! \\n Agentic RAG is an API able + to index and process any kind of data, including audio and video files, to + boost applications with powerful search capability, using natural language + processing and machine learning to understand the searcher's intent and return + results that are more relevant to the searcher's needs. 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nua\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-29T07:32:38.792855\",\"modified\":\"2026-07-29T07:32:38.792869\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"7c9e318a8fcc4c9485b8639fdbe93b38/t/page/0-496\":{\"score\":0.8438951373100281,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\" + \\n id: nua \\n title: Nuclia Understanding API \\n \\n Using the Nuclia Understanding + API \\n The Nuclia Understanding API (NUA) allows you to process data outside + of a Knowledge Box. It is a set of endpoints that allow you to send data to + the Progress Agentic RAG platform for processing, or to make calls to models + to generate text, summaries, or other outputs. The information is stored temporarily + for the duration of the processing, nothing remains in the ProgressAgentic + RAG cloud infrastructure. \\n\",\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38/t/page/0-496\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":496,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"7c9e318a8fcc4c9485b8639fdbe93b38/t/page/934-1170\":{\"score\":0.5865820646286011,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\" + \\n \\n Once you have the API key, you can use it in the NUA endpoints by + setting the header X-NUCLIA-NUAKEY in each request. \\n The primary usage + of a NUA key is to allow running data processing jobs on the Progress Agentic + RAG platform. 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headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -770,15 +706,13 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 15 Jul 2026 07:54:28 GMT + - Wed, 05 Aug 2026 07:25:08 GMT nuclia-learning-id: - - c15972081f9e47059d8ae0f1e9aa4754 + - dbdb01fafe7f49e9aa5b0746733014a0 via: - 1.1 google x-envoy-upstream-service-time: - - '973' - x-nuclia-trace-id: - - d18ca33c70d43522eb4f613a71100cb6 + - '1078' status: code: 200 message: OK @@ -794,14 +728,21 @@ interactions: {}, "query_context_order": {}, "truncate": true, "user_prompt": {"prompt": "\n## Question\nWhat is Progress Agentic RAG?\n\n## Provided Context\n[START OF CONTEXT]\n## Nuclia Docs Retrieval Agent\n\n# What is Progress Agentic RAG?\n\n Progress - Agentic RAG is an API that indexes and processes various types of data, including - audio and video files, to enhance applications with advanced search capabilities. - It utilizes natural language processing and machine learning to understand user - intent and deliver relevant search results. Additionally, it provides AI search - and generative answers on unstructured data, supporting multiple languages and - data sources.\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read - all context; it may be lengthy or detailed\n- Do not omit or overlook any relevant - information\n- If the context is incomplete or insufficient, state: \"Not enough + Agentic RAG is an API that enhances applications with powerful search capabilities + by indexing and processing various types of data, including audio and video + files. It utilizes natural language processing and machine learning to understand + the searcher''s intent and deliver relevant results. Additionally, it offers + features like automatic indexing of page contents and integration with various + AI models for generating answers and processing data.\n[END OF CONTEXT]\n\n## + Answering Guidelines\n- Carefully read all context; it may be lengthy or detailed\n- + Do not omit or overlook any relevant information\n- Existing context summaries + are answer attempts produced by retrieval agents. Treat them as first-class + evidence and preserve their supported facts.\n- Combine complementary summaries + from multiple contexts when the question has multiple parts. Do not require + every context to answer the whole question by itself.\n- If a context summary + directly answers the question, do not replace it with an insufficient-data answer + merely because one retrieved chunk is incomplete; use the chunks for supporting + citations.\n- If the context is incomplete or insufficient, state: \"Not enough data to answer this.\"\n- Read carefully any extra instructions below if provided and use them to answer\n\nNow provide your answer to the question: What is Progress Agentic RAG?"}, "citations": null, "citation_threshold": null, "generative_model": @@ -816,7 +757,7 @@ interactions: Connection: - keep-alive Content-Length: - - '1998' + - '2544' Content-Type: - application/json Host: @@ -826,7 +767,7 @@ interactions: x-client-ident: - default x-message: - - bea85d2b264f44cf9a769a3618cfd055 + - 1708e66b6f0d48b28ae19610d32d75e1 x-origin: - RAO x-session: @@ -855,13 +796,29 @@ interactions: {"chunk":{"type":"text","text":" API"}} - {"chunk":{"type":"text","text":" that"}} + {"chunk":{"type":"text","text":" designed"}} + + {"chunk":{"type":"text","text":" to"}} + + {"chunk":{"type":"text","text":" enhance"}} + + {"chunk":{"type":"text","text":" applications"}} + + {"chunk":{"type":"text","text":" with"}} + + {"chunk":{"type":"text","text":" advanced"}} + + {"chunk":{"type":"text","text":" search"}} + + {"chunk":{"type":"text","text":" capabilities"}} + + {"chunk":{"type":"text","text":" by"}} - 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- h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -998,34 +939,35 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 15 Jul 2026 07:54:31 GMT + - Wed, 05 Aug 2026 07:25:10 GMT nuclia-learning-id: - - 5020823081d54ab19de6081723f9c4c4 + - b3272632eaca405badd01757c7d60a8d nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '737' + - '1033' x-nuclia-trace-id: - - 32cb4c4f4d061ac72d10e3c31ed6197f + - 8765d0f10987f9e75c33ca4e12cd9689 status: code: 200 message: OK - request: body: '{"user_id": "arag_evaluate", "question": null, "answer": "Progress Agentic - RAG is an API that indexes and processes various types of data, including audio - and video files, to enhance applications with advanced search capabilities. - It utilizes natural language processing and machine learning to understand user - intent and deliver relevant search results. Additionally, it provides AI search - and generative answers on unstructured data, supporting multiple languages and - data sources.", "contexts": ["## Nuclia Docs Retrieval Agent\n\n# What is Progress - Agentic RAG?\n\n Progress Agentic RAG is an API that indexes and processes various - types of data, including audio and video files, to enhance applications with - advanced search capabilities. It utilizes natural language processing and machine - learning to understand user intent and deliver relevant search results. Additionally, - it provides AI search and generative answers on unstructured data, supporting - multiple languages and data sources."]}' + RAG is an API designed to enhance applications with advanced search capabilities + by indexing and processing various types of data, including audio and video + files. It employs natural language processing and machine learning to comprehend + the searcher''s intent and deliver relevant results. Key features include automatic + indexing of page contents and integration with various AI models for generating + answers and processing data.", "contexts": ["## Nuclia Docs Retrieval Agent\n\n# + What is Progress Agentic RAG?\n\n Progress Agentic RAG is an API that enhances + applications with powerful search capabilities by indexing and processing various + types of data, including audio and video files. It utilizes natural language + processing and machine learning to understand the searcher''s intent and deliver + relevant results. Additionally, it offers features like automatic indexing of + page contents and integration with various AI models for generating answers + and processing data."]}' headers: Accept: - '*/*' @@ -1034,7 +976,7 @@ interactions: Connection: - keep-alive Content-Length: - - '991' + - '1045' Content-Type: - application/json Host: @@ -1047,7 +989,7 @@ interactions: uri: https://europe-1.dp.progress.cloud/api/v1/predict/remi response: body: - string: '{"time":3.0135927200317383,"answer_relevance":null,"context_relevance":[],"groundedness":[5]}' + string: '{"time":0.1853013038635254,"answer_relevance":null,"context_relevance":[],"groundedness":[5]}' headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 @@ -1058,26 +1000,27 @@ interactions: content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:32 GMT + - Wed, 05 Aug 2026 07:25:12 GMT nuclia-learning-model: - Llama-REMi-v1 via: - 1.1 google x-envoy-upstream-service-time: - - '3020' + - '191' x-nuclia-trace-id: - - 6506d451e96fbd4b8110734a04ed731a + - a5decec39af14b66bc24093a617fa9a4 status: code: 200 message: OK - request: body: '{"user_id": "arag_evaluate", "question": "What is Progress Agentic RAG?", - "answer": "Progress Agentic RAG is an API that indexes and processes various - types of data, including audio and video files, to enhance applications with - advanced search capabilities. It utilizes natural language processing and machine - learning to understand user intent and deliver relevant search results. Additionally, - it provides AI search and generative answers on unstructured data, supporting - multiple languages and data sources.", "contexts": null}' + "answer": "Progress Agentic RAG is an API designed to enhance applications with + advanced search capabilities by indexing and processing various types of data, + including audio and video files. It employs natural language processing and + machine learning to comprehend the searcher''s intent and deliver relevant results. + Key features include automatic indexing of page contents and integration with + various AI models for generating answers and processing data.", "contexts": + null}' headers: Accept: - '*/*' @@ -1086,7 +1029,7 @@ interactions: Connection: - keep-alive Content-Length: - - '523' + - '544' Content-Type: - application/json Host: @@ -1099,10 +1042,10 @@ interactions: uri: https://europe-1.dp.progress.cloud/api/v1/predict/remi response: body: - string: '{"time":3.4314804077148438,"answer_relevance":{"score":4,"reason":""},"context_relevance":[],"groundedness":[]}' + string: '{"time":0.6617584228515625,"answer_relevance":{"score":4,"reason":""},"context_relevance":[],"groundedness":[]}' headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Content-Length: - '111' access-control-expose-headers: @@ -1110,15 +1053,15 @@ interactions: content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:33 GMT + - Wed, 05 Aug 2026 07:25:12 GMT nuclia-learning-model: - Llama-REMi-v1 via: - 1.1 google x-envoy-upstream-service-time: - - '3436' + - '668' x-nuclia-trace-id: - - 747c389e61303c9aa91fe92619450c8f + - 95d0fa831051bd0d8b94812ea279652a status: code: 200 message: OK diff --git a/agents/remi/tests/cassettes/test_remi/test_remi_not_enough_data[full].yaml b/agents/remi/tests/cassettes/test_remi/test_remi_not_enough_data[full].yaml index c08c0738..85fcad2b 100644 --- a/agents/remi/tests/cassettes/test_remi/test_remi_not_enough_data[full].yaml +++ b/agents/remi/tests/cassettes/test_remi/test_remi_not_enough_data[full].yaml @@ -18,7 +18,7 @@ interactions: uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: - string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"7fe77405-a6de-43cf-ac27-ac09f80b66c6","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' + string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"da1740fa-ab3e-4971-b374-7bb31b5dd325","account_id":"39f5fa6e-680a-475e-a757-812597e86d06","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' headers: Alt-Svc: - 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> agentic > how to > agentic retrieval\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-29T13:39:03.379512\",\"modified\":\"2026-06-29T13:39:03.379525\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Outbound \u2014 the source IP addresses that Progress Agentic RAG uses when - making connections to your systems (e.g., webhooks, sync agents, or other - integrations). Allowlist these if you restrict inbound traffic to your infrastructure. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n :::note \\n The current list of IP addresses is also available in machine-readable - format: JSON | YAML. These lists may change over time, so we recommend periodically - fetching and applying updates to your firewall rules to ensure uninterrupted - service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall - restricts network traffic, you may need to allowlist the following IP addresses. - They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | - --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 - | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 - | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- - | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n - | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 - | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | - 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 - | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 - | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United - States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- - | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 - | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS - PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately - through an AWS endpoint service (AWS PrivateLink) instead of over the public - internet, allowing connections to be established from your VPC without traversing - public IP addresses. This option is not available through self-service configuration. - Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests - on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent - \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful - tool that enhances the capabilities of traditional retrieval-augmented generation - (RAG) systems. Regular RAG's fixed search-then-generate process is limiting - for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Different models can be chosen for different tasks: \\n \\n Context validation - happens when the Prune context option is enabled (recommended), we recommend - using a fast model - planning or the execution model (depending on the planning - mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Note: the rephrasing model is only used in more complex workflow, it can - be ignored in the present case. \\n Finally, add a Summarize agent in the - Generation step to generate a final answer from the retrieved information. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - The Smart Agent plans the answer: picks the most appropriate sources, splits - the question into sub-questions, evaluates relevancy, and iterates autonomously - until the information is sufficient. \\n Basic usage \\n To set up a Smart - Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, - etc.) in the Sources section of the left menu. Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. It will be slower but more accurate when processing - complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Also select the proper function for each registered agent, depending on the - type of source (MCP agents will not need one, the functions are provided dynamically - by the MCP server). \\n In the Smart Agent configuration, you can select the - planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - In the Summarize Agent, enable the Conversational mode. This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. You can embed it in - your website or application, and it will provide a chat user interface for - interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Go to the Widgets section in the left menu, and click on Create widget to - create a new widget. You can customize its appearance, and then copy the generated - code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" + string: '{"facets":{"/n/i":994,"/n/i/application":1,"/n/i/application/json":1,"/n/i/text":993,"/n/i/text/markdown":993}}' headers: Alt-Svc: - h3=":443"; ma=2592000 Content-Length: - - '12993' + - '111' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:48 GMT + - Wed, 05 Aug 2026 07:25:24 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '46' + - '13' x-nuclia-trace-id: - - ceced66f3089d8ed7d6e9382b8ab51d8 + - 39b7a4a5f9b8a8cfb4ea39165651d35b status: code: 200 message: OK - request: - body: '' + body: '{"features": ["keyword"], "faceted": ["/classification.labels"]}' headers: Accept: - '*/*' @@ -407,40 +266,123 @@ interactions: - gzip, deflate Connection: - keep-alive + Content-Length: + - '61' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: - application/json x-stf-serviceaccount: - DUMMY - method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm + method: POST + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: - string: '{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner - Content","related":"","text":"","uri":""},{"title":"Softcat","related":"","text":"","uri":""},{"title":"Sales - Enablement Assets","related":"","text":"","uri":""},{"title":"KO 26","related":"","text":"","uri":""},{"title":"Data - Sheets","related":"","text":"","uri":""},{"title":"Progress Agentic RAG Training - Materials 2026","related":"","text":"","uri":""}]}' + string: "{\"resources\":{\"7c9e318a8fcc4c9485b8639fdbe93b38\":{\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"slug\":\"docs-develop-nua-md\",\"title\":\"docs + > develop > nua\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-29T07:32:38.792855\",\"modified\":\"2026-07-29T07:32:38.792869\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Processing \\n Push a file \\n Processing data works in 2 steps: \\n + \\n First you will upload the file with /processing/upload, which returns + an upload token. \\n Then you will put this token in the processing queue + with /processing/push so the file is processed. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1627,\"end\":1890},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + json \\n { \\n webhook_config : { \\n uri : http://some.where/my-custom-webhook + , \\n headers : { \\n api-key : xxxxxxxxxx \\n } \\n } \\n } \\n Also, you + can choose to use a fixed uri on your token, and provide the headers in the + /push calls. In this case you don't need to provide the uri parameter. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":23,\"start\":9053,\"end\":9339},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Get a NUA key \\n In order to use the Nuclia Understanding API (NUA), you + first need to generate an API key. \\n There are two options to create an + API key: \\n \\n Using the Agentic RAG dashboard top-right menu: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":496,\"end\":703},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Note: If you have a Knowledge Box and want to use the predict endpoints, they + are proxied through the /api/v1/kb//predict endpoint. You will need to provide + a KB's regular authentication, a NUA API key will not be necessary.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":28,\"start\":10377,\"end\":10603},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The payload received from /requests is based on the fdbwriter.BrokerMessage + provided by writer.proto. \\n Streamed results \\n The /processing/requests//results + endpoint is similar but it returns directly the decoded results as a stream. + You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":18,\"start\":7453,\"end\":7716},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Processing happens asynchronously, so you will need to regularly check the + queue output using one of the two endpoints available to retrieve the results. + \\n Protobuffer results \\n The /processing/requests/ endpoint returns a protobuffer + payload with the processing results. You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":12,\"start\":5098,\"end\":5399},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: nua \\n title: Nuclia Understanding API \\n \\n Using the Nuclia Understanding + API \\n The Nuclia Understanding API (NUA) allows you to process data outside + of a Knowledge Box. It is a set of endpoints that allow you to send data to + the Progress Agentic RAG platform for processing, or to make calls to models + to generate text, summaries, or other outputs. The information is stored temporarily + for the duration of the processing, nothing remains in the ProgressAgentic + RAG cloud infrastructure. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":496},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests/' \\\\ + \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n The response is a JSON object containing + completed indicating if the processing is complete or not, and in case it + is,a response string. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":13,\"start\":5399,\"end\":5644},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n In Python, you can use nucliadb_protos to decode the results: \\n + ```python \\n import base64 \\n import requests \\n from nucliadb_protos.writer_pb2 + import BrokerMessage \\n processing_id = THE_PROCESSING_ID_YOU_RECEIVED_FROM_PUSH + \\n res = requests.get(f'https://europe-1.nuclia.cloud/api/v1/processing/requests/{processing_id}',headers={ + \\n X-NUCLIA-NUAKEY : Bearer YOUR_NUA_KEY , \\n }).json() \\n if payload in + res: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":16,\"start\":6812,\"end\":7224},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/push' \\\\ \\n + -X POST \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\\\ \\n -H 'Content-Type: + application/json' \\\\ \\n --data-raw '{ filefield :{ my_file_1 : eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.W8wfVj04aYicREYXRatCTb8F8-PD4Ph7MmiTliHi6DI + }}' \\n Push text \\n Instead of uploading a file and then pushing it to the + queue, you can also push some text directly to the queue. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":9,\"start\":2730,\"end\":3646},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + It may also be used to create (or delete) Knowledge Boxes via the API \u2013 + for example, if you need to automate Knowledge Box creation. In that case + you will need to select the Allow management of Knowledge Boxes checkbox during + the NUA key creation. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1170,\"end\":1420},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + /predict/rerank reranks a list of results to improve the relevance of the + top results. \\n /predict/sentence computes the embedding of a sentence. \\n + /predict/summarize summarizes a text. \\n \\n The calls must provides the + X-NUCLIA-NUAKEY header with your NUA key: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":26,\"start\":9847,\"end\":10108},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests//results' + \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n Moreover the data_types parameter + allows you to filter the results by data type. For example: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":19,\"start\":7716,\"end\":7926},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Here is a typical example: \\n shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/upload' + \\\\ \\n -X POST \\\\ \\n -H X-NUCLIA-NUAKEY: Bearer \\\\ \\n -H 'content-type: + ' \\\\ \\n -T /path/to/file \\n Will return something like: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":1890,\"end\":2109},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + :::note \\n If an error occurs when posting the result to the webhook URL, + the result is stored in the queue and can be retrieved by calling the /pull + endpoint (see previous section). The error message is appended to the result. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":24,\"start\":9339,\"end\":9568},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + pb = BrokerMessage() \\n pb.ParseFromString( \\n base64.b64decode(res[ payload + ]) \\n ) \\n print(pb) \\n else: \\n print('No payload') \\n ``` \\n For other + languages, Nuclia protobuffer models can be found on the NucliaDB GitHub repository. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":17,\"start\":7224,\"end\":7453},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Model calls \\n The predict endpoints offer various services: \\n + \\n /predict/chat makes a direct call to an LLM. \\n /predict/remi calls the + REMi model to measure the quality of a RAG response. \\n /predict/rephrase + rephrases a question to make it more suitable for a RAG query. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":25,\"start\":9568,\"end\":9847},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJ1cm46cHJveHkiLCJzdWIiOiJmaWxlIiwiYXVkIjoidXJuOnByb3h5IiwiZXhwIjoxNjU1ODkyMDgwLCJpYXQiOjE2NTU4ODg0ODAsImp0aSI6ImFmN2ZmYjU1ZjAxMjRlMzM5MmRjMDY5MmM2NWI5NzY3Iiwic2l6ZSI6ODk3LCJidWNrZXRfbmFtZSI6ImV1cm9wZS0xLXN0b3JhZ2UtcHJveHkiLCJ1cmkiOiIwZDg2YTFmYTcxN2Q0NDUxYTAwM2Q1NGIyNzM2YTA0ZSIsImRyaXZlciI6MCwiY29udGVudF90eXBlIjoiYXBwbGljYXRpb24vb2N0ZXQtc3RyZWFtIiwiZmlsZW5hbWUiOiIiLCJwYXNzd29yZCI6bnVsbCwibGFuZ3VhZ2UiOm51bGwsInNvdXJjZSI6MCwibWQ1IjpudWxsfQ.VItLa_fUen2Pt5W2440Bjwc7Zx64rv6mJnRMFIdao5o + \\n That is your upload token. Now you can push this token to the processing + queue with: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2109,\"end\":2730},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also at any level, if an attribute exceeds a certain size, it will be put + in a downloadable file and will be replaced in the document by a file pointer. + This will consist of { file : { uri : JWT_TOKEN }}. The rule is that if the + size of the message is greater than 1000000 characters, the biggest parts + will be moved to downloadable files. First, the compression process will target + vectors. If that is not enough, it will target large field metadata, and finally + it will target extracted text. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":15,\"start\":6315,\"end\":6812},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In this case, any time a new result is available Nuclia will post it (i.e. + make an actual POST call) to this URL, sending the protobuffer result as payload. + \\n To use a webhook, you will need to fill in the Webhook URL field in the + NUA key creation form when you create your key. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":21,\"start\":8236,\"end\":8517},\"fuzzy_result\":false}],\"facets\":{},\"query\":\"\",\"total\":5358,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Content-Length: - - '507' + - '12190' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:48 GMT + - Wed, 05 Aug 2026 07:25:24 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '12' + - '53' x-nuclia-trace-id: - - 56d00b19ad6cd68be7af7918bb75e14e + - 11e5b8a25a8e66009616f22aa16ddf67 status: code: 200 message: OK @@ -456,7 +398,7 @@ interactions: Content-Length: - '18' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -464,126 +406,121 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: - string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs - > agentic > deploy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-29T13:39:02.557258\",\"modified\":\"2026-06-29T13:39:02.557276\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"f13642b2862f4a1ea2144c9eb2abb2a3\":{\"id\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"slug\":\"docs-develop-js-sdk-functions-normalizeGlobalBackendUrl-md\",\"title\":\"docs - > develop > js sdk > functions > normalizeGlobalBackendUrl\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-26T08:38:33.060378\",\"modified\":\"2026-07-14T12:47:15.556468\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"a572ce0c7eb949e4a17babae21a03a4a\":{\"id\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"slug\":\"navigation-pages\",\"title\":\"navigation-pages\",\"summary\":\"\",\"icon\":\"application/json\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"fr\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-23T10:58:22.812220\",\"modified\":\"2026-06-23T10:58:22.812242\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"ed6fda7434aa43a3bd5138b95e7fe081\":{\"id\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"slug\":\"docs-develop-python-sdk-15-memory-md\",\"title\":\"docs - > develop > python sdk > 15 memory\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-26T08:31:21.372271\",\"modified\":\"2026-06-26T08:59:38.187065\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"007b445866574d7ca69891d388663cc6\":{\"id\":\"007b445866574d7ca69891d388663cc6\",\"slug\":\"docs-management-security-5-public-ips-md\",\"title\":\"docs - > management > security > 5 public ips\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-03T09:28:57.937064\",\"modified\":\"2026-07-03T09:28:57.937076\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"b28e388104644fc5bba68c0cd44e01d4\":{\"id\":\"b28e388104644fc5bba68c0cd44e01d4\",\"slug\":\"docs-agentic-how-to-agentic-retrieval-md\",\"title\":\"docs - > agentic > how to > agentic retrieval\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-29T13:39:03.379512\",\"modified\":\"2026-06-29T13:39:03.379525\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Outbound \u2014 the source IP addresses that Progress Agentic RAG uses when - making connections to your systems (e.g., webhooks, sync agents, or other - integrations). Allowlist these if you restrict inbound traffic to your infrastructure. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n :::note \\n The current list of IP addresses is also available in machine-readable - format: JSON | YAML. These lists may change over time, so we recommend periodically - fetching and applying updates to your firewall rules to ensure uninterrupted - service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall - restricts network traffic, you may need to allowlist the following IP addresses. - They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | - --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 - | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 - | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- - | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n - | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 - | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | - 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 - | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 - | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United - States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- - | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 - | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS - PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately - through an AWS endpoint service (AWS PrivateLink) instead of over the public - internet, allowing connections to be established from your VPC without traversing - public IP addresses. This option is not available through self-service configuration. - Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests - on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent - \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful - tool that enhances the capabilities of traditional retrieval-augmented generation - (RAG) systems. Regular RAG's fixed search-then-generate process is limiting - for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Different models can be chosen for different tasks: \\n \\n Context validation - happens when the Prune context option is enabled (recommended), we recommend - using a fast model - planning or the execution model (depending on the planning - mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Note: the rephrasing model is only used in more complex workflow, it can - be ignored in the present case. \\n Finally, add a Summarize agent in the - Generation step to generate a final answer from the retrieved information. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - The Smart Agent plans the answer: picks the most appropriate sources, splits - the question into sub-questions, evaluates relevancy, and iterates autonomously - until the information is sufficient. \\n Basic usage \\n To set up a Smart - Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, - etc.) in the Sources section of the left menu. Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. It will be slower but more accurate when processing - complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Also select the proper function for each registered agent, depending on the - type of source (MCP agents will not need one, the functions are provided dynamically - by the MCP server). \\n In the Smart Agent configuration, you can select the - planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - In the Summarize Agent, enable the Conversational mode. This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. You can embed it in - your website or application, and it will provide a chat user interface for - interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Go to the Widgets section in the left menu, and click on Create widget to - create a new widget. You can customize its appearance, and then copy the generated - code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{\"/k\":{\"/k/text\":5294}},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"fulltext\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-resources\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-search\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-rag-lab\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"account-arag\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-kv-schemas\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"user-profile\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-users\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-widgets\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-remi-analytics\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"agent-users\",\"labels\":[]}],\"facets\":{},\"query\":\"\",\"total\":2013,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" 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access\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-16T08:13:36.926639\",\"modified\":\"2026-07-16T08:13:36.926650\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"78943baafe6a49848b4b29e683eaa983\":{\"id\":\"78943baafe6a49848b4b29e683eaa983\",\"slug\":\"docs-develop-js-sdk-interfaces-NUAClientResponse-md\",\"title\":\"docs + > develop > js sdk > interfaces > NUAClientResponse\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"ca\",\"languages\":[\"eo\",\"ca\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-28T13:26:37.201678\",\"modified\":\"2026-08-03T13:16:09.581726\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Processing \\n Push a file \\n Processing data works in 2 steps: \\n + \\n First you will upload the file with /processing/upload, which returns + an upload token. \\n Then you will put this token in the processing queue + with /processing/push so the file is processed. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1627,\"end\":1890},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + json \\n { \\n webhook_config : { \\n uri : http://some.where/my-custom-webhook + , \\n headers : { \\n api-key : xxxxxxxxxx \\n } \\n } \\n } \\n Also, you + can choose to use a fixed uri on your token, and provide the headers in the + /push calls. In this case you don't need to provide the uri parameter. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":23,\"start\":9053,\"end\":9339},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Get a NUA key \\n In order to use the Nuclia Understanding API (NUA), you + first need to generate an API key. \\n There are two options to create an + API key: \\n \\n Using the Agentic RAG dashboard top-right menu: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":496,\"end\":703},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Note: If you have a Knowledge Box and want to use the predict endpoints, they + are proxied through the /api/v1/kb//predict endpoint. You will need to provide + a KB's regular authentication, a NUA API key will not be necessary.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":28,\"start\":10377,\"end\":10603},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The payload received from /requests is based on the fdbwriter.BrokerMessage + provided by writer.proto. \\n Streamed results \\n The /processing/requests//results + endpoint is similar but it returns directly the decoded results as a stream. + You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":18,\"start\":7453,\"end\":7716},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Processing happens asynchronously, so you will need to regularly check the + queue output using one of the two endpoints available to retrieve the results. + \\n Protobuffer results \\n The /processing/requests/ endpoint returns a protobuffer + payload with the processing results. You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":12,\"start\":5098,\"end\":5399},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: nua \\n title: Nuclia Understanding API \\n \\n Using the Nuclia Understanding + API \\n The Nuclia Understanding API (NUA) allows you to process data outside + of a Knowledge Box. It is a set of endpoints that allow you to send data to + the Progress Agentic RAG platform for processing, or to make calls to models + to generate text, summaries, or other outputs. The information is stored temporarily + for the duration of the processing, nothing remains in the ProgressAgentic + RAG cloud infrastructure. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":496},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests/' \\\\ + \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n The response is a JSON object containing + completed indicating if the processing is complete or not, and in case it + is,a response string. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":13,\"start\":5399,\"end\":5644},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n In Python, you can use nucliadb_protos to decode the results: \\n + ```python \\n import base64 \\n import requests \\n from nucliadb_protos.writer_pb2 + import BrokerMessage \\n processing_id = THE_PROCESSING_ID_YOU_RECEIVED_FROM_PUSH + \\n res = requests.get(f'https://europe-1.nuclia.cloud/api/v1/processing/requests/{processing_id}',headers={ + \\n X-NUCLIA-NUAKEY : Bearer YOUR_NUA_KEY , \\n }).json() \\n if payload in + res: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":16,\"start\":6812,\"end\":7224},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/push' \\\\ \\n + -X POST \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\\\ \\n -H 'Content-Type: + application/json' \\\\ \\n --data-raw '{ filefield :{ my_file_1 : eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.W8wfVj04aYicREYXRatCTb8F8-PD4Ph7MmiTliHi6DI + }}' \\n Push text \\n Instead of uploading a file and then pushing it to the + queue, you can also push some text directly to the queue. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":9,\"start\":2730,\"end\":3646},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + It may also be used to create (or delete) Knowledge Boxes via the API \u2013 + for example, if you need to automate Knowledge Box creation. In that case + you will need to select the Allow management of Knowledge Boxes checkbox during + the NUA key creation. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1170,\"end\":1420},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + /predict/rerank reranks a list of results to improve the relevance of the + top results. \\n /predict/sentence computes the embedding of a sentence. \\n + /predict/summarize summarizes a text. \\n \\n The calls must provides the + X-NUCLIA-NUAKEY header with your NUA key: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":26,\"start\":9847,\"end\":10108},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests//results' + \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n Moreover the data_types parameter + allows you to filter the results by data type. For example: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":19,\"start\":7716,\"end\":7926},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Here is a typical example: \\n shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/upload' + \\\\ \\n -X POST \\\\ \\n -H X-NUCLIA-NUAKEY: Bearer \\\\ \\n -H 'content-type: + ' \\\\ \\n -T /path/to/file \\n Will return something like: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":1890,\"end\":2109},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + :::note \\n If an error occurs when posting the result to the webhook URL, + the result is stored in the queue and can be retrieved by calling the /pull + endpoint (see previous section). The error message is appended to the result. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":24,\"start\":9339,\"end\":9568},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + pb = BrokerMessage() \\n pb.ParseFromString( \\n base64.b64decode(res[ payload + ]) \\n ) \\n print(pb) \\n else: \\n print('No payload') \\n ``` \\n For other + languages, Nuclia protobuffer models can be found on the NucliaDB GitHub repository. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":17,\"start\":7224,\"end\":7453},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Model calls \\n The predict endpoints offer various services: \\n + \\n /predict/chat makes a direct call to an LLM. \\n /predict/remi calls the + REMi model to measure the quality of a RAG response. \\n /predict/rephrase + rephrases a question to make it more suitable for a RAG query. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":25,\"start\":9568,\"end\":9847},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJ1cm46cHJveHkiLCJzdWIiOiJmaWxlIiwiYXVkIjoidXJuOnByb3h5IiwiZXhwIjoxNjU1ODkyMDgwLCJpYXQiOjE2NTU4ODg0ODAsImp0aSI6ImFmN2ZmYjU1ZjAxMjRlMzM5MmRjMDY5MmM2NWI5NzY3Iiwic2l6ZSI6ODk3LCJidWNrZXRfbmFtZSI6ImV1cm9wZS0xLXN0b3JhZ2UtcHJveHkiLCJ1cmkiOiIwZDg2YTFmYTcxN2Q0NDUxYTAwM2Q1NGIyNzM2YTA0ZSIsImRyaXZlciI6MCwiY29udGVudF90eXBlIjoiYXBwbGljYXRpb24vb2N0ZXQtc3RyZWFtIiwiZmlsZW5hbWUiOiIiLCJwYXNzd29yZCI6bnVsbCwibGFuZ3VhZ2UiOm51bGwsInNvdXJjZSI6MCwibWQ1IjpudWxsfQ.VItLa_fUen2Pt5W2440Bjwc7Zx64rv6mJnRMFIdao5o + \\n That is your upload token. Now you can push this token to the processing + queue with: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2109,\"end\":2730},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also at any level, if an attribute exceeds a certain size, it will be put + in a downloadable file and will be replaced in the document by a file pointer. + This will consist of { file : { uri : JWT_TOKEN }}. The rule is that if the + size of the message is greater than 1000000 characters, the biggest parts + will be moved to downloadable files. First, the compression process will target + vectors. If that is not enough, it will target large field metadata, and finally + it will target extracted text. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":15,\"start\":6315,\"end\":6812},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In this case, any time a new result is available Nuclia will post it (i.e. + make an actual POST call) to this URL, sending the protobuffer result as payload. + \\n To use a webhook, you will need to fill in the Webhook URL field in the + NUA key creation form when you create your key. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":21,\"start\":8236,\"end\":8517},\"fuzzy_result\":false}],\"facets\":{\"/k\":{\"/k/text\":5358}},\"query\":\"\",\"total\":5358,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"fulltext\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"14b3bd967e2b44ba98372a8d9a0716b6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"14b3bd967e2b44ba98372a8d9a0716b6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"78943baafe6a49848b4b29e683eaa983\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"78943baafe6a49848b4b29e683eaa983\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b5eec709afcf4068a4211a16f1a79576\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b5eec709afcf4068a4211a16f1a79576\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5c4166eea30d4b329fb3f141e395781a\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5c4166eea30d4b329fb3f141e395781a\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"09305118c7314e1483068fb9a588578f\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"09305118c7314e1483068fb9a588578f\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"9ae2d3a90d0d452db50f170c535905d4\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"9ae2d3a90d0d452db50f170c535905d4\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"831a4c9bcc2e49d6a1f2a84c811f4fb6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"831a4c9bcc2e49d6a1f2a84c811f4fb6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"d97695fece7948c59cb9b95404b3a5f9\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"d97695fece7948c59cb9b95404b3a5f9\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5ae74950b55c4d60b754fa706314b24a\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5ae74950b55c4d60b754fa706314b24a\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]}],\"facets\":{},\"query\":\"\",\"total\":2029,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Content-Length: - - '16898' + - '19708' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:48 GMT + - Wed, 05 Aug 2026 07:25:24 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '57' + - '70' x-nuclia-trace-id: - - 928a69d86b46ccf541a20af616c06ec6 + - ff93260ed96222b6111531f7e24832ed status: code: 200 message: OK @@ -600,7 +537,7 @@ interactions: Content-Length: - '154' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -608,19 +545,17 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/ask + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/ask response: body: string: "{\"item\":{\"type\":\"answer\",\"text\":\"Not\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" enough\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" to\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" answer\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - this\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"retrieval\",\"results\":{\"resources\":{\"d1e1eaa16d6646b2b8ac88df5726f82f\":{\"id\":\"d1e1eaa16d6646b2b8ac88df5726f82f\",\"slug\":\"docs-develop-js-sdk-interfaces-ExtractVLLMConfig-md\",\"title\":\"docs - > develop > js sdk > interfaces > ExtractVLLMConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:01:23.529670\",\"modified\":\"2026-07-14T12:52:10.106536\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"d1e1eaa16d6646b2b8ac88df5726f82f/t/page/0-230\":{\"score\":0.00038296362617984414,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ExtractVLLMConfig \\n Interface: ExtractVLLMConfig - \\n Properties \\n llm? \\n \\n optional llm: ExtractLLMConfig \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:524 \\n \\n max_pages_to_merge? - \\n\",\"id\":\"d1e1eaa16d6646b2b8ac88df5726f82f/t/page/0-230\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":230,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"4ffdd42c713149249892d3b643ab3c81\":{\"id\":\"4ffdd42c713149249892d3b643ab3c81\",\"slug\":\"docs-develop-js-sdk-namespaces-Widget-interfaces-RagStrategiesConfig-md\",\"title\":\"docs - > develop > js sdk > namespaces > Widget > interfaces > RagStrategiesConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:52.988969\",\"modified\":\"2026-07-14T12:48:53.133910\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"4ffdd42c713149249892d3b643ab3c81/t/page/1081-2749\":{\"score\":0.0018969200318679214,\"score_type\":\"RERANKER\",\"order\":1,\"text\":\" + this\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"retrieval\",\"results\":{\"resources\":{\"d006bf039f294682acd86cfb49bb59df\":{\"id\":\"d006bf039f294682acd86cfb49bb59df\",\"slug\":\"docs-account-api-mdx\",\"title\":\"docs + > account api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"ca\",\"la\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:44.738214\",\"modified\":\"2026-06-09T08:18:14.888754\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"d006bf039f294682acd86cfb49bb59df/t/page/262-339\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":16,\"text\":\" + } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } + \\n `} \\n \\n \",\"id\":\"d006bf039f294682acd86cfb49bb59df/t/page/262-339\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":262,\"end\":339,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"4ffdd42c713149249892d3b643ab3c81\":{\"id\":\"4ffdd42c713149249892d3b643ab3c81\",\"slug\":\"docs-develop-js-sdk-namespaces-Widget-interfaces-RagStrategiesConfig-md\",\"title\":\"docs + > develop > js sdk > namespaces > Widget > interfaces > RagStrategiesConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:52.988969\",\"modified\":\"2026-08-03T13:14:13.201266\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"4ffdd42c713149249892d3b643ab3c81/t/page/1081-2749\":{\"score\":0.0018969200318679214,\"score_type\":\"RERANKER\",\"order\":0,\"text\":\" graph: undefined \\\\| object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/widget.ts:55 \\n \\n graphRagStrategy \\n \\n graphRagStrategy: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/widget.ts:54 \\n \\n includeNeighbouringParagraphs @@ -642,83 +577,79 @@ interactions: \\n \\n precedingParagraphs \\n \\n precedingParagraphs: null \\\\| number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/widget.ts:70 \\n \\n succeedingParagraphs \\n \\n succeedingParagraphs: null \\\\| number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/widget.ts:71\",\"id\":\"4ffdd42c713149249892d3b643ab3c81/t/page/1081-2749\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":1081,\"end\":2749,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs - > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-07-14T12:49:58.922592\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\":{\"score\":0.00046010586083866656,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" + Defined in \\n libs/sdk-core/src/lib/db/search/widget.ts:71\",\"id\":\"4ffdd42c713149249892d3b643ab3c81/t/page/1081-2749\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":1081,\"end\":2749,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"ecabb0862fa24c8fb8e01d4930a3f7a2\":{\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2\",\"slug\":\"docs-develop-js-sdk-variables-MAX_FACETS_PER_REQUEST-md\",\"title\":\"docs + > develop > js sdk > variables > MAX_FACETS_PER_REQUEST\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:18.992004\",\"modified\":\"2026-08-03T13:18:51.120089\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/a/title\":{\"paragraphs\":{\"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60\":{\"score\":0.0018102111062034965,\"score_type\":\"RERANKER\",\"order\":1,\"text\":\"docs + > develop > js sdk > variables > MAX_FACETS_PER_REQUEST\",\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":60,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}},\"/t/page\":{\"paragraphs\":{\"ecabb0862fa24c8fb8e01d4930a3f7a2/t/page/0-201\":{\"score\":0.0008659809827804565,\"score_type\":\"RERANKER\",\"order\":3,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / MAX_FACETS_PER_REQUEST \\n Variable: MAX_FACETS_PER_REQUEST + \\n \\n const MAX_FACETS_PER_REQUEST: 50 = 50 \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/filter.ts:18\",\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2/t/page/0-201\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":201,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"d1e1eaa16d6646b2b8ac88df5726f82f\":{\"id\":\"d1e1eaa16d6646b2b8ac88df5726f82f\",\"slug\":\"docs-develop-js-sdk-interfaces-ExtractVLLMConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ExtractVLLMConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:01:23.529670\",\"modified\":\"2026-08-03T13:16:19.914981\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"d1e1eaa16d6646b2b8ac88df5726f82f/t/page/0-230\":{\"score\":0.00038296362617984414,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ExtractVLLMConfig \\n Interface: ExtractVLLMConfig + \\n Properties \\n llm? \\n \\n optional llm: ExtractLLMConfig \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:524 \\n \\n max_pages_to_merge? + \\n\",\"id\":\"d1e1eaa16d6646b2b8ac88df5726f82f/t/page/0-230\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":230,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e3051c443121417496c925390ef67a5c\":{\"id\":\"e3051c443121417496c925390ef67a5c\",\"slug\":\"docs-develop-js-sdk-interfaces-MagicAction-md\",\"title\":\"docs + > develop > js sdk > interfaces > MagicAction\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-03-10T15:05:37.080679\",\"modified\":\"2026-08-03T13:15:22.094297\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/a/title\":{\"paragraphs\":{\"e3051c443121417496c925390ef67a5c/a/title/0-50\":{\"score\":0.0008559006964787841,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\"docs + > develop > js sdk > interfaces > MagicAction\",\"id\":\"e3051c443121417496c925390ef67a5c/a/title/0-50\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":50,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"8870dfa28ab342f9ba2b1832f4ce864c\":{\"id\":\"8870dfa28ab342f9ba2b1832f4ce864c\",\"slug\":\"docs-develop-js-sdk-interfaces-SqlAgent-md\",\"title\":\"docs + > develop > js sdk > interfaces > SqlAgent\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"eo\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:00:54.678573\",\"modified\":\"2026-08-03T13:15:25.687284\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"8870dfa28ab342f9ba2b1832f4ce864c/t/page/1535-1748\":{\"score\":0.0002251682453788817,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" + \\n optional lazy_table_reflection: boolean \\n \\n Inherited from \\n SqlAgentCreation.lazy_table_reflection + \\n Defined in \\n libs/sdk-core/src/lib/db/retrieval-agent/retrieval-agent.models.ts:216 + \\n \\n max_string_length? \\n\",\"id\":\"8870dfa28ab342f9ba2b1832f4ce864c/t/page/1535-1748\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1535,\"end\":1748,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"c053e849251b4a5296ffeb79ed00200e\":{\"id\":\"c053e849251b4a5296ffeb79ed00200e\",\"slug\":\"docs-nua-api-mdx\",\"title\":\"docs + > nua api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:43.966941\",\"modified\":\"2026-06-09T08:18:14.251220\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"c053e849251b4a5296ffeb79ed00200e/t/page/289-366\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\" + } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } + \\n `} \\n \\n \",\"id\":\"c053e849251b4a5296ffeb79ed00200e/t/page/289-366\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":289,\"end\":366,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs + > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-08-03T13:17:48.557889\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\":{\"score\":0.0002673826238606125,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" + \\n optional max_tokens: number \\\\| object \\n \\n Defines the maximum number + of tokens that the model will take as context. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \\n \\n min_score? \\n\",\"id\":\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2808,\"end\":3011,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"9ac9bbc6ad5c41f687b4a5f96b3b161a\":{\"id\":\"9ac9bbc6ad5c41f687b4a5f96b3b161a\",\"slug\":\"docs-develop-js-sdk-interfaces-RemiQueryCriteria-md\",\"title\":\"docs + > develop > js sdk > interfaces > RemiQueryCriteria\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:02.221744\",\"modified\":\"2026-08-03T13:16:14.394022\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"9ac9bbc6ad5c41f687b4a5f96b3b161a/t/page/0-273\":{\"score\":0.0002182420575991273,\"score_type\":\"RERANKER\",\"order\":15,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / RemiQueryCriteria \\n Interface: RemiQueryCriteria + \\n Properties \\n context_relevance? \\n \\n optional context_relevance: + object \\n \\n aggregation \\n \\n aggregation: average \\\\| min \\\\| max + \\n \\n operation \\n \\n operation: gt \\\\| lt \\\\| eq \\n \\n value \\n + \\n\",\"id\":\"9ac9bbc6ad5c41f687b4a5f96b3b161a/t/page/0-273\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":273,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-08-03T13:17:30.667856\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\":{\"score\":0.00046010586083866656,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\" \\n optional max_images: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \\n \\n output_tokens \\n \\n output_tokens: object \\n \\n default_max? \\n \\n optional default_max: number \\n \\n max \\n \\n max: number \\n \\n min? - \\n \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"91d9ee7dc2bd47e5b4a1011ca8e42bfd\":{\"id\":\"91d9ee7dc2bd47e5b4a1011ca8e42bfd\",\"slug\":\"docs-zone-api-mdx\",\"title\":\"docs - > zone api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:43.137585\",\"modified\":\"2026-06-09T08:18:13.619843\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"91d9ee7dc2bd47e5b4a1011ca8e42bfd/t/page/252-329\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":19,\"text\":\" - } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } - \\n `} \\n \\n \",\"id\":\"91d9ee7dc2bd47e5b4a1011ca8e42bfd/t/page/252-329\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":252,\"end\":329,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"c053e849251b4a5296ffeb79ed00200e\":{\"id\":\"c053e849251b4a5296ffeb79ed00200e\",\"slug\":\"docs-nua-api-mdx\",\"title\":\"docs - > nua api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:43.966941\",\"modified\":\"2026-06-09T08:18:14.251220\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"c053e849251b4a5296ffeb79ed00200e/t/page/289-366\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\" + \\n \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"53b91ad0dd5f48a7ac8b59f9775ed7e0\":{\"id\":\"53b91ad0dd5f48a7ac8b59f9775ed7e0\",\"slug\":\"docs-api-mdx\",\"title\":\"docs + > api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"ca\",\"en\",\"hu\",\"la\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:45.557031\",\"modified\":\"2026-06-09T08:18:15.494834\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"53b91ad0dd5f48a7ac8b59f9775ed7e0/t/page/257-334\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":19,\"text\":\" } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } - \\n `} \\n \\n \",\"id\":\"c053e849251b4a5296ffeb79ed00200e/t/page/289-366\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":289,\"end\":366,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"78aebdf4ca3a4028a555552a07e10e6d\":{\"id\":\"78aebdf4ca3a4028a555552a07e10e6d\",\"slug\":\"docs-rag-advanced-score-rank-and-rerank-md\",\"title\":\"docs - > rag > advanced > score rank and rerank\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-12-02T13:02:38.557991\",\"modified\":\"2026-06-09T08:07:41.924988\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"78aebdf4ca3a4028a555552a07e10e6d/t/page/5733-6021\":{\"score\":0.00029595711384899914,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" + \\n `} \\n \\n \",\"id\":\"53b91ad0dd5f48a7ac8b59f9775ed7e0/t/page/257-334\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":257,\"end\":334,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"42a4cd5a30314e94aa079ed0cfe81381\":{\"id\":\"42a4cd5a30314e94aa079ed0cfe81381\",\"slug\":\"docs-develop-js-sdk-interfaces-SplitStrategy-md\",\"title\":\"docs + > develop > js sdk > interfaces > SplitStrategy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:02:38.468609\",\"modified\":\"2026-08-03T13:14:41.671354\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\":{\"score\":0.0005770345451310277,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" + \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 + \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"id\":\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"220eb37c167f4eb9bb8e9454e7ba8cf5\":{\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5\",\"slug\":\"docs-develop-python-sdk-05-search-md\",\"title\":\"docs + > develop > python sdk > 05 search\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:48:33.723913\",\"modified\":\"2026-06-09T08:08:04.866092\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\":{\"score\":0.0007524627726525068,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" + ::: \\n :::warning \\n Enabling reasoning can use additional tokens, which + may increase your usage costs. \\n You may need to increase max_tokens to + give the LLM enough room to reason and generate an answer. \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2505,\"end\":2709,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"9e6238e3377d41699643ba954dd500fa\":{\"id\":\"9e6238e3377d41699643ba954dd500fa\",\"slug\":\"docs-ingestion-how-to-extract-strategies-md\",\"title\":\"docs + > ingestion > how to > extract strategies\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-06-13T08:13:07.100304\",\"modified\":\"2026-06-09T08:18:12.970227\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"9e6238e3377d41699643ba954dd500fa/t/page/5760-6199\":{\"score\":0.00038446192047558725,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" + merge_pages and max_pages_to_merge: These parameters are used to control how + many pages of the document will be merged together to extract the tables. + The default value is 1, which means that each page will be processed separately. + If we set it to a higher value, the strategy will merge the specified number + of pages together and extract the tables from them. This can be useful for + documents that have tables that span multiple pages. \\n\",\"id\":\"9e6238e3377d41699643ba954dd500fa/t/page/5760-6199\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":5760,\"end\":6199,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"78aebdf4ca3a4028a555552a07e10e6d\":{\"id\":\"78aebdf4ca3a4028a555552a07e10e6d\",\"slug\":\"docs-rag-advanced-score-rank-and-rerank-md\",\"title\":\"docs + > rag > advanced > score rank and rerank\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-12-02T13:02:38.557991\",\"modified\":\"2026-06-09T08:07:41.924988\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"78aebdf4ca3a4028a555552a07e10e6d/t/page/5733-6021\":{\"score\":0.00029595711384899914,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" In an actual request, these are the parameters to use in /find or /ask: \\n json \\n { \\n features : [ semantic , keyword ], \\n rank_fusion : { \\n name : rrf , \\n boosting : { \\n semantic : 2, \\n }, \\n window : 80, \\n }, \\n reranker : { \\n name : predict , \\n window : 50, \\n }, \\n top_k - : 20, \\n ... \\n }\",\"id\":\"78aebdf4ca3a4028a555552a07e10e6d/t/page/5733-6021\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":5733,\"end\":6021,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"ecabb0862fa24c8fb8e01d4930a3f7a2\":{\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2\",\"slug\":\"docs-develop-js-sdk-variables-MAX_FACETS_PER_REQUEST-md\",\"title\":\"docs - > develop > js sdk > variables > MAX_FACETS_PER_REQUEST\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:18.992004\",\"modified\":\"2026-07-14T12:54:35.795661\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/a/title\":{\"paragraphs\":{\"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60\":{\"score\":0.0018102111062034965,\"score_type\":\"RERANKER\",\"order\":2,\"text\":\"docs - > develop > js sdk > variables > MAX_FACETS_PER_REQUEST\",\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":60,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}},\"/t/page\":{\"paragraphs\":{\"ecabb0862fa24c8fb8e01d4930a3f7a2/t/page/0-201\":{\"score\":0.0008659809827804565,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / MAX_FACETS_PER_REQUEST \\n Variable: MAX_FACETS_PER_REQUEST - \\n \\n const MAX_FACETS_PER_REQUEST: 50 = 50 \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/filter.ts:18\",\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2/t/page/0-201\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":201,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"d006bf039f294682acd86cfb49bb59df\":{\"id\":\"d006bf039f294682acd86cfb49bb59df\",\"slug\":\"docs-account-api-mdx\",\"title\":\"docs - > account api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"ca\",\"la\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:44.738214\",\"modified\":\"2026-06-09T08:18:14.888754\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"d006bf039f294682acd86cfb49bb59df/t/page/262-339\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\" + : 20, \\n ... \\n }\",\"id\":\"78aebdf4ca3a4028a555552a07e10e6d/t/page/5733-6021\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":5733,\"end\":6021,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"91d9ee7dc2bd47e5b4a1011ca8e42bfd\":{\"id\":\"91d9ee7dc2bd47e5b4a1011ca8e42bfd\",\"slug\":\"docs-zone-api-mdx\",\"title\":\"docs + > zone api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:43.137585\",\"modified\":\"2026-06-09T08:18:13.619843\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"91d9ee7dc2bd47e5b4a1011ca8e42bfd/t/page/252-329\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\" } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } - \\n `} \\n \\n \",\"id\":\"d006bf039f294682acd86cfb49bb59df/t/page/262-339\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":262,\"end\":339,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"220eb37c167f4eb9bb8e9454e7ba8cf5\":{\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5\",\"slug\":\"docs-develop-python-sdk-05-search-md\",\"title\":\"docs - > develop > python sdk > 05 search\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:48:33.723913\",\"modified\":\"2026-06-09T08:08:04.866092\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\":{\"score\":0.0007524627726525068,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" - ::: \\n :::warning \\n Enabling reasoning can use additional tokens, which - may increase your usage costs. \\n You may need to increase max_tokens to - give the LLM enough room to reason and generate an answer. \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2505,\"end\":2709,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"f56767f7277944a58092904d0041e207\":{\"id\":\"f56767f7277944a58092904d0041e207\",\"slug\":\"docs-develop-js-sdk-interfaces-Account-md\",\"title\":\"docs - > develop > js sdk > interfaces > Account\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:49:04.980510\",\"modified\":\"2026-07-14T12:50:35.584737\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"f56767f7277944a58092904d0041e207/t/page/1396-2005\":{\"score\":0.0023322338238358498,\"score_type\":\"RERANKER\",\"order\":0,\"text\":\" - \\n optional limits: AccountLimits \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:26 - \\n \\n max_agents \\n \\n max_agents: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:27 - \\n \\n ~~max_arags~~ \\n \\n max_arags: number \\n \\n Deprecated \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:31 \\n \\n max_kbs \\n \\n max_kbs: - number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:28 \\n - \\n max_memories \\n \\n max_memories: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:29 - \\n \\n max_users \\n \\n max_users: null \\\\| number \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/db.models.ts:32 \\n \\n saml_config? \\n\",\"id\":\"f56767f7277944a58092904d0041e207/t/page/1396-2005\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":1396,\"end\":2005,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"42a4cd5a30314e94aa079ed0cfe81381\":{\"id\":\"42a4cd5a30314e94aa079ed0cfe81381\",\"slug\":\"docs-develop-js-sdk-interfaces-SplitStrategy-md\",\"title\":\"docs - > develop > js sdk > interfaces > SplitStrategy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:02:38.468609\",\"modified\":\"2026-07-14T12:51:02.450318\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\":{\"score\":0.0005770345451310277,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\" - \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 - \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"id\":\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"38ec4cc5c66e436a946ea7893b6662a3\":{\"id\":\"38ec4cc5c66e436a946ea7893b6662a3\",\"slug\":\"docs-changelog-updates-2024-10-md\",\"title\":\"docs - > changelog > updates > 2024 10\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:49.934688\",\"modified\":\"2026-06-09T08:07:26.696807\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708\":{\"score\":0.00045474793296307325,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\" + \\n `} \\n \\n \",\"id\":\"91d9ee7dc2bd47e5b4a1011ca8e42bfd/t/page/252-329\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":252,\"end\":329,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"38ec4cc5c66e436a946ea7893b6662a3\":{\"id\":\"38ec4cc5c66e436a946ea7893b6662a3\",\"slug\":\"docs-changelog-updates-2024-10-md\",\"title\":\"docs + > changelog > updates > 2024 10\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:49.934688\",\"modified\":\"2026-06-09T08:07:26.696807\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708\":{\"score\":0.00045474793296307325,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" Important API Updates (All changes will be effective as of November 11th, please make your plans): \\n \\n Remember we are moving forward with better parameters: \\n Farewell to page_number and page_size in /search and /find - endpoints as they will be discontinued on the 11th - say hello to top_k! \\n\",\"id\":\"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":1414,\"end\":1708,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs - > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-07-14T12:51:04.368823\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\":{\"score\":0.0002673826238606125,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" - \\n optional max_tokens: number \\\\| object \\n \\n Defines the maximum number - of tokens that the model will take as context. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 - \\n \\n min_score? \\n\",\"id\":\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2808,\"end\":3011,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"bd8ccba0ddc341dd851891ba2cccc08f\":{\"id\":\"bd8ccba0ddc341dd851891ba2cccc08f\",\"slug\":\"docs-develop-js-sdk-type-aliases-MagicActionType-md\",\"title\":\"docs - > develop > js sdk > type aliases > MagicActionType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-03-10T15:04:00.830962\",\"modified\":\"2026-07-14T12:53:20.254416\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/a/title\":{\"paragraphs\":{\"bd8ccba0ddc341dd851891ba2cccc08f/a/title/0-56\":{\"score\":0.0014953383943066,\"score_type\":\"RERANKER\",\"order\":3,\"text\":\"docs - > develop > js sdk > type aliases > MagicActionType\",\"id\":\"bd8ccba0ddc341dd851891ba2cccc08f/a/title/0-56\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":56,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"9e6238e3377d41699643ba954dd500fa\":{\"id\":\"9e6238e3377d41699643ba954dd500fa\",\"slug\":\"docs-ingestion-how-to-extract-strategies-md\",\"title\":\"docs - > ingestion > how to > extract strategies\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-06-13T08:13:07.100304\",\"modified\":\"2026-06-09T08:18:12.970227\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"9e6238e3377d41699643ba954dd500fa/t/page/5760-6199\":{\"score\":0.00038446192047558725,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\" - merge_pages and max_pages_to_merge: These parameters are used to control how - many pages of the document will be merged together to extract the tables. - The default value is 1, which means that each page will be processed separately. - If we set it to a higher value, the strategy will merge the specified number - of pages together and extract the tables from them. This can be useful for - documents that have tables that span multiple pages. \\n\",\"id\":\"9e6238e3377d41699643ba954dd500fa/t/page/5760-6199\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":5760,\"end\":6199,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e3051c443121417496c925390ef67a5c\":{\"id\":\"e3051c443121417496c925390ef67a5c\",\"slug\":\"docs-develop-js-sdk-interfaces-MagicAction-md\",\"title\":\"docs - > develop > js sdk > interfaces > MagicAction\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-03-10T15:05:37.080679\",\"modified\":\"2026-07-14T12:50:10.679327\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/a/title\":{\"paragraphs\":{\"e3051c443121417496c925390ef67a5c/a/title/0-50\":{\"score\":0.0008559006964787841,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\"docs - > develop > js sdk > interfaces > MagicAction\",\"id\":\"e3051c443121417496c925390ef67a5c/a/title/0-50\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":50,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"fa7e8853eaf54849aecfedb5c8fc5979\":{\"id\":\"fa7e8853eaf54849aecfedb5c8fc5979\",\"slug\":\"docs-develop-js-sdk-type-aliases-MagicActionError-md\",\"title\":\"docs - > develop > js sdk > type aliases > MagicActionError\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-03-10T15:04:19.733786\",\"modified\":\"2026-07-14T12:53:50.579249\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/a/title\":{\"paragraphs\":{\"fa7e8853eaf54849aecfedb5c8fc5979/a/title/0-57\":{\"score\":0.00043733438360504806,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\"docs - > develop > js sdk > type aliases > 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headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -726,15 +657,13 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 15 Jul 2026 07:54:48 GMT + - Wed, 05 Aug 2026 07:25:25 GMT nuclia-learning-id: - - 21b81af3f68f4e92a6465acde06f52b8 + - 04b2ea1734634b47bbb1b86f26b55dda via: - 1.1 google x-envoy-upstream-service-time: - - '995' - x-nuclia-trace-id: - - 09628e00907fb58e1d122a31059c1499 + - '5827' status: code: 200 message: OK @@ -751,14 +680,21 @@ interactions: Question\nComo usar max_magic y dime como cambiar\u00e1 este parametro en el futuro\n\n## Provided Context\n[START OF CONTEXT]\n\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all context; it may be lengthy or detailed\n- - Do not omit or overlook any relevant information\n- If the context is incomplete - or insufficient, state: \"Not enough data to answer this.\"\n- Read carefully - any extra instructions below if provided and use them to answer\n\nNow provide - your answer to the question: Como usar max_magic y dime como cambiar\u00e1 este - parametro en el futuro"}, "citations": null, "citation_threshold": null, "generative_model": - "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": - null, "json_schema": null, "format_prompt": false, "rerank_context": false, - "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": null}' + Do not omit or overlook any relevant information\n- Existing context summaries + are answer attempts produced by retrieval agents. Treat them as first-class + evidence and preserve their supported facts.\n- Combine complementary summaries + from multiple contexts when the question has multiple parts. Do not require + every context to answer the whole question by itself.\n- If a context summary + directly answers the question, do not replace it with an insufficient-data answer + merely because one retrieved chunk is incomplete; use the chunks for supporting + citations.\n- If the context is incomplete or insufficient, state: \"Not enough + data to answer this.\"\n- Read carefully any extra instructions below if provided + and use them to answer\n\nNow provide your answer to the question: Como usar + max_magic y dime como cambiar\u00e1 este parametro en el futuro"}, "citations": + null, "citation_threshold": null, "generative_model": "chatgpt-azure-4o-mini", + "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": null, "json_schema": + null, "format_prompt": false, "rerank_context": false, "tools": [], "tool_choice": + {"type": "auto"}, "reasoning": false, "seed": null}' headers: Accept: - application/x-ndjson @@ -767,7 +703,7 @@ interactions: Connection: - keep-alive Content-Length: - - '1583' + - '2096' Content-Type: - application/json Host: @@ -777,7 +713,7 @@ interactions: x-client-ident: - default x-message: - - cd53f9b3fe794812820ded296d32bbd6 + - 3acda4fcd790421d94b31c26074dd134 x-origin: - RAO x-session: @@ -806,14 +742,14 @@ interactions: {"chunk":{"type":"status","code":"-2"}} - {"chunk":{"type":"meta","input_tokens":7,"output_tokens":1,"timings":{"generative_first_chunk":0.33807772300497163,"generative":0.5206490700074937},"input_nuclia_tokens":0.007,"output_nuclia_tokens":0.001}} + {"chunk":{"type":"meta","input_tokens":9,"output_tokens":1,"timings":{"generative_first_chunk":0.6237019269992743,"generative":0.801959292999527},"input_nuclia_tokens":0.009,"output_nuclia_tokens":0.001}} - {"chunk":{"normalized_tokens":{"input":0.00681,"output":0.00096,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} + {"chunk":{"normalized_tokens":{"input":0.00936,"output":0.00096,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} ' headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -821,17 +757,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 15 Jul 2026 07:54:49 GMT + - Wed, 05 Aug 2026 07:25:31 GMT nuclia-learning-id: - - 1e058e30d3ac4c60b46f82524f899534 + - a5a5891e1f3f4bed90a45b271cee8907 nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '345' + - '633' x-nuclia-trace-id: - - c6da8b20dd2594f52910954d152e3ad0 + - ee593aa1d28f7d6f58bc58aa2a7bcb07 status: code: 200 message: OK @@ -848,22 +784,35 @@ interactions: Question\nComo usar max_magic y dime como cambiar\u00e1 este parametro en el futuro\n\n## Provided Context\n[START OF CONTEXT]\n\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all context; it may be lengthy or detailed\n- - Do not omit or overlook any relevant information\n- If the context is incomplete - or insufficient, state: \"Not enough data to answer this.\"\n- Read carefully - any extra instructions below if provided and use them to answer\n\n## Additional - Instructions for answering\n- \n## Question\nComo usar max_magic y dime como - cambiar\u00e1 este parametro en el futuro\n\n## Provided Context\n[START OF - CONTEXT]\n\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all - context; it may be lengthy or detailed\n- Do not omit or overlook any relevant - information\n- If the context is incomplete or insufficient, state: \"Not enough + Do not omit or overlook any relevant information\n- Existing context summaries + are answer attempts produced by retrieval agents. Treat them as first-class + evidence and preserve their supported facts.\n- Combine complementary summaries + from multiple contexts when the question has multiple parts. Do not require + every context to answer the whole question by itself.\n- If a context summary + directly answers the question, do not replace it with an insufficient-data answer + merely because one retrieved chunk is incomplete; use the chunks for supporting + citations.\n- If the context is incomplete or insufficient, state: \"Not enough data to answer this.\"\n- Read carefully any extra instructions below if provided - and use them to answer\n\nNow provide your answer to the question: Como usar - max_magic y dime como cambiar\u00e1 este parametro en el futuro\nNow provide - your answer to the question: Como usar max_magic y dime como cambiar\u00e1 este - parametro en el futuro"}, "citations": null, "citation_threshold": null, "generative_model": - "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": - null, "json_schema": null, "format_prompt": false, "rerank_context": false, - "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": null}' + and use them to answer\n\n## Additional Instructions for answering\n- \n## Question\nComo + usar max_magic y dime como cambiar\u00e1 este parametro en el futuro\n\n## Provided + Context\n[START OF CONTEXT]\n\n[END OF CONTEXT]\n\n## Answering Guidelines\n- + Carefully read all context; it may be lengthy or detailed\n- Do not omit or + overlook any relevant information\n- Existing context summaries are answer attempts + produced by retrieval agents. Treat them as first-class evidence and preserve + their supported facts.\n- Combine complementary summaries from multiple contexts + when the question has multiple parts. Do not require every context to answer + the whole question by itself.\n- If a context summary directly answers the question, + do not replace it with an insufficient-data answer merely because one retrieved + chunk is incomplete; use the chunks for supporting citations.\n- If the context + is incomplete or insufficient, state: \"Not enough data to answer this.\"\n- + Read carefully any extra instructions below if provided and use them to answer\n\nNow + provide your answer to the question: Como usar max_magic y dime como cambiar\u00e1 + este parametro en el futuro\nNow provide your answer to the question: Como usar + max_magic y dime como cambiar\u00e1 este parametro en el futuro"}, "citations": + null, "citation_threshold": null, "generative_model": "chatgpt-azure-4o-mini", + "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": null, "json_schema": + null, "format_prompt": false, "rerank_context": false, "tools": [], "tool_choice": + {"type": "auto"}, "reasoning": false, "seed": null}' headers: Accept: - application/x-ndjson @@ -872,7 +821,7 @@ interactions: Connection: - keep-alive Content-Length: - - '2204' + - '3230' Content-Type: - application/json Host: @@ -882,7 +831,7 @@ interactions: x-client-ident: - default x-message: - - cd53f9b3fe794812820ded296d32bbd6 + - 3acda4fcd790421d94b31c26074dd134 x-origin: - RAO x-session: @@ -911,9 +860,9 @@ interactions: {"chunk":{"type":"status","code":"-2"}} - {"chunk":{"type":"meta","input_tokens":11,"output_tokens":1,"timings":{"generative_first_chunk":0.3341072570037795,"generative":0.5523442519915989},"input_nuclia_tokens":0.011,"output_nuclia_tokens":0.001}} + {"chunk":{"type":"meta","input_tokens":16,"output_tokens":1,"timings":{"generative_first_chunk":0.8226836570029263,"generative":1.061455756003852},"input_nuclia_tokens":0.016,"output_nuclia_tokens":0.001}} - {"chunk":{"normalized_tokens":{"input":0.01062,"output":0.00096,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} + {"chunk":{"normalized_tokens":{"input":0.01572,"output":0.00096,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} ' headers: @@ -926,17 +875,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 15 Jul 2026 07:54:50 GMT + - Wed, 05 Aug 2026 07:25:32 GMT nuclia-learning-id: - - 1fff6a66d42a4397979b7d26a845dd5e + - 68504f8362b047cc97c2a9455eb4179c nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '341' + - '831' x-nuclia-trace-id: - - f4f0fcc92a3cb9816e6c4f432e2ea480 + - 0402bc021ab321004a0a3d025258a129 status: code: 200 message: OK @@ -965,7 +914,7 @@ interactions: uri: https://europe-1.dp.progress.cloud/api/v1/predict/remi response: body: - string: '{"time":3.3548359870910645,"answer_relevance":{"score":0,"reason":""},"context_relevance":[],"groundedness":[]}' + string: '{"time":0.5821390151977539,"answer_relevance":{"score":0,"reason":""},"context_relevance":[],"groundedness":[]}' headers: Alt-Svc: - h3=":443"; 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These lists may change over time, so we recommend periodically - fetching and applying updates to your firewall rules to ensure uninterrupted - service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall - restricts network traffic, you may need to allowlist the following IP addresses. - They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | - --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 - | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 - | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- - | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n - | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 - | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | - 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 - | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 - | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United - States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- - | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 - | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS - PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately - through an AWS endpoint service (AWS PrivateLink) instead of over the public - internet, allowing connections to be established from your VPC without traversing - public IP addresses. This option is not available through self-service configuration. - Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests - on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent - \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful - tool that enhances the capabilities of traditional retrieval-augmented generation - (RAG) systems. Regular RAG's fixed search-then-generate process is limiting - for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Different models can be chosen for different tasks: \\n \\n Context validation - happens when the Prune context option is enabled (recommended), we recommend - using a fast model - planning or the execution model (depending on the planning - mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Note: the rephrasing model is only used in more complex workflow, it can - be ignored in the present case. \\n Finally, add a Summarize agent in the - Generation step to generate a final answer from the retrieved information. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - The Smart Agent plans the answer: picks the most appropriate sources, splits - the question into sub-questions, evaluates relevancy, and iterates autonomously - until the information is sufficient. \\n Basic usage \\n To set up a Smart - Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, - etc.) in the Sources section of the left menu. Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. It will be slower but more accurate when processing - complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Also select the proper function for each registered agent, depending on the - type of source (MCP agents will not need one, the functions are provided dynamically - by the MCP server). \\n In the Smart Agent configuration, you can select the - planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - In the Summarize Agent, enable the Conversational mode. This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. You can embed it in - your website or application, and it will provide a chat user interface for - interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Go to the Widgets section in the left menu, and click on Create widget to - create a new widget. You can customize its appearance, and then copy the generated - code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" - headers: - Alt-Svc: - - h3=":443"; ma=2592000 - Content-Length: - - '12993' - access-control-expose-headers: - - X-NUCLIA-TRACE-ID - content-type: - - application/json - date: - - Wed, 15 Jul 2026 07:54:43 GMT - via: - - 1.1 google - x-envoy-upstream-service-time: - - '55' - x-nuclia-trace-id: - - 0567f1d3747ec542b0481fcc98a42a75 - status: - code: 200 - message: OK -- request: - body: '' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Host: - - europe-1.nuclia.cloud - User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: - - DUMMY - method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: - string: '{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner - Content","related":"","text":"","uri":""},{"title":"Softcat","related":"","text":"","uri":""},{"title":"Sales - Enablement Assets","related":"","text":"","uri":""},{"title":"KO 26","related":"","text":"","uri":""},{"title":"Data - Sheets","related":"","text":"","uri":""},{"title":"Progress Agentic RAG Training - Materials 2026","related":"","text":"","uri":""}]}' + string: "{\"resources\":{\"7c9e318a8fcc4c9485b8639fdbe93b38\":{\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"slug\":\"docs-develop-nua-md\",\"title\":\"docs + > develop > nua\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-29T07:32:38.792855\",\"modified\":\"2026-07-29T07:32:38.792869\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Processing \\n Push a file \\n Processing data works in 2 steps: \\n + \\n First you will upload the file with /processing/upload, which returns + an upload token. \\n Then you will put this token in the processing queue + with /processing/push so the file is processed. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1627,\"end\":1890},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + json \\n { \\n webhook_config : { \\n uri : http://some.where/my-custom-webhook + , \\n headers : { \\n api-key : xxxxxxxxxx \\n } \\n } \\n } \\n Also, you + can choose to use a fixed uri on your token, and provide the headers in the + /push calls. In this case you don't need to provide the uri parameter. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":23,\"start\":9053,\"end\":9339},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Get a NUA key \\n In order to use the Nuclia Understanding API (NUA), you + first need to generate an API key. \\n There are two options to create an + API key: \\n \\n Using the Agentic RAG dashboard top-right menu: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":496,\"end\":703},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Note: If you have a Knowledge Box and want to use the predict endpoints, they + are proxied through the /api/v1/kb//predict endpoint. You will need to provide + a KB's regular authentication, a NUA API key will not be necessary.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":28,\"start\":10377,\"end\":10603},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The payload received from /requests is based on the fdbwriter.BrokerMessage + provided by writer.proto. \\n Streamed results \\n The /processing/requests//results + endpoint is similar but it returns directly the decoded results as a stream. + You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":18,\"start\":7453,\"end\":7716},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Processing happens asynchronously, so you will need to regularly check the + queue output using one of the two endpoints available to retrieve the results. + \\n Protobuffer results \\n The /processing/requests/ endpoint returns a protobuffer + payload with the processing results. You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":12,\"start\":5098,\"end\":5399},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: nua \\n title: Nuclia Understanding API \\n \\n Using the Nuclia Understanding + API \\n The Nuclia Understanding API (NUA) allows you to process data outside + of a Knowledge Box. It is a set of endpoints that allow you to send data to + the Progress Agentic RAG platform for processing, or to make calls to models + to generate text, summaries, or other outputs. The information is stored temporarily + for the duration of the processing, nothing remains in the ProgressAgentic + RAG cloud infrastructure. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":496},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests/' \\\\ + \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n The response is a JSON object containing + completed indicating if the processing is complete or not, and in case it + is,a response string. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":13,\"start\":5399,\"end\":5644},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n In Python, you can use nucliadb_protos to decode the results: \\n + ```python \\n import base64 \\n import requests \\n from nucliadb_protos.writer_pb2 + import BrokerMessage \\n processing_id = THE_PROCESSING_ID_YOU_RECEIVED_FROM_PUSH + \\n res = requests.get(f'https://europe-1.nuclia.cloud/api/v1/processing/requests/{processing_id}',headers={ + \\n X-NUCLIA-NUAKEY : Bearer YOUR_NUA_KEY , \\n }).json() \\n if payload in + res: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":16,\"start\":6812,\"end\":7224},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/push' \\\\ \\n + -X POST \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\\\ \\n -H 'Content-Type: + application/json' \\\\ \\n --data-raw '{ filefield :{ my_file_1 : eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.W8wfVj04aYicREYXRatCTb8F8-PD4Ph7MmiTliHi6DI + }}' \\n Push text \\n Instead of uploading a file and then pushing it to the + queue, you can also push some text directly to the queue. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":9,\"start\":2730,\"end\":3646},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + It may also be used to create (or delete) Knowledge Boxes via the API \u2013 + for example, if you need to automate Knowledge Box creation. In that case + you will need to select the Allow management of Knowledge Boxes checkbox during + the NUA key creation. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1170,\"end\":1420},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + /predict/rerank reranks a list of results to improve the relevance of the + top results. \\n /predict/sentence computes the embedding of a sentence. \\n + /predict/summarize summarizes a text. \\n \\n The calls must provides the + X-NUCLIA-NUAKEY header with your NUA key: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":26,\"start\":9847,\"end\":10108},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests//results' + \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n Moreover the data_types parameter + allows you to filter the results by data type. For example: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":19,\"start\":7716,\"end\":7926},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Here is a typical example: \\n shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/upload' + \\\\ \\n -X POST \\\\ \\n -H X-NUCLIA-NUAKEY: Bearer \\\\ \\n -H 'content-type: + ' \\\\ \\n -T /path/to/file \\n Will return something like: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":1890,\"end\":2109},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + :::note \\n If an error occurs when posting the result to the webhook URL, + the result is stored in the queue and can be retrieved by calling the /pull + endpoint (see previous section). The error message is appended to the result. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":24,\"start\":9339,\"end\":9568},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + pb = BrokerMessage() \\n pb.ParseFromString( \\n base64.b64decode(res[ payload + ]) \\n ) \\n print(pb) \\n else: \\n print('No payload') \\n ``` \\n For other + languages, Nuclia protobuffer models can be found on the NucliaDB GitHub repository. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":17,\"start\":7224,\"end\":7453},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Model calls \\n The predict endpoints offer various services: \\n + \\n /predict/chat makes a direct call to an LLM. \\n /predict/remi calls the + REMi model to measure the quality of a RAG response. \\n /predict/rephrase + rephrases a question to make it more suitable for a RAG query. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":25,\"start\":9568,\"end\":9847},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJ1cm46cHJveHkiLCJzdWIiOiJmaWxlIiwiYXVkIjoidXJuOnByb3h5IiwiZXhwIjoxNjU1ODkyMDgwLCJpYXQiOjE2NTU4ODg0ODAsImp0aSI6ImFmN2ZmYjU1ZjAxMjRlMzM5MmRjMDY5MmM2NWI5NzY3Iiwic2l6ZSI6ODk3LCJidWNrZXRfbmFtZSI6ImV1cm9wZS0xLXN0b3JhZ2UtcHJveHkiLCJ1cmkiOiIwZDg2YTFmYTcxN2Q0NDUxYTAwM2Q1NGIyNzM2YTA0ZSIsImRyaXZlciI6MCwiY29udGVudF90eXBlIjoiYXBwbGljYXRpb24vb2N0ZXQtc3RyZWFtIiwiZmlsZW5hbWUiOiIiLCJwYXNzd29yZCI6bnVsbCwibGFuZ3VhZ2UiOm51bGwsInNvdXJjZSI6MCwibWQ1IjpudWxsfQ.VItLa_fUen2Pt5W2440Bjwc7Zx64rv6mJnRMFIdao5o + \\n That is your upload token. Now you can push this token to the processing + queue with: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2109,\"end\":2730},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also at any level, if an attribute exceeds a certain size, it will be put + in a downloadable file and will be replaced in the document by a file pointer. + This will consist of { file : { uri : JWT_TOKEN }}. The rule is that if the + size of the message is greater than 1000000 characters, the biggest parts + will be moved to downloadable files. First, the compression process will target + vectors. If that is not enough, it will target large field metadata, and finally + it will target extracted text. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":15,\"start\":6315,\"end\":6812},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In this case, any time a new result is available Nuclia will post it (i.e. + make an actual POST call) to this URL, sending the protobuffer result as payload. + \\n To use a webhook, you will need to fill in the Webhook URL field in the + NUA key creation form when you create your key. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":21,\"start\":8236,\"end\":8517},\"fuzzy_result\":false}],\"facets\":{},\"query\":\"\",\"total\":5358,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - - h3=":443"; ma=2592000 + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - - '507' + - '12190' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:43 GMT + - Wed, 05 Aug 2026 07:25:19 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '13' + - '49' x-nuclia-trace-id: - - 0a07ad51c7cdae2339938241bc3a2162 + - 58f03bed4e7d5288ac11eccdd7471846 status: code: 200 message: OK @@ -456,7 +398,7 @@ interactions: Content-Length: - '18' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -464,126 +406,121 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: - string: "{\"resources\":{\"b28e388104644fc5bba68c0cd44e01d4\":{\"id\":\"b28e388104644fc5bba68c0cd44e01d4\",\"slug\":\"docs-agentic-how-to-agentic-retrieval-md\",\"title\":\"docs - > agentic > how to > agentic retrieval\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-29T13:39:03.379512\",\"modified\":\"2026-06-29T13:39:03.379525\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"f13642b2862f4a1ea2144c9eb2abb2a3\":{\"id\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"slug\":\"docs-develop-js-sdk-functions-normalizeGlobalBackendUrl-md\",\"title\":\"docs - > develop > js sdk > functions > normalizeGlobalBackendUrl\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-26T08:38:33.060378\",\"modified\":\"2026-07-14T12:47:15.556468\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"ed6fda7434aa43a3bd5138b95e7fe081\":{\"id\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"slug\":\"docs-develop-python-sdk-15-memory-md\",\"title\":\"docs - > develop > python sdk > 15 memory\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-26T08:31:21.372271\",\"modified\":\"2026-06-26T08:59:38.187065\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"a572ce0c7eb949e4a17babae21a03a4a\":{\"id\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"slug\":\"navigation-pages\",\"title\":\"navigation-pages\",\"summary\":\"\",\"icon\":\"application/json\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"fr\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-23T10:58:22.812220\",\"modified\":\"2026-06-23T10:58:22.812242\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs - > agentic > deploy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-29T13:39:02.557258\",\"modified\":\"2026-06-29T13:39:02.557276\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"007b445866574d7ca69891d388663cc6\":{\"id\":\"007b445866574d7ca69891d388663cc6\",\"slug\":\"docs-management-security-5-public-ips-md\",\"title\":\"docs - > management > security > 5 public ips\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-03T09:28:57.937064\",\"modified\":\"2026-07-03T09:28:57.937076\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Outbound \u2014 the source IP addresses that Progress Agentic RAG uses when - making connections to your systems (e.g., webhooks, sync agents, or other - integrations). Allowlist these if you restrict inbound traffic to your infrastructure. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n :::note \\n The current list of IP addresses is also available in machine-readable - format: JSON | YAML. These lists may change over time, so we recommend periodically - fetching and applying updates to your firewall rules to ensure uninterrupted - service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall - restricts network traffic, you may need to allowlist the following IP addresses. - They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | - --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 - | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 - | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- - | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n - | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 - | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | - 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 - | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 - | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United - States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- - | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 - | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS - PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately - through an AWS endpoint service (AWS PrivateLink) instead of over the public - internet, allowing connections to be established from your VPC without traversing - public IP addresses. This option is not available through self-service configuration. - Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests - on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent - \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful - tool that enhances the capabilities of traditional retrieval-augmented generation - (RAG) systems. Regular RAG's fixed search-then-generate process is limiting - for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Different models can be chosen for different tasks: \\n \\n Context validation - happens when the Prune context option is enabled (recommended), we recommend - using a fast model - planning or the execution model (depending on the planning - mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Note: the rephrasing model is only used in more complex workflow, it can - be ignored in the present case. \\n Finally, add a Summarize agent in the - Generation step to generate a final answer from the retrieved information. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - The Smart Agent plans the answer: picks the most appropriate sources, splits - the question into sub-questions, evaluates relevancy, and iterates autonomously - until the information is sufficient. \\n Basic usage \\n To set up a Smart - Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, - etc.) in the Sources section of the left menu. Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. It will be slower but more accurate when processing - complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Also select the proper function for each registered agent, depending on the - type of source (MCP agents will not need one, the functions are provided dynamically - by the MCP server). \\n In the Smart Agent configuration, you can select the - planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - In the Summarize Agent, enable the Conversational mode. This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. You can embed it in - your website or application, and it will provide a chat user interface for - interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Go to the Widgets section in the left menu, and click on Create widget to - create a new widget. You can customize its appearance, and then copy the generated - code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{\"/k\":{\"/k/text\":5294}},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"fulltext\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-resources\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-search\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-rag-lab\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"account-arag\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-kv-schemas\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"user-profile\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-users\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-widgets\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-remi-analytics\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"agent-users\",\"labels\":[]}],\"facets\":{},\"query\":\"\",\"total\":2013,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" + string: "{\"resources\":{\"09305118c7314e1483068fb9a588578f\":{\"id\":\"09305118c7314e1483068fb9a588578f\",\"slug\":\"docs-develop-js-sdk-interfaces-KeyValueRangeFilter-md\",\"title\":\"docs + > develop > js sdk > interfaces > KeyValueRangeFilter\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-17T09:12:59.683605\",\"modified\":\"2026-08-03T13:15:39.704705\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"7c9e318a8fcc4c9485b8639fdbe93b38\":{\"id\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"slug\":\"docs-develop-nua-md\",\"title\":\"docs + > develop > 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file_storage\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-16T08:13:35.152238\",\"modified\":\"2026-07-16T08:13:35.152248\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"b5eec709afcf4068a4211a16f1a79576\":{\"id\":\"b5eec709afcf4068a4211a16f1a79576\",\"slug\":\"docs-develop-js-sdk-type-aliases-KeyValueFilterExpression-md\",\"title\":\"docs + > develop > js sdk > type aliases > KeyValueFilterExpression\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-17T09:16:41.330227\",\"modified\":\"2026-08-03T13:19:49.747344\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"5c4166eea30d4b329fb3f141e395781a\":{\"id\":\"5c4166eea30d4b329fb3f141e395781a\",\"slug\":\"docs-develop-js-sdk-interfaces-KeyValueContainsFilter-md\",\"title\":\"docs + > develop > js sdk > interfaces > KeyValueContainsFilter\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"fr\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-17T09:13:32.136172\",\"modified\":\"2026-08-03T13:14:39.313725\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"14b3bd967e2b44ba98372a8d9a0716b6\":{\"id\":\"14b3bd967e2b44ba98372a8d9a0716b6\",\"slug\":\"docs-develop-js-sdk-interfaces-NUAClientEditPayload-md\",\"title\":\"docs + > develop > js sdk > interfaces > NUAClientEditPayload\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"eo\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-28T13:27:28.455426\",\"modified\":\"2026-08-03T13:14:53.788626\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"831a4c9bcc2e49d6a1f2a84c811f4fb6\":{\"id\":\"831a4c9bcc2e49d6a1f2a84c811f4fb6\",\"slug\":\"docs-management-nucliadb-deploy-01-basics-md\",\"title\":\"docs + > management > nucliadb > deploy > 01 basics\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-16T08:13:36.319511\",\"modified\":\"2026-07-16T08:13:36.319522\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"9ae2d3a90d0d452db50f170c535905d4\":{\"id\":\"9ae2d3a90d0d452db50f170c535905d4\",\"slug\":\"docs-develop-js-sdk-interfaces-KeyValueEqualFilter-md\",\"title\":\"docs + > develop > js sdk > interfaces > KeyValueEqualFilter\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-17T09:11:44.148330\",\"modified\":\"2026-08-03T13:16:53.789716\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"d97695fece7948c59cb9b95404b3a5f9\":{\"id\":\"d97695fece7948c59cb9b95404b3a5f9\",\"slug\":\"docs-management-nucliadb-deploy-05-access-md\",\"title\":\"docs + > management > nucliadb > deploy > 05 access\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-16T08:13:36.926639\",\"modified\":\"2026-07-16T08:13:36.926650\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"78943baafe6a49848b4b29e683eaa983\":{\"id\":\"78943baafe6a49848b4b29e683eaa983\",\"slug\":\"docs-develop-js-sdk-interfaces-NUAClientResponse-md\",\"title\":\"docs + > develop > js sdk > interfaces > NUAClientResponse\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"ca\",\"languages\":[\"eo\",\"ca\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-28T13:26:37.201678\",\"modified\":\"2026-08-03T13:16:09.581726\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Processing \\n Push a file \\n Processing data works in 2 steps: \\n + \\n First you will upload the file with /processing/upload, which returns + an upload token. \\n Then you will put this token in the processing queue + with /processing/push so the file is processed. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1627,\"end\":1890},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + json \\n { \\n webhook_config : { \\n uri : http://some.where/my-custom-webhook + , \\n headers : { \\n api-key : xxxxxxxxxx \\n } \\n } \\n } \\n Also, you + can choose to use a fixed uri on your token, and provide the headers in the + /push calls. In this case you don't need to provide the uri parameter. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":23,\"start\":9053,\"end\":9339},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Get a NUA key \\n In order to use the Nuclia Understanding API (NUA), you + first need to generate an API key. \\n There are two options to create an + API key: \\n \\n Using the Agentic RAG dashboard top-right menu: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":496,\"end\":703},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Note: If you have a Knowledge Box and want to use the predict endpoints, they + are proxied through the /api/v1/kb//predict endpoint. You will need to provide + a KB's regular authentication, a NUA API key will not be necessary.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":28,\"start\":10377,\"end\":10603},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The payload received from /requests is based on the fdbwriter.BrokerMessage + provided by writer.proto. \\n Streamed results \\n The /processing/requests//results + endpoint is similar but it returns directly the decoded results as a stream. + You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":18,\"start\":7453,\"end\":7716},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Processing happens asynchronously, so you will need to regularly check the + queue output using one of the two endpoints available to retrieve the results. + \\n Protobuffer results \\n The /processing/requests/ endpoint returns a protobuffer + payload with the processing results. You can call it like this: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":12,\"start\":5098,\"end\":5399},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: nua \\n title: Nuclia Understanding API \\n \\n Using the Nuclia Understanding + API \\n The Nuclia Understanding API (NUA) allows you to process data outside + of a Knowledge Box. It is a set of endpoints that allow you to send data to + the Progress Agentic RAG platform for processing, or to make calls to models + to generate text, summaries, or other outputs. The information is stored temporarily + for the duration of the processing, nothing remains in the ProgressAgentic + RAG cloud infrastructure. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":496},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests/' \\\\ + \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n The response is a JSON object containing + completed indicating if the processing is complete or not, and in case it + is,a response string. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":13,\"start\":5399,\"end\":5644},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n In Python, you can use nucliadb_protos to decode the results: \\n + ```python \\n import base64 \\n import requests \\n from nucliadb_protos.writer_pb2 + import BrokerMessage \\n processing_id = THE_PROCESSING_ID_YOU_RECEIVED_FROM_PUSH + \\n res = requests.get(f'https://europe-1.nuclia.cloud/api/v1/processing/requests/{processing_id}',headers={ + \\n X-NUCLIA-NUAKEY : Bearer YOUR_NUA_KEY , \\n }).json() \\n if payload in + res: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":16,\"start\":6812,\"end\":7224},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/push' \\\\ \\n + -X POST \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\\\ \\n -H 'Content-Type: + application/json' \\\\ \\n --data-raw '{ filefield :{ my_file_1 : eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.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.W8wfVj04aYicREYXRatCTb8F8-PD4Ph7MmiTliHi6DI + }}' \\n Push text \\n Instead of uploading a file and then pushing it to the + queue, you can also push some text directly to the queue. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":9,\"start\":2730,\"end\":3646},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + It may also be used to create (or delete) Knowledge Boxes via the API \u2013 + for example, if you need to automate Knowledge Box creation. In that case + you will need to select the Allow management of Knowledge Boxes checkbox during + the NUA key creation. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1170,\"end\":1420},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + /predict/rerank reranks a list of results to improve the relevance of the + top results. \\n /predict/sentence computes the embedding of a sentence. \\n + /predict/summarize summarizes a text. \\n \\n The calls must provides the + X-NUCLIA-NUAKEY header with your NUA key: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":26,\"start\":9847,\"end\":10108},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/requests//results' + \\\\ \\n -H 'X-NUCLIA-NUAKEY: Bearer ' \\n Moreover the data_types parameter + allows you to filter the results by data type. For example: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":19,\"start\":7716,\"end\":7926},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Here is a typical example: \\n shell \\n curl 'https://.dp.progress.cloud/api/v1/processing/upload' + \\\\ \\n -X POST \\\\ \\n -H X-NUCLIA-NUAKEY: Bearer \\\\ \\n -H 'content-type: + ' \\\\ \\n -T /path/to/file \\n Will return something like: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":1890,\"end\":2109},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + :::note \\n If an error occurs when posting the result to the webhook URL, + the result is stored in the queue and can be retrieved by calling the /pull + endpoint (see previous section). The error message is appended to the result. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":24,\"start\":9339,\"end\":9568},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + pb = BrokerMessage() \\n pb.ParseFromString( \\n base64.b64decode(res[ payload + ]) \\n ) \\n print(pb) \\n else: \\n print('No payload') \\n ``` \\n For other + languages, Nuclia protobuffer models can be found on the NucliaDB GitHub repository. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":17,\"start\":7224,\"end\":7453},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Model calls \\n The predict endpoints offer various services: \\n + \\n /predict/chat makes a direct call to an LLM. \\n /predict/remi calls the + REMi model to measure the quality of a RAG response. \\n /predict/rephrase + rephrases a question to make it more suitable for a RAG query. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":25,\"start\":9568,\"end\":9847},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJ1cm46cHJveHkiLCJzdWIiOiJmaWxlIiwiYXVkIjoidXJuOnByb3h5IiwiZXhwIjoxNjU1ODkyMDgwLCJpYXQiOjE2NTU4ODg0ODAsImp0aSI6ImFmN2ZmYjU1ZjAxMjRlMzM5MmRjMDY5MmM2NWI5NzY3Iiwic2l6ZSI6ODk3LCJidWNrZXRfbmFtZSI6ImV1cm9wZS0xLXN0b3JhZ2UtcHJveHkiLCJ1cmkiOiIwZDg2YTFmYTcxN2Q0NDUxYTAwM2Q1NGIyNzM2YTA0ZSIsImRyaXZlciI6MCwiY29udGVudF90eXBlIjoiYXBwbGljYXRpb24vb2N0ZXQtc3RyZWFtIiwiZmlsZW5hbWUiOiIiLCJwYXNzd29yZCI6bnVsbCwibGFuZ3VhZ2UiOm51bGwsInNvdXJjZSI6MCwibWQ1IjpudWxsfQ.VItLa_fUen2Pt5W2440Bjwc7Zx64rv6mJnRMFIdao5o + \\n That is your upload token. Now you can push this token to the processing + queue with: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2109,\"end\":2730},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also at any level, if an attribute exceeds a certain size, it will be put + in a downloadable file and will be replaced in the document by a file pointer. + This will consist of { file : { uri : JWT_TOKEN }}. The rule is that if the + size of the message is greater than 1000000 characters, the biggest parts + will be moved to downloadable files. First, the compression process will target + vectors. If that is not enough, it will target large field metadata, and finally + it will target extracted text. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":15,\"start\":6315,\"end\":6812},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In this case, any time a new result is available Nuclia will post it (i.e. + make an actual POST call) to this URL, sending the protobuffer result as payload. + \\n To use a webhook, you will need to fill in the Webhook URL field in the + NUA key creation form when you create your key. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":21,\"start\":8236,\"end\":8517},\"fuzzy_result\":false}],\"facets\":{\"/k\":{\"/k/text\":5358}},\"query\":\"\",\"total\":5358,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"fulltext\":{\"results\":[{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"7c9e318a8fcc4c9485b8639fdbe93b38\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"14b3bd967e2b44ba98372a8d9a0716b6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"14b3bd967e2b44ba98372a8d9a0716b6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"78943baafe6a49848b4b29e683eaa983\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"78943baafe6a49848b4b29e683eaa983\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b5eec709afcf4068a4211a16f1a79576\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b5eec709afcf4068a4211a16f1a79576\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5c4166eea30d4b329fb3f141e395781a\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5c4166eea30d4b329fb3f141e395781a\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"09305118c7314e1483068fb9a588578f\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"09305118c7314e1483068fb9a588578f\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"9ae2d3a90d0d452db50f170c535905d4\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"9ae2d3a90d0d452db50f170c535905d4\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"831a4c9bcc2e49d6a1f2a84c811f4fb6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"831a4c9bcc2e49d6a1f2a84c811f4fb6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"d97695fece7948c59cb9b95404b3a5f9\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"d97695fece7948c59cb9b95404b3a5f9\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5ae74950b55c4d60b754fa706314b24a\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"5ae74950b55c4d60b754fa706314b24a\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]}],\"facets\":{},\"query\":\"\",\"total\":2029,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - - h3=":443"; ma=2592000 + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - - '16898' + - '19708' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:43 GMT + - Wed, 05 Aug 2026 07:25:19 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '63' + - '72' x-nuclia-trace-id: - - a4e4d13e9bf1231c7a5b78029d6f5ab4 + - 94985f7fa1f53e5f0ca859b1e83a7467 status: code: 200 message: OK @@ -600,7 +537,7 @@ interactions: Content-Length: - '154' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -608,19 +545,42 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/ask + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/ask response: body: string: "{\"item\":{\"type\":\"answer\",\"text\":\"Not\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" enough\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" data\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" to\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" answer\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\" - this\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"retrieval\",\"results\":{\"resources\":{\"d1e1eaa16d6646b2b8ac88df5726f82f\":{\"id\":\"d1e1eaa16d6646b2b8ac88df5726f82f\",\"slug\":\"docs-develop-js-sdk-interfaces-ExtractVLLMConfig-md\",\"title\":\"docs - > develop > js sdk > interfaces > ExtractVLLMConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:01:23.529670\",\"modified\":\"2026-07-14T12:52:10.106536\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"d1e1eaa16d6646b2b8ac88df5726f82f/t/page/0-230\":{\"score\":0.00038296362617984414,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ExtractVLLMConfig \\n Interface: ExtractVLLMConfig - \\n Properties \\n llm? \\n \\n optional llm: ExtractLLMConfig \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:524 \\n \\n max_pages_to_merge? - \\n\",\"id\":\"d1e1eaa16d6646b2b8ac88df5726f82f/t/page/0-230\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":230,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"4ffdd42c713149249892d3b643ab3c81\":{\"id\":\"4ffdd42c713149249892d3b643ab3c81\",\"slug\":\"docs-develop-js-sdk-namespaces-Widget-interfaces-RagStrategiesConfig-md\",\"title\":\"docs - > develop > js sdk > namespaces > Widget > interfaces > RagStrategiesConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:52.988969\",\"modified\":\"2026-07-14T12:48:53.133910\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"4ffdd42c713149249892d3b643ab3c81/t/page/1081-2749\":{\"score\":0.0018969200318679214,\"score_type\":\"RERANKER\",\"order\":1,\"text\":\" + this\"}}\n{\"item\":{\"type\":\"answer\",\"text\":\".\"}}\n{\"item\":{\"type\":\"retrieval\",\"results\":{\"resources\":{\"220eb37c167f4eb9bb8e9454e7ba8cf5\":{\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5\",\"slug\":\"docs-develop-python-sdk-05-search-md\",\"title\":\"docs + > develop > python sdk > 05 search\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:48:33.723913\",\"modified\":\"2026-06-09T08:08:04.866092\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\":{\"score\":0.0007524627726525068,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" + ::: \\n :::warning \\n Enabling reasoning can use additional tokens, which + may increase your usage costs. \\n You may need to increase max_tokens to + give the LLM enough room to reason and generate an answer. \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2505,\"end\":2709,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-08-03T13:17:30.667856\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\":{\"score\":0.00046010586083866656,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\" + \\n optional max_images: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 + \\n \\n output_tokens \\n \\n output_tokens: object \\n \\n default_max? \\n + \\n optional default_max: number \\n \\n max \\n \\n max: number \\n \\n min? + \\n \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"bd8ccba0ddc341dd851891ba2cccc08f\":{\"id\":\"bd8ccba0ddc341dd851891ba2cccc08f\",\"slug\":\"docs-develop-js-sdk-type-aliases-MagicActionType-md\",\"title\":\"docs + > develop > js sdk > type aliases > MagicActionType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-03-10T15:04:00.830962\",\"modified\":\"2026-08-03T13:19:36.955363\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/a/title\":{\"paragraphs\":{\"bd8ccba0ddc341dd851891ba2cccc08f/a/title/0-56\":{\"score\":0.0014953383943066,\"score_type\":\"RERANKER\",\"order\":2,\"text\":\"docs + > develop > js sdk > type aliases > MagicActionType\",\"id\":\"bd8ccba0ddc341dd851891ba2cccc08f/a/title/0-56\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":56,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"53b91ad0dd5f48a7ac8b59f9775ed7e0\":{\"id\":\"53b91ad0dd5f48a7ac8b59f9775ed7e0\",\"slug\":\"docs-api-mdx\",\"title\":\"docs + > api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"ca\",\"en\",\"hu\",\"la\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:45.557031\",\"modified\":\"2026-06-09T08:18:15.494834\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"53b91ad0dd5f48a7ac8b59f9775ed7e0/t/page/257-334\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":19,\"text\":\" + } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } + \\n `} \\n \\n \",\"id\":\"53b91ad0dd5f48a7ac8b59f9775ed7e0/t/page/257-334\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":257,\"end\":334,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"9ac9bbc6ad5c41f687b4a5f96b3b161a\":{\"id\":\"9ac9bbc6ad5c41f687b4a5f96b3b161a\",\"slug\":\"docs-develop-js-sdk-interfaces-RemiQueryCriteria-md\",\"title\":\"docs + > develop > js sdk > interfaces > RemiQueryCriteria\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:02.221744\",\"modified\":\"2026-08-03T13:16:14.394022\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"9ac9bbc6ad5c41f687b4a5f96b3b161a/t/page/0-273\":{\"score\":0.0002182420575991273,\"score_type\":\"RERANKER\",\"order\":15,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / RemiQueryCriteria \\n Interface: RemiQueryCriteria + \\n Properties \\n context_relevance? \\n \\n optional context_relevance: + object \\n \\n aggregation \\n \\n aggregation: average \\\\| min \\\\| max + \\n \\n operation \\n \\n operation: gt \\\\| lt \\\\| eq \\n \\n value \\n + \\n\",\"id\":\"9ac9bbc6ad5c41f687b4a5f96b3b161a/t/page/0-273\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":273,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"38ec4cc5c66e436a946ea7893b6662a3\":{\"id\":\"38ec4cc5c66e436a946ea7893b6662a3\",\"slug\":\"docs-changelog-updates-2024-10-md\",\"title\":\"docs + > changelog > updates > 2024 10\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:49.934688\",\"modified\":\"2026-06-09T08:07:26.696807\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708\":{\"score\":0.00045474793296307325,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" + Important API Updates (All changes will be effective as of November 11th, + please make your plans): \\n \\n Remember we are moving forward with better + parameters: \\n Farewell to page_number and page_size in /search and /find + endpoints as they will be discontinued on the 11th - say hello to top_k! \\n\",\"id\":\"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":1414,\"end\":1708,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"42a4cd5a30314e94aa079ed0cfe81381\":{\"id\":\"42a4cd5a30314e94aa079ed0cfe81381\",\"slug\":\"docs-develop-js-sdk-interfaces-SplitStrategy-md\",\"title\":\"docs + > develop > js sdk > interfaces > SplitStrategy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:02:38.468609\",\"modified\":\"2026-08-03T13:14:41.671354\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\":{\"score\":0.0005770345451310277,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" + \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 + \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"id\":\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"4ffdd42c713149249892d3b643ab3c81\":{\"id\":\"4ffdd42c713149249892d3b643ab3c81\",\"slug\":\"docs-develop-js-sdk-namespaces-Widget-interfaces-RagStrategiesConfig-md\",\"title\":\"docs + > develop > js sdk > namespaces > Widget > interfaces > RagStrategiesConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:52.988969\",\"modified\":\"2026-08-03T13:14:13.201266\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"4ffdd42c713149249892d3b643ab3c81/t/page/1081-2749\":{\"score\":0.0018969200318679214,\"score_type\":\"RERANKER\",\"order\":0,\"text\":\" graph: undefined \\\\| object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/widget.ts:55 \\n \\n graphRagStrategy \\n \\n graphRagStrategy: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/widget.ts:54 \\n \\n includeNeighbouringParagraphs @@ -642,80 +602,51 @@ interactions: \\n \\n precedingParagraphs \\n \\n precedingParagraphs: null \\\\| number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/widget.ts:70 \\n \\n succeedingParagraphs \\n \\n succeedingParagraphs: null \\\\| number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/widget.ts:71\",\"id\":\"4ffdd42c713149249892d3b643ab3c81/t/page/1081-2749\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":1081,\"end\":2749,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs - > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-07-14T12:49:58.922592\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\":{\"score\":0.00046010586083866656,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" - \\n optional max_images: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 - \\n \\n output_tokens \\n \\n output_tokens: object \\n \\n default_max? \\n - \\n optional default_max: number \\n \\n max \\n \\n max: number \\n \\n min? - \\n \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"91d9ee7dc2bd47e5b4a1011ca8e42bfd\":{\"id\":\"91d9ee7dc2bd47e5b4a1011ca8e42bfd\",\"slug\":\"docs-zone-api-mdx\",\"title\":\"docs - > zone api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:43.137585\",\"modified\":\"2026-06-09T08:18:13.619843\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"91d9ee7dc2bd47e5b4a1011ca8e42bfd/t/page/252-329\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":19,\"text\":\" - } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } - \\n `} \\n \\n \",\"id\":\"91d9ee7dc2bd47e5b4a1011ca8e42bfd/t/page/252-329\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":252,\"end\":329,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"c053e849251b4a5296ffeb79ed00200e\":{\"id\":\"c053e849251b4a5296ffeb79ed00200e\",\"slug\":\"docs-nua-api-mdx\",\"title\":\"docs - > nua api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:43.966941\",\"modified\":\"2026-06-09T08:18:14.251220\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"c053e849251b4a5296ffeb79ed00200e/t/page/289-366\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\" - } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } - \\n `} \\n \\n \",\"id\":\"c053e849251b4a5296ffeb79ed00200e/t/page/289-366\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":289,\"end\":366,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"78aebdf4ca3a4028a555552a07e10e6d\":{\"id\":\"78aebdf4ca3a4028a555552a07e10e6d\",\"slug\":\"docs-rag-advanced-score-rank-and-rerank-md\",\"title\":\"docs - > rag > advanced > score rank and rerank\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-12-02T13:02:38.557991\",\"modified\":\"2026-06-09T08:07:41.924988\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"78aebdf4ca3a4028a555552a07e10e6d/t/page/5733-6021\":{\"score\":0.00029595711384899914,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" + Defined in \\n libs/sdk-core/src/lib/db/search/widget.ts:71\",\"id\":\"4ffdd42c713149249892d3b643ab3c81/t/page/1081-2749\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":1081,\"end\":2749,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"8870dfa28ab342f9ba2b1832f4ce864c\":{\"id\":\"8870dfa28ab342f9ba2b1832f4ce864c\",\"slug\":\"docs-develop-js-sdk-interfaces-SqlAgent-md\",\"title\":\"docs + > develop > js sdk > interfaces > SqlAgent\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"eo\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:00:54.678573\",\"modified\":\"2026-08-03T13:15:25.687284\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"8870dfa28ab342f9ba2b1832f4ce864c/t/page/1535-1748\":{\"score\":0.0002251682453788817,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" + \\n optional lazy_table_reflection: boolean \\n \\n Inherited from \\n SqlAgentCreation.lazy_table_reflection + \\n Defined in \\n libs/sdk-core/src/lib/db/retrieval-agent/retrieval-agent.models.ts:216 + \\n \\n max_string_length? \\n\",\"id\":\"8870dfa28ab342f9ba2b1832f4ce864c/t/page/1535-1748\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1535,\"end\":1748,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"78aebdf4ca3a4028a555552a07e10e6d\":{\"id\":\"78aebdf4ca3a4028a555552a07e10e6d\",\"slug\":\"docs-rag-advanced-score-rank-and-rerank-md\",\"title\":\"docs + > rag > advanced > score rank and rerank\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-12-02T13:02:38.557991\",\"modified\":\"2026-06-09T08:07:41.924988\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"78aebdf4ca3a4028a555552a07e10e6d/t/page/5733-6021\":{\"score\":0.00029595711384899914,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" In an actual request, these are the parameters to use in /find or /ask: \\n json \\n { \\n features : [ semantic , keyword ], \\n rank_fusion : { \\n name : rrf , \\n boosting : { \\n semantic : 2, \\n }, \\n window : 80, \\n }, \\n reranker : { \\n name : predict , \\n window : 50, \\n }, \\n top_k - : 20, \\n ... \\n }\",\"id\":\"78aebdf4ca3a4028a555552a07e10e6d/t/page/5733-6021\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":5733,\"end\":6021,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"ecabb0862fa24c8fb8e01d4930a3f7a2\":{\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2\",\"slug\":\"docs-develop-js-sdk-variables-MAX_FACETS_PER_REQUEST-md\",\"title\":\"docs - > develop > js sdk > variables > MAX_FACETS_PER_REQUEST\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:18.992004\",\"modified\":\"2026-07-14T12:54:35.795661\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/a/title\":{\"paragraphs\":{\"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60\":{\"score\":0.0018102111062034965,\"score_type\":\"RERANKER\",\"order\":2,\"text\":\"docs - > develop > js sdk > variables > MAX_FACETS_PER_REQUEST\",\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":60,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}},\"/t/page\":{\"paragraphs\":{\"ecabb0862fa24c8fb8e01d4930a3f7a2/t/page/0-201\":{\"score\":0.0008659809827804565,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / MAX_FACETS_PER_REQUEST \\n Variable: MAX_FACETS_PER_REQUEST - \\n \\n const MAX_FACETS_PER_REQUEST: 50 = 50 \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/filter.ts:18\",\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2/t/page/0-201\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":201,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"d006bf039f294682acd86cfb49bb59df\":{\"id\":\"d006bf039f294682acd86cfb49bb59df\",\"slug\":\"docs-account-api-mdx\",\"title\":\"docs - > account api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"ca\",\"la\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:44.738214\",\"modified\":\"2026-06-09T08:18:14.888754\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"d006bf039f294682acd86cfb49bb59df/t/page/262-339\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\" + : 20, \\n ... \\n }\",\"id\":\"78aebdf4ca3a4028a555552a07e10e6d/t/page/5733-6021\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":5733,\"end\":6021,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"d006bf039f294682acd86cfb49bb59df\":{\"id\":\"d006bf039f294682acd86cfb49bb59df\",\"slug\":\"docs-account-api-mdx\",\"title\":\"docs + > account api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"ca\",\"la\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:44.738214\",\"modified\":\"2026-06-09T08:18:14.888754\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"d006bf039f294682acd86cfb49bb59df/t/page/262-339\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":16,\"text\":\" } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } - \\n `} \\n \\n \",\"id\":\"d006bf039f294682acd86cfb49bb59df/t/page/262-339\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":262,\"end\":339,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"220eb37c167f4eb9bb8e9454e7ba8cf5\":{\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5\",\"slug\":\"docs-develop-python-sdk-05-search-md\",\"title\":\"docs - > develop > python sdk > 05 search\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:48:33.723913\",\"modified\":\"2026-06-09T08:08:04.866092\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\":{\"score\":0.0007524627726525068,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" - ::: \\n :::warning \\n Enabling reasoning can use additional tokens, which - may increase your usage costs. \\n You may need to increase max_tokens to - give the LLM enough room to reason and generate an answer. \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2505,\"end\":2709,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"f56767f7277944a58092904d0041e207\":{\"id\":\"f56767f7277944a58092904d0041e207\",\"slug\":\"docs-develop-js-sdk-interfaces-Account-md\",\"title\":\"docs - > develop > js sdk > interfaces > Account\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:49:04.980510\",\"modified\":\"2026-07-14T12:50:35.584737\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"f56767f7277944a58092904d0041e207/t/page/1396-2005\":{\"score\":0.0023322338238358498,\"score_type\":\"RERANKER\",\"order\":0,\"text\":\" - \\n optional limits: AccountLimits \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:26 - \\n \\n max_agents \\n \\n max_agents: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:27 - \\n \\n ~~max_arags~~ \\n \\n max_arags: number \\n \\n Deprecated \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:31 \\n \\n max_kbs \\n \\n max_kbs: - number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:28 \\n - \\n max_memories \\n \\n max_memories: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:29 - \\n \\n max_users \\n \\n max_users: null \\\\| number \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/db.models.ts:32 \\n \\n saml_config? \\n\",\"id\":\"f56767f7277944a58092904d0041e207/t/page/1396-2005\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":1396,\"end\":2005,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"42a4cd5a30314e94aa079ed0cfe81381\":{\"id\":\"42a4cd5a30314e94aa079ed0cfe81381\",\"slug\":\"docs-develop-js-sdk-interfaces-SplitStrategy-md\",\"title\":\"docs - > develop > js sdk > interfaces > SplitStrategy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:02:38.468609\",\"modified\":\"2026-07-14T12:51:02.450318\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\":{\"score\":0.0005770345451310277,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\" - \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 - \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"id\":\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"38ec4cc5c66e436a946ea7893b6662a3\":{\"id\":\"38ec4cc5c66e436a946ea7893b6662a3\",\"slug\":\"docs-changelog-updates-2024-10-md\",\"title\":\"docs - > changelog > updates > 2024 10\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:49.934688\",\"modified\":\"2026-06-09T08:07:26.696807\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708\":{\"score\":0.00045474793296307325,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\" - Important API Updates (All changes will be effective as of November 11th, - please make your plans): \\n \\n Remember we are moving forward with better - parameters: \\n Farewell to page_number and page_size in /search and /find - endpoints as they will be discontinued on the 11th - say hello to top_k! \\n\",\"id\":\"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":1414,\"end\":1708,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs - > develop > js sdk > interfaces > 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api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:43.137585\",\"modified\":\"2026-06-09T08:18:13.619843\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"91d9ee7dc2bd47e5b4a1011ca8e42bfd/t/page/252-329\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\" + } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } + \\n `} \\n \\n 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The default value is 1, which means that each page will be processed separately. If we set it to a higher value, the strategy will merge the specified number of pages together and extract the tables from them. This can be useful for - documents that have tables that span multiple pages. \\n\",\"id\":\"9e6238e3377d41699643ba954dd500fa/t/page/5760-6199\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":5760,\"end\":6199,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e3051c443121417496c925390ef67a5c\":{\"id\":\"e3051c443121417496c925390ef67a5c\",\"slug\":\"docs-develop-js-sdk-interfaces-MagicAction-md\",\"title\":\"docs - > develop > js sdk > interfaces > 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libs/sdk-core/src/lib/db/search/filter.ts:18\",\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2/t/page/0-201\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":201,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"fa7e8853eaf54849aecfedb5c8fc5979\":{\"id\":\"fa7e8853eaf54849aecfedb5c8fc5979\",\"slug\":\"docs-develop-js-sdk-type-aliases-MagicActionError-md\",\"title\":\"docs + > develop > js sdk > type aliases > 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MagicActionError\",\"id\":\"fa7e8853eaf54849aecfedb5c8fc5979/a/title/0-57\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":57,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"d1e1eaa16d6646b2b8ac88df5726f82f\":{\"id\":\"d1e1eaa16d6646b2b8ac88df5726f82f\",\"slug\":\"docs-develop-js-sdk-interfaces-ExtractVLLMConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ExtractVLLMConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:01:23.529670\",\"modified\":\"2026-08-03T13:16:19.914981\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"d1e1eaa16d6646b2b8ac88df5726f82f/t/page/0-230\":{\"score\":0.00038296362617984414,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ExtractVLLMConfig \\n Interface: ExtractVLLMConfig + \\n Properties \\n llm? \\n \\n optional llm: ExtractLLMConfig \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:524 \\n \\n max_pages_to_merge? + \\n\",\"id\":\"d1e1eaa16d6646b2b8ac88df5726f82f/t/page/0-230\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":230,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs + > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-08-03T13:17:48.557889\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\":{\"score\":0.0002673826238606125,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" + \\n optional max_tokens: number \\\\| object \\n \\n Defines the maximum number + of tokens that the model will take as context. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \\n \\n min_score? \\n\",\"id\":\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2808,\"end\":3011,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"c053e849251b4a5296ffeb79ed00200e\":{\"id\":\"c053e849251b4a5296ffeb79ed00200e\",\"slug\":\"docs-nua-api-mdx\",\"title\":\"docs + > nua api.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"ca\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T15:30:43.966941\",\"modified\":\"2026-06-09T08:18:14.251220\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"c053e849251b4a5296ffeb79ed00200e/t/page/289-366\":{\"score\":0.00019411319226492196,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\" + } \\n [class ='docItemCol'] { \\n max-width: 100% !important; \\n } \\n } + \\n `} \\n \\n \",\"id\":\"c053e849251b4a5296ffeb79ed00200e/t/page/289-366\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":289,\"end\":366,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}}},\"query\":\"Como + usar max_magic y dime como cambiar\xE1 este parametro en el futuro\",\"total\":20,\"page_number\":0,\"page_size\":20,\"next_page\":false,\"autofilters\":[],\"min_score\":{\"bm25\":0.0},\"best_matches\":[\"4ffdd42c713149249892d3b643ab3c81/t/page/1081-2749\",\"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60\",\"bd8ccba0ddc341dd851891ba2cccc08f/a/title/0-56\",\"ecabb0862fa24c8fb8e01d4930a3f7a2/t/page/0-201\",\"e3051c443121417496c925390ef67a5c/a/title/0-50\",\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\",\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\",\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708\",\"fa7e8853eaf54849aecfedb5c8fc5979/a/title/0-57\",\"9e6238e3377d41699643ba954dd500fa/t/page/5760-6199\",\"d1e1eaa16d6646b2b8ac88df5726f82f/t/page/0-230\",\"78aebdf4ca3a4028a555552a07e10e6d/t/page/5733-6021\",\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\",\"8870dfa28ab342f9ba2b1832f4ce864c/t/page/1535-1748\",\"9ac9bbc6ad5c41f687b4a5f96b3b161a/t/page/0-273\",\"d006bf039f294682acd86cfb49bb59df/t/page/262-339\",\"c053e849251b4a5296ffeb79ed00200e/t/page/289-366\",\"91d9ee7dc2bd47e5b4a1011ca8e42bfd/t/page/252-329\",\"53b91ad0dd5f48a7ac8b59f9775ed7e0/t/page/257-334\"]},\"best_matches\":[{\"id\":\"4ffdd42c713149249892d3b643ab3c81/t/page/1081-2749\"},{\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60\"},{\"id\":\"bd8ccba0ddc341dd851891ba2cccc08f/a/title/0-56\"},{\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2/t/page/0-201\"},{\"id\":\"e3051c443121417496c925390ef67a5c/a/title/0-50\"},{\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\"},{\"id\":\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\"},{\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\"},{\"id\":\"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708\"},{\"id\":\"fa7e8853eaf54849aecfedb5c8fc5979/a/title/0-57\"},{\"id\":\"9e6238e3377d41699643ba954dd500fa/t/page/5760-6199\"},{\"id\":\"d1e1eaa16d6646b2b8ac88df5726f82f/t/page/0-230\"},{\"id\":\"78aebdf4ca3a4028a555552a07e10e6d/t/page/5733-6021\"},{\"id\":\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\"},{\"id\":\"8870dfa28ab342f9ba2b1832f4ce864c/t/page/1535-1748\"},{\"id\":\"9ac9bbc6ad5c41f687b4a5f96b3b161a/t/page/0-273\"},{\"id\":\"53b91ad0dd5f48a7ac8b59f9775ed7e0/t/page/257-334\"},{\"id\":\"d006bf039f294682acd86cfb49bb59df/t/page/262-339\"},{\"id\":\"91d9ee7dc2bd47e5b4a1011ca8e42bfd/t/page/252-329\"},{\"id\":\"c053e849251b4a5296ffeb79ed00200e/t/page/289-366\"}]}}\n{\"item\":{\"type\":\"status\",\"code\":\"-2\",\"status\":\"no_context\"}}\n{\"item\":{\"type\":\"augmented_context\",\"augmented\":{\"paragraphs\":{},\"fields\":{}}}}\n{\"item\":{\"type\":\"citations\",\"citations\":{}}}\n{\"item\":{\"type\":\"metadata\",\"tokens\":{\"input\":41,\"output\":1,\"input_nuclia\":0.041,\"output_nuclia\":0.001},\"timings\":{\"generative_first_chunk\":0.8011547410860658,\"generative_total\":0.9729958071839064}}}\n" headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 @@ -726,15 +657,13 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 15 Jul 2026 07:54:43 GMT + - Wed, 05 Aug 2026 07:25:19 GMT nuclia-learning-id: - - 9766742f11354bc8ae298ba635a29858 + - 95c4e7bbbff246fda4d9cc28848bc534 via: - 1.1 google x-envoy-upstream-service-time: - - '1149' - x-nuclia-trace-id: - - 024a940ca31a3240199f24d7c0cf39e2 + - '1299' status: code: 200 message: OK @@ -751,14 +680,21 @@ interactions: Question\nComo usar max_magic y dime como cambiar\u00e1 este parametro en el futuro\n\n## Provided Context\n[START OF CONTEXT]\n\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all context; it may be lengthy or detailed\n- - Do not omit or overlook any relevant information\n- If the context is incomplete - or insufficient, state: \"Not enough data to answer this.\"\n- Read carefully - any extra instructions below if provided and use them to answer\n\nNow provide - your answer to the question: Como usar max_magic y dime como cambiar\u00e1 este - parametro en el futuro"}, "citations": null, "citation_threshold": null, "generative_model": - "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": - null, "json_schema": null, "format_prompt": false, "rerank_context": false, - "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": null}' + Do not omit or overlook any relevant information\n- Existing context summaries + are answer attempts produced by retrieval agents. Treat them as first-class + evidence and preserve their supported facts.\n- Combine complementary summaries + from multiple contexts when the question has multiple parts. Do not require + every context to answer the whole question by itself.\n- If a context summary + directly answers the question, do not replace it with an insufficient-data answer + merely because one retrieved chunk is incomplete; use the chunks for supporting + citations.\n- If the context is incomplete or insufficient, state: \"Not enough + data to answer this.\"\n- Read carefully any extra instructions below if provided + and use them to answer\n\nNow provide your answer to the question: Como usar + max_magic y dime como cambiar\u00e1 este parametro en el futuro"}, "citations": + null, "citation_threshold": null, "generative_model": "chatgpt-azure-4o-mini", + "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": null, "json_schema": + null, "format_prompt": false, "rerank_context": false, "tools": [], "tool_choice": + {"type": "auto"}, "reasoning": false, "seed": null}' headers: Accept: - application/x-ndjson @@ -767,7 +703,7 @@ interactions: Connection: - keep-alive Content-Length: - - '1583' + - '2096' Content-Type: - application/json Host: @@ -777,7 +713,7 @@ interactions: x-client-ident: - default x-message: - - 2972f9d7bb3449969ec795d29ede30a3 + - 62131902177a4233b079c3dd5d4f9cc1 x-origin: - RAO x-session: @@ -806,14 +742,14 @@ interactions: {"chunk":{"type":"status","code":"-2"}} - {"chunk":{"type":"meta","input_tokens":7,"output_tokens":1,"timings":{"generative_first_chunk":0.5137942020000992,"generative":0.6906043120006871},"input_nuclia_tokens":0.007,"output_nuclia_tokens":0.001}} + {"chunk":{"type":"meta","input_tokens":9,"output_tokens":1,"timings":{"generative_first_chunk":0.5790002290013945,"generative":0.8402466180050396},"input_nuclia_tokens":0.009,"output_nuclia_tokens":0.001}} - {"chunk":{"normalized_tokens":{"input":0.00681,"output":0.00096,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} + {"chunk":{"normalized_tokens":{"input":0.00936,"output":0.00096,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} ' headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -821,17 +757,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 15 Jul 2026 07:54:46 GMT + - Wed, 05 Aug 2026 07:25:21 GMT nuclia-learning-id: - - ada85257a29a486fb4042c4689422da7 + - 7b1e2ce66ec54f1d96961f5d43bbdbd5 nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '520' + - '586' x-nuclia-trace-id: - - 0666fe7baac8552f6e6729f2b5ad0619 + - eceed909bda6714c129b82e5954a113c status: code: 200 message: OK @@ -848,22 +784,35 @@ interactions: Question\nComo usar max_magic y dime como cambiar\u00e1 este parametro en el futuro\n\n## Provided Context\n[START OF CONTEXT]\n\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all context; it may be lengthy or detailed\n- - Do not omit or overlook any relevant information\n- If the context is incomplete - or insufficient, state: \"Not enough data to answer this.\"\n- Read carefully - any extra instructions below if provided and use them to answer\n\n## Additional - Instructions for answering\n- \n## Question\nComo usar max_magic y dime como - cambiar\u00e1 este parametro en el futuro\n\n## Provided Context\n[START OF - CONTEXT]\n\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all - context; it may be lengthy or detailed\n- Do not omit or overlook any relevant - information\n- If the context is incomplete or insufficient, state: \"Not enough + Do not omit or overlook any relevant information\n- Existing context summaries + are answer attempts produced by retrieval agents. Treat them as first-class + evidence and preserve their supported facts.\n- Combine complementary summaries + from multiple contexts when the question has multiple parts. Do not require + every context to answer the whole question by itself.\n- If a context summary + directly answers the question, do not replace it with an insufficient-data answer + merely because one retrieved chunk is incomplete; use the chunks for supporting + citations.\n- If the context is incomplete or insufficient, state: \"Not enough data to answer this.\"\n- Read carefully any extra instructions below if provided - and use them to answer\n\nNow provide your answer to the question: Como usar - max_magic y dime como cambiar\u00e1 este parametro en el futuro\nNow provide - your answer to the question: Como usar max_magic y dime como cambiar\u00e1 este - parametro en el futuro"}, "citations": null, "citation_threshold": null, "generative_model": - "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": - null, "json_schema": null, "format_prompt": false, "rerank_context": false, - "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": null}' + and use them to answer\n\n## Additional Instructions for answering\n- \n## Question\nComo + usar max_magic y dime como cambiar\u00e1 este parametro en el futuro\n\n## Provided + Context\n[START OF CONTEXT]\n\n[END OF CONTEXT]\n\n## Answering Guidelines\n- + Carefully read all context; it may be lengthy or detailed\n- Do not omit or + overlook any relevant information\n- Existing context summaries are answer attempts + produced by retrieval agents. Treat them as first-class evidence and preserve + their supported facts.\n- Combine complementary summaries from multiple contexts + when the question has multiple parts. Do not require every context to answer + the whole question by itself.\n- If a context summary directly answers the question, + do not replace it with an insufficient-data answer merely because one retrieved + chunk is incomplete; use the chunks for supporting citations.\n- If the context + is incomplete or insufficient, state: \"Not enough data to answer this.\"\n- + Read carefully any extra instructions below if provided and use them to answer\n\nNow + provide your answer to the question: Como usar max_magic y dime como cambiar\u00e1 + este parametro en el futuro\nNow provide your answer to the question: Como usar + max_magic y dime como cambiar\u00e1 este parametro en el futuro"}, "citations": + null, "citation_threshold": null, "generative_model": "chatgpt-azure-4o-mini", + "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": null, "json_schema": + null, "format_prompt": false, "rerank_context": false, "tools": [], "tool_choice": + {"type": "auto"}, "reasoning": false, "seed": null}' headers: Accept: - application/x-ndjson @@ -872,7 +821,7 @@ interactions: Connection: - keep-alive Content-Length: - - '2204' + - '3230' Content-Type: - application/json Host: @@ -882,7 +831,7 @@ interactions: x-client-ident: - default x-message: - - 2972f9d7bb3449969ec795d29ede30a3 + - 62131902177a4233b079c3dd5d4f9cc1 x-origin: - RAO x-session: @@ -911,9 +860,9 @@ interactions: {"chunk":{"type":"status","code":"-2"}} - {"chunk":{"type":"meta","input_tokens":11,"output_tokens":1,"timings":{"generative_first_chunk":0.6975756550091319,"generative":1.0033389890013495},"input_nuclia_tokens":0.011,"output_nuclia_tokens":0.001}} + {"chunk":{"type":"meta","input_tokens":16,"output_tokens":1,"timings":{"generative_first_chunk":0.685196165999514,"generative":1.1538108969998575},"input_nuclia_tokens":0.016,"output_nuclia_tokens":0.001}} - {"chunk":{"normalized_tokens":{"input":0.01062,"output":0.00096,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} + {"chunk":{"normalized_tokens":{"input":0.01572,"output":0.00096,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} ' headers: @@ -926,17 +875,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 15 Jul 2026 07:54:46 GMT + - Wed, 05 Aug 2026 07:25:22 GMT nuclia-learning-id: - - e8433c6f0b514926ae2d448b0a143f57 + - 14231e2812194f9e9f0b7482aac144c6 nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '711' + - '693' x-nuclia-trace-id: - - a1d90982e572f80638d44d8c04f89298 + - c7161c178ceba7543d4f284182bae4ad status: code: 200 message: OK @@ -965,7 +914,7 @@ interactions: uri: https://europe-1.dp.progress.cloud/api/v1/predict/remi response: body: - string: '{"time":0.18207073211669922,"answer_relevance":{"score":0,"reason":""},"context_relevance":[],"groundedness":[]}' + string: '{"time":0.17912912368774414,"answer_relevance":{"score":0,"reason":""},"context_relevance":[],"groundedness":[]}' headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 @@ -976,7 +925,7 @@ interactions: content-type: - application/json date: - - Wed, 15 Jul 2026 07:54:47 GMT + - Wed, 05 Aug 2026 07:25:24 GMT nuclia-learning-model: - Llama-REMi-v1 via: @@ -984,7 +933,7 @@ interactions: x-envoy-upstream-service-time: - '187' x-nuclia-trace-id: - - 3c51f8864ced451ece74cea59b9cb2ad + - 186789a285f8c1b292b1cc795c7754ac status: code: 200 message: OK diff --git a/agents/remi/tests/conftest.py b/agents/remi/tests/conftest.py index 4bec9ce0..c733d5e8 100644 --- a/agents/remi/tests/conftest.py +++ b/agents/remi/tests/conftest.py @@ -1 +1,21 @@ +import json + pytest_plugins = ["hyperforge.minimal_fixtures"] + + +def nua_chat_match(request, recorded_request): + if request.path != "/api/v1/predict/chat": + return request.body == recorded_request.body + if recorded_request.path != "/api/v1/predict/chat": + return False + + request_payload = json.loads(request.body) + recorded_payload = json.loads(recorded_request.body) + return all( + request_payload.get(field) == recorded_payload.get(field) + for field in ("question", "user_id", "generative_model") + ) + + +def pytest_recording_configure(config, vcr): + vcr.register_matcher("nua_chat", nua_chat_match) diff --git a/agents/remi/tests/test_remi.py b/agents/remi/tests/test_remi.py index d03b4972..0685058d 100644 --- a/agents/remi/tests/test_remi.py +++ b/agents/remi/tests/test_remi.py @@ -9,7 +9,7 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") KB_DF8B4C24_2807_4888_AD6C_AE97357A638B = os.environ.get( "KB_DF8B4C24_2807_4888_AD6C_AE97357A638B", "DUMMY_KEY" @@ -32,8 +32,8 @@ "identifier": "nuclia-docs", "name": "nuclia-docs", "config": { - "url": "https://europe-1.nuclia.cloud/api", - "manager": "https://europe-1.nuclia.cloud/api", + "url": "https://europe-1.dp.progress.cloud/api", + "manager": "https://europe-1.dp.progress.cloud/api", "kbid": "df8b4c24-2807-4888-ad6c-ae97357a638b", "key": KB_DF8B4C24_2807_4888_AD6C_AE97357A638B, "filters": [], @@ -74,8 +74,9 @@ } -# Match on body since we send parallel requests and otherwise they get played back in a different order -@pytest.mark.vcr(match_on=["method", "scheme", "host", "port", "path", "query", "body"]) +# Match NUA chats by their stable routing fields; retrieved context in their +# prompts changes as the documentation KB evolves. +@pytest.mark.vcr(match_on=["method", "scheme", "host", "port", "path", "query", "nua_chat"]) @pytest.mark.parametrize( "granularity", (ContextGranularity.PARTIAL_ANSWERS, ContextGranularity.FULL) ) @@ -155,7 +156,7 @@ async def test_remi(granularity: ContextGranularity): assert "Errors:" not in remi_ctx.summary -@pytest.mark.vcr(match_on=["method", "scheme", "host", "port", "path", "query", "body"]) +@pytest.mark.vcr(match_on=["method", "scheme", "host", "port", "path", "query", "nua_chat"]) @pytest.mark.parametrize( "granularity", [ContextGranularity.PARTIAL_ANSWERS, ContextGranularity.FULL] ) diff --git a/agents/rephrase/tests/cassettes/test_rephrase/test_rephrase_agent.yaml b/agents/rephrase/tests/cassettes/test_rephrase/test_rephrase_agent.yaml index dc7dfc2f..43ce5262 100644 --- a/agents/rephrase/tests/cassettes/test_rephrase/test_rephrase_agent.yaml +++ b/agents/rephrase/tests/cassettes/test_rephrase/test_rephrase_agent.yaml @@ -49,7 +49,7 @@ interactions: Content-Length: - '167' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -57,7 +57,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"9f7036a7a6694700b72d52eb58a8326c\":{\"id\":\"9f7036a7a6694700b72d52eb58a8326c\",\"slug\":\"docs-rag-advanced-widget-features-md\",\"title\":\"docs @@ -362,7 +362,7 @@ interactions: Content-Length: - '61' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -370,7 +370,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs @@ -501,7 +501,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -509,7 +509,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b response: body: string: '{"slug":"nuclia-docs","uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","config":{"uuid":null,"slug":"4f9285c7-7151-4431-94e6-3f1fb0d66aca:nuclia-docs","title":"Nuclia @@ -544,7 +544,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -552,7 +552,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b response: body: string: '{"slug":"nuclia-docs","uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","config":{"uuid":null,"slug":"4f9285c7-7151-4431-94e6-3f1fb0d66aca:nuclia-docs","title":"Nuclia @@ -587,7 +587,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -595,7 +595,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration response: body: string: '{"resource_labelers_models":null,"paragraph_labelers_models":null,"intent_models":null,"visual_labeling":"disabled","ner_model":"multilingual","relation_model":"base","anonymization_model":"disabled","semantic_model":"multilingual-2024-05-06","semantic_models":["multilingual-2024-05-06"],"default_semantic_model":"multilingual-2024-05-06","semantic_graph_node_models":[],"default_semantic_graph_node_model":null,"semantic_graph_edge_models":[],"default_semantic_graph_edge_model":null,"semantic_vector_similarity":"DOT","semantic_vector_size":1024,"semantic_matryoshka_dims":[],"semantic_threshold":0.4,"generative_model":"chatgpt-azure-4o","user_keys":{"openai":null,"azure_openai":null,"mistral":null,"palm":null,"anthropic":null,"claude3":null,"anthropic_vertex":null,"anthropic_bedrock":null,"azure_mistral":null,"hf_llm":null,"hf_embedding":null,"azure_aii":null,"openai_compat":null},"user_prompts":{"openai":null,"azure_openai":{"system":"You @@ -634,7 +634,7 @@ interactions: Content-Length: - 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keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -816,7 +816,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets response: body: string: '{"uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","labelsets":{"pmm":{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -854,7 +854,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -862,7 +862,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets response: body: string: '{"uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","labelsets":{"pmm":{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -900,7 +900,7 @@ interactions: Connection: - 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'61' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -955,7 +955,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs @@ -1088,7 +1088,7 @@ interactions: Content-Length: - '18' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -1096,7 +1096,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs @@ -1229,7 +1229,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -1237,7 +1237,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm response: body: string: '{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -1275,7 +1275,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -1283,7 +1283,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm response: body: string: '{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -1323,7 +1323,7 @@ interactions: Content-Length: - '18' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -1331,7 +1331,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs @@ -1470,7 +1470,7 @@ interactions: Content-Length: - '349' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -1478,7 +1478,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"6e8250e6b5264156988657a221fd5e94\":{\"id\":\"6e8250e6b5264156988657a221fd5e94\",\"slug\":\"docs-develop-js-sdk-namespaces-Ask-interfaces-ConsumptionAskResponseItem-md\",\"title\":\"docs @@ -3279,13 +3279,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"b14cf452a3434839a04c111f2ea4dc51":{"id":"b14cf452a3434839a04c111f2ea4dc51","slug":"docs-develop-js-sdk-enums-UsageType-md","title":"docs @@ -3342,7 +3342,7 @@ interactions: Content-Length: - '329' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -3350,7 +3350,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"6e8250e6b5264156988657a221fd5e94\":{\"id\":\"6e8250e6b5264156988657a221fd5e94\",\"slug\":\"docs-develop-js-sdk-namespaces-Ask-interfaces-ConsumptionAskResponseItem-md\",\"title\":\"docs @@ -5056,13 +5056,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"f02da6c4bdf34596a89a8106f4b0ea9f":{"id":"f02da6c4bdf34596a89a8106f4b0ea9f","slug":"docs-develop-js-sdk-interfaces-PageToken-md","title":"docs @@ -5710,7 +5710,7 @@ interactions: Content-Length: - '329' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -5718,7 +5718,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"6e8250e6b5264156988657a221fd5e94\":{\"id\":\"6e8250e6b5264156988657a221fd5e94\",\"slug\":\"docs-develop-js-sdk-namespaces-Ask-interfaces-ConsumptionAskResponseItem-md\",\"title\":\"docs @@ -7238,13 +7238,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"b14cf452a3434839a04c111f2ea4dc51":{"id":"b14cf452a3434839a04c111f2ea4dc51","slug":"docs-develop-js-sdk-enums-UsageType-md","title":"docs diff --git a/agents/rephrase/tests/cassettes/test_rephrase/test_rephrase_agent_only_rephrase.yaml b/agents/rephrase/tests/cassettes/test_rephrase/test_rephrase_agent_only_rephrase.yaml index 8238d5b5..75bad060 100644 --- a/agents/rephrase/tests/cassettes/test_rephrase/test_rephrase_agent_only_rephrase.yaml +++ b/agents/rephrase/tests/cassettes/test_rephrase/test_rephrase_agent_only_rephrase.yaml @@ -49,7 +49,7 @@ interactions: Content-Length: - '167' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -57,7 +57,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs @@ -344,7 +344,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -352,7 +352,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b response: body: string: '{"slug":"nuclia-docs","uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","config":{"uuid":null,"slug":"4f9285c7-7151-4431-94e6-3f1fb0d66aca:nuclia-docs","title":"Nuclia @@ -389,7 +389,7 @@ interactions: Content-Length: - '32' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -397,7 +397,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/n/i":986,"/n/i/application":1,"/n/i/application/json":1,"/n/i/text":985,"/n/i/text/markdown":985}}' @@ -431,7 +431,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -439,7 +439,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets response: body: string: '{"uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","labelsets":{"pmm":{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -479,7 +479,7 @@ interactions: Content-Length: - '32' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -487,7 +487,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/s/p":986,"/s/p/ca":3,"/s/p/cy":1,"/s/p/da":1,"/s/p/en":967,"/s/p/eo":4,"/s/p/la":7,"/s/p/nb":1,"/s/p/tl":1,"/s/p/yo":1}}' @@ -521,7 +521,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -529,7 +529,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration response: body: string: '{"resource_labelers_models":null,"paragraph_labelers_models":null,"intent_models":null,"visual_labeling":"disabled","ner_model":"multilingual","relation_model":"base","anonymization_model":"disabled","semantic_model":"multilingual-2024-05-06","semantic_models":["multilingual-2024-05-06"],"default_semantic_model":"multilingual-2024-05-06","semantic_graph_node_models":[],"default_semantic_graph_node_model":null,"semantic_graph_edge_models":[],"default_semantic_graph_edge_model":null,"semantic_vector_similarity":"DOT","semantic_vector_size":1024,"semantic_matryoshka_dims":[],"semantic_threshold":0.4,"generative_model":"chatgpt-azure-4o","user_keys":{"openai":null,"azure_openai":null,"mistral":null,"palm":null,"anthropic":null,"claude3":null,"anthropic_vertex":null,"anthropic_bedrock":null,"azure_mistral":null,"hf_llm":null,"hf_embedding":null,"azure_aii":null,"openai_compat":null},"user_prompts":{"openai":null,"azure_openai":{"system":"You @@ -568,7 +568,7 @@ interactions: Content-Length: - '61' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -576,7 +576,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs @@ -707,7 +707,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -715,7 +715,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm response: body: string: '{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -755,7 +755,7 @@ interactions: Content-Length: - '18' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -763,7 +763,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs @@ -903,7 +903,7 @@ interactions: Content-Length: - '393' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -911,7 +911,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs @@ -2331,13 +2331,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"1cf976a5ca5947cd89a2f2a047b71ce9":{"id":"1cf976a5ca5947cd89a2f2a047b71ce9","slug":"docs-ingestion-how-to-split-strategies-md","title":"docs @@ -2721,7 +2721,7 @@ interactions: Content-Length: - '393' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -2729,7 +2729,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs @@ -4149,13 +4149,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"1cf976a5ca5947cd89a2f2a047b71ce9":{"id":"1cf976a5ca5947cd89a2f2a047b71ce9","slug":"docs-ingestion-how-to-split-strategies-md","title":"docs diff --git a/agents/rephrase/tests/test_rephrase.py b/agents/rephrase/tests/test_rephrase.py index 10f34474..afaabc08 100644 --- a/agents/rephrase/tests/test_rephrase.py +++ b/agents/rephrase/tests/test_rephrase.py @@ -7,16 +7,16 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") DE48CFAA_3209_4041_BB64_8604AFF061FB = os.environ.get( "KB_DE48CFAA_3209_4041_BB64_8604AFF061FB" -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") DF8B4C24_2807_4888_AD6C_AE97357A638B = os.environ.get( "KB_DF8B4C24_2807_4888_AD6C_AE97357A638B" -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") pytestmark = [ pytest.mark.vcr(ignore_localhost=True, ignore_hosts=["test"]), pytest.mark.asyncio, @@ -44,8 +44,8 @@ "identifier": "nucliadb-2", "config": { "identifier": "nucliadb-2", - "url": "https://europe-1.nuclia.cloud/api", - "manager": "https://europe-1.nuclia.cloud/api", + "url": "https://europe-1.dp.progress.cloud/api", + "manager": "https://europe-1.dp.progress.cloud/api", "kbid": "df8b4c24-2807-4888-ad6c-ae97357a638b", "key": DF8B4C24_2807_4888_AD6C_AE97357A638B, "filters": [], diff --git a/agents/smart/tests/cassettes/test_smart/test_smart[default].yaml b/agents/smart/tests/cassettes/test_smart/test_smart[default].yaml index e02df575..56b616ce 100644 --- a/agents/smart/tests/cassettes/test_smart/test_smart[default].yaml +++ b/agents/smart/tests/cassettes/test_smart/test_smart[default].yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -105,7 +105,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -121,7 +121,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"No @@ -223,7 +223,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -239,7 +239,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -337,7 +337,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -353,7 +353,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -455,7 +455,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -471,7 +471,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -577,7 +577,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -593,7 +593,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -703,7 +703,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -719,7 +719,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -851,7 +851,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -867,7 +867,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"done","reasoning":"The @@ -996,7 +996,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -1006,7 +1006,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -1080,7 +1080,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1096,7 +1096,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"S"}} @@ -1200,13 +1200,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -1296,7 +1296,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1312,7 +1312,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"The @@ -1417,7 +1417,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1433,7 +1433,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba":[{"function":{"name":"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba","arguments":{}}}]}}} @@ -1532,7 +1532,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1548,7 +1548,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba":[{"function":{"name":"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba","arguments":{}}}]}}} @@ -1650,7 +1650,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1666,7 +1666,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba":[{"function":{"name":"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba","arguments":{}}}]}}} @@ -1771,7 +1771,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1787,7 +1787,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba":[{"function":{"name":"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba","arguments":{}}}]}}} @@ -1895,7 +1895,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1911,7 +1911,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba":[{"function":{"name":"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba","arguments":{}}}]}}} @@ -2036,7 +2036,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -2052,7 +2052,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"done","reasoning":"The @@ -2172,7 +2172,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -2182,7 +2182,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -2256,7 +2256,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -2272,7 +2272,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"RA"}} diff --git a/agents/smart/tests/cassettes/test_smart/test_smart[gemini].yaml b/agents/smart/tests/cassettes/test_smart/test_smart[gemini].yaml index 50d60417..9a20652f 100644 --- a/agents/smart/tests/cassettes/test_smart/test_smart[gemini].yaml +++ b/agents/smart/tests/cassettes/test_smart/test_smart[gemini].yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -105,7 +105,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -121,7 +121,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"The @@ -225,7 +225,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -241,7 +241,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -341,7 +341,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -357,7 +357,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -461,7 +461,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -477,7 +477,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -585,7 +585,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -601,7 +601,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -713,7 +713,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -729,7 +729,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -861,7 +861,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -877,7 +877,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"done","reasoning":"The @@ -1004,7 +1004,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -1014,7 +1014,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -1088,7 +1088,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1104,7 +1104,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"S"}} @@ -1208,13 +1208,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -1304,7 +1304,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1320,7 +1320,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"The @@ -1419,7 +1419,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1435,7 +1435,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba":[{"function":{"name":"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba","arguments":{}}}]}}} @@ -1531,7 +1531,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1547,7 +1547,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba":[{"function":{"name":"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba","arguments":{}}}]}}} @@ -1646,7 +1646,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1662,7 +1662,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba":[{"function":{"name":"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba","arguments":{}}}]}}} @@ -1764,7 +1764,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1780,7 +1780,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba":[{"function":{"name":"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba","arguments":{}}}]}}} @@ -1885,7 +1885,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1901,7 +1901,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba":[{"function":{"name":"static_context__1d372a1a-8aaf-4dc7-bcf2-b8393751beba","arguments":{}}}]}}} @@ -2026,7 +2026,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -2042,7 +2042,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"done","reasoning":"The @@ -2161,7 +2161,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -2171,7 +2171,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -2245,7 +2245,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -2261,7 +2261,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"RA"}} diff --git a/agents/smart/tests/cassettes/test_smart/test_smart_calls_correct_agent.yaml b/agents/smart/tests/cassettes/test_smart/test_smart_calls_correct_agent.yaml index 88af6b2b..231e5754 100644 --- a/agents/smart/tests/cassettes/test_smart/test_smart_calls_correct_agent.yaml +++ b/agents/smart/tests/cassettes/test_smart/test_smart_calls_correct_agent.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -105,7 +105,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -121,7 +121,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"No @@ -226,7 +226,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -242,7 +242,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -343,7 +343,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -359,7 +359,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -464,7 +464,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -480,7 +480,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -589,7 +589,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -605,7 +605,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -718,7 +718,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -734,7 +734,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -866,7 +866,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -882,7 +882,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"done","reasoning":"The @@ -1010,7 +1010,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -1020,7 +1020,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context clearly states @@ -1091,7 +1091,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1107,7 +1107,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"Yes"}} diff --git a/agents/smart/tests/cassettes/test_smart/test_smart_parameters.yaml b/agents/smart/tests/cassettes/test_smart/test_smart_parameters.yaml index b61ca1b9..91bf20a1 100644 --- a/agents/smart/tests/cassettes/test_smart/test_smart_parameters.yaml +++ b/agents/smart/tests/cassettes/test_smart/test_smart_parameters.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -106,7 +106,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -122,7 +122,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"The @@ -236,7 +236,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -252,7 +252,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -357,7 +357,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -373,7 +373,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -482,7 +482,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -498,7 +498,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -611,7 +611,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -627,7 +627,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -744,7 +744,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -760,7 +760,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -893,7 +893,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -909,7 +909,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"We @@ -1016,7 +1016,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1032,7 +1032,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -1216,7 +1216,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1232,7 +1232,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -1417,7 +1417,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1433,7 +1433,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -1622,7 +1622,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1638,7 +1638,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -1831,7 +1831,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1847,7 +1847,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -2079,7 +2079,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -2095,7 +2095,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"done","reasoning":"All @@ -2226,7 +2226,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -2236,7 +2236,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -2317,7 +2317,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -2333,7 +2333,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"S"}} @@ -2497,13 +2497,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -2594,7 +2594,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -2610,7 +2610,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"The @@ -2734,7 +2734,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -2750,7 +2750,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -2862,7 +2862,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -2878,7 +2878,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -3075,7 +3075,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -3091,7 +3091,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}],"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -3293,7 +3293,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -3309,7 +3309,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -3437,7 +3437,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -3453,7 +3453,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -3591,7 +3591,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -3607,7 +3607,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"We @@ -3714,7 +3714,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -3730,7 +3730,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -3911,7 +3911,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -3927,7 +3927,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}],"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -4116,7 +4116,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -4132,7 +4132,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -4325,7 +4325,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -4341,7 +4341,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -4538,7 +4538,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -4554,7 +4554,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f":[{"function":{"name":"internet_search__0f5487c8-432d-4205-b5e0-d5c06b7a638f","arguments":{"question":"current @@ -4796,7 +4796,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -4812,7 +4812,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"done","reasoning":"All @@ -4943,7 +4943,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -4953,7 +4953,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -5035,7 +5035,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -5051,7 +5051,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"S"}} diff --git a/agents/smart/tests/cassettes/test_smart/test_smart_with_history.yaml b/agents/smart/tests/cassettes/test_smart/test_smart_with_history.yaml index 39d8d8a6..a337f7d9 100644 --- a/agents/smart/tests/cassettes/test_smart/test_smart_with_history.yaml +++ b/agents/smart/tests/cassettes/test_smart/test_smart_with_history.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -107,7 +107,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -123,7 +123,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"No @@ -225,7 +225,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -241,7 +241,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -340,7 +340,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -356,7 +356,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -460,7 +460,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -476,7 +476,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -584,7 +584,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -600,7 +600,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -712,7 +712,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -728,7 +728,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -863,7 +863,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -879,7 +879,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"done","reasoning":"The @@ -1006,7 +1006,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -1016,7 +1016,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -1090,7 +1090,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1106,7 +1106,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"S"}} diff --git a/agents/smart/tests/cassettes/test_smart/test_smart_with_user_feedback.yaml b/agents/smart/tests/cassettes/test_smart/test_smart_with_user_feedback.yaml index 3050e3de..83108543 100644 --- a/agents/smart/tests/cassettes/test_smart/test_smart_with_user_feedback.yaml +++ b/agents/smart/tests/cassettes/test_smart/test_smart_with_user_feedback.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -106,7 +106,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -122,7 +122,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"plan","reasoning":"The @@ -235,7 +235,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -251,7 +251,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"user_feedback":[{"function":{"name":"user_feedback","arguments":{"question":"Are @@ -357,7 +357,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -373,7 +373,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -481,7 +481,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -497,7 +497,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -609,7 +609,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -625,7 +625,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -741,7 +741,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -757,7 +757,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"tools","tools":{"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c":[{"function":{"name":"static_context__269192da-f5b6-4196-8c9a-bd77e32f237c","arguments":{}}}]}}} @@ -886,7 +886,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -902,7 +902,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"status":"done","reasoning":"The @@ -1028,7 +1028,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -1038,7 +1038,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -1115,7 +1115,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -1131,7 +1131,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"S"}} diff --git a/agents/smart/tests/test_smart.py b/agents/smart/tests/test_smart.py index 8461a830..5a207913 100644 --- a/agents/smart/tests/test_smart.py +++ b/agents/smart/tests/test_smart.py @@ -22,7 +22,7 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") PERPLEXITY_KEY = os.environ.get("PERPLEXITY_API_KEY", "DUMMY_PERPLEXITY_KEY") diff --git a/agents/smart/tests/test_smart_mcp_perplexity.py b/agents/smart/tests/test_smart_mcp_perplexity.py index 3e81372f..34e2e213 100644 --- a/agents/smart/tests/test_smart_mcp_perplexity.py +++ b/agents/smart/tests/test_smart_mcp_perplexity.py @@ -13,7 +13,7 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") PERPLEXITY_KEY = os.environ.get("PERPLEXITY_API_KEY", "DUMMY_PERPLEXITY_KEY") diff --git a/agents/summarize/tests/cassettes/test_summarize/test_summarize_answers.yaml b/agents/summarize/tests/cassettes/test_summarize/test_summarize_answers.yaml index 2f10fdce..8ba71a97 100644 --- a/agents/summarize/tests/cassettes/test_summarize/test_summarize_answers.yaml +++ b/agents/summarize/tests/cassettes/test_summarize/test_summarize_answers.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -45,7 +45,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -53,7 +53,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets response: body: string: '{"uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","labelsets":{"pmm":{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -93,7 +93,7 @@ interactions: Content-Length: - '42' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -101,7 +101,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/n/i":974,"/n/i/text":974,"/n/i/text/markdown":974}}' @@ -137,7 +137,7 @@ interactions: Content-Length: - '40' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -145,7 +145,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{}}' @@ -179,7 +179,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -187,7 +187,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration response: body: string: '{"resource_labelers_models":null,"paragraph_labelers_models":null,"intent_models":null,"visual_labeling":"disabled","ner_model":"multilingual","relation_model":"base","anonymization_model":"disabled","semantic_model":"multilingual-2024-05-06","semantic_models":["multilingual-2024-05-06"],"default_semantic_model":"multilingual-2024-05-06","semantic_graph_node_models":[],"default_semantic_graph_node_model":null,"semantic_graph_edge_models":[],"default_semantic_graph_edge_model":null,"semantic_vector_similarity":"DOT","semantic_vector_size":1024,"semantic_matryoshka_dims":[],"semantic_threshold":0.4,"generative_model":"chatgpt-azure-4o","user_keys":{"openai":null,"azure_openai":null,"mistral":null,"palm":null,"anthropic":null,"claude3":null,"anthropic_vertex":null,"anthropic_bedrock":null,"azure_mistral":null,"hf_llm":null,"hf_embedding":null,"azure_aii":null,"openai_compat":null},"user_prompts":{"openai":null,"azure_openai":{"system":"You @@ -226,7 +226,7 @@ interactions: Content-Length: - 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application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"89cc367c149e4f6eab0e06a743d1edba":{"id":"89cc367c149e4f6eab0e06a743d1edba","slug":"docs-rag-advanced-openai-api-compatible-models-md","title":"docs @@ -3885,13 +3885,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/rerank + uri: https://europe-1.dp.progress.cloud/api/v1/predict/rerank response: body: string: '{"context_scores":{"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340":0.8115267157554626,"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011":0.4579244554042816,"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412":0.4333818256855011,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221":0.4003390371799469,"43004f553e534ffe9c9e735856bd9b23/t/page/212-480":0.2372223436832428,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276":0.21551580727100372,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709":0.2107662856578827,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977":0.16118815541267395,"43004f553e534ffe9c9e735856bd9b23/t/page/480-703":0.1359187662601471,"e8525e64c5b44982b958d32cf6090613/t/page/2450-2808":0.10800065845251083,"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575":0.0634823590517044,"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043":0.05665242671966553,"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60":0.016850080341100693,"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139":0.015967654064297676,"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833":0.012431650422513485,"328ed5b87692439a881303c7c1d4eefc/a/title/0-52":0.00854433048516512,"666b3a9d01f74323b6ca6c9939834bec/t/page/0-1386":0.007431773468852043,"1cf976a5ca5947cd89a2f2a047b71ce9/t/page/963-1239":0.0032224843744188547,"53b91ad0dd5f48a7ac8b59f9775ed7e0/t/page/257-334":0.0015427323523908854,"828a119645574efd908c8ecb5ee6c013/t/page/34400-34802":0.0014269596431404352}}' @@ -4034,7 +4034,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -4044,7 +4044,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -4126,7 +4126,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -4136,7 +4136,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"text\",\"text\":\"Para\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" diff --git a/agents/summarize/tests/cassettes/test_summarize/test_summarize_tokens.yaml b/agents/summarize/tests/cassettes/test_summarize/test_summarize_tokens.yaml index 8a15ebb8..88f251d1 100644 --- a/agents/summarize/tests/cassettes/test_summarize/test_summarize_tokens.yaml +++ b/agents/summarize/tests/cassettes/test_summarize/test_summarize_tokens.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -45,7 +45,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -53,7 +53,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b response: body: string: '{"slug":"nuclia-docs","uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","config":{"uuid":null,"slug":"4f9285c7-7151-4431-94e6-3f1fb0d66aca:nuclia-docs","title":"Nuclia @@ -90,7 +90,7 @@ interactions: Content-Length: - '40' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -98,7 +98,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{}}' @@ -132,7 +132,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -140,7 +140,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelsets response: body: string: '{"uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","labelsets":{"pmm":{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -180,7 +180,7 @@ interactions: Content-Length: - '42' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -188,7 +188,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/n/i":974,"/n/i/text":974,"/n/i/text/markdown":974}}' @@ -222,7 +222,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -230,7 +230,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/configuration response: body: string: '{"resource_labelers_models":null,"paragraph_labelers_models":null,"intent_models":null,"visual_labeling":"disabled","ner_model":"multilingual","relation_model":"base","anonymization_model":"disabled","semantic_model":"multilingual-2024-05-06","semantic_models":["multilingual-2024-05-06"],"default_semantic_model":"multilingual-2024-05-06","semantic_graph_node_models":[],"default_semantic_graph_node_model":null,"semantic_graph_edge_models":[],"default_semantic_graph_edge_model":null,"semantic_vector_similarity":"DOT","semantic_vector_size":1024,"semantic_matryoshka_dims":[],"semantic_threshold":0.4,"generative_model":"chatgpt-azure-4o","user_keys":{"openai":null,"azure_openai":null,"mistral":null,"palm":null,"anthropic":null,"claude3":null,"anthropic_vertex":null,"anthropic_bedrock":null,"azure_mistral":null,"hf_llm":null,"hf_embedding":null,"azure_aii":null,"openai_compat":null},"user_prompts":{"openai":null,"azure_openai":{"system":"You @@ -269,7 +269,7 @@ interactions: Content-Length: - '42' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -277,7 +277,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: string: '{"facets":{"/s/p":974,"/s/p/ca":3,"/s/p/cy":1,"/s/p/da":1,"/s/p/en":955,"/s/p/eo":4,"/s/p/la":7,"/s/p/nb":1,"/s/p/tl":1,"/s/p/yo":1}}' @@ -313,7 +313,7 @@ interactions: Content-Length: - '61' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -321,7 +321,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"256f6b95e3fb476c8f47b6b057d02fa0\":{\"id\":\"256f6b95e3fb476c8f47b6b057d02fa0\",\"slug\":\"docs-management-security-5-outbound-ips-md\",\"title\":\"docs @@ -418,7 +418,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -426,7 +426,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/labelset/pmm response: body: string: '{"title":"pmm","color":"#DAF3E6","multiple":true,"kind":["RESOURCES"],"labels":[{"title":"Videos","related":"","text":"","uri":""},{"title":"Partner @@ -466,7 +466,7 @@ interactions: Content-Length: - '18' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -474,7 +474,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search response: body: string: "{\"resources\":{\"256f6b95e3fb476c8f47b6b057d02fa0\":{\"id\":\"256f6b95e3fb476c8f47b6b057d02fa0\",\"slug\":\"docs-management-security-5-outbound-ips-md\",\"title\":\"docs @@ -579,7 +579,7 @@ interactions: Content-Length: - '235' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -587,7 +587,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs @@ -3698,13 +3698,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"89cc367c149e4f6eab0e06a743d1edba":{"id":"89cc367c149e4f6eab0e06a743d1edba","slug":"docs-rag-advanced-openai-api-compatible-models-md","title":"docs @@ -3885,13 +3885,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/rerank + uri: https://europe-1.dp.progress.cloud/api/v1/predict/rerank response: body: string: '{"context_scores":{"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340":0.8115267157554626,"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011":0.4579244554042816,"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412":0.4333818256855011,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221":0.4003390371799469,"43004f553e534ffe9c9e735856bd9b23/t/page/212-480":0.2372223436832428,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276":0.21551580727100372,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709":0.2107662856578827,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977":0.16118815541267395,"43004f553e534ffe9c9e735856bd9b23/t/page/480-703":0.1359187662601471,"e8525e64c5b44982b958d32cf6090613/t/page/2450-2808":0.10800065845251083,"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575":0.0634823590517044,"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043":0.05665242671966553,"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60":0.016850080341100693,"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139":0.015967654064297676,"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833":0.012431650422513485,"328ed5b87692439a881303c7c1d4eefc/a/title/0-52":0.00854433048516512,"666b3a9d01f74323b6ca6c9939834bec/t/page/0-1386":0.007431773468852043,"1cf976a5ca5947cd89a2f2a047b71ce9/t/page/963-1239":0.0032224843744188547,"53b91ad0dd5f48a7ac8b59f9775ed7e0/t/page/257-334":0.0015427323523908854,"828a119645574efd908c8ecb5ee6c013/t/page/34400-34802":0.0014269596431404352}}' @@ -4034,7 +4034,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -4044,7 +4044,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -4128,7 +4128,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -4144,7 +4144,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"text\",\"text\":\"#\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" diff --git a/agents/summarize/tests/cassettes/test_summarize/test_summarize_with_funny_system_prompt.yaml b/agents/summarize/tests/cassettes/test_summarize/test_summarize_with_funny_system_prompt.yaml index 4eccfded..1fd466a9 100644 --- a/agents/summarize/tests/cassettes/test_summarize/test_summarize_with_funny_system_prompt.yaml +++ b/agents/summarize/tests/cassettes/test_summarize/test_summarize_with_funny_system_prompt.yaml @@ -9,13 +9,13 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"03d47998-f672-4a9b-a57b-bde3a9c3ee8c","account_id":"4f9285c7-7151-4431-94e6-3f1fb0d66aca","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' @@ -45,7 +45,7 @@ interactions: Connection: - keep-alive Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -53,7 +53,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b response: body: string: '{"slug":"nuclia-docs","uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","config":{"uuid":null,"slug":"4f9285c7-7151-4431-94e6-3f1fb0d66aca:nuclia-docs","title":"Nuclia @@ -90,7 +90,7 @@ interactions: Content-Length: - 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application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"d6c2f64455f74787b8712e842ebae216":{"id":"d6c2f64455f74787b8712e842ebae216","slug":"docs-develop-js-sdk-classes-Nuclia-md","title":"docs @@ -5633,13 +5633,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/rerank + uri: https://europe-1.dp.progress.cloud/api/v1/predict/rerank response: body: string: '{"context_scores":{"26c052c248504f87bffc9b409a4c15a2/t/page/0-220":0.03861093148589134,"d986c88467d148a79cb7a4147210c33f/t/page/4975-5400":0.0219902191311121,"38ec4cc5c66e436a946ea7893b6662a3/t/page/0-400":0.010368157178163528,"122233fea96b4ec3963a699f87926cf8/t/page/0-393":0.005620036739856005,"45af8c5b091141fea73e4ae9b0cd7dfd/t/page/747-1158":0.0020111582707613707,"710d18047689405e977108f03598aa06/t/page/346-860":0.0018821860430762172,"6e61cf1c638845dd96eada959090b854/t/page/368-673":0.001536727068014443,"e6605960cc46412da0e5e5404f511d53/a/summary/212-254":0.0005815576296299696,"d6c2f64455f74787b8712e842ebae216/a/title/0-42":0.0005571116926148534,"0adbaa86a2ed4a56aeda10cc889243d4/t/page/0-80":0.00040765260928310454,"40eca97b12694acf8bc35f33c6de84ba/t/page/0-91":0.00037555923336185515,"05549b4da610422d9ff3dc36ddb9ea66/t/page/0-75":0.0003101559996139258,"8aa955e0bb6c438b8217d8de387602e0/t/page/0-79":0.00029595711384899914,"a9668c4c0d6c4e1fbb8f7da97db0fa1f/a/title/0-70":0.00025118677876889706,"8798b24b72a74c63a79ec0e2f10a1423/t/page/804-1128":0.0002492325147613883,"68210356030a4bd9834c92fd8e9632c9/t/page/565-783":7.254361844388768e-05,"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708":2.977311669383198e-05,"68210356030a4bd9834c92fd8e9632c9/t/page/314-565":1.6187581422855146e-05,"1cf976a5ca5947cd89a2f2a047b71ce9/t/page/1513-1817":1.6187581422855146e-05,"a3da5b7efa8944e193c734e7d1138473/t/page/810-1244":1.6061610949691385e-05}}' @@ -5680,7 +5680,7 @@ interactions: Content-Length: - '259' Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 content-type: @@ -5688,7 +5688,7 @@ interactions: x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: string: "{\"resources\":{\"38ec4cc5c66e436a946ea7893b6662a3\":{\"id\":\"38ec4cc5c66e436a946ea7893b6662a3\",\"slug\":\"docs-changelog-updates-2024-10-md\",\"title\":\"docs @@ -7874,13 +7874,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nucliadb-sdk/6.13.1.post6414 x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate + uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/hydrate response: body: string: '{"resources":{"d6c2f64455f74787b8712e842ebae216":{"id":"d6c2f64455f74787b8712e842ebae216","slug":"docs-develop-js-sdk-classes-Nuclia-md","title":"docs @@ -8012,13 +8012,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/rerank + uri: https://europe-1.dp.progress.cloud/api/v1/predict/rerank response: body: string: '{"context_scores":{"26c052c248504f87bffc9b409a4c15a2/t/page/0-220":0.03861093148589134,"d986c88467d148a79cb7a4147210c33f/t/page/4975-5400":0.0219902191311121,"38ec4cc5c66e436a946ea7893b6662a3/t/page/0-400":0.010368157178163528,"122233fea96b4ec3963a699f87926cf8/t/page/0-393":0.005620036739856005,"45af8c5b091141fea73e4ae9b0cd7dfd/t/page/747-1158":0.0020111582707613707,"710d18047689405e977108f03598aa06/t/page/346-860":0.0018821860430762172,"6e61cf1c638845dd96eada959090b854/t/page/368-673":0.001536727068014443,"e6605960cc46412da0e5e5404f511d53/a/summary/212-254":0.0005815576296299696,"d6c2f64455f74787b8712e842ebae216/a/title/0-42":0.0005571116926148534,"0adbaa86a2ed4a56aeda10cc889243d4/t/page/0-80":0.00040765260928310454,"40eca97b12694acf8bc35f33c6de84ba/t/page/0-91":0.00037555923336185515,"05549b4da610422d9ff3dc36ddb9ea66/t/page/0-75":0.0003101559996139258,"8aa955e0bb6c438b8217d8de387602e0/t/page/0-79":0.00029595711384899914,"a9668c4c0d6c4e1fbb8f7da97db0fa1f/a/title/0-70":0.00025118677876889706,"8798b24b72a74c63a79ec0e2f10a1423/t/page/804-1128":0.0002492325147613883,"68210356030a4bd9834c92fd8e9632c9/t/page/565-783":7.254361844388768e-05,"38ec4cc5c66e436a946ea7893b6662a3/t/page/1414-1708":2.977311669383198e-05,"68210356030a4bd9834c92fd8e9632c9/t/page/314-565":1.6187581422855146e-05,"1cf976a5ca5947cd89a2f2a047b71ce9/t/page/1513-1817":1.6187581422855146e-05,"a3da5b7efa8944e193c734e7d1138473/t/page/810-1244":1.6061610949691385e-05}}' @@ -8108,7 +8108,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-origin: @@ -8118,7 +8118,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context does not @@ -8196,7 +8196,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.nuclia.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.9.25 x-client-ident: @@ -8212,7 +8212,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.nuclia.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"text\",\"text\":\"It\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" diff --git a/agents/summarize/tests/test_summarize.py b/agents/summarize/tests/test_summarize.py index b2eea838..73ec5f28 100644 --- a/agents/summarize/tests/test_summarize.py +++ b/agents/summarize/tests/test_summarize.py @@ -20,17 +20,17 @@ # Real key used when recording; the stub is sufficient for cassette replay. NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") pytestmark = [pytest.mark.vcr(ignore_localhost=True), pytest.mark.asyncio] DE48CFAA_3209_4041_BB64_8604AFF061FB = os.environ.get( "KB_DE48CFAA_3209_4041_BB64_8604AFF061FB" -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") DF8B4C24_2807_4888_AD6C_AE97357A638B = os.environ.get( "KB_DF8B4C24_2807_4888_AD6C_AE97357A638B" -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") CONFIG = { "drivers": [ @@ -53,8 +53,8 @@ "identifier": "nucliadb-2", "config": { "identifier": "nucliadb-2", - "url": "https://europe-1.nuclia.cloud/api", - "manager": "https://europe-1.nuclia.cloud/api", + "url": "https://europe-1.dp.progress.cloud/api", + "manager": "https://europe-1.dp.progress.cloud/api", "kbid": "df8b4c24-2807-4888-ad6c-ae97357a638b", "key": DF8B4C24_2807_4888_AD6C_AE97357A638B, "filters": [], diff --git a/hyperforge/src/hyperforge/fixtures.py b/hyperforge/src/hyperforge/fixtures.py index a092c759..5b8fb953 100644 --- a/hyperforge/src/hyperforge/fixtures.py +++ b/hyperforge/src/hyperforge/fixtures.py @@ -16,9 +16,6 @@ from cryptography.fernet import Fernet from httpx import AsyncClient from httpx._transports.asgi import ASGITransport -from nuclia.config import NuaKey, Selection -from nuclia.data import get_auth -from nuclia.sdk import NucliaPredict from nucliadb_models.resource import KnowledgeBoxObj from nucliadb_sdk import NucliaDB, NucliaDBAsync from nucliadb_sdk.tests.fixtures import NucliaFixture @@ -39,6 +36,7 @@ from hyperforge.broker.redis import RedisBroker from hyperforge.db.agents import AgentManager from hyperforge.db.settings import DataManagerSettings +from hyperforge.minimal_fixtures import cassette_nua_key from hyperforge.models import MemoryConfig, NucliaDBMemoryConfig, Rules from hyperforge.server.cache import ValkeyCache from hyperforge.server.session import SessionManager @@ -47,10 +45,9 @@ _package_path = pathlib.Path(hyperforge.__file__).parent.absolute() -NUA = os.environ.get("NUA_KEY", "DUMMY") - -images.settings["nucliadb"]["env"]["NUA_API_KEY"] = NUA # type: ignore -images.settings["nucliadb"]["env"]["DUMMY_PREDICT"] = "False" # type: ignore +# Keep the test NucliaDB self-contained. This applies when recording and +# replaying cassettes so local search results do not depend on an external NUA. +images.settings["nucliadb"]["env"]["dummy_predict"] = "True" # type: ignore NUCLIA_Make_article = "https://storage.googleapis.com/ncl-testbed-gcp-stage-1/test_nucliadb/articles.export" @@ -72,13 +69,6 @@ async def init_fixture( generative_model: str = "chatgpt-azure-4o", kbid: str | None = None, ): - async with AsyncClient() as client: - resp = await client.get( - f"http://{nucliadb.host}:{nucliadb.port}/api/v1/config-check", - headers={"X-NUCLIADB-ROLES": "READER"}, - ) - assert resp.status_code == 200, "NUA KEY not configured" - assert resp.json()["nua_api_key"]["valid"], "NUA KEY not valid" sdk = nucliadb_sdk.NucliaDB(region="on-prem", url=nucliadb.url) slug = dataset_slug learning_configuration = { @@ -100,23 +90,6 @@ async def init_fixture( "generative_model": generative_model, } - if kbid is not None: - auth = get_auth() - auth._config.nuas_token = [ - NuaKey( - client_id="nucliadb", - region="europe-1", - account="nuclia", - token=NUA, - account_type="service", - ) - ] - auth._config.default = Selection(nua="nucliadb") - np = NucliaPredict() - np.del_config( - kbid, - ) - kb_obj = sdk.create_knowledge_box( uuid=kbid, slug=slug, learning_configuration=learning_configuration ) @@ -384,7 +357,8 @@ async def arag_server( internal_nucliadb_url=sdk.base_url, internal_nua=False, local_openai=None, - external_nua_api_key=NUA, + external_nua_api_key=os.environ.get("NUA_KEY") + or cassette_nua_key("https://europe-1.dp.progress.cloud/"), ) broker = RedisBroker.from_url( url=valkey_url, diff --git a/hyperforge/tests/api/test_chat_history_workflow.py b/hyperforge/tests/api/test_chat_history_workflow.py index efd095f7..35a08431 100644 --- a/hyperforge/tests/api/test_chat_history_workflow.py +++ b/hyperforge/tests/api/test_chat_history_workflow.py @@ -8,7 +8,7 @@ from hyperforge.models import HistoryQuestionAnswer NUA_KEY = os.environ.get("NUA_KEY") or cassette_nua_key( - "https://europe-1.nuclia.cloud/" + "https://europe-1.dp.progress.cloud/" ) pytestmark = [ diff --git a/hyperforge/tests/context/test_validation.py b/hyperforge/tests/context/test_validation.py index fb7fff89..f3653e1c 100644 --- a/hyperforge/tests/context/test_validation.py +++ b/hyperforge/tests/context/test_validation.py @@ -13,7 +13,7 @@ from hyperforge.models import Chunk, Context, MemoryConfig, Rules NUA_KEY = os.environ.get("NUA_KEY") or cassette_nua_key( - "https://europe-1.nuclia.cloud/" + "https://europe-1.dp.progress.cloud/" ) VALIDATION_MODEL = "gemini-2.5-flash" diff --git a/hyperforge/tests/test_mcp_interaction.py b/hyperforge/tests/test_mcp_interaction.py index 3b833c19..3f144de1 100644 --- a/hyperforge/tests/test_mcp_interaction.py +++ b/hyperforge/tests/test_mcp_interaction.py @@ -21,12 +21,12 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") KB_2603EE3A_2EE0_46BA_85A7_A1A2EC5A8FFE = os.environ.get( "KB_2603EE3A_2EE0_46BA_85A7_A1A2EC5A8FFE" -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") DRIVERS = [ { diff --git a/hyperforge/tests/test_next.py b/hyperforge/tests/test_next.py index d7657169..5877053e 100644 --- a/hyperforge/tests/test_next.py +++ b/hyperforge/tests/test_next.py @@ -8,12 +8,12 @@ NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") KB_DF8B4C24_2807_4888_AD6C_AE97357A638B = os.environ.get( "KB_DF8B4C24_2807_4888_AD6C_AE97357A638B" -) or cassette_nua_key("https://europe-1.nuclia.cloud/") +) or cassette_nua_key("https://europe-1.dp.progress.cloud/") CONFIG = { "drivers": [ From e42de33e35b4f1fba81834cce9ca5961c3481c7f Mon Sep 17 00:00:00 2001 From: Carles Onielfa Date: Wed, 5 Aug 2026 09:37:29 +0200 Subject: [PATCH 2/6] fmt --- agents/remi/tests/test_remi.py | 8 ++++++-- 1 file changed, 6 insertions(+), 2 deletions(-) diff --git a/agents/remi/tests/test_remi.py b/agents/remi/tests/test_remi.py index 0685058d..d52c96d8 100644 --- a/agents/remi/tests/test_remi.py +++ b/agents/remi/tests/test_remi.py @@ -76,7 +76,9 @@ # Match NUA chats by their stable routing fields; retrieved context in their # prompts changes as the documentation KB evolves. -@pytest.mark.vcr(match_on=["method", "scheme", "host", "port", "path", "query", "nua_chat"]) +@pytest.mark.vcr( + match_on=["method", "scheme", "host", "port", "path", "query", "nua_chat"] +) @pytest.mark.parametrize( "granularity", (ContextGranularity.PARTIAL_ANSWERS, ContextGranularity.FULL) ) @@ -156,7 +158,9 @@ async def test_remi(granularity: ContextGranularity): assert "Errors:" not in remi_ctx.summary -@pytest.mark.vcr(match_on=["method", "scheme", "host", "port", "path", "query", "nua_chat"]) +@pytest.mark.vcr( + match_on=["method", "scheme", "host", "port", "path", "query", "nua_chat"] +) @pytest.mark.parametrize( "granularity", [ContextGranularity.PARTIAL_ANSWERS, ContextGranularity.FULL] ) From a21e1468144f6a89c4e7bafb7d5c9c8fc1d18ff7 Mon Sep 17 00:00:00 2001 From: Carles Onielfa Date: Wed, 5 Aug 2026 09:58:44 +0200 Subject: [PATCH 3/6] no remote nua on nucliadb tests --- .../test_nucliadb_agent_basic_ask.yaml | 977 +--- .../test_nucliadb_agent_simple.yaml | 2740 ++-------- ...nt_simple_disable_ai_parameter_search.yaml | 4816 +++-------------- .../cassettes/test_sync/test_sync_agent.yaml | 2428 ++------- agents/nucliadb/tests/test_nucliadb.py | 13 +- agents/nucliadb/tests/test_sync.py | 8 +- 6 files changed, 2067 insertions(+), 8915 deletions(-) diff --git a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml index be8c430e..9efdf529 100644 --- a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml +++ b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml @@ -1,48 +1,4 @@ interactions: -- request: - body: '{"prefixes": [{"prefix": "/n/i"}]}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '32' - Host: - - europe-1.dp.progress.cloud - User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: - - DUMMY - method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets - response: - body: - string: '{"facets":{"/n/i":986,"/n/i/application":1,"/n/i/application/json":1,"/n/i/text":985,"/n/i/text/markdown":985}}' - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Length: - - '111' - access-control-expose-headers: - - X-NUCLIA-TRACE-ID - content-type: - - application/json - date: - - Wed, 15 Jul 2026 08:11:22 GMT - via: - - 1.1 google - x-envoy-upstream-service-time: - - '15' - x-nuclia-trace-id: - - 5fb40576d4d8cf1a6cb3c5e23df20600 - status: - code: 200 - message: OK - request: body: '' headers: @@ -53,751 +9,400 @@ interactions: Connection: - keep-alive Host: - - europe-1.dp.progress.cloud + - europe-1.dp.stashify.cloud User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: + - nuclia.py/4.11.5 + x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b + uri: https://europe-1.dp.stashify.cloud/api/authorizer/info response: body: - string: '{"slug":"nuclia-docs","uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","config":{"uuid":null,"slug":"4f9285c7-7151-4431-94e6-3f1fb0d66aca:nuclia-docs","title":"Nuclia - Docs","description":"","learning_configuration":null,"external_index_provider":null,"configured_external_index_provider":{"type":"unset"},"similarity":null,"hidden_resources_enabled":false,"hidden_resources_hide_on_creation":false,"enforce_security":false},"model":null}' + string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"da1740fa-ab3e-4971-b374-7bb31b5dd325","account_id":"39f5fa6e-680a-475e-a757-812597e86d06","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Content-Length: - - '434' - access-control-expose-headers: - - X-NUCLIA-TRACE-ID + - '227' content-type: - application/json date: - - Wed, 15 Jul 2026 08:11:22 GMT + - Wed, 05 Aug 2026 07:57:25 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '14' - x-nuclia-trace-id: - - 6d25f6a520f85405e56545eb3847fca9 + - '7' status: code: 200 message: OK - request: - body: '{"prefixes": [{"prefix": "/s/p"}]}' + body: '{"question": "", "retrieval": true, "user_id": "rephrase", "system": null, + "chat_history": [], "context": [], "query_context": {}, "query_context_order": + {}, "truncate": true, "user_prompt": {"prompt": "\nYou are an expert at rephrasing + complex questions for an agentic RAG system.\n\nYour task is to review the main + question and any provided context, then rephrase the question to maximize clarity + and focus. Follow these steps:\n\n1. Carefully analyze the main question and + all context provided, including sources, previous questions and answers, and + any other relevant information.\n2. I present, assess whether previous questions + and answers (history) are necessary for rephrasing. Only use history if it is + relevant and improves the clarity or specificity of the main question; otherwise, + ignore it.\n3. If the question can be made clearer or more specific, rephrase + it accordingly. If it is already clear and focused, return it unchanged.\n4. + Only use information present in the provided context. Do not introduce external + knowledge or assumptions.\n5. Return a JSON object with the following fields:\n - + \"rephrased_question\": The rephrased version of the main question, keep the + same question if no rephrasing is needed or possible.\n - \"rules\": Any + rules or guidelines that should be followed when generating the answer.\n - + \"reason\": Explain why the rephrasing was necessary or beneficial.\nReturn + only the JSON object as your response.\n\n\n\n\n# MAIN QUESTION:\nComo usar + max_tokens.answer. En espa\u00f1ol y dame link a la doucmentaci\u00f3n"}, "citations": + false, "citation_threshold": null, "generative_model": "gemini-2.5-flash-lite", + "max_tokens": 8192, "query_context_images": {}, "prefer_markdown": null, "json_schema": + {"title": "rephrase", "description": "", "type": "object", "properties": {"rephrased_question": + {"type": "string", "description": "Rephrased version of the main question."}, + "rules": {"type": "array", "items": {"type": "string"}, "description": "Rules + or guidelines to follow when generating the answer."}, "reason": {"type": "string", + "description": "Reason for rephrasing explaining why it is necessary."}}, "required": + ["rephrased_question"]}, "format_prompt": false, "rerank_context": false, "tools": + [], "tool_choice": {"type": "required"}, "reasoning": false, "seed": null}' headers: Accept: - - '*/*' + - application/x-ndjson Accept-Encoding: - gzip, deflate Connection: - keep-alive Content-Length: - - '32' + - '2251' + Content-Type: + - application/json Host: - - europe-1.dp.progress.cloud + - europe-1.dp.stashify.cloud User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: + - nuclia.py/4.11.5 + x-client-ident: + - default + x-message: + - 0dfefb8a0b7b40f6a89fc902c85a8d80 + x-origin: + - RAO + x-session: + - default_default_session + x-show-consumption: + - 'true' + x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat response: body: - string: '{"facets":{"/s/p":986,"/s/p/ca":3,"/s/p/cy":1,"/s/p/da":1,"/s/p/en":967,"/s/p/eo":4,"/s/p/la":7,"/s/p/nb":1,"/s/p/tl":1,"/s/p/yo":1}}' + string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"rephrased_question\":\"Explica + el uso de `max_tokens` en espa\xF1ol y proporciona un enlace a la documentaci\xF3n + oficial.\",\"rules\":[\"Responde en espa\xF1ol.\",\"Incluye un enlace a la + documentaci\xF3n oficial de `max_tokens`.\"],\"reason\":\"La pregunta original + es clara pero se puede mejorar ligeramente al especificar que se busca la + explicaci\xF3n y el enlace a la documentaci\xF3n de manera expl\xEDcita, adem\xE1s + de asegurar que la respuesta sea en espa\xF1ol.\"}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":7,\"output_tokens\":9,\"timings\":{\"generative\":0.8064458860026207},\"input_nuclia_tokens\":0.007,\"output_nuclia_tokens\":0.009}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0071,\"output\":0.0092,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Length: - - '133' + Transfer-Encoding: + - chunked access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - - application/json + - application/x-ndjson date: - - Wed, 15 Jul 2026 08:11:22 GMT + - Wed, 05 Aug 2026 07:57:25 GMT + nuclia-learning-id: + - 773cc8e292d24a8399e92e28cc05601f + nuclia-learning-model: + - gemini-2.5-flash-lite via: - 1.1 google x-envoy-upstream-service-time: - - '14' + - '812' x-nuclia-trace-id: - - 2f2e8645595643b4012d7435e7d0da5c + - fc73b490383741aa83d36633cd9a6d98 status: code: 200 message: OK - request: - body: '' + body: '{"question": "", "retrieval": true, "user_id": "rao_answer_summary-basic_ask", + "system": null, "chat_history": [], "context": [], "query_context": {}, "query_context_order": + {}, "truncate": true, "user_prompt": {"prompt": "\nBased on the provided context + and user question, perform the following tasks:\n\n1. Select only information + directly relevant to the question.\n2. Break down compound sentences into simple, + single-idea statements. Preserve original phrasing when possible.\n3. For any + named entity with descriptive details, separate those details into distinct + propositions.\n4. Ensure clarity by replacing pronouns (e.g., \"it\", \"he\", + \"she\", \"they\", \"this\", \"that\") with the full names of the entities they + reference, and add necessary modifiers to clarify meaning.\n5. The context may + be delimited by tags such as and . Treat + everything between these tags as context.\n6. Assess whether the context sufficiently + answers the question. If it answers it partially, provide the answer; if it + does not answer it fully, specify what information is missing to answer the + question.\n7. If the context does not answer the question at all, just return + the original question as the missing information.\n8. The `citations` field + consists ONLY in a list of block IDs that are relevant to the answer, following + these rules:\n - Use the format: block-AB\n - Just mention the block IDs, + do NOT include any other text.\n - Just mention the blocks actually relevant + and that contain information used in the answer, do NOT include blocks that + are not relevant.\n - No duplicates.\n9. Do NOT hallucinate block IDs. Only + use those provided in the context.\n10. Your output must be a JSON object with + the following fields:\n - \"reason\": Explain your reasoning for the answer + or validation.\n - \"answer\": Provide a partial or complete answer to the + user query strictly from the information in the context. If there isn''t enough + information to even provide a partial answer, leave ''answer'' empty.\n - + \"missing_info_query\": If the context is insufficient, specify what information + is missing in a query shape; otherwise, leave it empty. Just return the query + needed to retrieve the missing information.\n - \"useful\": Indicate if the + context is useful to answer the question (\"yes\" or \"no\").\n - \"citations\": + List the IDs of the blocks relevant to the answer, if any (e.g., [\"block-AB\", + \"block-CD\"]).\n11. **IMPORTANT** If any extra instructions are provided, you + MUST follow them carefully when generating the answer field. These instructions + may specify the format, style, tools to use, or other requirements for the answer.\n\n\nExplica + el uso de `max_tokens` en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n + oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### Chunk: docs + > develop > js sdk > interfaces > PredictAnswerOptions\n``` \n optional max_tokens: + number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? + \n ```\n\n\n---\"\n\n\n**block-AB**\n\n#### Chunk: docs > rag > advanced > consumption.\n``` Use + the max_tokens parameter on the /ask endpoint to set hard limits on: \n - Context + size: Limits the amount of retrieved information sent to the LLM \n - Answer + length: Limits the length of the generated response \n Important Considerations + \n Context Limitations: \n ```\n\n\n---\"\n\n\n**block-AC**\n\n#### Chunk: docs + > rag > advanced > widget > features\n``` max_tokens: the maximum number of + input tokens to put in the final context (including the prompt, the retrieved + results and the user question). \n max_output_tokens: the maximum number of + tokens to generate. \n ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: docs + > develop > js sdk > interfaces > ChatOptions\n``` \n optional max_tokens: + number \\| object \n \n Defines the maximum number of tokens that the model + will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \n \n min_score? \n ```\n\n\n---\"\n\n\n**block-AE**\n\n#### Chunk: docs > rag + > advanced > openai api compatible models\n``` \n \n Maximum supported input + tokens: \n Description: The maximum number of tokens that the model can accept + as input. Be mindful that this takes into account the tokens used in the prompt, + query and context. Also take note that some models may provide their context + window as the total between input and output tokens, while others may provide + it as the input tokens only. \n ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: + docs > develop > python sdk > 05 search\n``` \n SDK: \n \n ```python \n from + nuclia import sdk \n from nucliadb_models.search import AskRequest, Reasoning + \n search = sdk.NucliaSearch() \n query = AskRequest( \n query= My question + with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( \n + display=True, # Show reasoning in the response \n effort= low , # Can be low + , medium , or high \n budget_tokens=1024 # How many tokens reasoning can use + \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning + Options: \n ```\n\n\n---\"\n\n\n**block-AG**\n\n#### Chunk: docs > develop > + js sdk > interfaces > PredictAnswerOptions\n``` \n optional generative_model: + string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 + \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 + \n \n max_tokens? \n ```\n\n\n---\"\n\n\n**block-AH**\n\n#### Chunk: docs > + develop > js sdk > interfaces > ChatOptions\n``` \n optional highlight: boolean + \n \n Inherited from \n BaseSearchOptions.highlight \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:76 + \n \n keyword_filters? \n \n optional keyword_filters: string[] \\| Filter[] + \n \n Inherited from \n BaseSearchOptions.keyword_filters \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:65 + \n \n max_tokens? \n ```\n\n\n---\"\n\n\n**block-AI**\n\n#### Chunk: docs > + rag > advanced > openai api compatible models\n``` Description: The maximum + number of tokens that the model can generate as output. Again, we should keep + in mind that this value summed to the Maximum supported input tokens should + not exceed the total context size supported by the model. \n ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": false, "citation_threshold": null, "generative_model": + "chatgpt-azure-4o-mini", "max_tokens": 8192, "query_context_images": {}, "prefer_markdown": + null, "json_schema": {"title": "validate_or_answer", "description": "Validate + or answer", "parameters": {"type": "object", "properties": {"reason": {"type": + "string", "description": "Reasoning for the answer or validation"}, "answer": + {"type": "string", "description": "Partial or complete answer to the user query + from the information in the context."}, "missing_info_query": {"type": "string", + "description": "Query needed to retrieve the missing information in case the + context is not enough to answer the question. 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This option is not available through self-service configuration. - Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests - on. 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It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. 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Allowlist these if you restrict inbound traffic to your infrastructure. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n :::note \\n The current list of IP addresses is also available in machine-readable - format: JSON | YAML. These lists may change over time, so we recommend periodically - fetching and applying updates to your firewall rules to ensure uninterrupted - service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall - restricts network traffic, you may need to allowlist the following IP addresses. - They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | - --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 - | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 - | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- - | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n - | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 - | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | - 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 - | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | - --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 - | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United - States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- - | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 - | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS - PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately - through an AWS endpoint service (AWS PrivateLink) instead of over the public - internet, allowing connections to be established from your VPC without traversing - public IP addresses. This option is not available through self-service configuration. - Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests - on. Allowlist these if you restrict outbound traffic from your infrastructure - and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs - > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent - \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful - tool that enhances the capabilities of traditional retrieval-augmented generation - (RAG) systems. Regular RAG's fixed search-then-generate process is limiting - for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Different models can be chosen for different tasks: \\n \\n Context validation - happens when the Prune context option is enabled (recommended), we recommend - using a fast model - planning or the execution model (depending on the planning - mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n Note: the rephrasing model is only used in more complex workflow, it can - be ignored in the present case. \\n Finally, add a Summarize agent in the - Generation step to generate a final answer from the retrieved information. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - The Smart Agent plans the answer: picks the most appropriate sources, splits - the question into sub-questions, evaluates relevancy, and iterates autonomously - until the information is sufficient. \\n Basic usage \\n To set up a Smart - Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, - etc.) in the Sources section of the left menu. Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. It will be slower but more accurate when processing - complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Also select the proper function for each registered agent, depending on the - type of source (MCP agents will not need one, the functions are provided dynamically - by the MCP server). \\n In the Smart Agent configuration, you can select the - planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - In the Summarize Agent, enable the Conversational mode. This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. 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libs/sdk-core/src/lib/db/resource/resource.models.ts:242\",\"id\":\"4194605cdfbd414f8fa762630d555bc1/t/page/0-358\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":358,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"1cf976a5ca5947cd89a2f2a047b71ce9\":{\"id\":\"1cf976a5ca5947cd89a2f2a047b71ce9\",\"slug\":\"docs-ingestion-how-to-split-strategies-md\",\"title\":\"docs - > ingestion > how to > split strategies\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-09-12T08:39:42.634556\",\"modified\":\"2026-06-09T08:18:07.009807\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"1cf976a5ca5947cd89a2f2a047b71ce9/t/page/963-1239\":{\"score\":0.00431468803435564,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" - Key components of a split strategy include: \\n \\n Max paragraph size: Sets - the maximum size (in characters or tokens) for each chunk. \\n Custom split: - Determines the method used for splitting: \\n Manual splitting: Splits content - based on a specified delimiter (default is \\\\n ). \\n\",\"id\":\"1cf976a5ca5947cd89a2f2a047b71ce9/t/page/963-1239\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":963,\"end\":1239,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"6e8250e6b5264156988657a221fd5e94\":{\"id\":\"6e8250e6b5264156988657a221fd5e94\",\"slug\":\"docs-develop-js-sdk-namespaces-Ask-interfaces-ConsumptionAskResponseItem-md\",\"title\":\"docs - > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:47:37.548412\",\"modified\":\"2026-07-14T12:48:09.327828\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\":{\"score\":0.0019418168812990189,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: - ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n - customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 - \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n - type \\n \\n\",\"id\":\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":397,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"89cc367c149e4f6eab0e06a743d1edba\":{\"id\":\"89cc367c149e4f6eab0e06a743d1edba\",\"slug\":\"docs-rag-advanced-openai-api-compatible-models-md\",\"title\":\"docs - > rag > advanced > openai api compatible models\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-05-23T07:21:32.894218\",\"modified\":\"2026-06-09T08:07:43.359058\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\":{\"score\":0.023197626695036888,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" - Description: The maximum number of tokens that the model can generate as output. - Again, we should keep in mind that this value summed to the Maximum supported - input tokens should not exceed the total context size supported by the model. - \\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":2804,\"end\":3043,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\":{\"score\":0.022499969229102135,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" - \\n \\n Maximum supported input tokens: \\n Description: The maximum number - of tokens that the model can accept as input. Be mindful that this takes into - account the tokens used in the prompt, query and context. Also take note that - some models may provide their context window as the total between input and - output tokens, while others may provide it as the input tokens only. \\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":2202,\"end\":2575,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"0a003c3f724e45e392a9c8d1ce8800c1\":{\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1\",\"slug\":\"docs-develop-js-sdk-interfaces-Consumption-md\",\"title\":\"docs - > develop > js sdk > interfaces > Consumption\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:51:46.788864\",\"modified\":\"2026-07-14T12:51:15.300757\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\":{\"score\":0.0018675660248845816,\"score_type\":\"RERANKER\",\"order\":19,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption - \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n - \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs - > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-07-14T12:49:58.922592\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\":{\"score\":0.06359858065843582,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" - \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 - \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: - number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \\n \\n max_images? \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\":{\"score\":0.03126191347837448,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" - \\n optional max_images: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 - \\n \\n output_tokens \\n \\n output_tokens: object \\n \\n default_max? \\n - \\n optional default_max: number \\n \\n max \\n \\n max: number \\n \\n min? - \\n \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs - > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-07-14T12:51:04.368823\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\":{\"score\":0.08647765219211578,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\" - \\n optional max_tokens: number \\\\| object \\n \\n Defines the maximum number - of tokens that the model will take as context. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 - \\n \\n min_score? \\n\",\"id\":\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2808,\"end\":3011,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"e8525e64c5b44982b958d32cf6090613/t/page/2450-2808\":{\"score\":0.053502149879932404,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\" - \\n optional highlight: boolean \\n \\n Inherited from \\n BaseSearchOptions.highlight - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:76 \\n - \\n keyword_filters? \\n \\n optional keyword_filters: string[] \\\\| Filter[] - \\n \\n Inherited from \\n BaseSearchOptions.keyword_filters \\n Defined in - \\n libs/sdk-core/src/lib/db/search/search.models.ts:65 \\n \\n max_tokens? - \\n\",\"id\":\"e8525e64c5b44982b958d32cf6090613/t/page/2450-2808\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2450,\"end\":2808,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"220eb37c167f4eb9bb8e9454e7ba8cf5\":{\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5\",\"slug\":\"docs-develop-python-sdk-05-search-md\",\"title\":\"docs - > develop > python sdk > 05 search\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:48:33.723913\",\"modified\":\"2026-06-09T08:08:04.866092\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\":{\"score\":0.09982066601514816,\"score_type\":\"RERANKER\",\"order\":3,\"text\":\" - \\n SDK: \\n \\n ```python \\n from nuclia import sdk \\n from nucliadb_models.search - import AskRequest, Reasoning \\n search = sdk.NucliaSearch() \\n query = AskRequest( - \\n query= My question with extra reasoning effort , \\n max_tokens=5000, - \\n reasoning=Reasoning( \\n display=True, # Show reasoning in the response - \\n effort= low , # Can be low , medium , or high \\n budget_tokens=1024 # - How many tokens reasoning can use \\n ), \\n ) \\n search.ask(query=query) - \\n ``` \\n Model Support for Reasoning Options: \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1790,\"end\":2276,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\":{\"score\":0.05582314357161522,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" - ::: \\n :::warning \\n Enabling reasoning can use additional tokens, which - may increase your usage costs. \\n You may need to increase max_tokens to - give the LLM enough room to reason and generate an answer. \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2505,\"end\":2709,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs - > rag > advanced > consumption.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-10-03T08:32:26.341394\",\"modified\":\"2026-06-09T08:18:16.730959\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\":{\"score\":0.456288605928421,\"score_type\":\"RERANKER\",\"order\":0,\"text\":\" - Use the max_tokens parameter on the /ask endpoint to set hard limits on: \\n - - Context size: Limits the amount of retrieved information sent to the LLM - \\n - Answer length: Limits the length of the generated response \\n Important - Considerations \\n Context Limitations: \\n\",\"id\":\"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":3075,\"end\":3340,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"66b6f0dbd883413e98fbbf5b59f049b9\":{\"id\":\"66b6f0dbd883413e98fbbf5b59f049b9\",\"slug\":\"docs-develop-js-sdk-enumerations-UsageType-md\",\"title\":\"docs - > develop > js sdk > enumerations > UsageType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"tl\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T09:59:02.349911\",\"modified\":\"2026-07-14T12:54:11.386825\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833\":{\"score\":0.029986508190631866,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / UsageType \\n Enumeration: UsageType \\n - Enumeration Members \\n AI_TOKENS_USED \\n \\n AI_TOKENS_USED: ai_tokens_used - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:206 \\n \\n BYTES_PROCESSED - \\n \\n BYTES_PROCESSED: bytes_processed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:197 - \\n \\n CHARS_PROCESSED \\n \\n CHARS_PROCESSED: chars_processed \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:198 \\n \\n MEDIA_FILES_PROCESSED - \\n \\n MEDIA_FILES_PROCESSED: media_files_processed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:200 \\n \\n MEDIA_SECONDS_PROCESSED - \\n \\n MEDIA_SECONDS_PROCESSED: media_seconds_processed \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n - NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 - \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED - \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n - \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 - \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED - \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 - \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED - \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: - train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"id\":\"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"50aac6f34b6d47de8e3b01f8b2de6e9c\":{\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c\",\"slug\":\"docs-develop-js-sdk-interfaces-PredictAnswerOptions-md\",\"title\":\"docs - 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Follow these steps:\n\n1. Carefully analyze the main question and + all context provided, including sources, previous questions and answers, and + any other relevant information.\n2. I present, assess whether previous questions + and answers (history) are necessary for rephrasing. Only use history if it is + relevant and improves the clarity or specificity of the main question; otherwise, + ignore it.\n3. If the question can be made clearer or more specific, rephrase + it accordingly. If it is already clear and focused, return it unchanged.\n4. + Only use information present in the provided context. Do not introduce external + knowledge or assumptions.\n5. 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Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. 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This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. 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It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. 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This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. 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ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - - '16898' + - '115' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 08:10:51 GMT + - Wed, 05 Aug 2026 07:56:58 GMT + nuclia-learning-model: + - multilingual via: - 1.1 google x-envoy-upstream-service-time: - - '67' + - '16' x-nuclia-trace-id: - - d477b16749982203d03ea7babb4155fd + - b146c40f938c36e41f8ce06ba3cc8959 status: code: 200 message: OK - request: - body: '{"user_id": "arag-ask", "texts": ["Explica c\u00f3mo usar el par\u00e1metro - `max_tokens` en las respuestas, proporciona la explicaci\u00f3n en espa\u00f1ol - y un enlace a la documentaci\u00f3n oficial."]}' + body: '{"question": "", "retrieval": true, "user_id": "arag-ask", "system": null, + "chat_history": [], "context": [], "query_context": {}, "query_context_order": + {}, "truncate": true, "user_prompt": {"prompt": "\n\nInformation about the KB:\n\n# + nuclia-docs\n\ndescription: Documentation of the Nuclia API, recipies, reference + \n\nAnd given the question: Explica c\u00f3mo usar el par\u00e1metro `max_tokens` + para controlar la longitud de las respuestas en espa\u00f1ol y proporciona un + enlace a la documentaci\u00f3n oficial.\n\n## labels: {''pmm'': [''Videos'', + ''Partner Content'', ''Softcat'', ''Sales Enablement Assets'', ''KO 26'', ''Data + Sheets'', ''Progress Agentic RAG Training Materials 2026'']}\n\n## Facets:\n\n## + Content Types\nThe following content types are available in the KB:\n\n- /n/i: + 994\n- application/json: 1\n- text/markdown: 993\nThe following languages are + available in the KB:\n\n- ca: 4\n- cy: 1\n- da: 1\n- en: 974\n- eo: 4\n- la: + 7\n- nb: 1\n- tl: 1\n- yo: 1\n\n\n# Important rules to follow\n\n\nprompt=''Be + polite''\n"}, "citations": false, "citation_threshold": null, "generative_model": + "gemini-2.5-flash", "max_tokens": 8192, "query_context_images": {}, "prefer_markdown": + null, "json_schema": {"title": "ask_configuration", "description": "Configuration + extracted from reasoning engine", "parameters": {"type": "object", "properties": + {"link": {"type": "boolean", "description": "The user wants link reference to + the answer?"}, "knowledge_scan": {"type": "string", "description": "If the query + requires a knowledge aggregation or scan search to answer define the entities, + labels and relations to query in the KB. Example queries: How many ..."}, "semantic_query": + {"type": "string", "description": "Rephrase this question so its better for + semantic retrieval, and keep the rephrased question in the same language as + the original. Please define ONLY the question without any explanation. JUST + A SENTENCE. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST ONE SENTENCE"}, "lexical_query": + {"type": "string", "description": "Rephrase this question so its better for + lexical retrieval, translate the lexical rephrased question to cy. Please define + ONLY the question without any explanation. JUST A SENTENCE. DO NOT ADD ANY EXTRA + NOTES AT THE END, JUST ONE SENTENCE"}, "visual": {"type": "boolean", "description": + "Is required an analysis of an image to answer this question, answer with false + or true"}, "keywords_filter": {"type": "array", "items": {"type": "string"}, + "description": "Extract if any the keywords that should appear on the retrieved + results and its a must match, make sure that are keywords that are not common + words, and that are not the same as the question or answer. Please define ONLY + the keywords without any explanation. Only one or two words maximum. JUST A + LIST OF KEYWORDS. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST A LIST OF KEYWORDS"}, + "reason": {"type": "string"}, "entities": {"type": "array", "description": "Entities + related to the user question to query in the KB", "items": {"type": "string"}}, + "relations": {"type": "array", "description": "Relations related to the user + question to query in the KB", "items": {"type": "string"}}, "pre_queries": {"type": + "array", "items": {"type": "string"}, "description": "Pre queries to run before + the main query to gather more information"}}, "required": ["semantic_query", + "lexical_query", "visual", "keywords_filter", "reason", "pre_queries"]}}, "format_prompt": + false, "rerank_context": false, "tools": [], "tool_choice": {"type": "required"}, + "reasoning": false, "seed": null}' headers: Accept: - - '*/*' + - application/x-ndjson Accept-Encoding: - gzip, deflate Connection: - keep-alive Content-Length: - - '180' - Host: - - europe-1.dp.progress.cloud - User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: - - DUMMY - method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/predict/run-agents-text - response: - body: - string: '{"results":[{"input_nuclia_tokens":0.0,"output_nuclia_tokens":0.0,"time":0.0001347064971923828,"payloads":[]}]}' - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Length: - - '111' - access-control-expose-headers: - - X-NUCLIA-TRACE-ID - content-type: + - '3420' + Content-Type: - application/json - date: - - Wed, 15 Jul 2026 08:10:52 GMT - via: - - 1.1 google - x-envoy-upstream-service-time: - - '26' - x-nuclia-trace-id: - - 284458cff294072478e6a1a2aa010e54 - status: - code: 200 - message: OK -- request: - body: '{"query": "Esboniwch sut i ddefnyddio''r paramedr ''max_tokens'' mewn atebion, - a darparwch ddolen i''r ddogfennaeth swyddogol.", "filters": [], "show": ["basic", - "origin", "extra", "extracted", "values", "relations"], "extracted": ["text", - "metadata", "file", "link"], "security": {"groups": []}, "features": ["keyword"], - "reranker": "noop", "keyword_filters": ["max_tokens", "par\u00e1metro"]}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '361' Host: - - europe-1.dp.progress.cloud + - europe-1.dp.stashify.cloud User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: + - nuclia.py/4.11.5 + x-client-ident: + - default + x-message: + - 8ed74a70fcdc44fda2e5768a74ef5b19 + x-origin: + - RAO + x-session: + - default_default_session + x-show-consumption: + - 'true' + x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat response: body: - string: '{"resources":{},"relations":{"entities":{}},"query":"Esboniwch sut - i ddefnyddio''r paramedr ''max_tokens'' mewn atebion, a darparwch ddolen i''r - ddogfennaeth swyddogol.","rephrased_query":null,"total":0,"page_number":0,"page_size":20,"next_page":false,"shards":["306cbabb-72a5-417c-827f-7874e205c858"],"min_score":{"semantic":0.0,"bm25":0.0},"best_matches":[]}' + string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"link\":true,\"semantic_query\":\"Explica + el uso del par\xE1metro `max_tokens` para controlar la longitud de las respuestas + y proporciona un enlace a la documentaci\xF3n oficial.\",\"lexical_query\":\"Sut + i ddefnyddio'r paramedr `max_tokens` i reoli hyd ymatebion a darparu dolen + i'r ddogfennaeth swyddogol?\",\"visual\":false,\"keywords_filter\":[\"max_tokens\",\"longitud\",\"respuestas\"],\"reason\":\"The + user is asking how to use a specific parameter (`max_tokens`) to control the + length of responses and wants a link to the official documentation. This requires + a semantic search for the parameter's usage and a link.\",\"pre_queries\":[]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":36,\"output_tokens\":97,\"timings\":{\"generative\":1.6855239240012452},\"input_nuclia_tokens\":0.036,\"output_nuclia_tokens\":0.097}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.03564,\"output\":0.097,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Length: - - '356' + - h3=":443"; ma=2592000 + Transfer-Encoding: + - chunked access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - - application/json + - application/x-ndjson date: - - Wed, 15 Jul 2026 08:10:54 GMT + - Wed, 05 Aug 2026 07:56:58 GMT + nuclia-learning-id: + - a7e8d9326fd649fdaf69d8c6dd824a2e + nuclia-learning-model: + - gemini-2.5-flash via: - 1.1 google x-envoy-upstream-service-time: - - '20' + - '1692' x-nuclia-trace-id: - - 71ff89dc0d0ade1551a517e2e94865aa + - 96862f234d56fe6dab0110cbd5a26d36 status: code: 200 message: OK - request: - body: '{"query": "Explica el uso del par\u00e1metro ''max_tokens'' en las respuestas - y proporciona un enlace a la documentaci\u00f3n oficial.", "filters": [], "min_score": - {"semantic": 0.4}, "show": ["basic", "origin", "extra", "extracted", "values", - "relations"], "extracted": ["text", "metadata", "file", "link"], "vectorset": - "multilingual-2024-05-06", "security": {"groups": []}, "features": ["semantic"], - "reranker": "noop"}' + body: '{"question": "Explica c\u00f3mo usar el par\u00e1metro `max_tokens` para + controlar la longitud de las respuestas en espa\u00f1ol y proporciona un enlace + a la documentaci\u00f3n oficial.", "user_id": "arag-ask-rerank", "context": + {"c27a1e5f5ddb4b118921345d713401b8/t/page/351-554": " full: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:386 \n \n max_messages? \n \n + optional max_messages: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:387 + \n \n name \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ConversationalStrategy\n", + "dd41482018924facb5dbb87a7d53f122/t/page/3310-3757": " ) \n time.sleep(wait_time) + \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( + Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers + = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_try_after_info(url, + headers) \n print(data) \n ``` \n These examples demonstrate how to handle rate + limits effectively, ensuring that your application respects the limits and retries + appropriately.\n\n\nLink: https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\n", + "dd41482018924facb5dbb87a7d53f122/t/page/1900-2653": " retries = 0 \n while + retries < max_retries: \n response = requests.get(url, headers=headers) \n if + response.status_code == 200: \n return response.json() \n elif response.status_code + == 429: \n wait_time = 2 retries # Exponential backoff: 2^retries \n print(f + Rate limit exceeded. Retrying in {wait_time} seconds... ) \n time.sleep(wait_time) + \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( + Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers + = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_exponential_backoff(url, + headers) \n print(data) \n ``` \n Example 2: Ingestion back pressure limits + \n Here''s an example of how to use the try_after key from the response to manage + rate limits: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\n", + "4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340": " Use the max_tokens parameter + on the /ask endpoint to set hard limits on: \n - Context size: Limits the amount + of retrieved information sent to the LLM \n - Answer length: Limits the length + of the generated response \n Important Considerations \n Context Limitations: + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", + "4039d76b0fff4962900836ab3fdec9f7/t/page/3340-4136": " - Restricting context + size may result in less relevant answers since the LLM has less information + to work with \n - Balance between cost control and answer quality \n Answer + Length Limitations: \n - The LLM might not complete its response if it hits + the token limit, potentially cutting sentences mid-way \n - Recommended approach: + Include length requirements in your prompt (e.g., Please answer in less than + 200 words ) rather than relying solely on hard limits \n - This allows the LLM + to naturally conclude its response within the desired length \n How to Monitor + Token Consumption \n Understanding Token Consumption Data \n You can receive + detailed token consumption information from the following endpoints that utilize + LLM models: ask, chat, remi, query, sentence, summarize, tokens, and rerank. + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", + "4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326": " \n Large context: Results + from using RAG strategies like Full resource or Neighbouring paragraphs , or + from using the extra_context parameter \n Long questions: More detailed or complex + questions require more input tokens \n Long prompts: Extensive system prompts + increase the input token count \n Detailed answers: Comprehensive responses + require more output tokens \n Images in context: When using multimodal models, + images included in the retrieved context significantly increase token consumption + \n \n How to Limit and Control Token Consumption \n Strategy 1: Optimize Your + Parameters \n The first approach to reducing token consumption is to fine-tune + your request parameters: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", + "4039d76b0fff4962900836ab3fdec9f7/t/page/5396-5615": " - input: Tokens used + for the prompt, context, and question \n - output: Tokens used for the generated + response \n - image: Tokens used for image processing (when applicable) \n Customer + Key Tokens (customer_key_tokens): \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", + "b6a6202b9f0d4611a980293ce53337d6/t/page/265-405": " last: boolean \n \n page + \n \n page: number \n \n size \n \n size: number \n \n Defined in \n libs/sdk-core/src/lib/db/training/training.models.ts:36\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/TrainingExecutions\n", + "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709": " ::: \n :::warning \n + Enabling reasoning can use additional tokens, which may increase your usage + costs. \n You may need to increase max_tokens to give the LLM enough room to + reason and generate an answer. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n", + "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276": " \n SDK: \n \n ```python + \n from nuclia import sdk \n from nucliadb_models.search import AskRequest, + Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( \n query= My + question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( + \n display=True, # Show reasoning in the response \n effort= low , # Can be + low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can + use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning + Options: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n", + "44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668": " \n step: Information + about the current processing step \n module: The module being executed (e.g., + rephrase , basic_ask , remi ) \n title: Display title for the step \n value: + Result of the step \n reason: Explanation for the step \n timeit: Time taken + in seconds \n \n input_nuclia_tokens/output_nuclia_tokens: Token usage \n \n + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/rao\n", + "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221": " \n optional max_tokens: + number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", + "43004f553e534ffe9c9e735856bd9b23/t/page/480-703": " \n optional max_images: + string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \n \n + output_tokens \n \n output_tokens: object \n \n default_max? \n \n optional + default_max: number \n \n max \n \n max: number \n \n min? \n \n\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n", + "43004f553e534ffe9c9e735856bd9b23/t/page/212-480": " \n optional driver: string + \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 \n \n input_tokens + \n \n input_tokens: object \n \n max \n \n max: number \n \n min? \n \n optional + min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \n \n max_images? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n", + "f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299": "@nuclia/core \u2022 Docs \n + \n @nuclia/core / PageToken \n Interface: PageToken \n Properties \n height + \n \n height: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 + \n \n line \n \n line: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 + \n \n text \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageToken\n", + "9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412": " max_tokens: the maximum + number of input tokens to put in the final context (including the prompt, the + retrieved results and the user question). \n max_output_tokens: the maximum + number of tokens to generate. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n", + "e8525e64c5b44982b958d32cf6090613/t/page/2808-3011": " \n optional max_tokens: + number \\| object \n \n Defines the maximum number of tokens that the model + will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n", + "89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575": " \n \n Maximum supported + input tokens: \n Description: The maximum number of tokens that the model can + accept as input. Be mindful that this takes into account the tokens used in + the prompt, query and context. Also take note that some models may provide their + context window as the total between input and output tokens, while others may + provide it as the input tokens only. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", + "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043": " Description: The maximum + number of tokens that the model can generate as output. Again, we should keep + in mind that this value summed to the Maximum supported input tokens should + not exceed the total context size supported by the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", + "42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696": " \n optional max_paragraph: + number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 \n \n + name? \n \n optional name: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/SplitStrategy\n"}}' headers: Accept: - '*/*' @@ -662,1772 +409,307 @@ interactions: Connection: - keep-alive Content-Length: - - '385' + - '9962' + Content-Type: + - application/json Host: - - europe-1.dp.progress.cloud + - europe-1.dp.stashify.cloud User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: + - nuclia.py/4.11.5 + x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.stashify.cloud/api/v1/predict/rerank response: body: - string: "{\"resources\":{\"6e8250e6b5264156988657a221fd5e94\":{\"id\":\"6e8250e6b5264156988657a221fd5e94\",\"slug\":\"docs-develop-js-sdk-namespaces-Ask-interfaces-ConsumptionAskResponseItem-md\",\"title\":\"docs - > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:47:37.548412\",\"modified\":\"2026-07-14T12:48:09.327828\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/namespaces/Ask/interfaces/ConsumptionAskResponseItem\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../../../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../../../globals.md) / [Ask](../README.md) - / ConsumptionAskResponseItem\\n\\n# Interface: ConsumptionAskResponseItem\\n\\n## - Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> **customer\\\\_key\\\\_tokens**: - [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L127)\\n\\n***\\n\\n### - normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L126)\\n\\n***\\n\\n### - type\\n\\n> **type**: `\\\"consumption\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:125](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L125)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"3d72cf5a8634c4719acbe4304e79b48d\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: - ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n - customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 - \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n - type \\n \\n type: consumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:125\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":397,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":397,\"key\":\"\"}]},{\"start\":397,\"end\":483,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":398,\"end\":483,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:48:23.234967Z\",\"last_understanding\":\"2026-07-14T12:48:22.068785Z\",\"last_extract\":\"2026-07-14T12:48:21.777104Z\",\"last_processing_start\":\"2026-07-14T12:48:21.755089Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\":{\"score\":0.6163696646690369,\"score_type\":\"VECTOR\",\"order\":8,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: - ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n - customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 - \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n - type \\n \\n\",\"id\":\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":397,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"9f7036a7a6694700b72d52eb58a8326c\":{\"id\":\"9f7036a7a6694700b72d52eb58a8326c\",\"slug\":\"docs-rag-advanced-widget-features-md\",\"title\":\"docs - > rag > advanced > widget > features\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T14:32:26.204740\",\"modified\":\"2026-06-09T08:07:51.648767\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - features\\ntitle: Features\\n---\\n\\n# Widgets features\\n\\nThe Agentic - RAG widgets allows you to embed the Agentic RAG search experience directly - into your website or web application through a simple HTML snippet:\\n\\n```html\\n\\n\\n\\n```\\n\\nThe - easiest way to explore the different features of the widgets is to use the - [Agentic RAG Dashboard](https://rag.progress.cloud/) in the Widgets section - and to play with the different options.\\n\\nThe _Embed widget_ button will - generate the HTML snippet for you.\\n\\n## Widget types\\n\\nThere are 3 different - types of widgets:\\n\\n- **Embedded in page**: the search input is embedded - in a page and the results are displayed under the input. Once the initial - answer is displayed, the user can click on _Ask more_ to access the full chat - interface. Note: For the correct reading of the results, the width of the - widget container should not be less than 384px.\\n\\n Web components:\\n\\n - \ ```html\\n \\n \\n - \ ```\\n\\n- **Chat mode**: displays directly the full chat interface.\\n\\n - \ Web component:\\n\\n ```html\\n \\n ```\\n\\n- - **Popup modal**: the search inout and the results are displayed in a popup - modal.\\n\\n Web component:\\n\\n ```html\\n \\n - \ ```\\n\\n## The `features` parameter\\n\\nThe `features` parameter allows - you to customize the behavior of the widget. It is a comma-separated list - of features among the following:\\n\\n- `filter`: display a filter dropdown - in the search bar.\\n- `navigateToFile`: open the file in the browser when - clicking on the result (by default, the file is displayed in the viewer).\\n- - `navigateToLink`: open the link in the browser when clicking on the result - (by default, the link is displayed in the viewer).\\n- `permalink`: add the - search query and criteria to the URL, allowing the widget to re-render the - same results upon loading.\\n- `relations`: display an info card on the right - side of the widget listing all the relations of the entity mentioned in the - user query.\\n- `suggestions`: display a list of suggested resource titles - matching the user input.\\n- `suggestLabels`: display a list of suggestions - based on the labels when the user starts typing in the search bar.\\n- `autocompleteFromNERs`: - display a list of suggestions based on the NERs extracted from the user query - when the user starts typing in the search bar.\\n- `displayMetadata`: display - the metadata associated with the resource in the result rows.\\n- `answers`: - trigger the answer generation process when the user makes a search.\\n- `hideResults`: - hide the search results, only the generative answer will be displayed.\\n- - `hideThumbnails`: hide the thumbnails associated with the resource in the - result rows.\\n- `displayFieldList`: display a section listing all the fields - of the resource in the right sidebar of the viewer. This section is only visible - for resources containing multiple fields.\\n- `citations`: include citations - in the generative answer.\\n- `rephrase`: rephrase the user question in order - to optimize the quality of the search results.\\n- `debug`: display extra - buttons to download the last request full log of the debug metadata returned - by the API. It must not be used in production.\\n- `preferMarkdown`: require - the generative answer to be formatted in Markdown.\\n- `openNewTab`: open - the link in a new tab when clicking on the result.\\n- `orFilterLogic`: use - the OR logic for filters instead of the default AND logic.\\n- `noChatHistory`: - the previous questions and answers in the chat mode will not be passed as - context when generating a new answer.\\n- `showHidden`: display hidden resources - in the search results.\\n- `showAttachedImages`: display images attached to - the matching paragraphs in the search results.\\n\\n### Other parameters\\n\\n- - `backend`: the URL of the backend to use. Useful if you use your own proxy - to access the Agentic RAG API.\\n- `zone`: the zone to use.\\n- `knowledgebox`: - the Knowledge Box id.\\n- `placeholder`: the text displayed in the search - bar when it is empty.\\n- `lang`: the language of the widget. Currently supported: - `ca`, `fr`, `en`, `es`. Default: `en`.\\n- `apikey`: the API key to use. It - is not recommended to use it in production (the API key is meant to be injected - by your proxy).\\n- `account`: the account id.\\n- `state`: the publication - state of the Knowledge Box.\\n- `standalone`: set to `true` when using a standalone - NucliaDB instance.\\n- `proxy`: set to `true` when using a proxy to access - the Agentic RAG API.\\n- `mode`: set to `dark` to display the widget in dark - mode.\\n- `filters`: define the filters offered to the user in the search - bar among `labels`, `entities`, `created` and `labelFamilies`.\\n- `preselected_filters`: - define filters that will be applied by default to any query.\\n- `csspath`: - the path to the CSS file to use to customize the widget style.\\n- `prompt`: - the prompt to use for the generative model. It must use `{context}` and `{question}` - variables.\\n- `system_prompt`: the system prompt to use for the generative - model.\\n- `rephrase_prompt`: the prompt to use when optimizing the user query - to get the best search results.\\n- `generativemodel`: the generative model - to use for the answer generation.\\n- `rag_strategies`: the RAG strategies - to apply to the retrieved paragraphs.\\n- `rag_images_strategies`: the RAG - strategies to apply to the retrieved images.\\n- `not_enough_data_message`: - the message to display when there is not enough data to generate an answer.\\n- - `ask_to_resource`: the resource ID to use as context for the generative model.\\n- - `max_tokens`: the maximum number of input tokens to put in the final context - (including the prompt, the retrieved results and the user question).\\n- `max_output_tokens`: - the maximum number of tokens to generate.\\n- `max_paragraphs`: the maximum - number of paragraphs to pass in the context to the generative model (default: - 20).\\n- `query_prepend`: the hard-coded text to prepend to the user query.\\n- - `json_schema`: the JSON schema to use to get a JSON answer from the generative - model.\\n- `vectorset`: the embedding model to use for the semantic search.\\n- - `chat_placeholder`: the placeholder to display in the chat input.\\n- `audit_metadata`: - custom metatada to add in API calls for auditing purposes.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"8f3044c65d6a551153cea36353a2cdac\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: features \\n title: Features \\n \\n Widgets features \\n The Agentic - RAG widgets allows you to embed the Agentic RAG search experience directly - into your website or web application through a simple HTML snippet: \\n ```html - \\n \\n \\n \\n ``` \\n The easiest way to explore the different features - of the widgets is to use the Agentic RAG Dashboard in the Widgets section - and to play with the different options. \\n The Embed widget button will generate - the HTML snippet for you. \\n Widget types \\n There are 3 different types - of widgets: \\n \\n Embedded in page: the search input is embedded in a page - and the results are displayed under the input. Once the initial answer is - displayed, the user can click on Ask more to access the full chat interface. - Note: For the correct reading of the results, the width of the widget container - should not be less than 384px. \\n \\n Web components: \\n html \\n \\n \\n - \\n Chat mode: displays directly the full chat interface. \\n \\n Web component: - \\n html \\n \\n \\n Popup modal: the search inout and the results are displayed - in a popup modal. \\n \\n Web component: \\n html \\n \\n The features parameter - \\n The features parameter allows you to customize the behavior of the widget. - It is a comma-separated list of features among the following: \\n \\n filter: - display a filter dropdown in the search bar. \\n navigateToFile: open the - file in the browser when clicking on the result (by default, the file is displayed - in the viewer). \\n navigateToLink: open the link in the browser when clicking - on the result (by default, the link is displayed in the viewer). \\n permalink: - add the search query and criteria to the URL, allowing the widget to re-render - the same results upon loading. \\n relations: display an info card on the - right side of the widget listing all the relations of the entity mentioned - in the user query. \\n suggestions: display a list of suggested resource titles - matching the user input. \\n suggestLabels: display a list of suggestions - based on the labels when the user starts typing in the search bar. \\n autocompleteFromNERs: - display a list of suggestions based on the NERs extracted from the user query - when the user starts typing in the search bar. \\n displayMetadata: display - the metadata associated with the resource in the result rows. \\n answers: - trigger the answer generation process when the user makes a search. \\n hideResults: - hide the search results, only the generative answer will be displayed. \\n - hideThumbnails: hide the thumbnails associated with the resource in the result - rows. \\n displayFieldList: display a section listing all the fields of the - resource in the right sidebar of the viewer. This section is only visible - for resources containing multiple fields. \\n citations: include citations - in the generative answer. \\n rephrase: rephrase the user question in order - to optimize the quality of the search results. \\n debug: display extra buttons - to download the last request full log of the debug metadata returned by the - API. It must not be used in production. \\n preferMarkdown: require the generative - answer to be formatted in Markdown. \\n openNewTab: open the link in a new - tab when clicking on the result. \\n orFilterLogic: use the OR logic for filters - instead of the default AND logic. \\n noChatHistory: the previous questions - and answers in the chat mode will not be passed as context when generating - a new answer. \\n showHidden: display hidden resources in the search results. - \\n showAttachedImages: display images attached to the matching paragraphs - in the search results. \\n \\n Other parameters \\n \\n backend: the URL of - the backend to use. Useful if you use your own proxy to access the Agentic - RAG API. \\n zone: the zone to use. \\n knowledgebox: the Knowledge Box id. - \\n placeholder: the text displayed in the search bar when it is empty. \\n - lang: the language of the widget. Currently supported: ca, fr, en, es. Default: - en. \\n apikey: the API key to use. It is not recommended to use it in production - (the API key is meant to be injected by your proxy). \\n account: the account - id. \\n state: the publication state of the Knowledge Box. \\n standalone: - set to true when using a standalone NucliaDB instance. \\n proxy: set to true - when using a proxy to access the Agentic RAG API. \\n mode: set to dark to - display the widget in dark mode. \\n filters: define the filters offered to - the user in the search bar among labels, entities, created and labelFamilies. - \\n preselected_filters: define filters that will be applied by default to - any query. \\n csspath: the path to the CSS file to use to customize the widget - style. \\n prompt: the prompt to use for the generative model. It must use - {context} and {question} variables. \\n system_prompt: the system prompt to - use for the generative model. \\n rephrase_prompt: the prompt to use when - optimizing the user query to get the best search results. \\n generativemodel: - the generative model to use for the answer generation. \\n rag_strategies: - the RAG strategies to apply to the retrieved paragraphs. \\n rag_images_strategies: - the RAG strategies to apply to the retrieved images. \\n not_enough_data_message: - the message to display when there is not enough data to generate an answer. - \\n ask_to_resource: the resource ID to use as context for the generative - model. \\n max_tokens: the maximum number of input tokens to put in the final - context (including the prompt, the retrieved results and the user question). - \\n max_output_tokens: the maximum number of tokens to generate. \\n max_paragraphs: - the maximum number of paragraphs to pass in the context to the generative - model (default: 20). \\n query_prepend: the hard-coded text to prepend to - the user query. \\n json_schema: the JSON schema to use to get a JSON answer - from the generative model. \\n vectorset: the embedding model to use for the - semantic search. \\n chat_placeholder: the placeholder to display in the chat - input. \\n audit_metadata: custom metatada to add in API calls for auditing - purposes. \\n 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`number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L249)\\n\\n***\\n\\n### - line\\n\\n> **line**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L251)\\n\\n***\\n\\n### - text\\n\\n> **text**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L250)\\n\\n***\\n\\n### - width\\n\\n> **width**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L248)\\n\\n***\\n\\n### - x\\n\\n> **x**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L246)\\n\\n***\\n\\n### - y\\n\\n> **y**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"e72ffebe78398e6654aceec2addfd240\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n - Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 - \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 - \\n \\n text \\n \\n text: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:250 - \\n \\n width \\n \\n width: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:248 - \\n \\n x \\n \\n x: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:246 - \\n \\n y \\n \\n y: number \\n \\n Defined in \\n 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- > develop > js sdk > interfaces > PageToken\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > PageToken\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\":{\"score\":0.599377453327179,\"score_type\":\"VECTOR\",\"order\":17,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n - Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 - \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 - \\n \\n text \\n \\n\",\"id\":\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":299,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"220eb37c167f4eb9bb8e9454e7ba8cf5\":{\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5\",\"slug\":\"docs-develop-python-sdk-05-search-md\",\"title\":\"docs - > develop > python sdk > 05 search\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:48:33.723913\",\"modified\":\"2026-06-09T08:08:04.866092\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/python-sdk/search\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"# - Search and answer generation\\n\\n## Search\\n\\nNuclia supports 2 different - search endpoints:\\n\\n- `search`: returns several result sets according the - different search techniques (full-text, fuzzy, semantic).\\n- `find`: returns - a single result set where all different results are merged into a hierarchical - structure.\\n\\nBoth endpoints support the same query parameters.\\n\\n- CLI:\\n\\n - \ ```bash\\n nuclia kb search search --query=\\\"My search\\\"\\n nuclia - kb search find --query=\\\"My search\\\" --filters=\\\"['/icon/application/pdf','/classification.labels/region/Asia']\\\"\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n search = - sdk.NucliaSearch()\\n search.search(query=\\\"My search\\\", filters=['/icon/application/pdf', - '/classification.labels/region/Asia'])\\n search.find(query=\\\"My search\\\")\\n - \ ```\\n\\nGet JSON output:\\n\\n```bash\\nnuclia kb search find --query=\\\"My - search\\\" --json\\n```\\n\\nGet YAML output:\\n\\n```bash\\nnuclia kb search - search --query=\\\"My search\\\" --yaml\\n```\\n\\n## Generative answer\\n\\nBased - on a `find` request, Nuclia uses a generative AI to answer the question based - on the context without hallucinations and with the find result and relations.\\n\\n- - CLI:\\n\\n ```bash\\n nuclia kb search ask --query=\\\"My question\\\"\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n search = - sdk.NucliaSearch()\\n search.ask(query=\\\"My question\\\")\\n ```\\n\\n - \ You can also use the `AskRequest` item to configure the request with all - the parameters supported:\\n\\n ```python\\n from nuclia import sdk\\n from - nucliadb_models.search import AskRequest\\n\\n search = sdk.NucliaSearch()\\n - \ query = AskRequest(query=\\\"My question\\\", prefer_markdown=True, citations=True)\\n - \ search.ask(query=query)\\n ```\\n\\n### Reasoning\\n\\nSome LLMs support - reasoning. In some models, reasoning is enabled by default, while in others - it must be explicitly requested. You can control this behavior using the reasoning - parameter.\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n from - nucliadb_models.search import AskRequest, Reasoning\\n\\n search = sdk.NucliaSearch()\\n - \ query = AskRequest(\\n query=\\\"My question with extra reasoning effort\\\",\\n - \ max_tokens=5000,\\n reasoning=Reasoning(\\n display=True, # - Show reasoning in the response\\n effort=\\\"low\\\", # Can be - \\\"low\\\", \\\"medium\\\", or \\\"high\\\"\\n budget_tokens=1024 - # How many tokens reasoning can use\\n ),\\n )\\n search.ask(query=query)\\n - \ ```\\n\\nModel Support for Reasoning Options:\\n\\n* **OpenAI models** \u2192 - support `effort` only.\\n* **Google & Anthropic models** \u2192 support `budget_tokens` - only.\\n\\n:::tip\\nIf you send just one of these values (`effort` or `budget_tokens`), - Nuclia will automatically fill in the other for you.\\n:::\\n\\n:::warning\\n* - Enabling reasoning can use additional tokens, which may increase your usage - costs.\\n* You may need to increase `max_tokens` to give the LLM enough room - to reason and generate an answer.\\n:::\\n\\n## Filtering\\n\\nAny endpoint - that involves search (`search`, `find` and `ask`) also support more advanced - filtering expressions. Expressions can have one of the following operators:\\n\\n- - `all`: this is the default. Will make search return results containing all - specified filter labels.\\n- `any`: returns results containing at least one - of the labels.\\n- `none`: returns results that do not contain any of the - labels.\\n- `not_all`: returns results that do not contain all specified labels.\\n\\nNote - that multiple expressions can be chained in the `filters` parameter and the - conjunction of all of them will be computed.\\n\\nHere are some examples:\\n\\n- - CLI:\\n\\n ```bash\\n nuclia kb search find --query=\\\"My search\\\" --filters=\\\"[{'any':['/icon/application/pdf','/icon/image/mp4']}]\\\"\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n from nucliadb_models.search - import Filter\\n\\n search = sdk.NucliaSearch()\\n search.ask(\\n query=\\\"My - question\\\",\\n filters=[Filter(any=['/classification.labels/region/Europe','/classification.labels/region/Asia'])],\\n - \ )\\n ```\\n\\n## Using RAG strategies\\n\\nRAG strategies can be used to - improve the quality of the answers by extending the search results passed - to the LLM as context.\\n\\n- CLI:\\n\\n ```bash\\n nuclia kb search ask - --query=\\\"My question\\\" --rag_strategies='[{\\\"name\\\":\\\"hierarchy\\\"}]'\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n search = - sdk.NucliaSearch()\\n search.ask(query=\\\"My question\\\", rag_strategies=[{\\\"name\\\": - \\\"hierarchy\\\"}])\\n ```\\n\\nSee the [RAG strategies documentation](https://docs.rag.progress.cloud/docs/rag/rag-strategy) - for more information.\\n\\n## Complex queries\\n\\nThe Python SDK allows to - use all the options supported by the `/find` and `/ask` endpoints,\\nbut not - all of the options can be passed as specific parameter.\\nIn these cases, - you can just pass your query as a dictionnary in the `query` parameter.\\n\\n- - CLI:\\n\\n ```bash\\n nuclia kb search find --query='{\\\"query\\\": \\\"My - search\\\", \\\"filters\\\": [\\\"/icon/application/pdf\\\", \\\"/classification.labels/region/Asia\\\"]}'\\n - \ nuclia kb search ask --query='{\\\"query\\\": \\\"My search\\\",\\\"top_k\\\": - 5}'\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n search - = sdk.NucliaSearch()\\n search.find(query={\\\"query\\\": \\\"My search\\\", - \\\"filters\\\": [\\\"/icon/application/pdf\\\", \\\"/classification.labels/region/Asia\\\"]})\\n - \ search.ask(query={\\\"query\\\": \\\"My search\\\",\\\"top_k\\\": 5})\\n - \ ```\\n\\n## Graph queries\\n\\nThe Python SDK allows graph queries supported - by the `/graph` endpoint. Although\\na bit cumbersome, the knowledge graph - can be queried as in this example:\\n\\n- CLI:\\n\\n ```bash\\n nuclia kb - search graph --query='{\\\"query\\\": {\\\"prop\\\": \\\"path\\\", \\\"source\\\": - {\\\"value\\\": \\\"Rust\\\"}, \\\"destination\\\": {\\\"value\\\": \\\"Python\\\"}}}'\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n search = - sdk.NucliaSearch()\\n search.graph(\\n query={\\n \\\"query\\\": - {\\n \\\"prop\\\": \\\"path\\\",\\n \\\"source\\\": - {\\\"value\\\": \\\"Rust\\\"},\\n \\\"destination\\\": {\\\"value\\\": - \\\"Python\\\"}\\n }\\n }\\n )\\n ```\\n\\nFor more information - about graph querying, please refer to [Nuclia's graph\\ndoc](https://docs.rag.progress.cloud/docs/rag/advanced/graph) - or the [API reference](https://docs.rag.progress.cloud/docs/api#tag/Search/operation/graph_search_knowledgebox_kb__kbid__graph_post)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"57ed2bd023399aee08015a57a948ebf2\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"Search - and answer generation \\n Search \\n Nuclia supports 2 different search endpoints: - \\n \\n search: returns several result sets according the different search - techniques (full-text, fuzzy, semantic). \\n find: returns a single result - set where all different results are merged into a hierarchical structure. - \\n \\n Both endpoints support the same query parameters. \\n \\n CLI: \\n - \\n bash \\n nuclia kb search search --query= My search \\n nuclia kb search - find --query= My search --filters= ['/icon/application/pdf','/classification.labels/region/Asia'] - \\n \\n SDK: \\n \\n python \\n from nuclia import sdk \\n search = sdk.NucliaSearch() - \\n search.search(query= My search , filters=['/icon/application/pdf', '/classification.labels/region/Asia']) - \\n search.find(query= My search ) \\n Get JSON output: \\n bash \\n nuclia - kb search find --query= My search --json \\n Get YAML output: \\n bash \\n - nuclia kb search search --query= My search --yaml \\n Generative answer \\n - Based on a find request, Nuclia uses a generative AI to answer the question - based on the context without hallucinations and with the find result and relations. - \\n \\n CLI: \\n \\n bash \\n nuclia kb search ask --query= My question \\n - \\n SDK: \\n \\n python \\n from nuclia import sdk \\n search = sdk.NucliaSearch() - \\n search.ask(query= My question ) \\n You can also use the AskRequest item - to configure the request with all the parameters supported: \\n ```python - \\n from nuclia import sdk \\n from nucliadb_models.search import AskRequest - \\n search = sdk.NucliaSearch() \\n query = AskRequest(query= My question - , prefer_markdown=True, citations=True) \\n search.ask(query=query) \\n ``` - \\n Reasoning \\n Some LLMs support reasoning. In some models, reasoning is - enabled by default, while in others it must be explicitly requested. You can - control this behavior using the reasoning parameter. \\n \\n SDK: \\n \\n - ```python \\n from nuclia import sdk \\n from nucliadb_models.search import - AskRequest, Reasoning \\n search = sdk.NucliaSearch() \\n query = AskRequest( - \\n query= My question with extra reasoning effort , \\n max_tokens=5000, - \\n reasoning=Reasoning( \\n display=True, # Show reasoning in the response - \\n effort= low , # Can be low , medium , or high \\n budget_tokens=1024 # - How many tokens reasoning can use \\n ), \\n ) \\n search.ask(query=query) - \\n ``` \\n Model Support for Reasoning Options: \\n \\n OpenAI models \u2192 - support effort only. \\n Google & Anthropic models \u2192 support budget_tokens - only. \\n \\n :::tip \\n If you send just one of these values (effort or budget_tokens), - Nuclia will automatically fill in the other for you. \\n ::: \\n :::warning - \\n Enabling reasoning can use additional tokens, which may increase your - usage costs. \\n You may need to increase max_tokens to give the LLM enough - room to reason and generate an answer. \\n ::: \\n Filtering \\n Any endpoint - that involves search (search, find and ask) also support more advanced filtering - expressions. Expressions can have one of the following operators: \\n \\n - all: this is the default. Will make search return results containing all specified - filter labels. \\n any: returns results containing at least one of the labels. - \\n none: returns results that do not contain any of the labels. \\n not_all: - returns results that do not contain all specified labels. \\n \\n Note that - multiple expressions can be chained in the filters parameter and the conjunction - of all of them will be computed. \\n Here are some examples: \\n \\n CLI: - \\n \\n bash \\n nuclia kb search find --query= My search --filters= [{'any':['/icon/application/pdf','/icon/image/mp4']}] - \\n \\n SDK: \\n \\n ```python \\n from nuclia import sdk \\n from nucliadb_models.search - import Filter \\n search = sdk.NucliaSearch() \\n search.ask( \\n query= My - question , \\n filters=[Filter(any=['/classification.labels/region/Europe','/classification.labels/region/Asia'])], - \\n ) \\n ``` \\n Using RAG strategies \\n RAG strategies can be used to improve - the quality of the answers by extending the search results passed to the LLM - as context. \\n \\n CLI: \\n \\n bash \\n nuclia kb search ask --query= My - question --rag_strategies='[{ name : hierarchy }]' \\n \\n SDK: \\n \\n python - \\n from nuclia import sdk \\n search = sdk.NucliaSearch() \\n search.ask(query= - My question , rag_strategies=[{ name : hierarchy }]) \\n See the RAG strategies - documentation for more information. \\n Complex queries \\n The Python SDK - allows to use all the options supported by the /find and /ask endpoints, \\n - but not all of the options can be passed as specific parameter. \\n In these - cases, you can just pass your query as a dictionnary in the query parameter. - \\n \\n CLI: \\n \\n bash \\n nuclia kb search find --query='{ query : My - search , filters : [ /icon/application/pdf , /classification.labels/region/Asia - ]}' \\n nuclia kb search ask --query='{ query : My search , top_k : 5}' \\n - \\n SDK: \\n \\n python \\n from nuclia import sdk \\n search = sdk.NucliaSearch() - \\n search.find(query={ query : My search , filters : [ /icon/application/pdf - , /classification.labels/region/Asia ]}) \\n search.ask(query={ query : My - search , top_k : 5}) \\n Graph queries \\n The Python SDK allows graph queries - supported by the /graph endpoint. Although \\n a bit cumbersome, the knowledge - graph can be queried as in this example: \\n \\n CLI: \\n \\n bash \\n nuclia - kb search graph --query='{ query : { prop : path , source : { value : Rust - }, destination : { value : Python }}}' \\n \\n SDK: \\n \\n python \\n from - nuclia import sdk \\n search = sdk.NucliaSearch() \\n search.graph( \\n query={ - \\n query : { \\n prop : path , \\n source : { value : Rust }, \\n destination - : { value : Python } \\n } \\n } \\n ) \\n For more information about graph - querying, please refer to Nuclia's graph \\n doc or the API 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- > develop > python sdk > 05 search\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > python sdk > 05 search\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\":{\"score\":0.6185709238052368,\"score_type\":\"VECTOR\",\"order\":7,\"text\":\" - \\n SDK: \\n \\n ```python \\n from nuclia import sdk \\n from nucliadb_models.search - import AskRequest, Reasoning \\n search = sdk.NucliaSearch() \\n query = AskRequest( - \\n query= My question with extra reasoning effort , \\n max_tokens=5000, - \\n reasoning=Reasoning( \\n display=True, # Show reasoning in the response - \\n effort= low , # Can be low , medium , or high \\n budget_tokens=1024 # - How many tokens reasoning can use \\n ), \\n ) \\n search.ask(query=query) - \\n ``` \\n Model Support for Reasoning Options: \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":6,\"start\":1790,\"end\":2276,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\":{\"score\":0.5997583270072937,\"score_type\":\"VECTOR\",\"order\":16,\"text\":\" - ::: \\n :::warning \\n Enabling reasoning can use additional tokens, which - may increase your usage costs. \\n You may need to increase max_tokens to - give the LLM enough room to reason and generate an answer. \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":8,\"start\":2505,\"end\":2709,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"44d05174f1954331b62f5e4026f2b01a\":{\"id\":\"44d05174f1954331b62f5e4026f2b01a\",\"slug\":\"docs-develop-python-sdk-14-rao-md\",\"title\":\"docs - > develop > python sdk > 14 rao\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-22T13:38:09.919472\",\"modified\":\"2026-06-09T08:08:04.176136\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/python-sdk/rao\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"# - Retrieval Agents Orchestrator\\n\\nInteract with Nuclia's Retrieval Agents - Orchestrator to have intelligent conversations over several knowledge sources - with persistent session management and real-time streaming responses.\\n\\n## - Prerequisites\\n\\nInstall the Nuclia SDK:\\n\\n```sh\\npip install nuclia\\n```\\n\\nEnsure - you have:\\n- A valid Nuclia authentication token (see [Authentication](02-auth.md))\\n- - Access to a configured Retrieval Agent\\n\\n## Overview\\n\\nThe nuclia.py - library provides several ways to interact with your Retrieval Agents Orchestrators:\\n\\n- - **Interactive CLI**: A rich, user-friendly terminal interface (recommended)\\n- - **Standard CLI**: Direct access to raw websocket messages for debugging\\n- - **Session Management**: Create and manage persistent conversation sessions\\n- - **Programmatic API**: Python SDK for building custom applications\\n\\n\\n## - Listing Available Agents\\n\\nDiscover what Retrieval Agents Orchestrators - you have access to.\\n\\n- CLI:\\n\\n ```sh\\n nuclia agents list\\n ```\\n\\n- - SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n - \ agents = NucliaAgents()\\n all_agents = agents.list()\\n\\n for agent - in all_agents:\\n print(f\\\"Agent: {agent.title} ({agent.id})\\\")\\n - \ print(f\\\" Slug: {agent.slug}\\\")\\n print(f\\\" Zone: {agent.zone}\\\")\\n - \ ```\\n\\n### Getting a Specific Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia - agents get --account=\\\"my-account\\\" --id=\\\"agent-uuid\\\" --zone=\\\"europe-1\\\"\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n - \ agents = NucliaAgents()\\n agent_details = agents.get(\\n account=\\\"my-account\\\",\\n - \ id=\\\"agent-uuid\\\",\\n zone=\\\"europe-1\\\"\\n )\\n print(agent_details)\\n - \ ```\\n\\n### Setting a Default Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia - agents default [AGENT_SLUG or AGENT_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n - \ from nuclia.sdk.agents import NucliaAgents\\n\\n agents = NucliaAgents()\\n - \ agents.default(\\\"my-agent\\\")\\n ```\\n\\nThis sets the default agent - for all subsequent operations.\\n\\n## Interactive CLI (Recommended)\\n\\nThe - interactive CLI provides a beautiful, real-time interface for conversing with - your Retrieval Agents Orchestrator.\\n\\n### Starting the Interactive CLI\\n\\n- - CLI:\\n\\n ```sh\\n nuclia agent cli interact\\n ```\\n\\n- SDK:\\n\\n - \ ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n - \ agent.cli.interact()\\n ```\\n\\nThis launches an interactive terminal - session where you can:\\n- Ask questions and see streaming responses\\n- View - processing steps in real-time\\n- Manage conversation sessions\\n- See retrieved - context and citations\\n\\n### Interactive CLI Commands\\n\\nThe CLI supports - several commands (prefix with `/`):\\n\\n| Command | Description |\\n|---------|-------------|\\n| - `/help` | Show available commands |\\n| `/new_session` | Create a new persistent - session |\\n| `/list_sessions` | List all your sessions |\\n| `/change_session` - | Switch to a different session, use 'ephemeral' for a temporary session |\\n| - `/clear` | Clear the screen |\\n| `/exit` | Exit the CLI |\\n\\nPlease note - that all commands related to sessions require a Retrieval Agent Orchestrator - with the option **Agent with memory** enabled during creation.\\n\\n## Session - Management\\n\\nSessions allow you to maintain conversation context across - multiple interactions.\\n\\n> This feature will only be available if you checked - **Agent with memory** during the creation of your Retrieval Agents Orchestrator.\\n\\n### - Creating a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent session new --name=\\\"My - Research Session\\\"\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent - import NucliaAgent\\n\\n agent = NucliaAgent()\\n session_uuid = agent.session.new(\\\"My - Research Session\\\")\\n print(f\\\"Created session: {session_uuid}\\\")\\n - \ ```\\n\\n### Listing Sessions\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent - session list\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent - import NucliaAgent\\n\\n agent = NucliaAgent()\\n sessions = agent.session.list()\\n - \ for session in sessions.resources:\\n print(f\\\"{session.title}: {session.id}\\\")\\n - \ ```\\n\\n### Getting a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent - session get --session_uuid=[SESSION_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n - \ from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n - \ session = agent.session.get(session_uuid)\\n print(f\\\"Session: {session.title}\\\")\\n - \ print(f\\\"Created: {session.created}\\\")\\n ```\\n\\n### Deleting a Session\\n\\n- - CLI:\\n\\n ```sh\\n nuclia agent session delete --session_uuid=[SESSION_UUID]\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n - \ agent = NucliaAgent()\\n agent.session.delete(session_uuid)\\n ```\\n\\n## - Interaction\\n\\nAside from the interactive CLI, you can interact with your - Retrieval Agents Orchestrator with the simple CLI or programmatically using - the SDK.\\n\\n### Basic Interaction\\n\\n\\n**CLI:**\\n```bash\\nnuclia agent - interact \\\"What is Eric known for?\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate - over streaming responses\\nfor response in agent.interact(\\n question=\\\"What - is Eric known for?\\\"\\n):\\n if response.operation == \\\"ANSWER\\\" - and response.answer:\\n print(response.answer)\\n elif response.step:\\n - \ print(f\\\"Processing: {response.step.module}\\\")\\n```\\n\\nNot - supplying a `session_uuid` when calling `interact` will use an ephemeral session - by default. To maintain context, provide a persistent session UUID.\\n\\n### - Using Persistent Sessions\\n\\n**CLI:**\\n```bash\\nnuclia agent sessions - new \\\"Customer Support Chat\\\"\\n# Note the session UUID returned\\nnuclia - agent interact \\\"What are your business hours?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\nnuclia - agent interact \\\"Are you open on weekends?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Create - a session\\nsession_uuid = agent.session.new(\\\"Customer Support Chat\\\")\\n\\n# - Have a conversation with context\\nfor response in agent.interact(\\n session_uuid=session_uuid,\\n - \ question=\\\"What are your business hours?\\\"\\n):\\n if response.answer:\\n - \ print(response.answer)\\n\\n# Follow-up question maintains context\\nfor - response in agent.interact(\\n session_uuid=session_uuid,\\n question=\\\"Are - you open on weekends?\\\"\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\n## - Understanding Response Types\\n\\nWhen interacting with an agent, you receive - a stream of `AragAnswer` objects with different operations:\\n\\n| Operation - | Description |\\n|-----------|-------------|\\n| `START` | Interaction has - begun |\\n| `ANSWER` | Processing step or partial answer |\\n| `DONE` | Interaction - complete |\\n| `ERROR` | An error occurred |\\n| `AGENT_REQUEST` | Agent needs - user feedback |\\n\\n### Response Attributes\\n\\nEach response may contain:\\n\\n- - **`step`**: Information about the current processing step\\n - `module`: - The module being executed (e.g., \\\"rephrase\\\", \\\"basic_ask\\\", \\\"remi\\\")\\n - \ - `title`: Display title for the step\\n - `value`: Result of the step\\n - \ - `reason`: Explanation for the step\\n - `timeit`: Time taken in seconds\\n - \ - `input_nuclia_tokens`/`output_nuclia_tokens`: Token usage\\n\\n- **`context`**: - Retrieved context from the knowledge base\\n - `chunks`: List of retrieved - text chunks with sources\\n - `summary`: Summary of the context or partial - answer\\n\\n- **`answer`**: The final answer text (Markdown formatted)\\n\\n- - **`generated_text`**: Intermediate generated text\\n\\n- **`possible_answer`**: - Alternative answer being considered\\n\\n- **`exception`**: Error details - if something went wrong\\n\\n### Processing Responses\\n\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\nfrom nuclia_models.agent.interaction - import AnswerOperation\\n\\nagent = NucliaAgent()\\n\\nfor response in agent.interact(question=\\\"Tell - me about AI\\\"):\\n if response.operation == AnswerOperation.START:\\n - \ print(\\\"Starting...\\\")\\n \\n elif response.step:\\n print(f\\\"Step: - {response.step.module} ({response.step.timeit:.2f}s)\\\")\\n \\n elif - response.context:\\n print(f\\\"Retrieved {len(response.context.chunks)} - chunks\\\")\\n for chunk in response.context.chunks:\\n print(f\\\" - \ - {chunk.title}: {chunk.text[:100]}...\\\")\\n \\n elif response.answer:\\n - \ print(f\\\"\\\\nFinal Answer:\\\\n{response.answer}\\\")\\n \\n - \ elif response.operation == AnswerOperation.DONE:\\n print(\\\"Complete!\\\")\\n - \ \\n elif response.operation == AnswerOperation.ERROR:\\n print(f\\\"Error: - {response.exception.detail if response.exception else 'Unknown'}\\\")\\n```\\n\\n## - Standard CLI for Raw Messages\\n\\nFor debugging or advanced use cases, you - can access raw websocket messages programmatically:\\n\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate - over all messages\\nfor message in agent.interact(\\n question=\\\"What - is RAO?\\\"\\n):\\n # message is an AragAnswer object with all raw data\\n - \ print(f\\\"Operation: {message.operation}\\\")\\n print(f\\\"Raw message: - {message.model_dump_json(indent=2)}\\\")\\n```\\n\\nThis gives you direct - access to all websocket message data for debugging or custom processing.\\n\\n## - Advanced Features\\n\\n### Agent Feedback Requests\\n\\nAgents can request - additional input from users during processing:\\n\\n```python\\nfrom nuclia.sdk.agent - import NucliaAgent\\nfrom nuclia_models.agent.interaction import AnswerOperation\\n\\nagent - = NucliaAgent()\\ngenerator = agent.interact(question=\\\"Help me with X\\\")\\n\\nfor - response in generator:\\n if response.operation == AnswerOperation.AGENT_REQUEST:\\n - \ # Agent is requesting user input\\n user_input = input(f\\\"Agent - asks: {response.feedback.question}\\\\n> \\\")\\n # Send response back\\n - \ generator.send(user_input)\\n elif response.answer:\\n print(response.answer)\\n```\\n\\n### - Error Handling\\n\\n```python\\nfrom nuclia.sdk.agent import NucliaAgent\\nfrom - nuclia.exceptions import RaoAPIException\\n\\nagent = NucliaAgent()\\n\\ntry:\\n - \ for response in agent.interact(question=\\\"Hello?\\\"):\\n if - response.exception:\\n print(f\\\"Agent error: {response.exception.detail}\\\")\\n - \ elif response.answer:\\n print(response.answer)\\nexcept - RaoAPIException as e:\\n print(f\\\"API error: {e.detail}\\\")\\nexcept - Exception as e:\\n print(f\\\"Unexpected error: {e}\\\")\\n```\\n\\n### - Passing Custom Headers to MCP\\n\\nIf your Retrieval Agents Orchestrator requires - custom headers for MCP Agents, you can pass them as follows:\\n\\n**CLI:**\\n```bash\\nnuclia - agent interact \\\"What is AI?\\\" --headers '{\\\"X-Custom-Header\\\": \\\"value\\\"}'\\n```\\n\\n**SDK:**\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\nfor response - in agent.interact(\\n question=\\\"What is AI?\\\",\\n headers={\\\"X-Custom-Header\\\": - \\\"value\\\"}\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\nPlease - ensure that the 'Allowed Headers' configuration in your MCP agent includes - any custom headers you wish to use.\\n\\n## Best Practices\\n\\n1. **Use Sessions - for Context**: Create sessions when you need multi-turn conversations with - context retention\\n2. **Use Ephemeral Sessions for One-offs**: Don't supply - a session UUID for using agents in a stateless manner.\\n3. **Stream for UX**: - Process responses as they arrive for better user experience\\n4. **Handle - All Operations**: Check for different operation types (START, ANSWER, DONE, - ERROR) when processing responses\\n5. **Clean Up Sessions**: Delete sessions - when done to avoid clutter\\n6. **Use Interactive CLI**: For manual testing - and exploration, the interactive CLI provides the best experience\\n\",\"format\":\"MARKDOWN\",\"md5\":\"bbaaf8cccd2b664ba4f7daf47d1f2bf4\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"Retrieval - Agents Orchestrator \\n Interact with Nuclia's Retrieval Agents Orchestrator - to have intelligent conversations over several knowledge sources with persistent - session management and real-time streaming responses. \\n Prerequisites \\n - Install the Nuclia SDK: \\n sh \\n pip install nuclia \\n Ensure you have: - \\n - A valid Nuclia authentication token (see Authentication) \\n - Access - to a configured Retrieval Agent \\n Overview \\n The nuclia.py library provides - several ways to interact with your Retrieval Agents Orchestrators: \\n \\n - Interactive CLI: A rich, user-friendly terminal interface (recommended) \\n - Standard CLI: Direct access to raw websocket messages for debugging \\n Session - Management: Create and manage persistent conversation sessions \\n Programmatic - API: Python SDK for building custom applications \\n \\n Listing Available - Agents \\n Discover what Retrieval Agents Orchestrators you have access to. - \\n \\n CLI: \\n \\n sh \\n nuclia agents list \\n \\n SDK: \\n \\n ```python - \\n from nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() - \\n all_agents = agents.list() \\n for agent in all_agents: \\n print(f Agent: - {agent.title} ({agent.id}) ) \\n print(f Slug: {agent.slug} ) \\n print(f - Zone: {agent.zone} ) \\n ``` \\n Getting a Specific Agent \\n \\n CLI: \\n - \\n sh \\n nuclia agents get --account= my-account --id= agent-uuid --zone= - europe-1 \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agents import - NucliaAgents \\n agents = NucliaAgents() \\n agent_details = agents.get( \\n - account= my-account , \\n id= agent-uuid , \\n zone= europe-1 \\n ) \\n print(agent_details) - \\n ``` \\n Setting a Default Agent \\n \\n CLI: \\n \\n sh \\n nuclia agents - default [AGENT_SLUG or AGENT_UUID] \\n \\n SDK: \\n \\n ```python \\n from - nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() \\n agents.default( - my-agent ) \\n ``` \\n This sets the default agent for all subsequent operations. - \\n Interactive CLI (Recommended) \\n The interactive CLI provides a beautiful, - real-time interface for conversing with your Retrieval Agents Orchestrator. - \\n Starting the Interactive CLI \\n \\n CLI: \\n \\n sh \\n nuclia agent - cli interact \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import - NucliaAgent \\n agent = NucliaAgent() \\n agent.cli.interact() \\n ``` \\n - This launches an interactive terminal session where you can: \\n - Ask questions - and see streaming responses \\n - View processing steps in real-time \\n - - Manage conversation sessions \\n - See retrieved context and citations \\n - Interactive CLI Commands \\n The CLI supports several commands (prefix with - /): \\n | Command | Description | \\n |---------|-------------| \\n | /help - | Show available commands | \\n | /new_session | Create a new persistent session - | \\n | /list_sessions | List all your sessions | \\n | /change_session | - Switch to a different session, use 'ephemeral' for a temporary session | \\n - | /clear | Clear the screen | \\n | /exit | Exit the CLI | \\n Please note - that all commands related to sessions require a Retrieval Agent Orchestrator - with the option Agent with memory enabled during creation. \\n Session Management - \\n Sessions allow you to maintain conversation context across multiple interactions. - \\n \\n This feature will only be available if you checked Agent with memory - during the creation of your Retrieval Agents Orchestrator. \\n \\n Creating - a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session new --name= My - Research Session \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent - import NucliaAgent \\n agent = NucliaAgent() \\n session_uuid = agent.session.new( - My Research Session ) \\n print(f Created session: {session_uuid} ) \\n ``` - \\n Listing Sessions \\n \\n CLI: \\n \\n sh \\n nuclia agent session list - \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import NucliaAgent - \\n agent = NucliaAgent() \\n sessions = agent.session.list() \\n for session - in sessions.resources: \\n print(f {session.title}: {session.id} ) \\n ``` - \\n Getting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session get - --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent - import NucliaAgent \\n agent = NucliaAgent() \\n session = agent.session.get(session_uuid) - \\n print(f Session: {session.title} ) \\n print(f Created: {session.created} - ) \\n ``` \\n Deleting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent - session delete --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python - \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n - agent.session.delete(session_uuid) \\n ``` \\n Interaction \\n Aside from - the interactive CLI, you can interact with your Retrieval Agents Orchestrator - with the simple CLI or programmatically using the SDK. \\n Basic Interaction - \\n CLI: \\n bash \\n nuclia agent interact What is Eric known for? \\n SDK: - \\n ```python \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() - \\n Iterate over streaming responses \\n for response in agent.interact( \\n - question= What is Eric known for? \\n ): \\n if response.operation == ANSWER - and response.answer: \\n print(response.answer) \\n elif response.step: \\n - print(f Processing: {response.step.module} ) \\n ``` \\n Not supplying a session_uuid - when calling interact will use an ephemeral session by default. To maintain - context, provide a persistent session UUID. \\n Using Persistent Sessions - \\n CLI: \\n ```bash \\n nuclia agent sessions new Customer Support Chat \\n - Note the session UUID returned \\n nuclia agent interact What are your business - hours? --session_uuid= SESSION_UUID \\n nuclia agent interact Are you open - on weekends? --session_uuid= SESSION_UUID \\n ``` \\n SDK: \\n ```python \\n - from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n Create - a session \\n session_uuid = agent.session.new( Customer Support Chat ) \\n - Have a conversation with context \\n for response in agent.interact( \\n session_uuid=session_uuid, - \\n question= What are your business hours? \\n ): \\n if response.answer: - \\n print(response.answer) \\n Follow-up question maintains context \\n for - response in agent.interact( \\n session_uuid=session_uuid, \\n question= Are - you open on weekends? \\n ): \\n if response.answer: \\n print(response.answer) - \\n ``` \\n Understanding Response Types \\n When interacting with an agent, - you receive a stream of AragAnswer objects with different operations: \\n - | Operation | Description | \\n |-----------|-------------| \\n | START | - Interaction has begun | \\n | ANSWER | Processing step or partial answer | - \\n | DONE | Interaction complete | \\n | ERROR | An error occurred | \\n - | AGENT_REQUEST | Agent needs user feedback | \\n Response Attributes \\n - Each response may contain: \\n \\n step: Information about the current processing - step \\n module: The module being executed (e.g., rephrase , basic_ask , remi - ) \\n title: Display title for the step \\n value: Result of the step \\n - reason: Explanation for the step \\n timeit: Time taken in seconds \\n \\n - input_nuclia_tokens/output_nuclia_tokens: Token usage \\n \\n \\n context: - Retrieved context from the knowledge base \\n \\n chunks: List of retrieved - text chunks with sources \\n \\n summary: Summary of the context or partial - answer \\n \\n \\n answer: The final answer text (Markdown formatted) \\n - \\n \\n generated_text: Intermediate generated text \\n \\n \\n possible_answer: - Alternative answer being considered \\n \\n \\n exception: Error details if - something went wrong \\n \\n \\n Processing Responses \\n ```python \\n from - nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction - import AnswerOperation \\n agent = NucliaAgent() \\n for response in agent.interact(question= - Tell me about AI ): \\n if response.operation == AnswerOperation.START: \\n - print( Starting... ) \\n elif response.step: \\n print(f Step: {response.step.module} - ({response.step.timeit:.2f}s) ) \\n \\n elif response.context: \\n print(f - Retrieved {len(response.context.chunks)} chunks ) \\n for chunk in response.context.chunks: - \\n print(f - {chunk.title}: {chunk.text[:100]}... ) \\n \\n elif response.answer: - \\n print(f \\\\nFinal Answer:\\\\n{response.answer} ) \\n \\n elif response.operation - == AnswerOperation.DONE: \\n print( Complete! ) \\n \\n elif response.operation - == AnswerOperation.ERROR: \\n print(f Error: {response.exception.detail if - response.exception else 'Unknown'} ) \\n \\n ``` \\n Standard CLI for Raw - Messages \\n For debugging or advanced use cases, you can access raw websocket - messages programmatically: \\n ```python \\n from nuclia.sdk.agent import - NucliaAgent \\n agent = NucliaAgent() \\n Iterate over all messages \\n for - message in agent.interact( \\n question= What is RAO? \\n ): \\n # message - is an AragAnswer object with all raw data \\n print(f Operation: {message.operation} - ) \\n print(f Raw message: {message.model_dump_json(indent=2)} ) \\n ``` \\n - This gives you direct access to all websocket message data for debugging or - custom processing. \\n Advanced Features \\n Agent Feedback Requests \\n Agents - can request additional input from users during processing: \\n ```python \\n - from nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction - import AnswerOperation \\n agent = NucliaAgent() \\n generator = agent.interact(question= - Help me with X ) \\n for response in generator: \\n if response.operation - == AnswerOperation.AGENT_REQUEST: \\n # Agent is requesting user input \\n - user_input = input(f Agent asks: {response.feedback.question}\\\\n> ) \\n - # Send response back \\n generator.send(user_input) \\n elif response.answer: - \\n print(response.answer) \\n ``` \\n Error Handling \\n ```python \\n from - nuclia.sdk.agent import NucliaAgent \\n from nuclia.exceptions import RaoAPIException - \\n agent = NucliaAgent() \\n try: \\n for response in agent.interact(question= - Hello? ): \\n if response.exception: \\n print(f Agent error: {response.exception.detail} - ) \\n elif response.answer: \\n print(response.answer) \\n except RaoAPIException - as e: \\n print(f API error: {e.detail} ) \\n except Exception as e: \\n print(f - Unexpected error: {e} ) \\n ``` \\n Passing Custom Headers to MCP \\n If your - Retrieval Agents Orchestrator requires custom headers for MCP Agents, you - can pass them as follows: \\n CLI: \\n bash \\n nuclia agent interact What - is AI? --headers '{ X-Custom-Header : value }' \\n SDK: \\n ```python \\n - from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n for - response in agent.interact( \\n question= What is AI? , \\n headers={ X-Custom-Header - : value } \\n ): \\n if response.answer: \\n print(response.answer) \\n ``` - \\n Please ensure that the 'Allowed Headers' configuration in your MCP agent - includes any custom headers you wish to use. \\n Best Practices \\n \\n Use - Sessions for Context: Create sessions when you need multi-turn conversations - with context retention \\n Use Ephemeral Sessions for One-offs: Don't supply - a session UUID for using agents in a stateless manner. \\n Stream for UX: - Process responses as they arrive for better user experience \\n Handle All - Operations: Check for different operation types (START, ANSWER, DONE, ERROR) - when processing responses \\n Clean Up Sessions: Delete sessions when done - to avoid clutter \\n Use Interactive CLI: For manual testing and exploration, - the interactive CLI provides the best experience \\n 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Properties\\n\\n### attachments\\\\_images\\n\\n> - **attachments\\\\_images**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:385](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L385)\\n\\n***\\n\\n### - attachments\\\\_text\\n\\n> **attachments\\\\_text**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:384](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L384)\\n\\n***\\n\\n### - full\\n\\n> **full**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:386](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L386)\\n\\n***\\n\\n### - max\\\\_messages?\\n\\n> `optional` **max\\\\_messages**: `number`\\n\\n#### - Defined 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budget\\\\_tokens?\\n\\n> - `optional` **budget\\\\_tokens**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:647](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L647)\\n\\n***\\n\\n### - effort?\\n\\n> `optional` **effort**: [`NumericReasoningEffort`](../enumerations/NumericReasoningEffort.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:648](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L648)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"940c8be17c938dcc14e4abb000b0f8b5\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ReasoningConfig \\n Interface: ReasoningConfig - \\n Properties \\n budget_tokens? \\n \\n optional budget_tokens: number \\n - \\n Defined in \\n 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AI\\\\_TOKENS\\\\_USED\\n\\n> - **AI\\\\_TOKENS\\\\_USED**: `\\\"ai_tokens_used\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:206](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L206)\\n\\n***\\n\\n### - BYTES\\\\_PROCESSED\\n\\n> **BYTES\\\\_PROCESSED**: `\\\"bytes_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:197](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L197)\\n\\n***\\n\\n### - CHARS\\\\_PROCESSED\\n\\n> **CHARS\\\\_PROCESSED**: `\\\"chars_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:198](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L198)\\n\\n***\\n\\n### - MEDIA\\\\_FILES\\\\_PROCESSED\\n\\n> **MEDIA\\\\_FILES\\\\_PROCESSED**: `\\\"media_files_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:200](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L200)\\n\\n***\\n\\n### - MEDIA\\\\_SECONDS\\\\_PROCESSED\\n\\n> **MEDIA\\\\_SECONDS\\\\_PROCESSED**: - `\\\"media_seconds_processed\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:199](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L199)\\n\\n***\\n\\n### - NUCLIA\\\\_TOKENS\\n\\n> **NUCLIA\\\\_TOKENS**: `\\\"nuclia_tokens_billed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:207](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L207)\\n\\n***\\n\\n### - PAGES\\\\_PROCESSED\\n\\n> **PAGES\\\\_PROCESSED**: `\\\"pages_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:201](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L201)\\n\\n***\\n\\n### - PARAGRAPHS\\\\_PROCESSED\\n\\n> **PARAGRAPHS\\\\_PROCESSED**: `\\\"paragraphs_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:202](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L202)\\n\\n***\\n\\n### - PRE\\\\_PROCESSING\\\\_TIME\\n\\n> **PRE\\\\_PROCESSING\\\\_TIME**: `\\\"pre_processing_time\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:194](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L194)\\n\\n***\\n\\n### - RESOURCES\\\\_PROCESSED\\n\\n> **RESOURCES\\\\_PROCESSED**: `\\\"resources_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:196](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L196)\\n\\n***\\n\\n### - SEARCHES\\\\_PERFORMED\\n\\n> **SEARCHES\\\\_PERFORMED**: `\\\"searches_performed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:204](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L204)\\n\\n***\\n\\n### - SLOW\\\\_PROCESSING\\\\_TIME\\n\\n> **SLOW\\\\_PROCESSING\\\\_TIME**: `\\\"slow_processing_time\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:195](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L195)\\n\\n***\\n\\n### - SUGGESTIONS\\\\_PERFORMED\\n\\n> **SUGGESTIONS\\\\_PERFORMED**: `\\\"suggestions_performed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:205](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L205)\\n\\n***\\n\\n### - TRAIN\\\\_SECONDS\\n\\n> **TRAIN\\\\_SECONDS**: `\\\"train_seconds\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:203](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L203)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"a6825b7bf9d5960444b0981f205811a3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / UsageType \\n Enumeration: UsageType \\n - Enumeration Members \\n AI_TOKENS_USED \\n \\n AI_TOKENS_USED: ai_tokens_used - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:206 \\n \\n BYTES_PROCESSED - \\n \\n BYTES_PROCESSED: bytes_processed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:197 - \\n \\n CHARS_PROCESSED \\n \\n CHARS_PROCESSED: chars_processed \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:198 \\n \\n MEDIA_FILES_PROCESSED - \\n \\n MEDIA_FILES_PROCESSED: media_files_processed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:200 \\n \\n MEDIA_SECONDS_PROCESSED - \\n \\n MEDIA_SECONDS_PROCESSED: media_seconds_processed \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n - NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 - \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED - \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n - \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 - \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED - \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 - \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED - \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: - train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":1833,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:54:13.123173Z\",\"last_understanding\":\"2026-07-14T12:54:12.864112Z\",\"last_extract\":\"2026-07-14T12:54:12.463871Z\",\"last_processing_start\":\"2026-07-14T12:54:12.433665Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > enumerations > UsageType\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > enumerations > 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libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n - NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 - \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED - \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n - \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 - \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED - \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 - \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED - \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: - train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"id\":\"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0a003c3f724e45e392a9c8d1ce8800c1\":{\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1\",\"slug\":\"docs-develop-js-sdk-interfaces-Consumption-md\",\"title\":\"docs - > develop > js sdk > interfaces > Consumption\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:51:46.788864\",\"modified\":\"2026-07-14T12:51:15.300757\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / Consumption\\n\\n# - Interface: Consumption\\n\\n## Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> - **customer\\\\_key\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:230](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L230)\\n\\n***\\n\\n### - normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:229](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L229)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"654b0dfe17ab08959c78891dd24c3424\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption - \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n - \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":349,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:16.563837Z\",\"last_understanding\":\"2026-07-14T12:51:16.208384Z\",\"last_extract\":\"2026-07-14T12:51:15.984803Z\",\"last_processing_start\":\"2026-07-14T12:51:15.966495Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > Consumption\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > Consumption\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\":{\"score\":0.6027967929840088,\"score_type\":\"VECTOR\",\"order\":14,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption - \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n - \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs - > rag > advanced > consumption.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-10-03T08:32:26.341394\",\"modified\":\"2026-06-09T08:18:16.730959\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - consumption\\ntitle: Token consumption\\n---\\n\\nimport Tabs from \\\"@theme/Tabs\\\";\\nimport - TabItem from \\\"@theme/TabItem\\\";\\n\\n# Token consumption\\n\\nAgentic - RAG is a license and consumption-based service. This means that you pay for - the computational resources you consume. The consumption is measured in **Agentic - RAG tokens**.\\nAll public 3rd-party LLMs base their pricing on the number - of tokens consumed. In the LLM world, a token is around 4-5 characters on - average, which might fit an entire word or be split into parts. The number - of tokens is proportional to the amount of text, measured in chunks of 4-5 - characters. It closely relates to words but not entirely. The longer a sentence - is, the more tokens it will consume to read or to generate it.\\nSince all - these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize - the cost across all of them.\\n\\n## How Tokens Are Consumed in RAG\\n\\nWhen - a user asks a question to your Knowledge Box, the token consumption process - follows these steps:\\n\\n1. **Question Processing**: The system finds the - most relevant paragraphs to answer the question\\n2. **Context Assembly**: - These paragraphs are used as context when calling the LLM model\\n3. **Prompt - Creation**: Agentic RAG assembles the **prompt**, **context**, and **question** - into a single string\\n4. **LLM Processing**: This complete string is sent - to the LLM, corresponding to a certain number of **input tokens**\\n5. **Answer - Generation**: The LLM generates the answer, which corresponds to a certain - number of **output tokens**\\n\\n**Total consumption** = Input tokens + Output - tokens + Image tokens\\n\\n### Factors That Impact Token Consumption\\n\\nToken - consumption is directly affected by:\\n\\n- **Large context**: Results from - using RAG strategies like \\\"Full resource\\\" or \\\"Neighbouring paragraphs\\\", - or from using the `extra_context` parameter\\n- **Long questions**: More detailed - or complex questions require more input tokens\\n- **Long prompts**: Extensive - system prompts increase the input token count\\n- **Detailed answers**: Comprehensive - responses require more output tokens\\n- **Images in context**: When using - multimodal models, images included in the retrieved context significantly - increase token consumption\\n\\n## How to Limit and Control Token Consumption\\n\\n### - Strategy 1: Optimize Your Parameters\\n\\nThe first approach to reducing token - consumption is to fine-tune your request parameters:\\n\\n- **Optimize prompts**: - Ensure your prompts are concise and focused, avoiding unnecessary verbosity\\n- - **Control resource scope**: When using the \\\"Full resource\\\" strategy, - use the `count` attribute to limit the number of resources returned\\n- **Tune - neighboring context**: For the \\\"Neighbouring paragraphs\\\" strategy, optimize - the `before` and `after` attributes to balance context quality with token - efficiency\\n- **Manage summary length**: When using the \\\"Hierarchical\\\" - strategy, ensure that resource summaries are appropriately sized\\n- **Choose - efficient models**: Select LLMs that offer better token efficiency (typically, - ChatGPT 4o-mini is more cost-effective than ChatGPT 4o)\\n\\n### Strategy - 2: Set Hard Limits\\n\\nYou can implement safeguards against excessive token - consumption:\\n\\nUse the `max_tokens` parameter on the [`/ask` endpoint](/docs/api#tag/Search/operation/ask_knowledgebox_endpoint_kb__kbid__ask_post) - to set hard limits on:\\n- **Context size**: Limits the amount of retrieved - information sent to the LLM\\n- **Answer length**: Limits the length of the - generated response\\n\\n#### Important Considerations\\n\\n**Context Limitations**:\\n- - Restricting context size may result in less relevant answers since the LLM - has less information to work with\\n- Balance between cost control and answer - quality\\n\\n**Answer Length Limitations**:\\n- The LLM might not complete - its response if it hits the token limit, potentially cutting sentences mid-way\\n- - **Recommended approach**: Include length requirements in your prompt (e.g., - \\\"Please answer in less than 200 words\\\") rather than relying solely on - hard limits\\n- This allows the LLM to naturally conclude its response within - the desired length\\n\\n## How to Monitor Token Consumption\\n\\n### Understanding - Token Consumption Data\\n\\nYou can receive detailed token consumption information - from the following endpoints that utilize LLM models: `ask`, `chat`, `remi`, - `query`, `sentence`, `summarize`, `tokens`, and `rerank`.\\n\\n:::note\\nThe - `rephrase` endpoint currently does not support token consumption monitoring.\\n:::\\n\\nTo - receive token consumption data, you must include the following header in your - request:\\n```\\nX-SHOW-CONSUMPTION: true\\n```\\n\\nThe token consumption - data is provided in different formats depending on the response type:\\n- - **Streaming responses** (`application/x-ndjson`): Token consumption appears - as a separate JSON chunk with type \\\"consumption\\\"\\n- **Standard responses** - (`application/json`): Token consumption is included in a \\\"consumption\\\" - field within the main response\\n\\n### Token Consumption Response Format\\n\\n\\n \\n ```json\\n {\\n \\\"item\\\": - {\\n \\\"type\\\": \\\"consumption\\\",\\n \\\"normalized_tokens\\\": - {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": - 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": - 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n - \ }\\n }\\n ```\\n \\n \\n ```json\\n {\\n \\\"consumption\\\": {\\n \\\"normalized_tokens\\\": - {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": - 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": - 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n - \ }\\n }\\n ```\\n \\n\\n\\n### Understanding - Token Types\\n\\n**Normalized Tokens** (`normalized_tokens`):\\n- These represent - the number of Agentic RAG tokens consumed and that you will be billed for\\n- - Values are normalized across different LLM providers for consistent billing\\n- - Include separate counts for:\\n - `input`: Tokens used for the prompt, context, - and question\\n - `output`: Tokens used for the generated response\\n - - `image`: Tokens used for image processing (when applicable)\\n\\n**Customer - Key Tokens** (`customer_key_tokens`):\\n- These represent tokens consumed - when using your own LLM API keys\\n- These tokens are **not billed** by Agentic - RAG since you're using your own API keys\\n- Values are also normalized for - comparison purposes across different providers\\n\",\"format\":\"MARKDOWN\",\"md5\":\"204fe47dbd7eb38d465d05fa7538e51e\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: consumption \\n title: Token consumption \\n \\n import Tabs from - @theme/Tabs ; \\n import TabItem from @theme/TabItem ; \\n Token consumption - \\n Agentic RAG is a license and consumption-based service. This means that - you pay for the computational resources you consume. The consumption is measured - in Agentic RAG tokens. \\n All public 3rd-party LLMs base their pricing on - the number of tokens consumed. In the LLM world, a token is around 4-5 characters - on average, which might fit an entire word or be split into parts. The number - of tokens is proportional to the amount of text, measured in chunks of 4-5 - characters. It closely relates to words but not entirely. The longer a sentence - is, the more tokens it will consume to read or to generate it. \\n Since all - these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize - the cost across all of them. \\n How Tokens Are Consumed in RAG \\n When a - user asks a question to your Knowledge Box, the token consumption process - follows these steps: \\n \\n Question Processing: The system finds the most - relevant paragraphs to answer the question \\n Context Assembly: These paragraphs - are used as context when calling the LLM model \\n Prompt Creation: Agentic - RAG assembles the prompt, context, and question into a single string \\n LLM - Processing: This complete string is sent to the LLM, corresponding to a certain - number of input tokens \\n Answer Generation: The LLM generates the answer, - which corresponds to a certain number of output tokens \\n \\n Total consumption - = Input tokens + Output tokens + Image tokens \\n Factors That Impact Token - Consumption \\n Token consumption is directly affected by: \\n \\n Large context: - Results from using RAG strategies like Full resource or Neighbouring paragraphs - , or from using the extra_context parameter \\n Long questions: More detailed - or complex questions require more input tokens \\n Long prompts: Extensive - system prompts increase the input token count \\n Detailed answers: Comprehensive - responses require more output tokens \\n Images in context: When using multimodal - models, images included in the retrieved context significantly increase token - consumption \\n \\n How to Limit and Control Token Consumption \\n Strategy - 1: Optimize Your Parameters \\n The first approach to reducing token consumption - is to fine-tune your request parameters: \\n \\n Optimize prompts: Ensure - your prompts are concise and focused, avoiding unnecessary verbosity \\n Control - resource scope: When using the Full resource strategy, use the count attribute - to limit the number of resources returned \\n Tune neighboring context: For - the Neighbouring paragraphs strategy, optimize the before and after attributes - to balance context quality with token efficiency \\n Manage summary length: - When using the Hierarchical strategy, ensure that resource summaries are appropriately - sized \\n Choose efficient models: Select LLMs that offer better token efficiency - (typically, ChatGPT 4o-mini is more cost-effective than ChatGPT 4o) \\n \\n - Strategy 2: Set Hard Limits \\n You can implement safeguards against excessive - token consumption: \\n Use the max_tokens parameter on the /ask endpoint to - set hard limits on: \\n - Context size: Limits the amount of retrieved information - sent to the LLM \\n - Answer length: Limits the length of the generated response - \\n Important Considerations \\n Context Limitations: \\n - Restricting context - size may result in less relevant answers since the LLM has less information - to work with \\n - Balance between cost control and answer quality \\n Answer - Length Limitations: \\n - The LLM might not complete its response if it hits - the token limit, potentially cutting sentences mid-way \\n - Recommended approach: - Include length requirements in your prompt (e.g., Please answer in less than - 200 words ) rather than relying solely on hard limits \\n - This allows the - LLM to naturally conclude its response within the desired length \\n How to - Monitor Token Consumption \\n Understanding Token Consumption Data \\n You - can receive detailed token consumption information from the following endpoints - that utilize LLM models: ask, chat, remi, query, sentence, summarize, tokens, - and rerank. \\n :::note \\n The rephrase endpoint currently does not support - token consumption monitoring. \\n ::: \\n To receive token consumption data, - you must include the following header in your request: \\n X-SHOW-CONSUMPTION: - true \\n The token consumption data is provided in different formats depending - on the response type: \\n - Streaming responses (application/x-ndjson): Token - consumption appears as a separate JSON chunk with type consumption \\n - Standard - responses (application/json): Token consumption is included in a consumption - field within the main response \\n Token Consumption Response Format \\n \\n - \\n json \\n { \\n item : { \\n type : consumption , \\n normalized_tokens - : { \\n input : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens - : { \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n - \\n \\n json \\n { \\n consumption : { \\n normalized_tokens : { \\n input - : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens : { - \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n \\n - \\n Understanding Token Types \\n Normalized Tokens (normalized_tokens): \\n - - These represent the number of Agentic RAG tokens consumed and that you will - be billed for \\n - Values are normalized across different LLM providers for - consistent billing \\n - Include separate counts for: \\n - input: Tokens - used for the prompt, context, and question \\n - output: Tokens used for the - generated response \\n - image: Tokens used for image processing (when applicable) - 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Considerations \\n Context Limitations: \\n\",\"id\":\"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":6,\"start\":3075,\"end\":3340,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326\":{\"score\":0.6072185635566711,\"score_type\":\"VECTOR\",\"order\":12,\"text\":\" - \\n Large context: Results from using RAG strategies like Full resource or - Neighbouring paragraphs , or from using the extra_context parameter \\n Long - questions: More detailed or complex questions require more input tokens \\n - Long prompts: Extensive system prompts increase the input token count \\n - Detailed answers: Comprehensive responses require more output tokens \\n Images - in context: When using multimodal models, images included in the retrieved - context significantly increase token consumption \\n \\n How to Limit and - Control Token Consumption \\n Strategy 1: Optimize Your Parameters \\n The - first approach to reducing token consumption is to fine-tune your request - parameters: \\n\",\"id\":\"4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":4,\"start\":1650,\"end\":2326,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"89cc367c149e4f6eab0e06a743d1edba\":{\"id\":\"89cc367c149e4f6eab0e06a743d1edba\",\"slug\":\"docs-rag-advanced-openai-api-compatible-models-md\",\"title\":\"docs - > rag > advanced > openai api compatible models\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-05-23T07:21:32.894218\",\"modified\":\"2026-06-09T08:07:43.359058\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - openai-api-compatible-models\\ntitle: Connect to any OpenAI API compatible - LLM\\n---\\n\\n# Connect to any OpenAI API compatible LLM\\n\\nAgentic RAG - allows you to connect to any OpenAI API compatible LLM. This means that you - can use any LLM that has an API compatible with the OpenAI API which has become - a standard in the industry.\\n\\nMany of the options for self-hosted LLMs, - open-source LLMs hosted by cloud providers or commercial LLMs are compatible - with the OpenAI API. This means that you can use them with Agentic RAG without - any modifications.\\n\\n## Configuration\\n\\nTo modify your knowledge box - configuration you can do so in three manners, through the API, the Nuclia - CLI / SDK or the Agentic RAG dashboard.\\n\\nThe Agentic RAG dashboard offers - the most user-friendly way to modify the configuration of your knowledge box - and we will use it in this example.\\n\\nWe will be setting up a connection - to the **Phi 4 Reasoning Plus** model, hosted by **OpenRouter** which offers - a wide range of open-source and commercial models compatible with the OpenAI - API. We can see more information about this specific model [here](https://openrouter.ai/microsoft/phi-4-reasoning-plus:free), - the API parameters are located under the **API** tab.\\n\\n1. **Open the AI - Models page** \\n In the left sidebar under **Advanced**, click **AI Models**.\\n2. - **Select \u201COpenAI API Compatible Model\u201D** \\n From the models - list, choose **OpenAI API Compatible Model**.\\n3. **Enable custom Key** \\n - \ Toggle the option for using you own `OpenAI API Compatible Key` if it is - not already enabled.\\n4. **Fill in the configuration parameters**\\n\\n - - **API Key**:\\n - Description: The API key for your LLM. This is the key - that you would use as an authorization header in the API. You may leave this - blank if the endpoint you are connecting to does not require an API key.\\n - \ - Example: We will set this to our OpenRouter API key.\\n - **API URL**:\\n - \ - Description: The URL of the API endpoint for your LLM. This may be - shared between multiple models.\\n - Example: For OpenRouter, it is the - same for all models: `https://openrouter.ai/api/v1`\\n - **Model**:\\n - - Description: The name of the model you want to use, it needs to exactly match - the name of the model in the API.\\n - Example: For Phi 4 Reasoning Plus - in the OpenRouter API, it is `microsoft/phi-4-reasoning-plus:free`.\\n - - **Maximum supported input tokens**:\\n - Description: The maximum number - of tokens that the model can accept as input. Be mindful that this takes into - account the tokens used in the prompt, query and context. Also take note that - some models may provide their context window as the total between input and - output tokens, while others may provide it as the input tokens only.\\n - - Example: For Phi 4 Reasoning Plus, the total context size is `32768` tokens, - as we want to leave room for the output, we will set the maximum supported - input tokens as `32768 - 1024 = 31744`.\\n - **Maximum supported output - tokens**:\\n - Description: The maximum number of tokens that the model - can generate as output. Again, we should keep in mind that this value summed - to the **Maximum supported input tokens** should not exceed the total context - size supported by the model.\\n - Example: For Phi 4 Reasoning Plus, the - maximum output tokens is specified at `32768`, but we already reserved `31744` - for the input tokens, so we will set this to `32768 - 31744 = 1024`.\\n - - **Model Features**:\\n - Description: Under this section you will find - multiple toggles related to features supported by the model, these vary from - model to model, but most often the default values are well suited to most - use cases. The most relevant toggle is for `Image Support` which allows you - to use images as input for the model.\\n - Example: Image input is not - supported by Phi 4 Reasoning Plus, so we will leave it disabled.\\n\\n5. **Save** - \ \\n Click **Save changes**.\\n\\n6. **Test your model** \\n Run a sample - query in Agentic RAG or via API/CLI. Adjust your prompt templates and token - settings as needed.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"37cd8aff748addd04a363fa50828d1fe\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: openai-api-compatible-models \\n title: Connect to any OpenAI API - compatible LLM \\n \\n Connect to any OpenAI API compatible LLM \\n Agentic - RAG allows you to connect to any OpenAI API compatible LLM. This means that - you can use any LLM that has an API compatible with the OpenAI API which has - become a standard in the industry. \\n Many of the options for self-hosted - LLMs, open-source LLMs hosted by cloud providers or commercial LLMs are compatible - with the OpenAI API. This means that you can use them with Agentic RAG without - any modifications. \\n Configuration \\n To modify your knowledge box configuration - you can do so in three manners, through the API, the Nuclia CLI / SDK or the - Agentic RAG dashboard. \\n The Agentic RAG dashboard offers the most user-friendly - way to modify the configuration of your knowledge box and we will use it in - this example. \\n We will be setting up a connection to the Phi 4 Reasoning - Plus model, hosted by OpenRouter which offers a wide range of open-source - and commercial models compatible with the OpenAI API. We can see more information - about this specific model here, the API parameters are located under the API - tab. \\n \\n Open the AI Models page \\n In the left sidebar under Advanced, - click AI Models. \\n Select OpenAI API Compatible Model \\n From the models - list, choose OpenAI API Compatible Model. \\n Enable custom Key \\n Toggle - the option for using you own OpenAI API Compatible Key if it is not already - enabled. \\n \\n Fill in the configuration parameters \\n \\n \\n API Key: - \\n \\n Description: The API key for your LLM. This is the key that you would - use as an authorization header in the API. You may leave this blank if the - endpoint you are connecting to does not require an API key. \\n Example: We - will set this to our OpenRouter API key. \\n \\n \\n API URL: \\n Description: - The URL of the API endpoint for your LLM. This may be shared between multiple - models. \\n Example: For OpenRouter, it is the same for all models: https://openrouter.ai/api/v1 - \\n \\n \\n Model: \\n Description: The name of the model you want to use, - it needs to exactly match the name of the model in the API. \\n Example: For - Phi 4 Reasoning Plus in the OpenRouter API, it is microsoft/phi-4-reasoning-plus:free. - \\n \\n \\n Maximum supported input tokens: \\n Description: The maximum number - of tokens that the model can accept as input. Be mindful that this takes into - account the tokens used in the prompt, query and context. Also take note that - some models may provide their context window as the total between input and - output tokens, while others may provide it as the input tokens only. \\n Example: - For Phi 4 Reasoning Plus, the total context size is 32768 tokens, as we want - to leave room for the output, we will set the maximum supported input tokens - as 32768 - 1024 = 31744. \\n \\n \\n Maximum supported output tokens: \\n - Description: The maximum number of tokens that the model can generate as output. - Again, we should keep in mind that this value summed to the Maximum supported - input tokens should not exceed the total context size supported by the model. - \\n Example: For Phi 4 Reasoning Plus, the maximum output tokens is specified - at 32768, but we already reserved 31744 for the input tokens, so we will set - this to 32768 - 31744 = 1024. \\n \\n \\n \\n Model Features: \\n \\n Description: - Under this section you will find multiple toggles related to features supported - by the model, these vary from model to model, but most often the default values - are well suited to most use cases. The most relevant toggle is for Image Support - which allows you to use images as input for the model. \\n Example: Image - input is not supported by Phi 4 Reasoning Plus, so we will leave it disabled. - \\n \\n \\n \\n Save \\n Click Save changes. \\n \\n \\n Test your model \\n - Run a sample query in Agentic RAG or via API/CLI. 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\\n \\n Maximum supported input tokens: \\n Description: The maximum number - of tokens that the model can accept as input. Be mindful that this takes into - account the tokens used in the prompt, query and context. Also take note that - some models may provide their context window as the total between input and - output tokens, while others may provide it as the input tokens only. \\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":8,\"start\":2202,\"end\":2575,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\":{\"score\":0.6517809629440308,\"score_type\":\"VECTOR\",\"order\":5,\"text\":\" - Description: The maximum number of tokens that the model can generate as output. - Again, we should keep in mind that this value summed to the Maximum supported - input tokens should not exceed the total context size supported by the model. - \\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":10,\"start\":2804,\"end\":3043,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs - > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-07-14T12:49:58.922592\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ModelConfig\\n\\n# - Interface: ModelConfig\\n\\n## Properties\\n\\n### assume\\\\_role?\\n\\n> - `optional` **assume\\\\_role**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:592](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L592)\\n\\n***\\n\\n### - driver?\\n\\n> `optional` **driver**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:590](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L590)\\n\\n***\\n\\n### - input\\\\_tokens\\n\\n> **input\\\\_tokens**: `object`\\n\\n#### max\\n\\n> - **max**: `number`\\n\\n#### min?\\n\\n> `optional` **min**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:587](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L587)\\n\\n***\\n\\n### - max\\\\_images?\\n\\n> `optional` **max\\\\_images**: `string`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:591](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L591)\\n\\n***\\n\\n### - output\\\\_tokens\\n\\n> **output\\\\_tokens**: `object`\\n\\n#### default\\\\_max?\\n\\n> - `optional` **default\\\\_max**: `number`\\n\\n#### max\\n\\n> **max**: `number`\\n\\n#### - min?\\n\\n> `optional` **min**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:588](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L588)\\n\\n***\\n\\n### - prompt\\\\_id?\\n\\n> `optional` **prompt\\\\_id**: `string`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:589](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L589)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"0ce41cb0494bcb99176527165e321fec\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ModelConfig \\n Interface: ModelConfig - \\n Properties \\n assume_role? \\n \\n optional assume_role: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:592 \\n \\n driver? - \\n \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 - \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: - number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \\n \\n max_images? \\n \\n optional max_images: string \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \\n \\n output_tokens \\n - \\n output_tokens: object \\n \\n default_max? \\n \\n optional default_max: - number \\n \\n max \\n \\n max: number \\n \\n min? \\n \\n optional min: - number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:588 - \\n \\n prompt_id? \\n \\n optional prompt_id: string \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/kb/kb.models.ts:589\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":212,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":108,\"key\":\"\"},{\"start\":108,\"end\":212,\"key\":\"\"}]},{\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":215,\"end\":380,\"key\":\"\"},{\"start\":380,\"end\":480,\"key\":\"\"}]},{\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":483,\"end\":638,\"key\":\"\"},{\"start\":638,\"end\":703,\"key\":\"\"}]},{\"start\":703,\"end\":895,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":704,\"end\":806,\"key\":\"\"},{\"start\":806,\"end\":895,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:01.191702Z\",\"last_understanding\":\"2026-07-14T12:50:00.962823Z\",\"last_extract\":\"2026-07-14T12:50:00.418522Z\",\"last_processing_start\":\"2026-07-14T12:50:00.364723Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > ModelConfig\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > ModelConfig\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\":{\"score\":0.6226930022239685,\"score_type\":\"VECTOR\",\"order\":6,\"text\":\" - \\n optional max_images: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 - \\n \\n output_tokens \\n \\n output_tokens: object \\n \\n default_max? \\n - \\n optional default_max: number \\n \\n max \\n \\n max: number \\n \\n min? - \\n \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":2,\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\":{\"score\":0.5966856479644775,\"score_type\":\"VECTOR\",\"order\":18,\"text\":\" - \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 - \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: - number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \\n \\n max_images? \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":1,\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"dd41482018924facb5dbb87a7d53f122\":{\"id\":\"dd41482018924facb5dbb87a7d53f122\",\"slug\":\"docs-ingestion-how-to-rate-limiting-md\",\"title\":\"docs - > ingestion > how to > rate limiting\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:05.339624\",\"modified\":\"2026-06-09T08:18:12.259849\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - rate-limiting\\ntitle: Manage rate limiting\\n---\\n\\n# Manage rate limiting\\n\\nRate - limits are an essential aspect of the Agentic RAG platform, ensuring fair - usage and optimal performance for all users interacting with Agentic RAG APIs. - This document outlines the rate limits enforced by Agentic RAG and provides - guidelines for handling rate-limited responses effectively.\\n\\n## Introduction\\n\\nAgentic - RAG can apply two types of limits to its APIs:\\n\\n- **Regular API rate limits**: - By default, the sum of all authenticated requests in a Agentic RAG account - cannot exceed 2400 requests per minute. Note that this limit can be customized - on a per-account basis. Please contact [Agentic RAG's support team](mailto:support@nuclia.com) - if you need an increase.\\n\\n- **Ingestion back pressure limits**: Agentic - RAG implements a back-pressure mechanism to manage ingestion pipeline overload. - This mainly affects endpoints for uploading data and creating or updating - resources.\\n\\n## Handling Rate-Limited Responses\\n\\nAgentic RAG adheres - to [the HTTP standard](https://datatracker.ietf.org/doc/html/rfc6585#section-4) - and will return a response with a `429` status codes when the limits are exceeded.\\n\\nThe - official Agentic RAG API clients already have built-in mechanisms for retrying - requests when rate limits are encountered:\\n\\n- [Nuclia Python client](/docs/develop/python-sdk/README)\\n- - [Nuclia JavaScript client](/docs/develop/js-sdk/)\\n\\nHowever, if you are - interacting directly with the API, we recommend using an [exponential backoff - retry strategy](https://en.wikipedia.org/wiki/Exponential_backoff) when limits - are reached.\\n\\nWhen ingestion back pressure rate limits are hit, the response - will include a `try_after` key with an estimated UTC time for retrying the - request. You can use this value for retry logic as an alternative to the exponential - backoff strategy.\\n\\n## Example 1: Regular API rate limits\\n\\nHere's an - example of how to implement an exponential backoff retry strategy in Python:\\n\\n```python\\nimport - time\\nimport requests\\n\\ndef make_request_with_exponential_backoff(url, - headers, max_retries=5):\\n retries = 0\\n while retries < max_retries:\\n - \ response = requests.get(url, headers=headers)\\n if response.status_code - == 200:\\n return response.json()\\n elif response.status_code - == 429:\\n wait_time = 2 ** retries # Exponential backoff: 2^retries\\n - \ print(f\\\"Rate limit exceeded. Retrying in {wait_time} seconds...\\\")\\n - \ time.sleep(wait_time)\\n retries += 1\\n else:\\n - \ response.raise_for_status()\\n raise Exception(\\\"Max retries - exceeded\\\")\\n\\n# Example usage\\nurl = \\\"https://your-endpoint\\\"\\nheaders - = {\\\"Authorization\\\": \\\"Bearer YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_exponential_backoff(url, - headers)\\nprint(data)\\n```\\n\\n## Example 2: Ingestion back pressure limits\\n\\nHere's - an example of how to use the try_after key from the response to manage rate - limits:\\n\\n```python\\nimport time\\nfrom datetime import datetime\\n\\nimport - requests\\n\\n\\ndef make_request_with_try_after_info(url, headers, max_retries=5):\\n - \ retries = 0\\n while retries < max_retries:\\n response = requests.get(url, - headers=headers)\\n response_body = response.json()\\n if response.status_code - == 200:\\n return response.json()\\n elif response.status_code - == 429 and \\\"try_after\\\" in response_body:\\n try_after = response_body[\\\"try_after\\\"]\\n - \ retry_time = datetime.strptime(try_after, \\\"%Y-%m-%dT%H:%M:%S.%fZ\\\")\\n - \ wait_time = (retry_time - datetime.utcnow()).total_seconds()\\n - \ print(\\n f\\\"Rate limit exceeded. Retrying at - {retry_time} (in {wait_time} seconds)...\\\"\\n )\\n time.sleep(wait_time)\\n - \ retries += 1\\n else:\\n response.raise_for_status()\\n - \ raise Exception(\\\"Max retries exceeded\\\")\\n\\n\\n# Example usage\\nurl - = \\\"https://your-endpoint\\\"\\nheaders = {\\\"Authorization\\\": \\\"Bearer - YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_try_after_info(url, headers)\\nprint(data)\\n```\\n\\nThese - examples demonstrate how to handle rate limits effectively, ensuring that - your application respects the limits and retries appropriately.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"ed11945857f4618eec7ed0d1b16ffa44\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: rate-limiting \\n title: Manage rate limiting \\n \\n Manage rate - limiting \\n Rate limits are an essential aspect of the Agentic RAG platform, - ensuring fair usage and optimal performance for all users interacting with - Agentic RAG APIs. This document outlines the rate limits enforced by Agentic - RAG and provides guidelines for handling rate-limited responses effectively. - \\n Introduction \\n Agentic RAG can apply two types of limits to its APIs: - \\n \\n \\n Regular API rate limits: By default, the sum of all authenticated - requests in a Agentic RAG account cannot exceed 2400 requests per minute. - Note that this limit can be customized on a per-account basis. Please contact - Agentic RAG's support team if you need an increase. \\n \\n \\n Ingestion - back pressure limits: Agentic RAG implements a back-pressure mechanism to - manage ingestion pipeline overload. This mainly affects endpoints for uploading - data and creating or updating resources. \\n \\n \\n Handling Rate-Limited - Responses \\n Agentic RAG adheres to the HTTP standard and will return a response - with a 429 status codes when the limits are exceeded. \\n The official Agentic - RAG API clients already have built-in mechanisms for retrying requests when - rate limits are encountered: \\n \\n Nuclia Python client \\n Nuclia JavaScript - client \\n \\n However, if you are interacting directly with the API, we recommend - using an exponential backoff retry strategy when limits are reached. \\n When - ingestion back pressure rate limits are hit, the response will include a try_after - key with an estimated UTC time for retrying the request. You can use this - value for retry logic as an alternative to the exponential backoff strategy. - \\n Example 1: Regular API rate limits \\n Here's an example of how to implement - an exponential backoff retry strategy in Python: \\n ```python \\n import - time \\n import requests \\n def make_request_with_exponential_backoff(url, - headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: - \\n response = requests.get(url, headers=headers) \\n if response.status_code - == 200: \\n return response.json() \\n elif response.status_code == 429: \\n - wait_time = 2 retries # Exponential backoff: 2^retries \\n print(f Rate limit - exceeded. Retrying in {wait_time} seconds... ) \\n time.sleep(wait_time) \\n - retries += 1 \\n else: \\n response.raise_for_status() \\n raise Exception( - Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint \\n - headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_exponential_backoff(url, - headers) \\n print(data) \\n ``` \\n Example 2: Ingestion back pressure limits - \\n Here's an example of how to use the try_after key from the response to - manage rate limits: \\n ```python \\n import time \\n from datetime import - datetime \\n import requests \\n def make_request_with_try_after_info(url, - headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: - \\n response = requests.get(url, headers=headers) \\n response_body = response.json() - \\n if response.status_code == 200: \\n return response.json() \\n elif response.status_code - == 429 and try_after in response_body: \\n try_after = response_body[ try_after - ] \\n retry_time = datetime.strptime(try_after, %Y-%m-%dT%H:%M:%S.%fZ ) \\n - wait_time = (retry_time - datetime.utcnow()).total_seconds() \\n print( \\n - f Rate limit exceeded. Retrying at {retry_time} (in {wait_time} seconds)... - \\n ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() - \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint - \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, - headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle - rate limits effectively, ensuring that your application respects the limits - and retries 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limiting\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\":{\"score\":0.6079242825508118,\"score_type\":\"VECTOR\",\"order\":11,\"text\":\" - ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() - \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint - \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, - headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle - rate limits effectively, ensuring that your application respects the limits - and retries 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PredictAnswerOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:11.443619\",\"modified\":\"2026-07-14T12:50:46.385594\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / PredictAnswerOptions\\n\\n# - Interface: PredictAnswerOptions\\n\\n## Properties\\n\\n### chat\\\\_history?\\n\\n> - `optional` **chat\\\\_history**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:242](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L242)\\n\\n***\\n\\n### - citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L249)\\n\\n***\\n\\n### - citations?\\n\\n> `optional` **citations**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L248)\\n\\n***\\n\\n### - context?\\n\\n> `optional` **context**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:243](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L243)\\n\\n***\\n\\n### - format\\\\_prompt?\\n\\n> `optional` **format\\\\_prompt**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:258](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L258)\\n\\n***\\n\\n### - generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L250)\\n\\n***\\n\\n### - json\\\\_schema?\\n\\n> `optional` **json\\\\_schema**: `object`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:257](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L257)\\n\\n***\\n\\n### - max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L251)\\n\\n***\\n\\n### - prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:256](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L256)\\n\\n***\\n\\n### - query\\\\_context?\\n\\n> `optional` **query\\\\_context**: `string`[] \\\\| - `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:244](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L244)\\n\\n***\\n\\n### - query\\\\_context\\\\_images?\\n\\n> `optional` **query\\\\_context\\\\_images**: - `object`\\n\\n#### b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> - **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:252](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L252)\\n\\n***\\n\\n### - query\\\\_context\\\\_order?\\n\\n> `optional` **query\\\\_context\\\\_order**: - `object`\\n\\n#### Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:245](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L245)\\n\\n***\\n\\n### - reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:260](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L260)\\n\\n***\\n\\n### - rerank\\\\_context?\\n\\n> `optional` **rerank\\\\_context**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:259](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L259)\\n\\n***\\n\\n### - retrieval?\\n\\n> `optional` **retrieval**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:240](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L240)\\n\\n***\\n\\n### - system?\\n\\n> `optional` **system**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:241](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L241)\\n\\n***\\n\\n### - truncate?\\n\\n> `optional` **truncate**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L246)\\n\\n***\\n\\n### - user\\\\_prompt?\\n\\n> `optional` **user\\\\_prompt**: `object`\\n\\n#### - prompt\\n\\n> **prompt**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"470be50f3c6aeeff5ae3310ed007b9b3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / PredictAnswerOptions \\n Interface: PredictAnswerOptions - \\n Properties \\n chat_history? \\n \\n optional chat_history: ContextEntry[] - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:242 \\n - \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:249 \\n \\n citations? - \\n \\n optional citations: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:248 - \\n \\n context? \\n \\n optional context: ContextEntry[] \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:243 \\n \\n format_prompt? - \\n \\n optional format_prompt: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:258 - \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 \\n \\n json_schema? - \\n \\n optional json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 - \\n \\n max_tokens? \\n \\n optional max_tokens: number \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 \\n \\n prefer_markdown? - \\n \\n optional prefer_markdown: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 - \\n \\n query_context? \\n \\n optional query_context: string[] \\\\| object - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:244 \\n - \\n query_context_images? \\n \\n optional query_context_images: object \\n - \\n b64encoded \\n \\n b64encoded: string \\n \\n content_type \\n \\n content_type: - string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:252 - \\n \\n query_context_order? \\n \\n optional query_context_order: object - \\n \\n Index Signature \\n [key: string]: number \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:245 - \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:260 \\n \\n rerank_context? - \\n \\n optional rerank_context: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:259 - \\n \\n retrieval? \\n \\n optional retrieval: boolean \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/ask.models.ts:240 \\n \\n system? \\n - \\n optional system: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:241 - \\n \\n truncate? \\n \\n optional truncate: boolean \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/search/ask.models.ts:246 \\n \\n user_prompt? \\n - \\n optional user_prompt: object \\n \\n prompt \\n \\n prompt: string \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:247\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":257,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":127,\"key\":\"\"},{\"start\":127,\"end\":257,\"key\":\"\"}]},{\"start\":257,\"end\":491,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":260,\"end\":382,\"key\":\"\"},{\"start\":382,\"end\":491,\"key\":\"\"}]},{\"start\":491,\"end\":739,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":494,\"end\":617,\"key\":\"\"},{\"start\":617,\"end\":739,\"key\":\"\"}]},{\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":742,\"end\":864,\"key\":\"\"},{\"start\":864,\"end\":977,\"key\":\"\"}]},{\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":980,\"end\":1100,\"key\":\"\"},{\"start\":1100,\"end\":1221,\"key\":\"\"}]},{\"start\":1221,\"end\":1575,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1224,\"end\":1364,\"key\":\"\"},{\"start\":1364,\"end\":1575,\"key\":\"\"}]},{\"start\":1575,\"end\":1866,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1578,\"end\":1743,\"key\":\"\"},{\"start\":1743,\"end\":1866,\"key\":\"\"}]},{\"start\":1866,\"end\":2096,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1869,\"end\":1988,\"key\":\"\"},{\"start\":1988,\"end\":2096,\"key\":\"\"}]},{\"start\":2096,\"end\":2320,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2099,\"end\":2208,\"key\":\"\"},{\"start\":2208,\"end\":2320,\"key\":\"\"}]},{\"start\":2320,\"end\":2449,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2323,\"end\":2449,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:49.024021Z\",\"last_understanding\":\"2026-07-14T12:50:48.461687Z\",\"last_extract\":\"2026-07-14T12:50:47.086918Z\",\"last_processing_start\":\"2026-07-14T12:50:47.048628Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > PredictAnswerOptions\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > PredictAnswerOptions\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\":{\"score\":0.6562845706939697,\"score_type\":\"VECTOR\",\"order\":4,\"text\":\" - \\n optional max_tokens: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \\n \\n query_context? - \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":4,\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\":{\"score\":0.6046878099441528,\"score_type\":\"VECTOR\",\"order\":13,\"text\":\" - \\n optional generative_model: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 - \\n \\n json_schema? \\n \\n optional json_schema: object \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 \\n \\n max_tokens? - \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":3,\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs - > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-07-14T12:51:04.368823\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ChatOptions\\n\\n# - Interface: ChatOptions\\n\\n## Extends\\n\\n- [`BaseSearchOptions`](BaseSearchOptions.md)\\n\\n## - Properties\\n\\n### answer\\\\_json\\\\_schema?\\n\\n> `optional` **answer\\\\_json\\\\_schema**: - `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:114](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L114)\\n\\n***\\n\\n### - audit\\\\_metadata?\\n\\n> `optional` **audit\\\\_metadata**: `object`\\n\\n#### - Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `string`\\n\\n#### Inherited - from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`audit_metadata`](BaseSearchOptions.md#audit_metadata)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:81](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L81)\\n\\n***\\n\\n### - citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:116](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L116)\\n\\n***\\n\\n### - citations?\\n\\n> `optional` **citations**: `boolean` \\\\| `\\\"none\\\"` - \\\\| `\\\"default\\\"` \\\\| `\\\"llm_footnotes\\\"`\\n\\nIt will return - the text blocks that have been effectively used to build each section of the - answer.\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:105](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L105)\\n\\n***\\n\\n### - debug?\\n\\n> `optional` **debug**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`debug`](BaseSearchOptions.md#debug)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:79](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L79)\\n\\n***\\n\\n### - extra\\\\_context?\\n\\n> `optional` **extra\\\\_context**: `string`[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:115](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L115)\\n\\n***\\n\\n### - extra\\\\_context\\\\_images?\\n\\n> `optional` **extra\\\\_context\\\\_images**: - `object`[]\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:118](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L118)\\n\\n***\\n\\n### - ~~extracted?~~\\n\\n> `optional` **extracted**: [`ExtractedDataTypes`](../enumerations/ExtractedDataTypes.md)[]\\n\\n#### - Deprecated\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`extracted`](BaseSearchOptions.md#extracted)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:73](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L73)\\n\\n***\\n\\n### - features?\\n\\n> `optional` **features**: [`Features`](../namespaces/Ask/enumerations/Features.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:117](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L117)\\n\\n***\\n\\n### - field\\\\_type\\\\_filter?\\n\\n> `optional` **field\\\\_type\\\\_filter**: - [`FIELD_TYPE`](../enumerations/FIELD_TYPE.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`field_type_filter`](BaseSearchOptions.md#field_type_filter)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:74](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L74)\\n\\n***\\n\\n### - fields?\\n\\n> `optional` **fields**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`fields`](BaseSearchOptions.md#fields)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:62](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L62)\\n\\n***\\n\\n### - filter\\\\_expression?\\n\\n> `optional` **filter\\\\_expression**: [`FilterExpression`](FilterExpression.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filter_expression`](BaseSearchOptions.md#filter_expression)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:64](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L64)\\n\\n***\\n\\n### - filters?\\n\\n> `optional` **filters**: `string`[] \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filters`](BaseSearchOptions.md#filters)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:63](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L63)\\n\\n***\\n\\n### - generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:108](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L108)\\n\\n***\\n\\n### - highlight?\\n\\n> `optional` **highlight**: `boolean`\\n\\n#### Inherited - from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`highlight`](BaseSearchOptions.md#highlight)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:76](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L76)\\n\\n***\\n\\n### - keyword\\\\_filters?\\n\\n> `optional` **keyword\\\\_filters**: `string`[] - \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`keyword_filters`](BaseSearchOptions.md#keyword_filters)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:65](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L65)\\n\\n***\\n\\n### - max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number` \\\\| `object`\\n\\nDefines - the maximum number of tokens that the model will take as context.\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:112](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L112)\\n\\n***\\n\\n### - min\\\\_score?\\n\\n> `optional` **min\\\\_score**: `number` \\\\| [`MinScore`](MinScore.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`min_score`](BaseSearchOptions.md#min_score)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:66](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L66)\\n\\n***\\n\\n### - prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:113](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L113)\\n\\n***\\n\\n### - prompt?\\n\\n> `optional` **prompt**: `string` \\\\| [`Prompts`](Prompts.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:101](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L101)\\n\\n***\\n\\n### - query\\\\_image?\\n\\n> `optional` **query\\\\_image**: `object`\\n\\n#### - b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> - **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:122](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L122)\\n\\n***\\n\\n### - rag\\\\_images\\\\_strategies?\\n\\n> `optional` **rag\\\\_images\\\\_strategies**: - [`RAGImageStrategy`](../type-aliases/RAGImageStrategy.md)[]\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:107](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L107)\\n\\n***\\n\\n### - rag\\\\_strategies?\\n\\n> `optional` **rag\\\\_strategies**: [`RAGStrategy`](../type-aliases/RAGStrategy.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:106](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L106)\\n\\n***\\n\\n### - range\\\\_creation\\\\_end?\\n\\n> `optional` **range\\\\_creation\\\\_end**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_end`](BaseSearchOptions.md#range_creation_end)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:68](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L68)\\n\\n***\\n\\n### - range\\\\_creation\\\\_start?\\n\\n> `optional` **range\\\\_creation\\\\_start**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_start`](BaseSearchOptions.md#range_creation_start)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:67](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L67)\\n\\n***\\n\\n### - range\\\\_modification\\\\_end?\\n\\n> `optional` **range\\\\_modification\\\\_end**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_end`](BaseSearchOptions.md#range_modification_end)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:70](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L70)\\n\\n***\\n\\n### - range\\\\_modification\\\\_start?\\n\\n> `optional` **range\\\\_modification\\\\_start**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_start`](BaseSearchOptions.md#range_modification_start)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:69](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L69)\\n\\n***\\n\\n### - rank\\\\_fusion?\\n\\n> `optional` **rank\\\\_fusion**: [`RankFusion`](RankFusion.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rank_fusion`](BaseSearchOptions.md#rank_fusion)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:84](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L84)\\n\\n***\\n\\n### - reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L126)\\n\\n***\\n\\n### - rephrase?\\n\\n> `optional` **rephrase**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rephrase`](BaseSearchOptions.md#rephrase)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:77](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L77)\\n\\n***\\n\\n### - reranker?\\n\\n> `optional` **reranker**: [`Reranker`](../enumerations/Reranker.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`reranker`](BaseSearchOptions.md#reranker)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:83](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L83)\\n\\n***\\n\\n### - resource\\\\_filters?\\n\\n> `optional` **resource\\\\_filters**: `string`[]\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`resource_filters`](BaseSearchOptions.md#resource_filters)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:75](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L75)\\n\\n***\\n\\n### - search\\\\_configuration?\\n\\n> `optional` **search\\\\_configuration**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`search_configuration`](BaseSearchOptions.md#search_configuration)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:86](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L86)\\n\\n***\\n\\n### - security?\\n\\n> `optional` **security**: `object`\\n\\n#### groups\\n\\n> - **groups**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`security`](BaseSearchOptions.md#security)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:85](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L85)\\n\\n***\\n\\n### - show?\\n\\n> `optional` **show**: [`ResourceProperties`](../enumerations/ResourceProperties.md)[]\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show`](BaseSearchOptions.md#show)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:71](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L71)\\n\\n***\\n\\n### - show\\\\_consumption?\\n\\n> `optional` **show\\\\_consumption**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L127)\\n\\n***\\n\\n### - show\\\\_hidden?\\n\\n> `optional` **show\\\\_hidden**: `boolean`\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show_hidden`](BaseSearchOptions.md#show_hidden)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:80](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L80)\\n\\n***\\n\\n### - synchronous?\\n\\n> `optional` **synchronous**: `boolean`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:100](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L100)\\n\\n***\\n\\n### - top\\\\_k?\\n\\n> `optional` **top\\\\_k**: `number`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`top_k`](BaseSearchOptions.md#top_k)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:82](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L82)\\n\\n***\\n\\n### - vectorset?\\n\\n> `optional` **vectorset**: `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`vectorset`](BaseSearchOptions.md#vectorset)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:78](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L78)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"d6b2f3f31ba0af4fa58490cdf6abeb52\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ChatOptions \\n Interface: ChatOptions - \\n Extends \\n \\n BaseSearchOptions \\n \\n Properties \\n answer_json_schema? - \\n \\n optional answer_json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:114 - \\n \\n audit_metadata? \\n \\n optional audit_metadata: object \\n \\n Index - Signature \\n [key: string]: string \\n Inherited from \\n BaseSearchOptions.audit_metadata - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:81 \\n - \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:116 \\n \\n - citations? \\n \\n optional citations: boolean \\\\| none \\\\| default \\\\| - llm_footnotes \\n \\n It will return the text blocks that have been effectively - used to build each section of the answer. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:105 - \\n \\n debug? \\n \\n optional debug: boolean \\n \\n Inherited from \\n - BaseSearchOptions.debug \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:79 - \\n \\n extra_context? \\n \\n optional extra_context: string[] \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:115 \\n \\n extra_context_images? - \\n \\n optional extra_context_images: object[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:118 - \\n \\n ~~extracted?~~ \\n \\n optional extracted: ExtractedDataTypes[] \\n - \\n Deprecated \\n Inherited from \\n BaseSearchOptions.extracted \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:73 \\n \\n features? - \\n \\n optional features: Features[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:117 - \\n \\n field_type_filter? \\n \\n optional field_type_filter: FIELD_TYPE[] - \\n \\n Inherited from \\n BaseSearchOptions.field_type_filter \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:74 \\n \\n fields? - \\n \\n optional fields: string[] \\n \\n Inherited from \\n BaseSearchOptions.fields - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:62 \\n - \\n filter_expression? \\n \\n optional filter_expression: FilterExpression - \\n \\n Inherited from \\n BaseSearchOptions.filter_expression \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:64 \\n \\n filters? - \\n \\n optional filters: string[] \\\\| Filter[] \\n \\n Inherited from \\n - BaseSearchOptions.filters \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:63 - \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:108 \\n \\n - highlight? \\n \\n optional highlight: boolean \\n \\n Inherited from \\n - BaseSearchOptions.highlight \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:76 - \\n \\n keyword_filters? \\n \\n optional keyword_filters: string[] \\\\| - Filter[] \\n \\n Inherited from \\n BaseSearchOptions.keyword_filters \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:65 \\n \\n - max_tokens? \\n \\n optional max_tokens: number \\\\| object \\n \\n Defines - the maximum number of tokens that the model will take as context. \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 \\n \\n min_score? - \\n \\n optional min_score: number \\\\| MinScore \\n \\n Inherited from \\n - BaseSearchOptions.min_score \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:66 - \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:113 \\n \\n - prompt? \\n \\n optional prompt: string \\\\| Prompts \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/search/search.models.ts:101 \\n \\n query_image? - \\n \\n optional query_image: object \\n \\n b64encoded \\n \\n b64encoded: - string \\n \\n content_type \\n \\n content_type: string \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/search.models.ts:122 \\n \\n rag_images_strategies? - \\n \\n optional rag_images_strategies: RAGImageStrategy[] \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:107 \\n \\n rag_strategies? - \\n \\n optional rag_strategies: RAGStrategy[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:106 - \\n \\n range_creation_end? \\n \\n optional range_creation_end: string \\n - \\n Inherited from \\n BaseSearchOptions.range_creation_end \\n Defined in - \\n libs/sdk-core/src/lib/db/search/search.models.ts:68 \\n \\n range_creation_start? - \\n \\n optional range_creation_start: string \\n \\n Inherited from \\n BaseSearchOptions.range_creation_start - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:67 \\n - \\n range_modification_end? \\n \\n optional range_modification_end: string - \\n \\n Inherited from \\n BaseSearchOptions.range_modification_end \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:70 \\n \\n range_modification_start? - \\n \\n optional range_modification_start: string \\n \\n Inherited from \\n - BaseSearchOptions.range_modification_start \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:69 - \\n \\n rank_fusion? \\n \\n optional rank_fusion: RankFusion \\n \\n Inherited - from \\n BaseSearchOptions.rank_fusion \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:84 - \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:126 \\n \\n rephrase? - \\n \\n optional rephrase: boolean \\n \\n Inherited from \\n BaseSearchOptions.rephrase - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:77 \\n - \\n reranker? \\n \\n optional reranker: Reranker \\n \\n Inherited from \\n - BaseSearchOptions.reranker \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:83 - \\n \\n resource_filters? \\n \\n optional resource_filters: string[] \\n - \\n Inherited from \\n BaseSearchOptions.resource_filters \\n Defined in \\n - libs/sdk-core/src/lib/db/search/search.models.ts:75 \\n \\n search_configuration? - \\n \\n optional search_configuration: string \\n \\n Inherited from \\n BaseSearchOptions.search_configuration - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:86 \\n - \\n security? \\n \\n optional security: object \\n \\n groups \\n \\n groups: - string[] \\n \\n Inherited from \\n BaseSearchOptions.security \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:85 \\n \\n show? \\n - \\n optional show: ResourceProperties[] \\n \\n Inherited from \\n BaseSearchOptions.show - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:71 \\n - \\n show_consumption? \\n \\n optional show_consumption: boolean \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:127 \\n \\n show_hidden? - \\n \\n optional show_hidden: boolean \\n \\n Inherited from \\n BaseSearchOptions.show_hidden - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:80 \\n - \\n synchronous? \\n \\n optional synchronous: boolean \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/search.models.ts:100 \\n \\n top_k? \\n - \\n optional top_k: number \\n \\n Inherited from \\n BaseSearchOptions.top_k - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:82 \\n - \\n vectorset? \\n \\n optional vectorset: string \\n \\n Inherited from \\n - BaseSearchOptions.vectorset \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:78\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[\"BaseSearchOptions.security\",\"BaseSearchOptions.show\"],\"paragraphs\":[{\"start\":0,\"end\":276,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":149,\"key\":\"\"},{\"start\":149,\"end\":276,\"key\":\"\"}]},{\"start\":276,\"end\":499,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":279,\"end\":499,\"key\":\"\"}]},{\"start\":499,\"end\":796,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":502,\"end\":627,\"key\":\"\"},{\"start\":627,\"end\":796,\"key\":\"\"}]},{\"start\":796,\"end\":1034,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":797,\"end\":878,\"key\":\"\"},{\"start\":878,\"end\":1034,\"key\":\"\"}]},{\"start\":1034,\"end\":1488,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1037,\"end\":1170,\"key\":\"\"},{\"start\":1170,\"end\":1296,\"key\":\"\"},{\"start\":1296,\"end\":1488,\"key\":\"\"}]},{\"start\":1488,\"end\":1796,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1491,\"end\":1618,\"key\":\"\"},{\"start\":1618,\"end\":1796,\"key\":\"\"}]},{\"start\":1796,\"end\":2148,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1799,\"end\":1965,\"key\":\"\"},{\"start\":1965,\"end\":2148,\"key\":\"\"}]},{\"start\":2148,\"end\":2450,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2151,\"end\":2330,\"key\":\"\"},{\"start\":2330,\"end\":2450,\"key\":\"\"}]},{\"start\":2450,\"end\":2808,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2453,\"end\":2622,\"key\":\"\"},{\"start\":2622,\"end\":2808,\"key\":\"\"}]},{\"start\":2808,\"end\":3011,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2811,\"end\":2929,\"key\":\"\"},{\"start\":2929,\"end\":3011,\"key\":\"\"}]},{\"start\":3011,\"end\":3311,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":3014,\"end\":3194,\"key\":\"\"},{\"start\":3194,\"end\":3311,\"key\":\"\"}]},{\"start\":3311,\"end\":3647,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":3314,\"end\":3440,\"key\":\"\"},{\"start\":3440,\"end\":3647,\"key\":\"\"}]},{\"start\":3647,\"end\":3929,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":3650,\"end\":3795,\"key\":\"\"},{\"start\":3795,\"end\":3929,\"key\":\"\"}]},{\"start\":3929,\"end\":4317,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":3932,\"end\":4123,\"key\":\"\"},{\"start\":4123,\"end\":4317,\"key\":\"\"}]},{\"start\":4317,\"end\":4520,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":4320,\"end\":4520,\"key\":\"\"}]},{\"start\":4520,\"end\":4884,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":4523,\"end\":4717,\"key\":\"\"},{\"start\":4717,\"end\":4884,\"key\":\"\"}]},{\"start\":4884,\"end\":5167,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":4887,\"end\":5010,\"key\":\"\"},{\"start\":5010,\"end\":5167,\"key\":\"\"}]},{\"start\":5167,\"end\":5525,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":5170,\"end\":5339,\"key\":\"\"},{\"start\":5339,\"end\":5525,\"key\":\"\"}]},{\"start\":5525,\"end\":5897,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":5528,\"end\":5711,\"key\":\"\"},{\"start\":5711,\"end\":5897,\"key\":\"\"}]},{\"start\":5897,\"end\":6194,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":5898,\"end\":6071,\"key\":\"\"},{\"start\":6071,\"end\":6194,\"key\":\"\"}]},{\"start\":6194,\"end\":6478,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":6197,\"end\":6366,\"key\":\"\"},{\"start\":6366,\"end\":6478,\"key\":\"\"}]},{\"start\":6478,\"end\":6778,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":6481,\"end\":6635,\"key\":\"\"},{\"start\":6635,\"end\":6778,\"key\":\"\"}]}],\"ner\":{\"boolean\":\"PERSON\",\"112 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headers: Alt-Svc: - h3=":443"; ma=2592000 Content-Length: - - '206566' + - '1454' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 08:10:54 GMT + - Wed, 05 Aug 2026 07:57:01 GMT + nuclia-learning-model: + - bge-reranker-v2-m3 via: - 1.1 google x-envoy-upstream-service-time: - - '273' + - '95' x-nuclia-trace-id: - - 5344ff142ea9a3656a6ad1eaae1c682c + - 338f5c8e8ab5c4e13ad42dc6fa176198 status: code: 200 message: OK - request: - body: '{"query": "Esboniwch sut i ddefnyddio''r paramedr ''max_tokens'' mewn atebion, - a darparwch ddolen i''r ddogfennaeth swyddogol.", "filters": [], "show": ["basic", - "origin", "extra", "extracted", "values", "relations"], "extracted": ["text", - "metadata", "file", "link"], "security": {"groups": []}, "features": ["keyword"], - "reranker": "noop", "keyword_filters": ["max_tokens", "par\u00e1metro"]}' + body: '{"question": "", "retrieval": true, "user_id": "rao_answer_summary-ask", + "system": null, "chat_history": [], "context": [], "query_context": {}, "query_context_order": + {}, "truncate": true, "user_prompt": {"prompt": "\nBased on the provided context + and user question, perform the following tasks:\n\n1. Select only information + directly relevant to the question.\n2. Break down compound sentences into simple, + single-idea statements. Preserve original phrasing when possible.\n3. For any + named entity with descriptive details, separate those details into distinct + propositions.\n4. Ensure clarity by replacing pronouns (e.g., \"it\", \"he\", + \"she\", \"they\", \"this\", \"that\") with the full names of the entities they + reference, and add necessary modifiers to clarify meaning.\n5. The context may + be delimited by tags such as and . Treat + everything between these tags as context.\n6. Assess whether the context sufficiently + answers the question. If it answers it partially, provide the answer; if it + does not answer it fully, specify what information is missing to answer the + question.\n7. If the context does not answer the question at all, just return + the original question as the missing information.\n8. The `citations` field + consists ONLY in a list of block IDs that are relevant to the answer, following + these rules:\n - Use the format: block-AB\n - Just mention the block IDs, + do NOT include any other text.\n - Just mention the blocks actually relevant + and that contain information used in the answer, do NOT include blocks that + are not relevant.\n - No duplicates.\n9. Do NOT hallucinate block IDs. Only + use those provided in the context.\n10. Your output must be a JSON object with + the following fields:\n - \"reason\": Explain your reasoning for the answer + or validation.\n - \"answer\": Provide a partial or complete answer to the + user query strictly from the information in the context. If there isn''t enough + information to even provide a partial answer, leave ''answer'' empty.\n - + \"missing_info_query\": If the context is insufficient, specify what information + is missing in a query shape; otherwise, leave it empty. Just return the query + needed to retrieve the missing information.\n - \"useful\": Indicate if the + context is useful to answer the question (\"yes\" or \"no\").\n - \"citations\": + List the IDs of the blocks relevant to the answer, if any (e.g., [\"block-AB\", + \"block-CD\"]).\n11. **IMPORTANT** If any extra instructions are provided, you + MUST follow them carefully when generating the answer field. These instructions + may specify the format, style, tools to use, or other requirements for the answer.\n\n\nExplica + c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar la longitud de + las respuestas en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n + oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### Chunk: 4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\nTags: + /k/text\n``` Use the max_tokens parameter on the /ask endpoint to set hard + limits on: \n - Context size: Limits the amount of retrieved information sent + to the LLM \n - Answer length: Limits the length of the generated response \n + Important Considerations \n Context Limitations: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n + ```\n\n\n---\"\n\n\n**block-AB**\n\n#### Chunk: 9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\nTags: + /k/text\n``` max_tokens: the maximum number of input tokens to put in the final + context (including the prompt, the retrieved results and the user question). + \n max_output_tokens: the maximum number of tokens to generate. \n\n\n\nLink: + https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n ```\n\n\n---\"\n\n\n**block-AC**\n\n#### + Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\nTags: /k/text\n``` \n + SDK: \n \n ```python \n from nuclia import sdk \n from nucliadb_models.search + import AskRequest, Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( + \n query= My question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( + \n display=True, # Show reasoning in the response \n effort= low , # Can be + low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can + use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning + Options: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n + ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\nTags: + /k/text\n``` ::: \n :::warning \n Enabling reasoning can use additional tokens, + which may increase your usage costs. \n You may need to increase max_tokens + to give the LLM enough room to reason and generate an answer. \n\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n ```\n\n\n---\"\n\n\n**block-AE**\n\n#### + Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\nTags: /k/text\n``` \n + optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n + ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\nTags: + /k/text\n``` \n optional max_tokens: number \\| object \n \n Defines the maximum + number of tokens that the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n + ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": false, "citation_threshold": + null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 8192, "query_context_images": + {}, "prefer_markdown": null, "json_schema": {"title": "validate_or_answer", + "description": "Validate or answer", "parameters": {"type": "object", "properties": + {"reason": {"type": "string", "description": "Reasoning for the answer or validation"}, + "answer": {"type": "string", "description": "Partial or complete answer to the + user query from the information in the context."}, "missing_info_query": {"type": + "string", "description": "Query needed to retrieve the missing information in + case the context is not enough to answer the question. If the context does not + answer the question at all, just return the original question."}, "useful": + {"type": "string", "description": "Is the context useful to answer the question?", + "enum": ["yes", "no"]}, "citations": {"type": "array", "items": {"type": "string", + "description": "Block ID cited in the answer, e.g. block-AB"}, "description": + "List of block IDs cited in the answer, if any"}}, "required": ["reason", "answer", + "missing_info_query", "useful", "citations"]}}, "format_prompt": false, "rerank_context": + false, "tools": [], "tool_choice": {"type": "required"}, "reasoning": false, + "seed": null}' headers: Accept: - - '*/*' + - application/x-ndjson Accept-Encoding: - gzip, deflate Connection: - keep-alive Content-Length: - - '361' + - '6987' + Content-Type: + - application/json Host: - - europe-1.dp.progress.cloud + - europe-1.dp.stashify.cloud User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: + - nuclia.py/4.11.5 + x-origin: + - RAO + x-show-consumption: + - 'true' + x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat response: body: - string: '{"resources":{},"relations":{"entities":{}},"query":"Esboniwch sut - i ddefnyddio''r paramedr ''max_tokens'' mewn atebion, a darparwch ddolen i''r - ddogfennaeth swyddogol.","rephrased_query":null,"total":0,"page_number":0,"page_size":20,"next_page":false,"shards":["306cbabb-72a5-417c-827f-7874e205c858"],"min_score":{"semantic":0.0,"bm25":0.0},"best_matches":[]}' + string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"reason\":\"The context + provides information on how to use the `max_tokens` parameter to control the + length of responses. It specifies that `max_tokens` sets limits on the answer + length and context size. Additionally, it includes links to the official documentation + for further details.\",\"answer\":\"Para usar el par\xE1metro `max_tokens`, + se debe establecer un l\xEDmite en la longitud de la respuesta generada. El + par\xE1metro `max_tokens` se utiliza en el endpoint /ask para limitar la longitud + de la respuesta generada. Tambi\xE9n se puede usar para limitar el tama\xF1o + del contexto. Para m\xE1s detalles, puedes consultar la documentaci\xF3n oficial + en el siguiente enlace: https://docs.rag.progress.cloud/docs/rag/advanced/consumption.\",\"missing_info_query\":\"\",\"useful\":\"yes\",\"citations\":[\"block-AA\",\"block-AB\"]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":45,\"output_tokens\":20,\"timings\":{\"generative\":4.430337170000712},\"input_nuclia_tokens\":0.045,\"output_nuclia_tokens\":0.02}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.04521,\"output\":0.0198,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Length: - - '356' + - h3=":443"; ma=2592000 + Transfer-Encoding: + - chunked access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - - application/json + - application/x-ndjson date: - - Wed, 15 Jul 2026 08:10:55 GMT + - Wed, 05 Aug 2026 07:57:01 GMT + nuclia-learning-id: + - 3332506d9f554b70b464562c52d6c050 + nuclia-learning-model: + - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '19' + - '4436' x-nuclia-trace-id: - - a3613d7081f6d17d8cee1e3dd35d91c4 + - dec9ad587d2e1065b9b2e8fd2594ebc4 status: code: 200 message: OK - request: - body: '{"data": ["6e8250e6b5264156988657a221fd5e94/t/page/0-397", "9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412", - "f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299", "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276", - "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709", "44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668", - "c27a1e5f5ddb4b118921345d713401b8/t/page/351-554", "0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224", - "66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833", "0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349", - "4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340", "4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326", - "89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575", "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043", - "43004f553e534ffe9c9e735856bd9b23/t/page/480-703", "43004f553e534ffe9c9e735856bd9b23/t/page/212-480", - "dd41482018924facb5dbb87a7d53f122/t/page/3310-3757", "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221", - "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977", "e8525e64c5b44982b958d32cf6090613/t/page/2808-3011"], - "hydration": {"resource": {"title": true, "summary": false, "origin": false, - "security": false}, "field": {"text": {"value": false, "extracted_text": false}, - "file": {"value": false, "extracted_text": false}, "link": {"value": false, - "extracted_text": false}, "conversation": {"value": false}, "generic": {"value": - false, "extracted_text": false}}, "paragraph": {"text": false, "image": {"source_image": - false}, "table": {"table_page_preview": true}, "page": {"page_with_visual": - false}, "related": null}}}' + body: '{"question": "", "retrieval": true, "user_id": "summarize", "system": "You + are a helpful AI assistant. Your role is to provide accurate, clear, and well-structured + answers based strictly on the information provided to you.\nKey principles:\n- + Answer only using the information in the provided context\n- Do not use external + knowledge, assumptions, or prior experience\n- Maintain a professional and informative + tone\n- Be concise yet thorough\n- If information is insufficient, acknowledge + this clearly\n\nAlways follow any additional instructions provided about format, + style, or domain-specific behavior.", "chat_history": [], "context": [], "query_context": + {}, "query_context_order": {}, "truncate": true, "user_prompt": {"prompt": "\n## + Question\nExplica c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar + la longitud de las respuestas en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n + oficial.\n\n## Provided Context\n[START OF CONTEXT]\n## Retrieval on nuclia-docs + Knowledge Box\n\n# Explica c\u00f3mo usar el par\u00e1metro `max_tokens` para + controlar la longitud de las respuestas en espa\u00f1ol y proporciona un enlace + a la documentaci\u00f3n oficial.\n\n Para usar el par\u00e1metro `max_tokens`, + se debe establecer un l\u00edmite en la longitud de la respuesta generada. El + par\u00e1metro `max_tokens` se utiliza en el endpoint /ask para limitar la longitud + de la respuesta generada. Tambi\u00e9n se puede usar para limitar el tama\u00f1o + del contexto. Para m\u00e1s detalles, puedes consultar la documentaci\u00f3n + oficial en el siguiente enlace: https://docs.rag.progress.cloud/docs/rag/advanced/consumption.\n[END + OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all context; it may + be lengthy or detailed\n- Do not omit or overlook any relevant information\n- + Existing context summaries are answer attempts produced by retrieval agents. + Treat them as first-class evidence and preserve their supported facts.\n- Combine + complementary summaries from multiple contexts when the question has multiple + parts. Do not require every context to answer the whole question by itself.\n- + If a context summary directly answers the question, do not replace it with an + insufficient-data answer merely because one retrieved chunk is incomplete; use + the chunks for supporting citations.\n- If the context is incomplete or insufficient, + state: \"Not enough data to answer this.\"\n- Read carefully any extra instructions + below if provided and use them to answer\n\nNow provide your answer to the question: + Explica c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar la longitud + de las respuestas en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n + oficial."}, "citations": null, "citation_threshold": null, "generative_model": + "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": + null, "json_schema": null, "format_prompt": false, "rerank_context": false, + "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": null}' 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Follow these steps:\n\n1. Carefully analyze the main question and + all context provided, including sources, previous questions and answers, and + any other relevant information.\n2. I present, assess whether previous questions + and answers (history) are necessary for rephrasing. Only use history if it is + relevant and improves the clarity or specificity of the main question; otherwise, + ignore it.\n3. If the question can be made clearer or more specific, rephrase + it accordingly. If it is already clear and focused, return it unchanged.\n4. + Only use information present in the provided context. Do not introduce external + knowledge or assumptions.\n5. 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Example queries: How many ..."}, "semantic_query": + {"type": "string", "description": "Rephrase this question so its better for + semantic retrieval, and keep the rephrased question in the same language as + the original. Please define ONLY the question without any explanation. JUST + A SENTENCE. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST ONE SENTENCE"}, "lexical_query": + {"type": "string", "description": "Rephrase this question so its better for + lexical retrieval, translate the lexical rephrased question to cy. Please define + ONLY the question without any explanation. JUST A SENTENCE. 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Then, create a new workflow - in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Chat mode \\n If you want to use the Smart Agent in a chat interface, you - need the following: \\n \\n Enable the Session history option in the Smart - Agent configuration. This will allow the Smart Agent to take into account - the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Then connect your sources as Registered Agents to the Smart Agent. It is very - important that you provide an extensive description of each registered agent, - so that the Smart Agent can understand what each source is about and when - to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n reactive: The Smart Agent will decide what to do first, and will plan - the next steps based on the information it retrieves. It is expected to be - faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, - and will execute them. It will be slower but more accurate when processing - complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Also select the proper function for each registered agent, depending on the - type of source (MCP agents will not need one, the functions are provided dynamically - by the MCP server). \\n In the Smart Agent configuration, you can select the - planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - In the Summarize Agent, enable the Conversational mode. This will allow the - Summarize Agent to generate a final answer that will not repeat the information - already provided in the previous conversation, and will be more natural for - a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Custom frontend \\n You can also create a custom frontend for your Retrieval - Agent. This allows you to have full control over the user interface and user - experience. \\n You can directly implement the API calls to your Retrieval - Agent in your frontend code (see the Websocket API section for more details), - or you can use the JavaScript SDK provided by Agentic to simplify the integration. - \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based - system (for example Claude Cowork or Copilot), it is reachable throught MCP. - \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval - Agent can be deployed in different ways, depending on your needs and the environment - you are working in. \\n Ready-to-use widget \\n The easiest way to deploy - your Retrieval Agent is to use the ready-to-use widget. You can embed it in - your website or application, and it will provide a chat user interface for - interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" - Go to the Widgets section in the left menu, and click on Create widget to - create a new widget. You can customize its appearance, and then copy the generated - code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{\"/k\":{\"/k/text\":5294}},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"fulltext\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-resources\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-search\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-rag-lab\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"account-arag\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-kv-schemas\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"user-profile\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-users\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-widgets\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-remi-analytics\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"agent-users\",\"labels\":[]}],\"facets\":{},\"query\":\"\",\"total\":2013,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" + string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"semantic_query\":\"Explica + el uso del par\xE1metro `max_tokens` para controlar la longitud de las respuestas + y proporciona un enlace a la documentaci\xF3n oficial.\",\"lexical_query\":\"Sut + mae'r paramedr `max_tokens` yn rheoli hyd ymatebion?\",\"visual\":false,\"keywords_filter\":[\"max_tokens\",\"longitud\"],\"reason\":\"The + user is asking for an explanation of how to use the `max_tokens` parameter + to control response length and a link to official documentation, which can + be directly answered by a knowledge base search.\",\"pre_queries\":[]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":36,\"output_tokens\":77,\"timings\":{\"generative\":1.7809446820028825},\"input_nuclia_tokens\":0.036,\"output_nuclia_tokens\":0.077}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0357,\"output\":0.077,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - h3=":443"; ma=2592000 - Content-Length: - - '16898' + Transfer-Encoding: + - chunked access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - - application/json + - application/x-ndjson date: - - Wed, 15 Jul 2026 08:11:05 GMT + - Wed, 05 Aug 2026 07:57:10 GMT + nuclia-learning-id: + - 69c65dd846b848dc883284335a452d8d + nuclia-learning-model: + - gemini-2.5-flash via: - 1.1 google x-envoy-upstream-service-time: - - '71' + - '1786' x-nuclia-trace-id: - - 903025bdfd59ddc87309b5ce82eff861 + - 9ac36e1828ae63fa42d77b222840f9b8 status: code: 200 message: OK - request: - body: '{"user_id": "arag-ask", "texts": ["Explica c\u00f3mo usar el par\u00e1metro - `max_tokens` en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n - oficial."]}' + body: '{"question": "Explica c\u00f3mo usar el par\u00e1metro `max_tokens` para + controlar la longitud de las respuestas en espa\u00f1ol, y proporciona un enlace + a la documentaci\u00f3n oficial.", "user_id": "arag-ask-rerank", "context": + {"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412": " max_tokens: the maximum + number of input tokens to put in the final context (including the prompt, the + retrieved results and the user question). \n max_output_tokens: the maximum + number of tokens to generate. \n\n", "c27a1e5f5ddb4b118921345d713401b8/t/page/351-554": + " full: boolean \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:386 + \n \n max_messages? \n \n optional max_messages: number \n \n Defined in \n + libs/sdk-core/src/lib/db/kb/kb.models.ts:387 \n \n name \n \n\n", "dd41482018924facb5dbb87a7d53f122/t/page/3310-3757": + " ) \n time.sleep(wait_time) \n retries += 1 \n else: \n response.raise_for_status() + \n raise Exception( Max retries exceeded ) \n Example usage \n url = https://your-endpoint + \n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_try_after_info(url, + headers) \n print(data) \n ``` \n These examples demonstrate how to handle rate + limits effectively, ensuring that your application respects the limits and retries + appropriately.\n", "dd41482018924facb5dbb87a7d53f122/t/page/1900-2653": " retries + = 0 \n while retries < max_retries: \n response = requests.get(url, headers=headers) + \n if response.status_code == 200: \n return response.json() \n elif response.status_code + == 429: \n wait_time = 2 retries # Exponential backoff: 2^retries \n print(f + Rate limit exceeded. Retrying in {wait_time} seconds... ) \n time.sleep(wait_time) + \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( + Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers + = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_exponential_backoff(url, + headers) \n print(data) \n ``` \n Example 2: Ingestion back pressure limits + \n Here''s an example of how to use the try_after key from the response to manage + rate limits: \n\n", "43004f553e534ffe9c9e735856bd9b23/t/page/480-703": " \n + optional max_images: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 + \n \n output_tokens \n \n output_tokens: object \n \n default_max? \n \n optional + default_max: number \n \n max \n \n max: number \n \n min? \n \n\n", "43004f553e534ffe9c9e735856bd9b23/t/page/212-480": + " \n optional driver: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 + \n \n input_tokens \n \n input_tokens: object \n \n max \n \n max: number \n + \n min? \n \n optional min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \n \n max_images? \n\n", "e8525e64c5b44982b958d32cf6090613/t/page/2808-3011": + " \n optional max_tokens: number \\| object \n \n Defines the maximum number + of tokens that the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \n \n min_score? \n\n", "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221": + " \n optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? + \n\n", "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709": " ::: \n :::warning + \n Enabling reasoning can use additional tokens, which may increase your usage + costs. \n You may need to increase max_tokens to give the LLM enough room to + reason and generate an answer. \n\n", "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276": + " \n SDK: \n \n ```python \n from nuclia import sdk \n from nucliadb_models.search + import AskRequest, Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( + \n query= My question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( + \n display=True, # Show reasoning in the response \n effort= low , # Can be + low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can + use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning + Options: \n\n", "f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299": "@nuclia/core + \u2022 Docs \n \n @nuclia/core / PageToken \n Interface: PageToken \n Properties + \n height \n \n height: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 + \n \n line \n \n line: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 + \n \n text \n \n\n", "44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668": " + \n step: Information about the current processing step \n module: The module + being executed (e.g., rephrase , basic_ask , remi ) \n title: Display title + for the step \n value: Result of the step \n reason: Explanation for the step + \n timeit: Time taken in seconds \n \n input_nuclia_tokens/output_nuclia_tokens: + Token usage \n \n \n\n", "4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340": + " Use the max_tokens parameter on the /ask endpoint to set hard limits on: \n + - Context size: Limits the amount of retrieved information sent to the LLM \n + - Answer length: Limits the length of the generated response \n Important Considerations + \n Context Limitations: \n\n", "4039d76b0fff4962900836ab3fdec9f7/t/page/3340-4136": + " - Restricting context size may result in less relevant answers since the LLM + has less information to work with \n - Balance between cost control and answer + quality \n Answer Length Limitations: \n - The LLM might not complete its response + if it hits the token limit, potentially cutting sentences mid-way \n - Recommended + approach: Include length requirements in your prompt (e.g., Please answer in + less than 200 words ) rather than relying solely on hard limits \n - This allows + the LLM to naturally conclude its response within the desired length \n How + to Monitor Token Consumption \n Understanding Token Consumption Data \n You + can receive detailed token consumption information from the following endpoints + that utilize LLM models: ask, chat, remi, query, sentence, summarize, tokens, + and rerank. \n\n", "4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326": " \n + Large context: Results from using RAG strategies like Full resource or Neighbouring + paragraphs , or from using the extra_context parameter \n Long questions: More + detailed or complex questions require more input tokens \n Long prompts: Extensive + system prompts increase the input token count \n Detailed answers: Comprehensive + responses require more output tokens \n Images in context: When using multimodal + models, images included in the retrieved context significantly increase token + consumption \n \n How to Limit and Control Token Consumption \n Strategy 1: + Optimize Your Parameters \n The first approach to reducing token consumption + is to fine-tune your request parameters: \n\n", "4039d76b0fff4962900836ab3fdec9f7/t/page/5396-5615": + " - input: Tokens used for the prompt, context, and question \n - output: Tokens + used for the generated response \n - image: Tokens used for image processing + (when applicable) \n Customer Key Tokens (customer_key_tokens): \n\n", "89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575": + " \n \n Maximum supported input tokens: \n Description: The maximum number of + tokens that the model can accept as input. Be mindful that this takes into account + the tokens used in the prompt, query and context. Also take note that some models + may provide their context window as the total between input and output tokens, + while others may provide it as the input tokens only. \n\n", "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043": + " Description: The maximum number of tokens that the model can generate as output. + Again, we should keep in mind that this value summed to the Maximum supported + input tokens should not exceed the total context size supported by the model. + \n\n", "b6a6202b9f0d4611a980293ce53337d6/t/page/265-405": " last: boolean \n + \n page \n \n page: number \n \n size \n \n size: number \n \n Defined in \n + libs/sdk-core/src/lib/db/training/training.models.ts:36\n", "42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696": + " \n optional max_paragraph: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 + \n \n name? \n \n optional name: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\n"}}' headers: Accept: - '*/*' @@ -563,1729 +386,189 @@ interactions: Connection: - keep-alive Content-Length: - - '145' + - '8322' + Content-Type: + - application/json Host: - - europe-1.dp.progress.cloud + - europe-1.dp.stashify.cloud User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: + - nuclia.py/4.11.5 + x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/predict/run-agents-text + uri: https://europe-1.dp.stashify.cloud/api/v1/predict/rerank response: body: - string: '{"results":[{"input_nuclia_tokens":0.0,"output_nuclia_tokens":0.0,"time":0.00010657310485839844,"payloads":[]}]}' + string: '{"context_scores":{"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340":0.8020908832550049,"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412":0.295738160610199,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709":0.10284407436847687,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276":0.07068779319524765,"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757":0.06816437840461731,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221":0.054098695516586304,"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011":0.02876158617436886,"4039d76b0fff4962900836ab3fdec9f7/t/page/3340-4136":0.018725162371993065,"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043":0.015130727551877499,"dd41482018924facb5dbb87a7d53f122/t/page/1900-2653":0.014172366820275784,"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575":0.013955709524452686,"43004f553e534ffe9c9e735856bd9b23/t/page/212-480":0.011072159744799137,"4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326":0.009974921122193336,"43004f553e534ffe9c9e735856bd9b23/t/page/480-703":0.005469274707138538,"4039d76b0fff4962900836ab3fdec9f7/t/page/5396-5615":0.002453428227454424,"c27a1e5f5ddb4b118921345d713401b8/t/page/351-554":0.0015247863484546542,"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696":0.0009075025445781648,"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299":0.0005463420529849827,"44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668":0.00039666122756898403,"b6a6202b9f0d4611a980293ce53337d6/t/page/265-405":6.868318450869992e-05}}' headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - - '112' + - '1462' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 08:11:05 GMT + - Wed, 05 Aug 2026 07:57:13 GMT + nuclia-learning-model: + - bge-reranker-v2-m3 via: - 1.1 google x-envoy-upstream-service-time: - - '77' + - '87' x-nuclia-trace-id: - - b6014ac30500dc75acb7511c85029cca + - 6805c19285258a2a8bf63f879102da69 status: code: 200 message: OK - request: - body: '{"query": "Esboniwch sut i ddefnyddio''r paramedr `max_tokens` a darparwch - ddolen i''r ddogfennaeth swyddogol.", "filters": [], "show": ["basic", "origin", - "extra", "extracted", "values", "relations"], "extracted": ["text", "metadata", - "file", "link"], "security": {"groups": []}, "features": ["keyword"], "reranker": - "noop", "keyword_filters": ["max_tokens", "par\u00e1metro"]}' + body: '{"question": "", "retrieval": true, "user_id": "rao_answer_summary-ask", + "system": null, "chat_history": [], "context": [], "query_context": {}, "query_context_order": + {}, "truncate": true, "user_prompt": {"prompt": "\nBased on the provided context + and user question, perform the following tasks:\n\n1. Select only information + directly relevant to the question.\n2. Break down compound sentences into simple, + single-idea statements. Preserve original phrasing when possible.\n3. For any + named entity with descriptive details, separate those details into distinct + propositions.\n4. Ensure clarity by replacing pronouns (e.g., \"it\", \"he\", + \"she\", \"they\", \"this\", \"that\") with the full names of the entities they + reference, and add necessary modifiers to clarify meaning.\n5. The context may + be delimited by tags such as and . Treat + everything between these tags as context.\n6. Assess whether the context sufficiently + answers the question. If it answers it partially, provide the answer; if it + does not answer it fully, specify what information is missing to answer the + question.\n7. If the context does not answer the question at all, just return + the original question as the missing information.\n8. The `citations` field + consists ONLY in a list of block IDs that are relevant to the answer, following + these rules:\n - Use the format: block-AB\n - Just mention the block IDs, + do NOT include any other text.\n - Just mention the blocks actually relevant + and that contain information used in the answer, do NOT include blocks that + are not relevant.\n - No duplicates.\n9. Do NOT hallucinate block IDs. Only + use those provided in the context.\n10. Your output must be a JSON object with + the following fields:\n - \"reason\": Explain your reasoning for the answer + or validation.\n - \"answer\": Provide a partial or complete answer to the + user query strictly from the information in the context. If there isn''t enough + information to even provide a partial answer, leave ''answer'' empty.\n - + \"missing_info_query\": If the context is insufficient, specify what information + is missing in a query shape; otherwise, leave it empty. Just return the query + needed to retrieve the missing information.\n - \"useful\": Indicate if the + context is useful to answer the question (\"yes\" or \"no\").\n - \"citations\": + List the IDs of the blocks relevant to the answer, if any (e.g., [\"block-AB\", + \"block-CD\"]).\n11. **IMPORTANT** If any extra instructions are provided, you + MUST follow them carefully when generating the answer field. These instructions + may specify the format, style, tools to use, or other requirements for the answer.\n\n\nExplica + c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar la longitud de + las respuestas en espa\u00f1ol, y proporciona un enlace a la documentaci\u00f3n + oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### Chunk: 4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\nTags: + /k/text\n``` Use the max_tokens parameter on the /ask endpoint to set hard + limits on: \n - Context size: Limits the amount of retrieved information sent + to the LLM \n - Answer length: Limits the length of the generated response \n + Important Considerations \n Context Limitations: \n\n ```\n\n\n---\"\n\n\n**block-AB**\n\n#### + Chunk: 9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\nTags: /k/text\n``` max_tokens: + the maximum number of input tokens to put in the final context (including the + prompt, the retrieved results and the user question). \n max_output_tokens: + the maximum number of tokens to generate. \n\n ```\n\n\n---\"\n\n\n**block-AC**\n\n#### + Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\nTags: /k/text\n``` ::: + \n :::warning \n Enabling reasoning can use additional tokens, which may increase + your usage costs. \n You may need to increase max_tokens to give the LLM enough + room to reason and generate an answer. \n\n ```\n\n\n---\"\n\n\n**block-AD**\n\n#### + Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\nTags: /k/text\n``` \n + SDK: \n \n ```python \n from nuclia import sdk \n from nucliadb_models.search + import AskRequest, Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( + \n query= My question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( + \n display=True, # Show reasoning in the response \n effort= low , # Can be + low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can + use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning + Options: \n\n ```\n\n\n---\"\n\n\n**block-AE**\n\n#### Chunk: dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\nTags: + /k/text\n``` ) \n time.sleep(wait_time) \n retries += 1 \n else: \n response.raise_for_status() + \n raise Exception( Max retries exceeded ) \n Example usage \n url = https://your-endpoint + \n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_try_after_info(url, + headers) \n print(data) \n ``` \n These examples demonstrate how to handle rate + limits effectively, ensuring that your application respects the limits and retries + appropriately.\n ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\nTags: + /k/text\n``` \n optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? + \n\n ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": false, "citation_threshold": + null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 8192, "query_context_images": + {}, "prefer_markdown": null, "json_schema": {"title": "validate_or_answer", + "description": "Validate or answer", "parameters": {"type": "object", "properties": + {"reason": {"type": "string", "description": "Reasoning for the answer or validation"}, + "answer": {"type": "string", "description": "Partial or complete answer to the + user query from the information in the context."}, "missing_info_query": {"type": + "string", "description": "Query needed to retrieve the missing information in + case the context is not enough to answer the question. If the context does not + answer the question at all, just return the original question."}, "useful": + {"type": "string", "description": "Is the context useful to answer the question?", + "enum": ["yes", "no"]}, "citations": {"type": "array", "items": {"type": "string", + "description": "Block ID cited in the answer, e.g. block-AB"}, "description": + "List of block IDs cited in the answer, if any"}}, "required": ["reason", "answer", + "missing_info_query", "useful", "citations"]}}, "format_prompt": false, "rerank_context": + false, "tools": [], "tool_choice": {"type": "required"}, "reasoning": false, + "seed": null}' headers: Accept: - - '*/*' + - application/x-ndjson Accept-Encoding: - gzip, deflate Connection: - keep-alive Content-Length: - - '347' - Host: - - europe-1.dp.progress.cloud - User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: - - DUMMY - method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find - response: - body: - string: '{"resources":{},"relations":{"entities":{}},"query":"Esboniwch sut - i ddefnyddio''r paramedr `max_tokens` a darparwch ddolen i''r ddogfennaeth - swyddogol.","rephrased_query":null,"total":0,"page_number":0,"page_size":20,"next_page":false,"shards":["306cbabb-72a5-417c-827f-7874e205c858"],"min_score":{"semantic":0.0,"bm25":0.0},"best_matches":[]}' - headers: - Alt-Svc: - - h3=":443"; ma=2592000 - Content-Length: - - '342' - access-control-expose-headers: - - X-NUCLIA-TRACE-ID - content-type: + - '6755' + Content-Type: - application/json - date: - - Wed, 15 Jul 2026 08:11:07 GMT - via: - - 1.1 google - x-envoy-upstream-service-time: - - '18' - x-nuclia-trace-id: - - c9e82256f6716efce37aba8dca5f700f - status: - code: 200 - message: OK -- request: - body: '{"query": "Explica el uso del par\u00e1metro `max_tokens` y enlaza a la - documentaci\u00f3n oficial.", "filters": [], "min_score": {"semantic": 0.4}, - "show": ["basic", "origin", "extra", "extracted", "values", "relations"], "extracted": - ["text", "metadata", "file", "link"], "vectorset": "multilingual-2024-05-06", - "security": {"groups": []}, "features": ["semantic"], "reranker": "noop"}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '352' Host: - - europe-1.dp.progress.cloud + - europe-1.dp.stashify.cloud User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: + - nuclia.py/4.11.5 + x-origin: + - RAO + x-show-consumption: + - 'true' + x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat response: body: - string: "{\"resources\":{\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs - > rag > advanced > consumption.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-10-03T08:32:26.341394\",\"modified\":\"2026-06-09T08:18:16.730959\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - consumption\\ntitle: Token consumption\\n---\\n\\nimport Tabs from \\\"@theme/Tabs\\\";\\nimport - TabItem from \\\"@theme/TabItem\\\";\\n\\n# Token consumption\\n\\nAgentic - RAG is a license and consumption-based service. This means that you pay for - the computational resources you consume. The consumption is measured in **Agentic - RAG tokens**.\\nAll public 3rd-party LLMs base their pricing on the number - of tokens consumed. In the LLM world, a token is around 4-5 characters on - average, which might fit an entire word or be split into parts. The number - of tokens is proportional to the amount of text, measured in chunks of 4-5 - characters. It closely relates to words but not entirely. The longer a sentence - is, the more tokens it will consume to read or to generate it.\\nSince all - these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize - the cost across all of them.\\n\\n## How Tokens Are Consumed in RAG\\n\\nWhen - a user asks a question to your Knowledge Box, the token consumption process - follows these steps:\\n\\n1. **Question Processing**: The system finds the - most relevant paragraphs to answer the question\\n2. **Context Assembly**: - These paragraphs are used as context when calling the LLM model\\n3. **Prompt - Creation**: Agentic RAG assembles the **prompt**, **context**, and **question** - into a single string\\n4. **LLM Processing**: This complete string is sent - to the LLM, corresponding to a certain number of **input tokens**\\n5. **Answer - Generation**: The LLM generates the answer, which corresponds to a certain - number of **output tokens**\\n\\n**Total consumption** = Input tokens + Output - tokens + Image tokens\\n\\n### Factors That Impact Token Consumption\\n\\nToken - consumption is directly affected by:\\n\\n- **Large context**: Results from - using RAG strategies like \\\"Full resource\\\" or \\\"Neighbouring paragraphs\\\", - or from using the `extra_context` parameter\\n- **Long questions**: More detailed - or complex questions require more input tokens\\n- **Long prompts**: Extensive - system prompts increase the input token count\\n- **Detailed answers**: Comprehensive - responses require more output tokens\\n- **Images in context**: When using - multimodal models, images included in the retrieved context significantly - increase token consumption\\n\\n## How to Limit and Control Token Consumption\\n\\n### - Strategy 1: Optimize Your Parameters\\n\\nThe first approach to reducing token - consumption is to fine-tune your request parameters:\\n\\n- **Optimize prompts**: - Ensure your prompts are concise and focused, avoiding unnecessary verbosity\\n- - **Control resource scope**: When using the \\\"Full resource\\\" strategy, - use the `count` attribute to limit the number of resources returned\\n- **Tune - neighboring context**: For the \\\"Neighbouring paragraphs\\\" strategy, optimize - the `before` and `after` attributes to balance context quality with token - efficiency\\n- **Manage summary length**: When using the \\\"Hierarchical\\\" - strategy, ensure that resource summaries are appropriately sized\\n- **Choose - efficient models**: Select LLMs that offer better token efficiency (typically, - ChatGPT 4o-mini is more cost-effective than ChatGPT 4o)\\n\\n### Strategy - 2: Set Hard Limits\\n\\nYou can implement safeguards against excessive token - consumption:\\n\\nUse the `max_tokens` parameter on the [`/ask` endpoint](/docs/api#tag/Search/operation/ask_knowledgebox_endpoint_kb__kbid__ask_post) - to set hard limits on:\\n- **Context size**: Limits the amount of retrieved - information sent to the LLM\\n- **Answer length**: Limits the length of the - generated response\\n\\n#### Important Considerations\\n\\n**Context Limitations**:\\n- - Restricting context size may result in less relevant answers since the LLM - has less information to work with\\n- Balance between cost control and answer - quality\\n\\n**Answer Length Limitations**:\\n- The LLM might not complete - its response if it hits the token limit, potentially cutting sentences mid-way\\n- - **Recommended approach**: Include length requirements in your prompt (e.g., - \\\"Please answer in less than 200 words\\\") rather than relying solely on - hard limits\\n- This allows the LLM to naturally conclude its response within - the desired length\\n\\n## How to Monitor Token Consumption\\n\\n### Understanding - Token Consumption Data\\n\\nYou can receive detailed token consumption information - from the following endpoints that utilize LLM models: `ask`, `chat`, `remi`, - `query`, `sentence`, `summarize`, `tokens`, and `rerank`.\\n\\n:::note\\nThe - `rephrase` endpoint currently does not support token consumption monitoring.\\n:::\\n\\nTo - receive token consumption data, you must include the following header in your - request:\\n```\\nX-SHOW-CONSUMPTION: true\\n```\\n\\nThe token consumption - data is provided in different formats depending on the response type:\\n- - **Streaming responses** (`application/x-ndjson`): Token consumption appears - as a separate JSON chunk with type \\\"consumption\\\"\\n- **Standard responses** - (`application/json`): Token consumption is included in a \\\"consumption\\\" - field within the main response\\n\\n### Token Consumption Response Format\\n\\n\\n \\n ```json\\n {\\n \\\"item\\\": - {\\n \\\"type\\\": \\\"consumption\\\",\\n \\\"normalized_tokens\\\": - {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": - 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": - 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n - \ }\\n }\\n ```\\n \\n \\n ```json\\n {\\n \\\"consumption\\\": {\\n \\\"normalized_tokens\\\": - {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": - 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": - 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n - \ }\\n }\\n ```\\n \\n\\n\\n### Understanding - Token Types\\n\\n**Normalized Tokens** (`normalized_tokens`):\\n- These represent - the number of Agentic RAG tokens consumed and that you will be billed for\\n- - Values are normalized across different LLM providers for consistent billing\\n- - Include separate counts for:\\n - `input`: Tokens used for the prompt, context, - and question\\n - `output`: Tokens used for the generated response\\n - - `image`: Tokens used for image processing (when applicable)\\n\\n**Customer - Key Tokens** (`customer_key_tokens`):\\n- These represent tokens consumed - when using your own LLM API keys\\n- These tokens are **not billed** by Agentic - RAG since you're using your own API keys\\n- Values are also normalized for - comparison purposes across different providers\\n\",\"format\":\"MARKDOWN\",\"md5\":\"204fe47dbd7eb38d465d05fa7538e51e\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: consumption \\n title: Token consumption \\n \\n import Tabs from - @theme/Tabs ; \\n import TabItem from @theme/TabItem ; \\n Token consumption - \\n Agentic RAG is a license and consumption-based service. This means that - you pay for the computational resources you consume. The consumption is measured - in Agentic RAG tokens. \\n All public 3rd-party LLMs base their pricing on - the number of tokens consumed. In the LLM world, a token is around 4-5 characters - on average, which might fit an entire word or be split into parts. The number - of tokens is proportional to the amount of text, measured in chunks of 4-5 - characters. It closely relates to words but not entirely. The longer a sentence - is, the more tokens it will consume to read or to generate it. \\n Since all - these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize - the cost across all of them. \\n How Tokens Are Consumed in RAG \\n When a - user asks a question to your Knowledge Box, the token consumption process - follows these steps: \\n \\n Question Processing: The system finds the most - relevant paragraphs to answer the question \\n Context Assembly: These paragraphs - are used as context when calling the LLM model \\n Prompt Creation: Agentic - RAG assembles the prompt, context, and question into a single string \\n LLM - Processing: This complete string is sent to the LLM, corresponding to a certain - number of input tokens \\n Answer Generation: The LLM generates the answer, - which corresponds to a certain number of output tokens \\n \\n Total consumption - = Input tokens + Output tokens + Image tokens \\n Factors That Impact Token - Consumption \\n Token consumption is directly affected by: \\n \\n Large context: - Results from using RAG strategies like Full resource or Neighbouring paragraphs - , or from using the extra_context parameter \\n Long questions: More detailed - or complex questions require more input tokens \\n Long prompts: Extensive - system prompts increase the input token count \\n Detailed answers: Comprehensive - responses require more output tokens \\n Images in context: When using multimodal - models, images included in the retrieved context significantly increase token - consumption \\n \\n How to Limit and Control Token Consumption \\n Strategy - 1: Optimize Your Parameters \\n The first approach to reducing token consumption - is to fine-tune your request parameters: \\n \\n Optimize prompts: Ensure - your prompts are concise and focused, avoiding unnecessary verbosity \\n Control - resource scope: When using the Full resource strategy, use the count attribute - to limit the number of resources returned \\n Tune neighboring context: For - the Neighbouring paragraphs strategy, optimize the before and after attributes - to balance context quality with token efficiency \\n Manage summary length: - When using the Hierarchical strategy, ensure that resource summaries are appropriately - sized \\n Choose efficient models: Select LLMs that offer better token efficiency - (typically, ChatGPT 4o-mini is more cost-effective than ChatGPT 4o) \\n \\n - Strategy 2: Set Hard Limits \\n You can implement safeguards against excessive - token consumption: \\n Use the max_tokens parameter on the /ask endpoint to - set hard limits on: \\n - Context size: Limits the amount of retrieved information - sent to the LLM \\n - Answer length: Limits the length of the generated response - \\n Important Considerations \\n Context Limitations: \\n - Restricting context - size may result in less relevant answers since the LLM has less information - to work with \\n - Balance between cost control and answer quality \\n Answer - Length Limitations: \\n - The LLM might not complete its response if it hits - the token limit, potentially cutting sentences mid-way \\n - Recommended approach: - Include length requirements in your prompt (e.g., Please answer in less than - 200 words ) rather than relying solely on hard limits \\n - This allows the - LLM to naturally conclude its response within the desired length \\n How to - Monitor Token Consumption \\n Understanding Token Consumption Data \\n You - can receive detailed token consumption information from the following endpoints - that utilize LLM models: ask, chat, remi, query, sentence, summarize, tokens, - and rerank. \\n :::note \\n The rephrase endpoint currently does not support - token consumption monitoring. \\n ::: \\n To receive token consumption data, - you must include the following header in your request: \\n X-SHOW-CONSUMPTION: - true \\n The token consumption data is provided in different formats depending - on the response type: \\n - Streaming responses (application/x-ndjson): Token - consumption appears as a separate JSON chunk with type consumption \\n - Standard - responses (application/json): Token consumption is included in a consumption - field within the main response \\n Token Consumption Response Format \\n \\n - \\n json \\n { \\n item : { \\n type : consumption , \\n normalized_tokens - : { \\n input : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens - : { \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n - \\n \\n json \\n { \\n consumption : { \\n normalized_tokens : { \\n input - : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens : { - \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n \\n - \\n Understanding Token Types \\n Normalized Tokens (normalized_tokens): \\n - - These represent the number of Agentic RAG tokens consumed and that you will - be billed for \\n - Values are normalized across different LLM providers for - consistent billing \\n - Include separate counts for: \\n - input: Tokens - used for the prompt, context, and question \\n - output: Tokens used for the - generated response \\n - image: Tokens used for image processing (when applicable) - 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> develop > js sdk > interfaces > PredictAnswerOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:11.443619\",\"modified\":\"2026-07-14T12:50:46.385594\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / PredictAnswerOptions\\n\\n# - Interface: PredictAnswerOptions\\n\\n## Properties\\n\\n### chat\\\\_history?\\n\\n> - `optional` **chat\\\\_history**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:242](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L242)\\n\\n***\\n\\n### - citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L249)\\n\\n***\\n\\n### - citations?\\n\\n> `optional` **citations**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L248)\\n\\n***\\n\\n### - context?\\n\\n> `optional` **context**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:243](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L243)\\n\\n***\\n\\n### - format\\\\_prompt?\\n\\n> `optional` **format\\\\_prompt**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:258](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L258)\\n\\n***\\n\\n### - generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L250)\\n\\n***\\n\\n### - json\\\\_schema?\\n\\n> `optional` **json\\\\_schema**: `object`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:257](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L257)\\n\\n***\\n\\n### - max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L251)\\n\\n***\\n\\n### - prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:256](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L256)\\n\\n***\\n\\n### - query\\\\_context?\\n\\n> `optional` **query\\\\_context**: `string`[] \\\\| - `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:244](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L244)\\n\\n***\\n\\n### - query\\\\_context\\\\_images?\\n\\n> `optional` **query\\\\_context\\\\_images**: - `object`\\n\\n#### b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> - **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:252](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L252)\\n\\n***\\n\\n### - query\\\\_context\\\\_order?\\n\\n> `optional` **query\\\\_context\\\\_order**: - `object`\\n\\n#### Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:245](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L245)\\n\\n***\\n\\n### - reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:260](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L260)\\n\\n***\\n\\n### - rerank\\\\_context?\\n\\n> `optional` **rerank\\\\_context**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:259](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L259)\\n\\n***\\n\\n### - retrieval?\\n\\n> `optional` **retrieval**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:240](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L240)\\n\\n***\\n\\n### - system?\\n\\n> `optional` **system**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:241](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L241)\\n\\n***\\n\\n### - truncate?\\n\\n> `optional` **truncate**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L246)\\n\\n***\\n\\n### - user\\\\_prompt?\\n\\n> `optional` **user\\\\_prompt**: `object`\\n\\n#### - prompt\\n\\n> **prompt**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"470be50f3c6aeeff5ae3310ed007b9b3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / PredictAnswerOptions \\n Interface: PredictAnswerOptions - \\n Properties \\n chat_history? \\n \\n optional chat_history: ContextEntry[] - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:242 \\n - \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:249 \\n \\n citations? - \\n \\n optional citations: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:248 - \\n \\n context? \\n \\n optional context: ContextEntry[] \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:243 \\n \\n format_prompt? - \\n \\n optional format_prompt: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:258 - \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 \\n \\n json_schema? - \\n \\n optional json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 - \\n \\n max_tokens? \\n \\n optional max_tokens: number \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 \\n \\n prefer_markdown? - \\n \\n optional prefer_markdown: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 - \\n \\n query_context? \\n \\n optional query_context: string[] \\\\| object - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:244 \\n - \\n query_context_images? \\n \\n optional query_context_images: object \\n - \\n b64encoded \\n \\n b64encoded: string \\n \\n content_type \\n \\n content_type: - string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:252 - \\n \\n query_context_order? \\n \\n optional query_context_order: object - \\n \\n Index Signature \\n [key: string]: number \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:245 - \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:260 \\n \\n rerank_context? - \\n \\n optional rerank_context: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:259 - \\n \\n retrieval? \\n \\n optional retrieval: boolean \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/ask.models.ts:240 \\n \\n system? \\n - \\n optional system: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:241 - \\n \\n truncate? \\n \\n optional truncate: boolean \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/search/ask.models.ts:246 \\n \\n user_prompt? \\n - \\n optional user_prompt: object \\n \\n prompt \\n \\n prompt: string \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:247\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":257,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":127,\"key\":\"\"},{\"start\":127,\"end\":257,\"key\":\"\"}]},{\"start\":257,\"end\":491,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":260,\"end\":382,\"key\":\"\"},{\"start\":382,\"end\":491,\"key\":\"\"}]},{\"start\":491,\"end\":739,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":494,\"end\":617,\"key\":\"\"},{\"start\":617,\"end\":739,\"key\":\"\"}]},{\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":742,\"end\":864,\"key\":\"\"},{\"start\":864,\"end\":977,\"key\":\"\"}]},{\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":980,\"end\":1100,\"key\":\"\"},{\"start\":1100,\"end\":1221,\"key\":\"\"}]},{\"start\":1221,\"end\":1575,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1224,\"end\":1364,\"key\":\"\"},{\"start\":1364,\"end\":1575,\"key\":\"\"}]},{\"start\":1575,\"end\":1866,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1578,\"end\":1743,\"key\":\"\"},{\"start\":1743,\"end\":1866,\"key\":\"\"}]},{\"start\":1866,\"end\":2096,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1869,\"end\":1988,\"key\":\"\"},{\"start\":1988,\"end\":2096,\"key\":\"\"}]},{\"start\":2096,\"end\":2320,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2099,\"end\":2208,\"key\":\"\"},{\"start\":2208,\"end\":2320,\"key\":\"\"}]},{\"start\":2320,\"end\":2449,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2323,\"end\":2449,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:49.024021Z\",\"last_understanding\":\"2026-07-14T12:50:48.461687Z\",\"last_extract\":\"2026-07-14T12:50:47.086918Z\",\"last_processing_start\":\"2026-07-14T12:50:47.048628Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > PredictAnswerOptions\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > PredictAnswerOptions\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\":{\"score\":0.6482165455818176,\"score_type\":\"VECTOR\",\"order\":3,\"text\":\" - \\n optional max_tokens: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \\n \\n query_context? - \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":4,\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\":{\"score\":0.5993967652320862,\"score_type\":\"VECTOR\",\"order\":12,\"text\":\" - \\n optional generative_model: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 - \\n \\n json_schema? \\n \\n optional json_schema: object \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 \\n \\n max_tokens? - \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":3,\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"8b3e0ef630a346d1b591143309db87ec\":{\"id\":\"8b3e0ef630a346d1b591143309db87ec\",\"slug\":\"docs-develop-js-sdk-interfaces-NucliaTokensMetric-md\",\"title\":\"docs - > develop > js sdk > interfaces > NucliaTokensMetric\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"la\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:48:48.423622\",\"modified\":\"2026-07-14T12:51:37.835367\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/NucliaTokensMetric\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / NucliaTokensMetric\\n\\n# - Interface: NucliaTokensMetric\\n\\n## Extends\\n\\n- [`UsageMetric`](UsageMetric.md)\\n\\n## - Properties\\n\\n### details\\n\\n> **details**: [`NucliaTokensDetails`](NucliaTokensDetails.md)[]\\n\\n#### - Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`details`](UsageMetric.md#details)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:185](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L185)\\n\\n***\\n\\n### - name\\n\\n> **name**: `\\\"nuclia_tokens\\\"`\\n\\n#### Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`name`](UsageMetric.md#name)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:183](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L183)\\n\\n***\\n\\n### - value\\n\\n> **value**: `number`\\n\\n#### Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`value`](UsageMetric.md#value)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:184](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L184)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"af7b6aa34935b09fa5ddc2badd6da04f\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / NucliaTokensMetric \\n Interface: NucliaTokensMetric - \\n Extends \\n \\n UsageMetric \\n \\n Properties \\n details \\n \\n details: - NucliaTokensDetails[] \\n \\n Overrides \\n UsageMetric.details \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n name \\n \\n name: - nuclia_tokens \\n \\n Overrides \\n UsageMetric.name \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:183 - \\n \\n value \\n \\n value: number \\n \\n Overrides \\n UsageMetric.value - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[\"UsageMetric.name\"],\"paragraphs\":[{\"start\":0,\"end\":281,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":281,\"key\":\"\"}]},{\"start\":281,\"end\":511,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":282,\"end\":511,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:39.809701Z\",\"last_understanding\":\"2026-07-14T12:51:39.578340Z\",\"last_extract\":\"2026-07-14T12:51:39.320533Z\",\"last_processing_start\":\"2026-07-14T12:51:39.300652Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > NucliaTokensMetric\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > NucliaTokensMetric\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"8b3e0ef630a346d1b591143309db87ec/t/page/0-281\":{\"score\":0.5960935354232788,\"score_type\":\"VECTOR\",\"order\":13,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / NucliaTokensMetric \\n Interface: NucliaTokensMetric - \\n Extends \\n \\n UsageMetric \\n \\n Properties \\n details \\n \\n details: - NucliaTokensDetails[] \\n \\n Overrides \\n UsageMetric.details \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n name \\n \\n\",\"id\":\"8b3e0ef630a346d1b591143309db87ec/t/page/0-281\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":281,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"42a4cd5a30314e94aa079ed0cfe81381\":{\"id\":\"42a4cd5a30314e94aa079ed0cfe81381\",\"slug\":\"docs-develop-js-sdk-interfaces-SplitStrategy-md\",\"title\":\"docs - > develop > js sdk > interfaces > SplitStrategy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:02:38.468609\",\"modified\":\"2026-07-14T12:51:02.450318\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/SplitStrategy\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / SplitStrategy\\n\\n# - Interface: SplitStrategy\\n\\n## Properties\\n\\n### custom\\\\_split?\\n\\n> - `optional` **custom\\\\_split**: [`CustomSplitStrategy`](../enumerations/CustomSplitStrategy.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:537](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L537)\\n\\n***\\n\\n### - llm\\\\_split?\\n\\n> `optional` **llm\\\\_split**: [`SplitLLMConfig`](SplitLLMConfig.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:538](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L538)\\n\\n***\\n\\n### - manual\\\\_split?\\n\\n> `optional` **manual\\\\_split**: `object`\\n\\n#### - splitter\\n\\n> **splitter**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:539](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L539)\\n\\n***\\n\\n### - max\\\\_paragraph?\\n\\n> `optional` **max\\\\_paragraph**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:536](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L536)\\n\\n***\\n\\n### - name?\\n\\n> `optional` **name**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:535](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L535)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"d24d884112df2f67b327ac6d6302ddf1\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / SplitStrategy \\n Interface: SplitStrategy - \\n Properties \\n custom_split? \\n \\n optional custom_split: CustomSplitStrategy - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:537 \\n \\n - llm_split? \\n \\n optional llm_split: SplitLLMConfig \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/kb/kb.models.ts:538 \\n \\n manual_split? \\n \\n - optional manual_split: object \\n \\n splitter \\n \\n splitter: string \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:539 \\n \\n max_paragraph? - \\n \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 - \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":234,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":113,\"key\":\"\"},{\"start\":113,\"end\":234,\"key\":\"\"}]},{\"start\":234,\"end\":502,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":237,\"end\":356,\"key\":\"\"},{\"start\":356,\"end\":502,\"key\":\"\"}]},{\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":505,\"end\":612,\"key\":\"\"},{\"start\":612,\"end\":696,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:04.701538Z\",\"last_understanding\":\"2026-07-14T12:51:04.225754Z\",\"last_extract\":\"2026-07-14T12:51:03.819024Z\",\"last_processing_start\":\"2026-07-14T12:51:03.798124Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > SplitStrategy\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > SplitStrategy\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\":{\"score\":0.5957005620002747,\"score_type\":\"VECTOR\",\"order\":15,\"text\":\" - \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 - \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"id\":\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":2,\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"6e8250e6b5264156988657a221fd5e94\":{\"id\":\"6e8250e6b5264156988657a221fd5e94\",\"slug\":\"docs-develop-js-sdk-namespaces-Ask-interfaces-ConsumptionAskResponseItem-md\",\"title\":\"docs - > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:47:37.548412\",\"modified\":\"2026-07-14T12:48:09.327828\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/namespaces/Ask/interfaces/ConsumptionAskResponseItem\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../../../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../../../globals.md) / [Ask](../README.md) - / ConsumptionAskResponseItem\\n\\n# Interface: ConsumptionAskResponseItem\\n\\n## - Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> **customer\\\\_key\\\\_tokens**: - [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L127)\\n\\n***\\n\\n### - normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L126)\\n\\n***\\n\\n### - type\\n\\n> **type**: `\\\"consumption\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:125](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L125)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"3d72cf5a8634c4719acbe4304e79b48d\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: - ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n - customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 - \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n - type \\n \\n type: consumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:125\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":397,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":397,\"key\":\"\"}]},{\"start\":397,\"end\":483,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":398,\"end\":483,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:48:23.234967Z\",\"last_understanding\":\"2026-07-14T12:48:22.068785Z\",\"last_extract\":\"2026-07-14T12:48:21.777104Z\",\"last_processing_start\":\"2026-07-14T12:48:21.755089Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\":{\"score\":0.599697470664978,\"score_type\":\"VECTOR\",\"order\":11,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: - ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n - customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 - \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n - type \\n \\n\",\"id\":\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":397,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs - > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-07-14T12:49:58.922592\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ModelConfig\\n\\n# - Interface: ModelConfig\\n\\n## Properties\\n\\n### assume\\\\_role?\\n\\n> - `optional` **assume\\\\_role**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:592](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L592)\\n\\n***\\n\\n### - driver?\\n\\n> `optional` **driver**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:590](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L590)\\n\\n***\\n\\n### - input\\\\_tokens\\n\\n> **input\\\\_tokens**: `object`\\n\\n#### max\\n\\n> - **max**: `number`\\n\\n#### min?\\n\\n> `optional` **min**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:587](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L587)\\n\\n***\\n\\n### - max\\\\_images?\\n\\n> `optional` **max\\\\_images**: `string`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:591](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L591)\\n\\n***\\n\\n### - output\\\\_tokens\\n\\n> **output\\\\_tokens**: `object`\\n\\n#### default\\\\_max?\\n\\n> - `optional` **default\\\\_max**: `number`\\n\\n#### max\\n\\n> **max**: `number`\\n\\n#### - min?\\n\\n> `optional` **min**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:588](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L588)\\n\\n***\\n\\n### - prompt\\\\_id?\\n\\n> `optional` **prompt\\\\_id**: `string`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:589](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L589)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"0ce41cb0494bcb99176527165e321fec\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ModelConfig \\n Interface: ModelConfig - \\n Properties \\n assume_role? \\n \\n optional assume_role: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:592 \\n \\n driver? - \\n \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 - \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: - number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \\n \\n max_images? \\n \\n optional max_images: string \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \\n \\n output_tokens \\n - \\n output_tokens: object \\n \\n default_max? \\n \\n optional default_max: - number \\n \\n max \\n \\n max: number \\n \\n min? \\n \\n optional min: - number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:588 - \\n \\n prompt_id? \\n \\n optional prompt_id: string \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/kb/kb.models.ts:589\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":212,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":108,\"key\":\"\"},{\"start\":108,\"end\":212,\"key\":\"\"}]},{\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":215,\"end\":380,\"key\":\"\"},{\"start\":380,\"end\":480,\"key\":\"\"}]},{\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":483,\"end\":638,\"key\":\"\"},{\"start\":638,\"end\":703,\"key\":\"\"}]},{\"start\":703,\"end\":895,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":704,\"end\":806,\"key\":\"\"},{\"start\":806,\"end\":895,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:01.191702Z\",\"last_understanding\":\"2026-07-14T12:50:00.962823Z\",\"last_extract\":\"2026-07-14T12:50:00.418522Z\",\"last_processing_start\":\"2026-07-14T12:50:00.364723Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - 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\\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 - \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: - number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \\n \\n max_images? \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":1,\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0d01e250360a4d6c91f3baf2de5e7d38\":{\"id\":\"0d01e250360a4d6c91f3baf2de5e7d38\",\"slug\":\"docs-develop-js-sdk-interfaces-ReasoningConfig-md\",\"title\":\"docs - > develop > js sdk > interfaces > ReasoningConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-24T11:15:01.495997\",\"modified\":\"2026-07-14T12:49:30.245034\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ReasoningConfig\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ReasoningConfig\\n\\n# - Interface: ReasoningConfig\\n\\n## Properties\\n\\n### budget\\\\_tokens?\\n\\n> - `optional` **budget\\\\_tokens**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:647](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L647)\\n\\n***\\n\\n### - effort?\\n\\n> `optional` **effort**: [`NumericReasoningEffort`](../enumerations/NumericReasoningEffort.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:648](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L648)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"940c8be17c938dcc14e4abb000b0f8b5\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ReasoningConfig \\n Interface: ReasoningConfig - \\n Properties \\n budget_tokens? \\n \\n optional budget_tokens: number \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 \\n \\n effort? - \\n \\n optional effort: NumericReasoningEffort \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:648\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":224,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":118,\"key\":\"\"},{\"start\":118,\"end\":224,\"key\":\"\"}]},{\"start\":224,\"end\":329,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":227,\"end\":329,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:49:31.596307Z\",\"last_understanding\":\"2026-07-14T12:49:31.194629Z\",\"last_extract\":\"2026-07-14T12:49:31.030734Z\",\"last_processing_start\":\"2026-07-14T12:49:30.980505Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > ReasoningConfig\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > ReasoningConfig\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224\":{\"score\":0.6052000522613525,\"score_type\":\"VECTOR\",\"order\":9,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ReasoningConfig \\n Interface: ReasoningConfig - \\n Properties \\n budget_tokens? \\n \\n optional budget_tokens: number \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 \\n \\n effort? - \\n\",\"id\":\"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":224,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"44d05174f1954331b62f5e4026f2b01a\":{\"id\":\"44d05174f1954331b62f5e4026f2b01a\",\"slug\":\"docs-develop-python-sdk-14-rao-md\",\"title\":\"docs - > develop > python sdk > 14 rao\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-22T13:38:09.919472\",\"modified\":\"2026-06-09T08:08:04.176136\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/python-sdk/rao\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"# - Retrieval Agents Orchestrator\\n\\nInteract with Nuclia's Retrieval Agents - Orchestrator to have intelligent conversations over several knowledge sources - with persistent session management and real-time streaming responses.\\n\\n## - Prerequisites\\n\\nInstall the Nuclia SDK:\\n\\n```sh\\npip install nuclia\\n```\\n\\nEnsure - you have:\\n- A valid Nuclia authentication token (see [Authentication](02-auth.md))\\n- - Access to a configured Retrieval Agent\\n\\n## Overview\\n\\nThe nuclia.py - library provides several ways to interact with your Retrieval Agents Orchestrators:\\n\\n- - **Interactive CLI**: A rich, user-friendly terminal interface (recommended)\\n- - **Standard CLI**: Direct access to raw websocket messages for debugging\\n- - **Session Management**: Create and manage persistent conversation sessions\\n- - **Programmatic API**: Python SDK for building custom applications\\n\\n\\n## - Listing Available Agents\\n\\nDiscover what Retrieval Agents Orchestrators - you have access to.\\n\\n- CLI:\\n\\n ```sh\\n nuclia agents list\\n ```\\n\\n- - SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n - \ agents = NucliaAgents()\\n all_agents = agents.list()\\n\\n for agent - in all_agents:\\n print(f\\\"Agent: {agent.title} ({agent.id})\\\")\\n - \ print(f\\\" Slug: {agent.slug}\\\")\\n print(f\\\" Zone: {agent.zone}\\\")\\n - \ ```\\n\\n### Getting a Specific Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia - agents get --account=\\\"my-account\\\" --id=\\\"agent-uuid\\\" --zone=\\\"europe-1\\\"\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n - \ agents = NucliaAgents()\\n agent_details = agents.get(\\n account=\\\"my-account\\\",\\n - \ id=\\\"agent-uuid\\\",\\n zone=\\\"europe-1\\\"\\n )\\n print(agent_details)\\n - \ ```\\n\\n### Setting a Default Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia - agents default [AGENT_SLUG or AGENT_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n - \ from nuclia.sdk.agents import NucliaAgents\\n\\n agents = NucliaAgents()\\n - \ agents.default(\\\"my-agent\\\")\\n ```\\n\\nThis sets the default agent - for all subsequent operations.\\n\\n## Interactive CLI (Recommended)\\n\\nThe - interactive CLI provides a beautiful, real-time interface for conversing with - your Retrieval Agents Orchestrator.\\n\\n### Starting the Interactive CLI\\n\\n- - CLI:\\n\\n ```sh\\n nuclia agent cli interact\\n ```\\n\\n- SDK:\\n\\n - \ ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n - \ agent.cli.interact()\\n ```\\n\\nThis launches an interactive terminal - session where you can:\\n- Ask questions and see streaming responses\\n- View - processing steps in real-time\\n- Manage conversation sessions\\n- See retrieved - context and citations\\n\\n### Interactive CLI Commands\\n\\nThe CLI supports - several commands (prefix with `/`):\\n\\n| Command | Description |\\n|---------|-------------|\\n| - `/help` | Show available commands |\\n| `/new_session` | Create a new persistent - session |\\n| `/list_sessions` | List all your sessions |\\n| `/change_session` - | Switch to a different session, use 'ephemeral' for a temporary session |\\n| - `/clear` | Clear the screen |\\n| `/exit` | Exit the CLI |\\n\\nPlease note - that all commands related to sessions require a Retrieval Agent Orchestrator - with the option **Agent with memory** enabled during creation.\\n\\n## Session - Management\\n\\nSessions allow you to maintain conversation context across - multiple interactions.\\n\\n> This feature will only be available if you checked - **Agent with memory** during the creation of your Retrieval Agents Orchestrator.\\n\\n### - Creating a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent session new --name=\\\"My - Research Session\\\"\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent - import NucliaAgent\\n\\n agent = NucliaAgent()\\n session_uuid = agent.session.new(\\\"My - Research Session\\\")\\n print(f\\\"Created session: {session_uuid}\\\")\\n - \ ```\\n\\n### Listing Sessions\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent - session list\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent - import NucliaAgent\\n\\n agent = NucliaAgent()\\n sessions = agent.session.list()\\n - \ for session in sessions.resources:\\n print(f\\\"{session.title}: {session.id}\\\")\\n - \ ```\\n\\n### Getting a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent - session get --session_uuid=[SESSION_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n - \ from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n - \ session = agent.session.get(session_uuid)\\n print(f\\\"Session: {session.title}\\\")\\n - \ print(f\\\"Created: {session.created}\\\")\\n ```\\n\\n### Deleting a Session\\n\\n- - CLI:\\n\\n ```sh\\n nuclia agent session delete --session_uuid=[SESSION_UUID]\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n - \ agent = NucliaAgent()\\n agent.session.delete(session_uuid)\\n ```\\n\\n## - Interaction\\n\\nAside from the interactive CLI, you can interact with your - Retrieval Agents Orchestrator with the simple CLI or programmatically using - the SDK.\\n\\n### Basic Interaction\\n\\n\\n**CLI:**\\n```bash\\nnuclia agent - interact \\\"What is Eric known for?\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate - over streaming responses\\nfor response in agent.interact(\\n question=\\\"What - is Eric known for?\\\"\\n):\\n if response.operation == \\\"ANSWER\\\" - and response.answer:\\n print(response.answer)\\n elif response.step:\\n - \ print(f\\\"Processing: {response.step.module}\\\")\\n```\\n\\nNot - supplying a `session_uuid` when calling `interact` will use an ephemeral session - by default. To maintain context, provide a persistent session UUID.\\n\\n### - Using Persistent Sessions\\n\\n**CLI:**\\n```bash\\nnuclia agent sessions - new \\\"Customer Support Chat\\\"\\n# Note the session UUID returned\\nnuclia - agent interact \\\"What are your business hours?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\nnuclia - agent interact \\\"Are you open on weekends?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Create - a session\\nsession_uuid = agent.session.new(\\\"Customer Support Chat\\\")\\n\\n# - Have a conversation with context\\nfor response in agent.interact(\\n session_uuid=session_uuid,\\n - \ question=\\\"What are your business hours?\\\"\\n):\\n if response.answer:\\n - \ print(response.answer)\\n\\n# Follow-up question maintains context\\nfor - response in agent.interact(\\n session_uuid=session_uuid,\\n question=\\\"Are - you open on weekends?\\\"\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\n## - Understanding Response Types\\n\\nWhen interacting with an agent, you receive - a stream of `AragAnswer` objects with different operations:\\n\\n| Operation - | Description |\\n|-----------|-------------|\\n| `START` | Interaction has - begun |\\n| `ANSWER` | Processing step or partial answer |\\n| `DONE` | Interaction - complete |\\n| `ERROR` | An error occurred |\\n| `AGENT_REQUEST` | Agent needs - user feedback |\\n\\n### Response Attributes\\n\\nEach response may contain:\\n\\n- - **`step`**: Information about the current processing step\\n - `module`: - The module being executed (e.g., \\\"rephrase\\\", \\\"basic_ask\\\", \\\"remi\\\")\\n - \ - `title`: Display title for the step\\n - `value`: Result of the step\\n - \ - `reason`: Explanation for the step\\n - `timeit`: Time taken in seconds\\n - \ - `input_nuclia_tokens`/`output_nuclia_tokens`: Token usage\\n\\n- **`context`**: - Retrieved context from the knowledge base\\n - `chunks`: List of retrieved - text chunks with sources\\n - `summary`: Summary of the context or partial - answer\\n\\n- **`answer`**: The final answer text (Markdown formatted)\\n\\n- - **`generated_text`**: Intermediate generated text\\n\\n- **`possible_answer`**: - Alternative answer being considered\\n\\n- **`exception`**: Error details - if something went wrong\\n\\n### Processing Responses\\n\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\nfrom nuclia_models.agent.interaction - import AnswerOperation\\n\\nagent = NucliaAgent()\\n\\nfor response in agent.interact(question=\\\"Tell - me about AI\\\"):\\n if response.operation == AnswerOperation.START:\\n - \ print(\\\"Starting...\\\")\\n \\n elif response.step:\\n print(f\\\"Step: - {response.step.module} ({response.step.timeit:.2f}s)\\\")\\n \\n elif - response.context:\\n print(f\\\"Retrieved {len(response.context.chunks)} - chunks\\\")\\n for chunk in response.context.chunks:\\n print(f\\\" - \ - {chunk.title}: {chunk.text[:100]}...\\\")\\n \\n elif response.answer:\\n - \ print(f\\\"\\\\nFinal Answer:\\\\n{response.answer}\\\")\\n \\n - \ elif response.operation == AnswerOperation.DONE:\\n print(\\\"Complete!\\\")\\n - \ \\n elif response.operation == AnswerOperation.ERROR:\\n print(f\\\"Error: - {response.exception.detail if response.exception else 'Unknown'}\\\")\\n```\\n\\n## - Standard CLI for Raw Messages\\n\\nFor debugging or advanced use cases, you - can access raw websocket messages programmatically:\\n\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate - over all messages\\nfor message in agent.interact(\\n question=\\\"What - is RAO?\\\"\\n):\\n # message is an AragAnswer object with all raw data\\n - \ print(f\\\"Operation: {message.operation}\\\")\\n print(f\\\"Raw message: - {message.model_dump_json(indent=2)}\\\")\\n```\\n\\nThis gives you direct - access to all websocket message data for debugging or custom processing.\\n\\n## - Advanced Features\\n\\n### Agent Feedback Requests\\n\\nAgents can request - additional input from users during processing:\\n\\n```python\\nfrom nuclia.sdk.agent - import NucliaAgent\\nfrom nuclia_models.agent.interaction import AnswerOperation\\n\\nagent - = NucliaAgent()\\ngenerator = agent.interact(question=\\\"Help me with X\\\")\\n\\nfor - response in generator:\\n if response.operation == AnswerOperation.AGENT_REQUEST:\\n - \ # Agent is requesting user input\\n user_input = input(f\\\"Agent - asks: {response.feedback.question}\\\\n> \\\")\\n # Send response back\\n - \ generator.send(user_input)\\n elif response.answer:\\n print(response.answer)\\n```\\n\\n### - Error Handling\\n\\n```python\\nfrom nuclia.sdk.agent import NucliaAgent\\nfrom - nuclia.exceptions import RaoAPIException\\n\\nagent = NucliaAgent()\\n\\ntry:\\n - \ for response in agent.interact(question=\\\"Hello?\\\"):\\n if - response.exception:\\n print(f\\\"Agent error: {response.exception.detail}\\\")\\n - \ elif response.answer:\\n print(response.answer)\\nexcept - RaoAPIException as e:\\n print(f\\\"API error: {e.detail}\\\")\\nexcept - Exception as e:\\n print(f\\\"Unexpected error: {e}\\\")\\n```\\n\\n### - Passing Custom Headers to MCP\\n\\nIf your Retrieval Agents Orchestrator requires - custom headers for MCP Agents, you can pass them as follows:\\n\\n**CLI:**\\n```bash\\nnuclia - agent interact \\\"What is AI?\\\" --headers '{\\\"X-Custom-Header\\\": \\\"value\\\"}'\\n```\\n\\n**SDK:**\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\nfor response - in agent.interact(\\n question=\\\"What is AI?\\\",\\n headers={\\\"X-Custom-Header\\\": - \\\"value\\\"}\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\nPlease - ensure that the 'Allowed Headers' configuration in your MCP agent includes - any custom headers you wish to use.\\n\\n## Best Practices\\n\\n1. **Use Sessions - for Context**: Create sessions when you need multi-turn conversations with - context retention\\n2. **Use Ephemeral Sessions for One-offs**: Don't supply - a session UUID for using agents in a stateless manner.\\n3. **Stream for UX**: - Process responses as they arrive for better user experience\\n4. **Handle - All Operations**: Check for different operation types (START, ANSWER, DONE, - ERROR) when processing responses\\n5. **Clean Up Sessions**: Delete sessions - when done to avoid clutter\\n6. **Use Interactive CLI**: For manual testing - and exploration, the interactive CLI provides the best experience\\n\",\"format\":\"MARKDOWN\",\"md5\":\"bbaaf8cccd2b664ba4f7daf47d1f2bf4\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"Retrieval - Agents Orchestrator \\n Interact with Nuclia's Retrieval Agents Orchestrator - to have intelligent conversations over several knowledge sources with persistent - session management and real-time streaming responses. \\n Prerequisites \\n - Install the Nuclia SDK: \\n sh \\n pip install nuclia \\n Ensure you have: - \\n - A valid Nuclia authentication token (see Authentication) \\n - Access - to a configured Retrieval Agent \\n Overview \\n The nuclia.py library provides - several ways to interact with your Retrieval Agents Orchestrators: \\n \\n - Interactive CLI: A rich, user-friendly terminal interface (recommended) \\n - Standard CLI: Direct access to raw websocket messages for debugging \\n Session - Management: Create and manage persistent conversation sessions \\n Programmatic - API: Python SDK for building custom applications \\n \\n Listing Available - Agents \\n Discover what Retrieval Agents Orchestrators you have access to. - \\n \\n CLI: \\n \\n sh \\n nuclia agents list \\n \\n SDK: \\n \\n ```python - \\n from nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() - \\n all_agents = agents.list() \\n for agent in all_agents: \\n print(f Agent: - {agent.title} ({agent.id}) ) \\n print(f Slug: {agent.slug} ) \\n print(f - Zone: {agent.zone} ) \\n ``` \\n Getting a Specific Agent \\n \\n CLI: \\n - \\n sh \\n nuclia agents get --account= my-account --id= agent-uuid --zone= - europe-1 \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agents import - NucliaAgents \\n agents = NucliaAgents() \\n agent_details = agents.get( \\n - account= my-account , \\n id= agent-uuid , \\n zone= europe-1 \\n ) \\n print(agent_details) - \\n ``` \\n Setting a Default Agent \\n \\n CLI: \\n \\n sh \\n nuclia agents - default [AGENT_SLUG or AGENT_UUID] \\n \\n SDK: \\n \\n ```python \\n from - nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() \\n agents.default( - my-agent ) \\n ``` \\n This sets the default agent for all subsequent operations. - \\n Interactive CLI (Recommended) \\n The interactive CLI provides a beautiful, - real-time interface for conversing with your Retrieval Agents Orchestrator. - \\n Starting the Interactive CLI \\n \\n CLI: \\n \\n sh \\n nuclia agent - cli interact \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import - NucliaAgent \\n agent = NucliaAgent() \\n agent.cli.interact() \\n ``` \\n - This launches an interactive terminal session where you can: \\n - Ask questions - and see streaming responses \\n - View processing steps in real-time \\n - - Manage conversation sessions \\n - See retrieved context and citations \\n - Interactive CLI Commands \\n The CLI supports several commands (prefix with - /): \\n | Command | Description | \\n |---------|-------------| \\n | /help - | Show available commands | \\n | /new_session | Create a new persistent session - | \\n | /list_sessions | List all your sessions | \\n | /change_session | - Switch to a different session, use 'ephemeral' for a temporary session | \\n - | /clear | Clear the screen | \\n | /exit | Exit the CLI | \\n Please note - that all commands related to sessions require a Retrieval Agent Orchestrator - with the option Agent with memory enabled during creation. \\n Session Management - \\n Sessions allow you to maintain conversation context across multiple interactions. - \\n \\n This feature will only be available if you checked Agent with memory - during the creation of your Retrieval Agents Orchestrator. \\n \\n Creating - a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session new --name= My - Research Session \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent - import NucliaAgent \\n agent = NucliaAgent() \\n session_uuid = agent.session.new( - My Research Session ) \\n print(f Created session: {session_uuid} ) \\n ``` - \\n Listing Sessions \\n \\n CLI: \\n \\n sh \\n nuclia agent session list - \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import NucliaAgent - \\n agent = NucliaAgent() \\n sessions = agent.session.list() \\n for session - in sessions.resources: \\n print(f {session.title}: {session.id} ) \\n ``` - \\n Getting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session get - --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent - import NucliaAgent \\n agent = NucliaAgent() \\n session = agent.session.get(session_uuid) - \\n print(f Session: {session.title} ) \\n print(f Created: {session.created} - ) \\n ``` \\n Deleting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent - session delete --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python - \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n - agent.session.delete(session_uuid) \\n ``` \\n Interaction \\n Aside from - the interactive CLI, you can interact with your Retrieval Agents Orchestrator - with the simple CLI or programmatically using the SDK. \\n Basic Interaction - \\n CLI: \\n bash \\n nuclia agent interact What is Eric known for? \\n SDK: - \\n ```python \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() - \\n Iterate over streaming responses \\n for response in agent.interact( \\n - question= What is Eric known for? \\n ): \\n if response.operation == ANSWER - and response.answer: \\n print(response.answer) \\n elif response.step: \\n - print(f Processing: {response.step.module} ) \\n ``` \\n Not supplying a session_uuid - when calling interact will use an ephemeral session by default. To maintain - context, provide a persistent session UUID. \\n Using Persistent Sessions - \\n CLI: \\n ```bash \\n nuclia agent sessions new Customer Support Chat \\n - Note the session UUID returned \\n nuclia agent interact What are your business - hours? --session_uuid= SESSION_UUID \\n nuclia agent interact Are you open - on weekends? --session_uuid= SESSION_UUID \\n ``` \\n SDK: \\n ```python \\n - from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n Create - a session \\n session_uuid = agent.session.new( Customer Support Chat ) \\n - Have a conversation with context \\n for response in agent.interact( \\n session_uuid=session_uuid, - \\n question= What are your business hours? \\n ): \\n if response.answer: - \\n print(response.answer) \\n Follow-up question maintains context \\n for - response in agent.interact( \\n session_uuid=session_uuid, \\n question= Are - you open on weekends? \\n ): \\n if response.answer: \\n print(response.answer) - \\n ``` \\n Understanding Response Types \\n When interacting with an agent, - you receive a stream of AragAnswer objects with different operations: \\n - | Operation | Description | \\n |-----------|-------------| \\n | START | - Interaction has begun | \\n | ANSWER | Processing step or partial answer | - \\n | DONE | Interaction complete | \\n | ERROR | An error occurred | \\n - | AGENT_REQUEST | Agent needs user feedback | \\n Response Attributes \\n - Each response may contain: \\n \\n step: Information about the current processing - step \\n module: The module being executed (e.g., rephrase , basic_ask , remi - ) \\n title: Display title for the step \\n value: Result of the step \\n - reason: Explanation for the step \\n timeit: Time taken in seconds \\n \\n - input_nuclia_tokens/output_nuclia_tokens: Token usage \\n \\n \\n context: - Retrieved context from the knowledge base \\n \\n chunks: List of retrieved - text chunks with sources \\n \\n summary: Summary of the context or partial - answer \\n \\n \\n answer: The final answer text (Markdown formatted) \\n - \\n \\n generated_text: Intermediate generated text \\n \\n \\n possible_answer: - Alternative answer being considered \\n \\n \\n exception: Error details if - something went wrong \\n \\n \\n Processing Responses \\n ```python \\n from - nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction - import AnswerOperation \\n agent = NucliaAgent() \\n for response in agent.interact(question= - Tell me about AI ): \\n if response.operation == AnswerOperation.START: \\n - print( Starting... ) \\n elif response.step: \\n print(f Step: {response.step.module} - ({response.step.timeit:.2f}s) ) \\n \\n elif response.context: \\n print(f - Retrieved {len(response.context.chunks)} chunks ) \\n for chunk in response.context.chunks: - \\n print(f - {chunk.title}: {chunk.text[:100]}... ) \\n \\n elif response.answer: - \\n print(f \\\\nFinal Answer:\\\\n{response.answer} ) \\n \\n elif response.operation - == AnswerOperation.DONE: \\n print( Complete! ) \\n \\n elif response.operation - == AnswerOperation.ERROR: \\n print(f Error: {response.exception.detail if - response.exception else 'Unknown'} ) \\n \\n ``` \\n Standard CLI for Raw - Messages \\n For debugging or advanced use cases, you can access raw websocket - messages programmatically: \\n ```python \\n from nuclia.sdk.agent import - NucliaAgent \\n agent = NucliaAgent() \\n Iterate over all messages \\n for - message in agent.interact( \\n question= What is RAO? \\n ): \\n # message - is an AragAnswer object with all raw data \\n print(f Operation: {message.operation} - ) \\n print(f Raw message: {message.model_dump_json(indent=2)} ) \\n ``` \\n - This gives you direct access to all websocket message data for debugging or - custom processing. \\n Advanced Features \\n Agent Feedback Requests \\n Agents - can request additional input from users during processing: \\n ```python \\n - from nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction - import AnswerOperation \\n agent = NucliaAgent() \\n generator = agent.interact(question= - Help me with X ) \\n for response in generator: \\n if response.operation - == AnswerOperation.AGENT_REQUEST: \\n # Agent is requesting user input \\n - user_input = input(f Agent asks: {response.feedback.question}\\\\n> ) \\n - # Send response back \\n generator.send(user_input) \\n elif response.answer: - \\n print(response.answer) \\n ``` \\n Error Handling \\n ```python \\n from - nuclia.sdk.agent import NucliaAgent \\n from nuclia.exceptions import RaoAPIException - \\n agent = NucliaAgent() \\n try: \\n for response in agent.interact(question= - Hello? ): \\n if response.exception: \\n print(f Agent error: {response.exception.detail} - ) \\n elif response.answer: \\n print(response.answer) \\n except RaoAPIException - as e: \\n print(f API error: {e.detail} ) \\n except Exception as e: \\n print(f - Unexpected error: {e} ) \\n ``` \\n Passing Custom Headers to MCP \\n If your - Retrieval Agents Orchestrator requires custom headers for MCP Agents, you - can pass them as follows: \\n CLI: \\n bash \\n nuclia agent interact What - is AI? --headers '{ X-Custom-Header : value }' \\n SDK: \\n ```python \\n - from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n for - response in agent.interact( \\n question= What is AI? , \\n headers={ X-Custom-Header - : value } \\n ): \\n if response.answer: \\n print(response.answer) \\n ``` - \\n Please ensure that the 'Allowed Headers' configuration in your MCP agent - includes any custom headers you wish to use. \\n Best Practices \\n \\n Use - Sessions for Context: Create sessions when you need multi-turn conversations - with context retention \\n Use Ephemeral Sessions for One-offs: Don't supply - a session UUID for using agents in a stateless manner. \\n Stream for UX: - Process responses as they arrive for better user experience \\n Handle All - Operations: Check for different operation types (START, ANSWER, DONE, ERROR) - when processing responses \\n Clean Up Sessions: Delete sessions when done - to avoid clutter \\n Use Interactive CLI: For manual testing and exploration, - the interactive CLI provides the best experience \\n 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\\n timeit: Time taken in seconds \\n \\n input_nuclia_tokens/output_nuclia_tokens: - Token usage \\n \\n \\n\",\"id\":\"44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":19,\"start\":6346,\"end\":6668,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0a003c3f724e45e392a9c8d1ce8800c1\":{\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1\",\"slug\":\"docs-develop-js-sdk-interfaces-Consumption-md\",\"title\":\"docs - > develop > js sdk > interfaces > Consumption\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:51:46.788864\",\"modified\":\"2026-07-14T12:51:15.300757\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / Consumption\\n\\n# - Interface: Consumption\\n\\n## Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> - **customer\\\\_key\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:230](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L230)\\n\\n***\\n\\n### - normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:229](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L229)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"654b0dfe17ab08959c78891dd24c3424\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption - \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n - \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":349,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:16.563837Z\",\"last_understanding\":\"2026-07-14T12:51:16.208384Z\",\"last_extract\":\"2026-07-14T12:51:15.984803Z\",\"last_processing_start\":\"2026-07-14T12:51:15.966495Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > 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libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"b14cf452a3434839a04c111f2ea4dc51\":{\"id\":\"b14cf452a3434839a04c111f2ea4dc51\",\"slug\":\"docs-develop-js-sdk-enums-UsageType-md\",\"title\":\"docs - > develop > js sdk > enums > UsageType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"tn\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:41.582110\",\"modified\":\"2026-06-09T08:13:34.112208\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/enums/UsageType\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[@nuclia/core](../README.md) - / [Exports](../modules.md) / UsageType\\n\\n# Enumeration: UsageType\\n\\n## - Table of contents\\n\\n### Enumeration Members\\n\\n- [AI\\\\_TOKENS\\\\_USED](UsageType.md#ai_tokens_used)\\n- - [BYTES\\\\_PROCESSED](UsageType.md#bytes_processed)\\n- [CHARS\\\\_PROCESSED](UsageType.md#chars_processed)\\n- - [MEDIA\\\\_FILES\\\\_PROCESSED](UsageType.md#media_files_processed)\\n- [MEDIA\\\\_SECONDS\\\\_PROCESSED](UsageType.md#media_seconds_processed)\\n- - [NUCLIA\\\\_TOKENS](UsageType.md#nuclia_tokens)\\n- [PAGES\\\\_PROCESSED](UsageType.md#pages_processed)\\n- - [PARAGRAPHS\\\\_PROCESSED](UsageType.md#paragraphs_processed)\\n- [PRE\\\\_PROCESSING\\\\_TIME](UsageType.md#pre_processing_time)\\n- - [RESOURCES\\\\_PROCESSED](UsageType.md#resources_processed)\\n- [SEARCHES\\\\_PERFORMED](UsageType.md#searches_performed)\\n- - [SLOW\\\\_PROCESSING\\\\_TIME](UsageType.md#slow_processing_time)\\n- [SUGGESTIONS\\\\_PERFORMED](UsageType.md#suggestions_performed)\\n- - [TRAIN\\\\_SECONDS](UsageType.md#train_seconds)\\n\\n## Enumeration Members\\n\\n### - AI\\\\_TOKENS\\\\_USED\\n\\n\u2022 **AI\\\\_TOKENS\\\\_USED** = ``\\\"ai_tokens_used\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:190](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L190)\\n\\n___\\n\\n### - BYTES\\\\_PROCESSED\\n\\n\u2022 **BYTES\\\\_PROCESSED** = ``\\\"bytes_processed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:181](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L181)\\n\\n___\\n\\n### - CHARS\\\\_PROCESSED\\n\\n\u2022 **CHARS\\\\_PROCESSED** = ``\\\"chars_processed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:182](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L182)\\n\\n___\\n\\n### - MEDIA\\\\_FILES\\\\_PROCESSED\\n\\n\u2022 **MEDIA\\\\_FILES\\\\_PROCESSED** - = ``\\\"media_files_processed\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:184](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L184)\\n\\n___\\n\\n### - MEDIA\\\\_SECONDS\\\\_PROCESSED\\n\\n\u2022 **MEDIA\\\\_SECONDS\\\\_PROCESSED** - = ``\\\"media_seconds_processed\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:183](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L183)\\n\\n___\\n\\n### - NUCLIA\\\\_TOKENS\\n\\n\u2022 **NUCLIA\\\\_TOKENS** = ``\\\"nuclia_tokens_billed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:191](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L191)\\n\\n___\\n\\n### - PAGES\\\\_PROCESSED\\n\\n\u2022 **PAGES\\\\_PROCESSED** = ``\\\"pages_processed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:185](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L185)\\n\\n___\\n\\n### - PARAGRAPHS\\\\_PROCESSED\\n\\n\u2022 **PARAGRAPHS\\\\_PROCESSED** = ``\\\"paragraphs_processed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:186](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L186)\\n\\n___\\n\\n### - PRE\\\\_PROCESSING\\\\_TIME\\n\\n\u2022 **PRE\\\\_PROCESSING\\\\_TIME** = - ``\\\"pre_processing_time\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:178](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L178)\\n\\n___\\n\\n### - RESOURCES\\\\_PROCESSED\\n\\n\u2022 **RESOURCES\\\\_PROCESSED** = ``\\\"resources_processed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:180](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L180)\\n\\n___\\n\\n### - SEARCHES\\\\_PERFORMED\\n\\n\u2022 **SEARCHES\\\\_PERFORMED** = ``\\\"searches_performed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:188](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L188)\\n\\n___\\n\\n### - SLOW\\\\_PROCESSING\\\\_TIME\\n\\n\u2022 **SLOW\\\\_PROCESSING\\\\_TIME** - = ``\\\"slow_processing_time\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:179](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L179)\\n\\n___\\n\\n### - SUGGESTIONS\\\\_PERFORMED\\n\\n\u2022 **SUGGESTIONS\\\\_PERFORMED** = ``\\\"suggestions_performed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:189](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L189)\\n\\n___\\n\\n### - TRAIN\\\\_SECONDS\\n\\n\u2022 **TRAIN\\\\_SECONDS** = ``\\\"train_seconds\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:187](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L187)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"232462bafe6a7eb30c1df7131403005e\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - / Exports / UsageType \\n Enumeration: UsageType \\n Table of contents \\n - Enumeration Members \\n \\n AI_TOKENS_USED \\n BYTES_PROCESSED \\n CHARS_PROCESSED - \\n MEDIA_FILES_PROCESSED \\n MEDIA_SECONDS_PROCESSED \\n NUCLIA_TOKENS \\n - PAGES_PROCESSED \\n PARAGRAPHS_PROCESSED \\n PRE_PROCESSING_TIME \\n RESOURCES_PROCESSED - \\n SEARCHES_PERFORMED \\n SLOW_PROCESSING_TIME \\n SUGGESTIONS_PERFORMED - \\n TRAIN_SECONDS \\n \\n Enumeration Members \\n AI_TOKENS_USED \\n \u2022 - AI_TOKENS_USED = ai_tokens_used \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:190 - \\n \\n BYTES_PROCESSED \\n \u2022 BYTES_PROCESSED = bytes_processed \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:181 \\n \\n CHARS_PROCESSED \\n - \u2022 CHARS_PROCESSED = chars_processed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:182 - \\n \\n MEDIA_FILES_PROCESSED \\n \u2022 MEDIA_FILES_PROCESSED = media_files_processed - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184 \\n \\n MEDIA_SECONDS_PROCESSED - \\n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \\n Defined in - \\n libs/sdk-core/src/lib/db/db.models.ts:183 \\n \\n NUCLIA_TOKENS \\n \u2022 - NUCLIA_TOKENS = nuclia_tokens_billed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:191 - \\n \\n PAGES_PROCESSED \\n \u2022 PAGES_PROCESSED = pages_processed \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n PARAGRAPHS_PROCESSED - \\n \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:186 \\n \\n PRE_PROCESSING_TIME \\n - \u2022 PRE_PROCESSING_TIME = pre_processing_time \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:178 - \\n \\n RESOURCES_PROCESSED \\n \u2022 RESOURCES_PROCESSED = resources_processed - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:180 \\n \\n SEARCHES_PERFORMED - \\n \u2022 SEARCHES_PERFORMED = searches_performed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:188 - \\n \\n SLOW_PROCESSING_TIME \\n \u2022 SLOW_PROCESSING_TIME = slow_processing_time - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:179 \\n \\n SUGGESTIONS_PERFORMED - \\n \u2022 SUGGESTIONS_PERFORMED = suggestions_performed \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:189 \\n \\n TRAIN_SECONDS \\n \u2022 - TRAIN_SECONDS = train_seconds \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:187\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":2139,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":2139,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-06-09T08:13:38.314222Z\",\"last_understanding\":\"2026-06-09T08:13:35.850668Z\",\"last_extract\":\"2026-06-09T08:13:35.182287Z\",\"last_processing_start\":\"2026-06-09T08:13:35.144379Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > enums > UsageType\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > enums > UsageType\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139\":{\"score\":0.5916038155555725,\"score_type\":\"VECTOR\",\"order\":17,\"text\":\"@nuclia/core - / Exports / UsageType \\n Enumeration: UsageType \\n Table of contents \\n - Enumeration Members \\n \\n AI_TOKENS_USED \\n BYTES_PROCESSED \\n CHARS_PROCESSED - \\n MEDIA_FILES_PROCESSED \\n MEDIA_SECONDS_PROCESSED \\n NUCLIA_TOKENS \\n - PAGES_PROCESSED \\n PARAGRAPHS_PROCESSED \\n PRE_PROCESSING_TIME \\n RESOURCES_PROCESSED - \\n SEARCHES_PERFORMED \\n SLOW_PROCESSING_TIME \\n SUGGESTIONS_PERFORMED - \\n TRAIN_SECONDS \\n \\n Enumeration Members \\n AI_TOKENS_USED \\n \u2022 - AI_TOKENS_USED = ai_tokens_used \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:190 - \\n \\n BYTES_PROCESSED \\n \u2022 BYTES_PROCESSED = bytes_processed \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:181 \\n \\n CHARS_PROCESSED \\n - \u2022 CHARS_PROCESSED = chars_processed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:182 - \\n \\n MEDIA_FILES_PROCESSED \\n \u2022 MEDIA_FILES_PROCESSED = media_files_processed - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184 \\n \\n MEDIA_SECONDS_PROCESSED - \\n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \\n Defined in - \\n libs/sdk-core/src/lib/db/db.models.ts:183 \\n \\n NUCLIA_TOKENS \\n \u2022 - NUCLIA_TOKENS = nuclia_tokens_billed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:191 - \\n \\n PAGES_PROCESSED \\n \u2022 PAGES_PROCESSED = pages_processed \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n PARAGRAPHS_PROCESSED - \\n \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:186 \\n \\n PRE_PROCESSING_TIME \\n - \u2022 PRE_PROCESSING_TIME = pre_processing_time \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:178 - \\n \\n RESOURCES_PROCESSED \\n \u2022 RESOURCES_PROCESSED = resources_processed - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:180 \\n \\n SEARCHES_PERFORMED - \\n \u2022 SEARCHES_PERFORMED = searches_performed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:188 - \\n \\n SLOW_PROCESSING_TIME \\n \u2022 SLOW_PROCESSING_TIME = slow_processing_time - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:179 \\n \\n SUGGESTIONS_PERFORMED - \\n \u2022 SUGGESTIONS_PERFORMED = suggestions_performed \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:189 \\n \\n TRAIN_SECONDS \\n \u2022 - TRAIN_SECONDS = train_seconds \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:187\",\"id\":\"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":2139,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"f02da6c4bdf34596a89a8106f4b0ea9f\":{\"id\":\"f02da6c4bdf34596a89a8106f4b0ea9f\",\"slug\":\"docs-develop-js-sdk-interfaces-PageToken-md\",\"title\":\"docs - > develop > js sdk > interfaces > PageToken\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:49:28.645864\",\"modified\":\"2026-07-14T12:51:05.803476\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageToken\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / PageToken\\n\\n# - Interface: PageToken\\n\\n## Properties\\n\\n### height\\n\\n> **height**: - `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L249)\\n\\n***\\n\\n### - line\\n\\n> **line**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L251)\\n\\n***\\n\\n### - text\\n\\n> **text**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L250)\\n\\n***\\n\\n### - width\\n\\n> **width**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L248)\\n\\n***\\n\\n### - x\\n\\n> **x**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L246)\\n\\n***\\n\\n### - y\\n\\n> **y**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"e72ffebe78398e6654aceec2addfd240\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n - Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 - \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 - \\n \\n text \\n \\n text: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:250 - \\n \\n width \\n \\n width: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:248 - \\n \\n x \\n \\n x: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:246 - \\n \\n y \\n \\n y: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:247\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":299,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":299,\"key\":\"\"}]},{\"start\":299,\"end\":592,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":300,\"end\":592,\"key\":\"\"}]},{\"start\":592,\"end\":677,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":593,\"end\":677,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:07.412857Z\",\"last_understanding\":\"2026-07-14T12:51:07.180359Z\",\"last_extract\":\"2026-07-14T12:51:06.857039Z\",\"last_processing_start\":\"2026-07-14T12:51:06.837097Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > PageToken\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > PageToken\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\":{\"score\":0.5957225561141968,\"score_type\":\"VECTOR\",\"order\":14,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n - Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 - \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 - \\n \\n text \\n \\n\",\"id\":\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":299,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"9f7036a7a6694700b72d52eb58a8326c\":{\"id\":\"9f7036a7a6694700b72d52eb58a8326c\",\"slug\":\"docs-rag-advanced-widget-features-md\",\"title\":\"docs - > rag > advanced > widget > features\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T14:32:26.204740\",\"modified\":\"2026-06-09T08:07:51.648767\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - features\\ntitle: Features\\n---\\n\\n# Widgets features\\n\\nThe Agentic - RAG widgets allows you to embed the Agentic RAG search experience directly - into your website or web application through a simple HTML snippet:\\n\\n```html\\n\\n\\n\\n```\\n\\nThe - easiest way to explore the different features of the widgets is to use the - [Agentic RAG Dashboard](https://rag.progress.cloud/) in the Widgets section - and to play with the different options.\\n\\nThe _Embed widget_ button will - generate the HTML snippet for you.\\n\\n## Widget types\\n\\nThere are 3 different - types of widgets:\\n\\n- **Embedded in page**: the search input is embedded - in a page and the results are displayed under the input. Once the initial - answer is displayed, the user can click on _Ask more_ to access the full chat - interface. Note: For the correct reading of the results, the width of the - widget container should not be less than 384px.\\n\\n Web components:\\n\\n - \ ```html\\n \\n \\n - \ ```\\n\\n- **Chat mode**: displays directly the full chat interface.\\n\\n - \ Web component:\\n\\n ```html\\n \\n ```\\n\\n- - **Popup modal**: the search inout and the results are displayed in a popup - modal.\\n\\n Web component:\\n\\n ```html\\n \\n - \ ```\\n\\n## The `features` parameter\\n\\nThe `features` parameter allows - you to customize the behavior of the widget. It is a comma-separated list - of features among the following:\\n\\n- `filter`: display a filter dropdown - in the search bar.\\n- `navigateToFile`: open the file in the browser when - clicking on the result (by default, the file is displayed in the viewer).\\n- - `navigateToLink`: open the link in the browser when clicking on the result - (by default, the link is displayed in the viewer).\\n- `permalink`: add the - search query and criteria to the URL, allowing the widget to re-render the - same results upon loading.\\n- `relations`: display an info card on the right - side of the widget listing all the relations of the entity mentioned in the - user query.\\n- `suggestions`: display a list of suggested resource titles - matching the user input.\\n- `suggestLabels`: display a list of suggestions - based on the labels when the user starts typing in the search bar.\\n- `autocompleteFromNERs`: - display a list of suggestions based on the NERs extracted from the user query - when the user starts typing in the search bar.\\n- `displayMetadata`: display - the metadata associated with the resource in the result rows.\\n- `answers`: - trigger the answer generation process when the user makes a search.\\n- `hideResults`: - hide the search results, only the generative answer will be displayed.\\n- - `hideThumbnails`: hide the thumbnails associated with the resource in the - result rows.\\n- `displayFieldList`: display a section listing all the fields - of the resource in the right sidebar of the viewer. This section is only visible - for resources containing multiple fields.\\n- `citations`: include citations - in the generative answer.\\n- `rephrase`: rephrase the user question in order - to optimize the quality of the search results.\\n- `debug`: display extra - buttons to download the last request full log of the debug metadata returned - by the API. It must not be used in production.\\n- `preferMarkdown`: require - the generative answer to be formatted in Markdown.\\n- `openNewTab`: open - the link in a new tab when clicking on the result.\\n- `orFilterLogic`: use - the OR logic for filters instead of the default AND logic.\\n- `noChatHistory`: - the previous questions and answers in the chat mode will not be passed as - context when generating a new answer.\\n- `showHidden`: display hidden resources - in the search results.\\n- `showAttachedImages`: display images attached to - the matching paragraphs in the search results.\\n\\n### Other parameters\\n\\n- - `backend`: the URL of the backend to use. Useful if you use your own proxy - to access the Agentic RAG API.\\n- `zone`: the zone to use.\\n- `knowledgebox`: - the Knowledge Box id.\\n- `placeholder`: the text displayed in the search - bar when it is empty.\\n- `lang`: the language of the widget. Currently supported: - `ca`, `fr`, `en`, `es`. Default: `en`.\\n- `apikey`: the API key to use. It - is not recommended to use it in production (the API key is meant to be injected - by your proxy).\\n- `account`: the account id.\\n- `state`: the publication - state of the Knowledge Box.\\n- `standalone`: set to `true` when using a standalone - NucliaDB instance.\\n- `proxy`: set to `true` when using a proxy to access - the Agentic RAG API.\\n- `mode`: set to `dark` to display the widget in dark - mode.\\n- `filters`: define the filters offered to the user in the search - bar among `labels`, `entities`, `created` and `labelFamilies`.\\n- `preselected_filters`: - define filters that will be applied by default to any query.\\n- `csspath`: - the path to the CSS file to use to customize the widget style.\\n- `prompt`: - the prompt to use for the generative model. It must use `{context}` and `{question}` - variables.\\n- `system_prompt`: the system prompt to use for the generative - model.\\n- `rephrase_prompt`: the prompt to use when optimizing the user query - to get the best search results.\\n- `generativemodel`: the generative model - to use for the answer generation.\\n- `rag_strategies`: the RAG strategies - to apply to the retrieved paragraphs.\\n- `rag_images_strategies`: the RAG - strategies to apply to the retrieved images.\\n- `not_enough_data_message`: - the message to display when there is not enough data to generate an answer.\\n- - `ask_to_resource`: the resource ID to use as context for the generative model.\\n- - `max_tokens`: the maximum number of input tokens to put in the final context - (including the prompt, the retrieved results and the user question).\\n- `max_output_tokens`: - the maximum number of tokens to generate.\\n- `max_paragraphs`: the maximum - number of paragraphs to pass in the context to the generative model (default: - 20).\\n- `query_prepend`: the hard-coded text to prepend to the user query.\\n- - `json_schema`: the JSON schema to use to get a JSON answer from the generative - model.\\n- `vectorset`: the embedding model to use for the semantic search.\\n- - `chat_placeholder`: the placeholder to display in the chat input.\\n- `audit_metadata`: - custom metatada to add in API calls for auditing purposes.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"8f3044c65d6a551153cea36353a2cdac\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: features \\n title: Features \\n \\n Widgets features \\n The Agentic - RAG widgets allows you to embed the Agentic RAG search experience directly - into your website or web application through a simple HTML snippet: \\n ```html - \\n \\n \\n \\n ``` \\n The easiest way to explore the different features - of the widgets is to use the Agentic RAG Dashboard in the Widgets section - and to play with the different options. \\n The Embed widget button will generate - the HTML snippet for you. \\n Widget types \\n There are 3 different types - of widgets: \\n \\n Embedded in page: the search input is embedded in a page - and the results are displayed under the input. Once the initial answer is - displayed, the user can click on Ask more to access the full chat interface. - Note: For the correct reading of the results, the width of the widget container - should not be less than 384px. \\n \\n Web components: \\n html \\n \\n \\n - \\n Chat mode: displays directly the full chat interface. \\n \\n Web component: - \\n html \\n \\n \\n Popup modal: the search inout and the results are displayed - in a popup modal. \\n \\n Web component: \\n html \\n \\n The features parameter - \\n The features parameter allows you to customize the behavior of the widget. - It is a comma-separated list of features among the following: \\n \\n filter: - display a filter dropdown in the search bar. \\n navigateToFile: open the - file in the browser when clicking on the result (by default, the file is displayed - in the viewer). \\n navigateToLink: open the link in the browser when clicking - on the result (by default, the link is displayed in the viewer). \\n permalink: - add the search query and criteria to the URL, allowing the widget to re-render - the same results upon loading. \\n relations: display an info card on the - right side of the widget listing all the relations of the entity mentioned - in the user query. \\n suggestions: display a list of suggested resource titles - matching the user input. \\n suggestLabels: display a list of suggestions - based on the labels when the user starts typing in the search bar. \\n autocompleteFromNERs: - display a list of suggestions based on the NERs extracted from the user query - when the user starts typing in the search bar. \\n displayMetadata: display - the metadata associated with the resource in the result rows. \\n answers: - trigger the answer generation process when the user makes a search. \\n hideResults: - hide the search results, only the generative answer will be displayed. \\n - hideThumbnails: hide the thumbnails associated with the resource in the result - rows. \\n displayFieldList: display a section listing all the fields of the - resource in the right sidebar of the viewer. This section is only visible - for resources containing multiple fields. \\n citations: include citations - in the generative answer. \\n rephrase: rephrase the user question in order - to optimize the quality of the search results. \\n debug: display extra buttons - to download the last request full log of the debug metadata returned by the - API. It must not be used in production. \\n preferMarkdown: require the generative - answer to be formatted in Markdown. \\n openNewTab: open the link in a new - tab when clicking on the result. \\n orFilterLogic: use the OR logic for filters - instead of the default AND logic. \\n noChatHistory: the previous questions - and answers in the chat mode will not be passed as context when generating - a new answer. \\n showHidden: display hidden resources in the search results. - \\n showAttachedImages: display images attached to the matching paragraphs - in the search results. \\n \\n Other parameters \\n \\n backend: the URL of - the backend to use. Useful if you use your own proxy to access the Agentic - RAG API. \\n zone: the zone to use. \\n knowledgebox: the Knowledge Box id. - \\n placeholder: the text displayed in the search bar when it is empty. \\n - lang: the language of the widget. Currently supported: ca, fr, en, es. Default: - en. \\n apikey: the API key to use. It is not recommended to use it in production - (the API key is meant to be injected by your proxy). \\n account: the account - id. \\n state: the publication state of the Knowledge Box. \\n standalone: - set to true when using a standalone NucliaDB instance. \\n proxy: set to true - when using a proxy to access the Agentic RAG API. \\n mode: set to dark to - display the widget in dark mode. \\n filters: define the filters offered to - the user in the search bar among labels, entities, created and labelFamilies. - \\n preselected_filters: define filters that will be applied by default to - any query. \\n csspath: the path to the CSS file to use to customize the widget - style. \\n prompt: the prompt to use for the generative model. It must use - {context} and {question} variables. \\n system_prompt: the system prompt to - use for the generative model. \\n rephrase_prompt: the prompt to use when - optimizing the user query to get the best search results. \\n generativemodel: - the generative model to use for the answer generation. \\n rag_strategies: - the RAG strategies to apply to the retrieved paragraphs. \\n rag_images_strategies: - the RAG strategies to apply to the retrieved images. \\n not_enough_data_message: - the message to display when there is not enough data to generate an answer. - \\n ask_to_resource: the resource ID to use as context for the generative - model. \\n max_tokens: the maximum number of input tokens to put in the final - context (including the prompt, the retrieved results and the user question). - \\n max_output_tokens: the maximum number of tokens to generate. \\n max_paragraphs: - the maximum number of paragraphs to pass in the context to the generative - model (default: 20). \\n query_prepend: the hard-coded text to prepend to - the user query. \\n json_schema: the JSON schema to use to get a JSON answer - from the generative model. \\n vectorset: the embedding model to use for the - semantic search. \\n chat_placeholder: the placeholder to display in the chat - input. \\n audit_metadata: custom metatada to add in API calls for auditing - purposes. \\n 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\\n\",\"id\":\"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":20,\"start\":5203,\"end\":5412,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"dd41482018924facb5dbb87a7d53f122\":{\"id\":\"dd41482018924facb5dbb87a7d53f122\",\"slug\":\"docs-ingestion-how-to-rate-limiting-md\",\"title\":\"docs - > ingestion > how to > rate limiting\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:05.339624\",\"modified\":\"2026-06-09T08:18:12.259849\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - rate-limiting\\ntitle: Manage rate limiting\\n---\\n\\n# Manage rate limiting\\n\\nRate - limits are an essential aspect of the Agentic RAG platform, ensuring fair - usage and optimal performance for all users interacting with Agentic RAG APIs. - This document outlines the rate limits enforced by Agentic RAG and provides - guidelines for handling rate-limited responses effectively.\\n\\n## Introduction\\n\\nAgentic - RAG can apply two types of limits to its APIs:\\n\\n- **Regular API rate limits**: - By default, the sum of all authenticated requests in a Agentic RAG account - cannot exceed 2400 requests per minute. Note that this limit can be customized - on a per-account basis. Please contact [Agentic RAG's support team](mailto:support@nuclia.com) - if you need an increase.\\n\\n- **Ingestion back pressure limits**: Agentic - RAG implements a back-pressure mechanism to manage ingestion pipeline overload. - This mainly affects endpoints for uploading data and creating or updating - resources.\\n\\n## Handling Rate-Limited Responses\\n\\nAgentic RAG adheres - to [the HTTP standard](https://datatracker.ietf.org/doc/html/rfc6585#section-4) - and will return a response with a `429` status codes when the limits are exceeded.\\n\\nThe - official Agentic RAG API clients already have built-in mechanisms for retrying - requests when rate limits are encountered:\\n\\n- [Nuclia Python client](/docs/develop/python-sdk/README)\\n- - [Nuclia JavaScript client](/docs/develop/js-sdk/)\\n\\nHowever, if you are - interacting directly with the API, we recommend using an [exponential backoff - retry strategy](https://en.wikipedia.org/wiki/Exponential_backoff) when limits - are reached.\\n\\nWhen ingestion back pressure rate limits are hit, the response - will include a `try_after` key with an estimated UTC time for retrying the - request. You can use this value for retry logic as an alternative to the exponential - backoff strategy.\\n\\n## Example 1: Regular API rate limits\\n\\nHere's an - example of how to implement an exponential backoff retry strategy in Python:\\n\\n```python\\nimport - time\\nimport requests\\n\\ndef make_request_with_exponential_backoff(url, - headers, max_retries=5):\\n retries = 0\\n while retries < max_retries:\\n - \ response = requests.get(url, headers=headers)\\n if response.status_code - == 200:\\n return response.json()\\n elif response.status_code - == 429:\\n wait_time = 2 ** retries # Exponential backoff: 2^retries\\n - \ print(f\\\"Rate limit exceeded. Retrying in {wait_time} seconds...\\\")\\n - \ time.sleep(wait_time)\\n retries += 1\\n else:\\n - \ response.raise_for_status()\\n raise Exception(\\\"Max retries - exceeded\\\")\\n\\n# Example usage\\nurl = \\\"https://your-endpoint\\\"\\nheaders - = {\\\"Authorization\\\": \\\"Bearer YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_exponential_backoff(url, - headers)\\nprint(data)\\n```\\n\\n## Example 2: Ingestion back pressure limits\\n\\nHere's - an example of how to use the try_after key from the response to manage rate - limits:\\n\\n```python\\nimport time\\nfrom datetime import datetime\\n\\nimport - requests\\n\\n\\ndef make_request_with_try_after_info(url, headers, max_retries=5):\\n - \ retries = 0\\n while retries < max_retries:\\n response = requests.get(url, - headers=headers)\\n response_body = response.json()\\n if response.status_code - == 200:\\n return response.json()\\n elif response.status_code - == 429 and \\\"try_after\\\" in response_body:\\n try_after = response_body[\\\"try_after\\\"]\\n - \ retry_time = datetime.strptime(try_after, \\\"%Y-%m-%dT%H:%M:%S.%fZ\\\")\\n - \ wait_time = (retry_time - datetime.utcnow()).total_seconds()\\n - \ print(\\n f\\\"Rate limit exceeded. Retrying at - {retry_time} (in {wait_time} seconds)...\\\"\\n )\\n time.sleep(wait_time)\\n - \ retries += 1\\n else:\\n response.raise_for_status()\\n - \ raise Exception(\\\"Max retries exceeded\\\")\\n\\n\\n# Example usage\\nurl - = \\\"https://your-endpoint\\\"\\nheaders = {\\\"Authorization\\\": \\\"Bearer - YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_try_after_info(url, headers)\\nprint(data)\\n```\\n\\nThese - examples demonstrate how to handle rate limits effectively, ensuring that - your application respects the limits and retries appropriately.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"ed11945857f4618eec7ed0d1b16ffa44\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: rate-limiting \\n title: Manage rate limiting \\n \\n Manage rate - limiting \\n Rate limits are an essential aspect of the Agentic RAG platform, - ensuring fair usage and optimal performance for all users interacting with - Agentic RAG APIs. This document outlines the rate limits enforced by Agentic - RAG and provides guidelines for handling rate-limited responses effectively. - \\n Introduction \\n Agentic RAG can apply two types of limits to its APIs: - \\n \\n \\n Regular API rate limits: By default, the sum of all authenticated - requests in a Agentic RAG account cannot exceed 2400 requests per minute. - Note that this limit can be customized on a per-account basis. Please contact - Agentic RAG's support team if you need an increase. \\n \\n \\n Ingestion - back pressure limits: Agentic RAG implements a back-pressure mechanism to - manage ingestion pipeline overload. This mainly affects endpoints for uploading - data and creating or updating resources. \\n \\n \\n Handling Rate-Limited - Responses \\n Agentic RAG adheres to the HTTP standard and will return a response - with a 429 status codes when the limits are exceeded. \\n The official Agentic - RAG API clients already have built-in mechanisms for retrying requests when - rate limits are encountered: \\n \\n Nuclia Python client \\n Nuclia JavaScript - client \\n \\n However, if you are interacting directly with the API, we recommend - using an exponential backoff retry strategy when limits are reached. \\n When - ingestion back pressure rate limits are hit, the response will include a try_after - key with an estimated UTC time for retrying the request. You can use this - value for retry logic as an alternative to the exponential backoff strategy. - \\n Example 1: Regular API rate limits \\n Here's an example of how to implement - an exponential backoff retry strategy in Python: \\n ```python \\n import - time \\n import requests \\n def make_request_with_exponential_backoff(url, - headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: - \\n response = requests.get(url, headers=headers) \\n if response.status_code - == 200: \\n return response.json() \\n elif response.status_code == 429: \\n - wait_time = 2 retries # Exponential backoff: 2^retries \\n print(f Rate limit - exceeded. Retrying in {wait_time} seconds... ) \\n time.sleep(wait_time) \\n - retries += 1 \\n else: \\n response.raise_for_status() \\n raise Exception( - Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint \\n - headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_exponential_backoff(url, - headers) \\n print(data) \\n ``` \\n Example 2: Ingestion back pressure limits - \\n Here's an example of how to use the try_after key from the response to - manage rate limits: \\n ```python \\n import time \\n from datetime import - datetime \\n import requests \\n def make_request_with_try_after_info(url, - headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: - \\n response = requests.get(url, headers=headers) \\n response_body = response.json() - \\n if response.status_code == 200: \\n return response.json() \\n elif response.status_code - == 429 and try_after in response_body: \\n try_after = response_body[ try_after - ] \\n retry_time = datetime.strptime(try_after, %Y-%m-%dT%H:%M:%S.%fZ ) \\n - wait_time = (retry_time - datetime.utcnow()).total_seconds() \\n print( \\n - f Rate limit exceeded. Retrying at {retry_time} (in {wait_time} seconds)... - \\n ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() - \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint - \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, - headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle - rate limits effectively, ensuring that your application respects the limits - and retries 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- Rate-Limited Responses Agentic RAG\":\"LAW\",\"Python\":\"PRODUCT\",\"Agentic - RAG API\":\"PRODUCT\",\"HTTP\":\"LAW\",\"Agentic RAG\":\"ORG\",\"seconds\":\"TIME\",\"Agentic - RAG's\":\"ORG\"},\"entities\":{\"processor\":{\"entities\":[{\"text\":\"Agentic - RAG\",\"label\":\"ORG\",\"positions\":[{\"start\":121,\"end\":132},{\"start\":287,\"end\":298},{\"start\":530,\"end\":541}]},{\"text\":\"Agentic - RAG's\",\"label\":\"ORG\",\"positions\":[{\"start\":668,\"end\":681}]},{\"text\":\"Handling - Rate-Limited Responses Agentic RAG\",\"label\":\"LAW\",\"positions\":[{\"start\":937,\"end\":982}]},{\"text\":\"HTTP\",\"label\":\"LAW\",\"positions\":[{\"start\":998,\"end\":1002}]},{\"text\":\"Agentic - RAG 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system\",\"metadata\":{\"paragraph_id\":\"dd41482018924facb5dbb87a7d53f122/t/page/1222-1656\",\"source_start\":1248,\"source_end\":1254,\"to_start\":1232,\"to_end\":1238},\"from\":{\"value\":\"Nuclia\",\"type\":\"entity\",\"group\":\"ORG\"},\"to\":{\"value\":\"Python\",\"type\":\"entity\",\"group\":\"PRODUCT\"}}],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > ingestion > how to > rate limiting\",\"extracted\":{\"text\":{\"text\":\"docs - > ingestion > how to > rate limiting\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\":{\"score\":0.590923011302948,\"score_type\":\"VECTOR\",\"order\":18,\"text\":\" - ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() - \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint - \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, - headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle - rate limits effectively, ensuring that your application respects the limits - and retries appropriately.\",\"id\":\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":9,\"start\":3310,\"end\":3757,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"1b2a9e67b9f14a0cb81efaa05b8793b8\":{\"id\":\"1b2a9e67b9f14a0cb81efaa05b8793b8\",\"slug\":\"docs-develop-js-sdk-interfaces-AugmentedField-md\",\"title\":\"docs - > develop > js sdk > interfaces > AugmentedField\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:00:05.937520\",\"modified\":\"2026-07-14T12:49:32.163110\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/AugmentedField\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / AugmentedField\\n\\n# - Interface: AugmentedField\\n\\n## Properties\\n\\n### applied\\\\_data\\\\_augmentation\\n\\n> - **applied\\\\_data\\\\_augmentation**: [`AppliedDataAugmentation`](AppliedDataAugmentation.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:571](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L571)\\n\\n***\\n\\n### - input\\\\_nuclia\\\\_tokens\\n\\n> **input\\\\_nuclia\\\\_tokens**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:572](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L572)\\n\\n***\\n\\n### - metadata\\n\\n> **metadata**: [`FieldMetadata`](FieldMetadata.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:570](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L570)\\n\\n***\\n\\n### - output\\\\_nuclia\\\\_tokens\\n\\n> **output\\\\_nuclia\\\\_tokens**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:573](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L573)\\n\\n***\\n\\n### - time\\n\\n> **time**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:574](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L574)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"1e8e95b886439059ae4ec717c9bcf283\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / AugmentedField \\n Interface: AugmentedField - \\n Properties \\n applied_data_augmentation \\n \\n applied_data_augmentation: - AppliedDataAugmentation \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:571 - \\n \\n input_nuclia_tokens \\n \\n input_nuclia_tokens: number \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:572 \\n \\n metadata - \\n \\n metadata: FieldMetadata \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:570 - \\n \\n output_nuclia_tokens \\n \\n output_nuclia_tokens: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:573 \\n - \\n time \\n \\n time: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:574\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":641,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":641,\"key\":\"\"}]},{\"start\":641,\"end\":729,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":642,\"end\":729,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:49:33.585675Z\",\"last_understanding\":\"2026-07-14T12:49:33.340252Z\",\"last_extract\":\"2026-07-14T12:49:32.941746Z\",\"last_processing_start\":\"2026-07-14T12:49:32.917812Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > AugmentedField\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > AugmentedField\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"1b2a9e67b9f14a0cb81efaa05b8793b8/t/page/0-641\":{\"score\":0.5881041884422302,\"score_type\":\"VECTOR\",\"order\":19,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / AugmentedField \\n Interface: AugmentedField - \\n Properties \\n applied_data_augmentation \\n \\n applied_data_augmentation: - AppliedDataAugmentation \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:571 - \\n \\n input_nuclia_tokens \\n \\n input_nuclia_tokens: number \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:572 \\n \\n metadata - \\n \\n metadata: FieldMetadata \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:570 - \\n \\n output_nuclia_tokens \\n \\n output_nuclia_tokens: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:573 \\n - \\n time \\n \\n\",\"id\":\"1b2a9e67b9f14a0cb81efaa05b8793b8/t/page/0-641\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":641,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs - > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-07-14T12:51:04.368823\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ChatOptions\\n\\n# - Interface: ChatOptions\\n\\n## Extends\\n\\n- [`BaseSearchOptions`](BaseSearchOptions.md)\\n\\n## - Properties\\n\\n### answer\\\\_json\\\\_schema?\\n\\n> `optional` **answer\\\\_json\\\\_schema**: - `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:114](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L114)\\n\\n***\\n\\n### - audit\\\\_metadata?\\n\\n> `optional` **audit\\\\_metadata**: `object`\\n\\n#### - Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `string`\\n\\n#### Inherited - from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`audit_metadata`](BaseSearchOptions.md#audit_metadata)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:81](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L81)\\n\\n***\\n\\n### - citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:116](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L116)\\n\\n***\\n\\n### - citations?\\n\\n> `optional` **citations**: `boolean` \\\\| `\\\"none\\\"` - \\\\| `\\\"default\\\"` \\\\| `\\\"llm_footnotes\\\"`\\n\\nIt will return - the text blocks that have been effectively used to build each section of the - answer.\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:105](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L105)\\n\\n***\\n\\n### - debug?\\n\\n> `optional` **debug**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`debug`](BaseSearchOptions.md#debug)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:79](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L79)\\n\\n***\\n\\n### - extra\\\\_context?\\n\\n> `optional` **extra\\\\_context**: `string`[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:115](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L115)\\n\\n***\\n\\n### - extra\\\\_context\\\\_images?\\n\\n> `optional` **extra\\\\_context\\\\_images**: - `object`[]\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:118](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L118)\\n\\n***\\n\\n### - ~~extracted?~~\\n\\n> `optional` **extracted**: [`ExtractedDataTypes`](../enumerations/ExtractedDataTypes.md)[]\\n\\n#### - Deprecated\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`extracted`](BaseSearchOptions.md#extracted)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:73](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L73)\\n\\n***\\n\\n### - features?\\n\\n> `optional` **features**: [`Features`](../namespaces/Ask/enumerations/Features.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:117](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L117)\\n\\n***\\n\\n### - field\\\\_type\\\\_filter?\\n\\n> `optional` **field\\\\_type\\\\_filter**: - [`FIELD_TYPE`](../enumerations/FIELD_TYPE.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`field_type_filter`](BaseSearchOptions.md#field_type_filter)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:74](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L74)\\n\\n***\\n\\n### - fields?\\n\\n> `optional` **fields**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`fields`](BaseSearchOptions.md#fields)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:62](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L62)\\n\\n***\\n\\n### - filter\\\\_expression?\\n\\n> `optional` **filter\\\\_expression**: [`FilterExpression`](FilterExpression.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filter_expression`](BaseSearchOptions.md#filter_expression)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:64](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L64)\\n\\n***\\n\\n### - filters?\\n\\n> `optional` **filters**: `string`[] \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filters`](BaseSearchOptions.md#filters)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:63](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L63)\\n\\n***\\n\\n### - generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:108](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L108)\\n\\n***\\n\\n### - highlight?\\n\\n> `optional` **highlight**: `boolean`\\n\\n#### Inherited - from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`highlight`](BaseSearchOptions.md#highlight)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:76](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L76)\\n\\n***\\n\\n### - keyword\\\\_filters?\\n\\n> `optional` **keyword\\\\_filters**: `string`[] - \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`keyword_filters`](BaseSearchOptions.md#keyword_filters)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:65](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L65)\\n\\n***\\n\\n### - max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number` \\\\| `object`\\n\\nDefines - the maximum number of tokens that the model will take as context.\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:112](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L112)\\n\\n***\\n\\n### - min\\\\_score?\\n\\n> `optional` **min\\\\_score**: `number` \\\\| [`MinScore`](MinScore.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`min_score`](BaseSearchOptions.md#min_score)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:66](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L66)\\n\\n***\\n\\n### - prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:113](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L113)\\n\\n***\\n\\n### - prompt?\\n\\n> `optional` **prompt**: `string` \\\\| [`Prompts`](Prompts.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:101](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L101)\\n\\n***\\n\\n### - query\\\\_image?\\n\\n> `optional` **query\\\\_image**: `object`\\n\\n#### - b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> - **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:122](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L122)\\n\\n***\\n\\n### - rag\\\\_images\\\\_strategies?\\n\\n> `optional` **rag\\\\_images\\\\_strategies**: - [`RAGImageStrategy`](../type-aliases/RAGImageStrategy.md)[]\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:107](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L107)\\n\\n***\\n\\n### - rag\\\\_strategies?\\n\\n> `optional` **rag\\\\_strategies**: [`RAGStrategy`](../type-aliases/RAGStrategy.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:106](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L106)\\n\\n***\\n\\n### - range\\\\_creation\\\\_end?\\n\\n> `optional` **range\\\\_creation\\\\_end**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_end`](BaseSearchOptions.md#range_creation_end)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:68](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L68)\\n\\n***\\n\\n### - range\\\\_creation\\\\_start?\\n\\n> `optional` **range\\\\_creation\\\\_start**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_start`](BaseSearchOptions.md#range_creation_start)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:67](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L67)\\n\\n***\\n\\n### - range\\\\_modification\\\\_end?\\n\\n> `optional` **range\\\\_modification\\\\_end**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_end`](BaseSearchOptions.md#range_modification_end)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:70](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L70)\\n\\n***\\n\\n### - range\\\\_modification\\\\_start?\\n\\n> `optional` **range\\\\_modification\\\\_start**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_start`](BaseSearchOptions.md#range_modification_start)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:69](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L69)\\n\\n***\\n\\n### - rank\\\\_fusion?\\n\\n> `optional` **rank\\\\_fusion**: [`RankFusion`](RankFusion.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rank_fusion`](BaseSearchOptions.md#rank_fusion)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:84](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L84)\\n\\n***\\n\\n### - reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L126)\\n\\n***\\n\\n### - rephrase?\\n\\n> `optional` **rephrase**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rephrase`](BaseSearchOptions.md#rephrase)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:77](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L77)\\n\\n***\\n\\n### - reranker?\\n\\n> `optional` **reranker**: [`Reranker`](../enumerations/Reranker.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`reranker`](BaseSearchOptions.md#reranker)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:83](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L83)\\n\\n***\\n\\n### - resource\\\\_filters?\\n\\n> `optional` **resource\\\\_filters**: `string`[]\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`resource_filters`](BaseSearchOptions.md#resource_filters)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:75](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L75)\\n\\n***\\n\\n### - search\\\\_configuration?\\n\\n> `optional` **search\\\\_configuration**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`search_configuration`](BaseSearchOptions.md#search_configuration)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:86](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L86)\\n\\n***\\n\\n### - security?\\n\\n> `optional` **security**: `object`\\n\\n#### groups\\n\\n> - **groups**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`security`](BaseSearchOptions.md#security)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:85](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L85)\\n\\n***\\n\\n### - show?\\n\\n> `optional` **show**: [`ResourceProperties`](../enumerations/ResourceProperties.md)[]\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show`](BaseSearchOptions.md#show)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:71](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L71)\\n\\n***\\n\\n### - show\\\\_consumption?\\n\\n> `optional` **show\\\\_consumption**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L127)\\n\\n***\\n\\n### - show\\\\_hidden?\\n\\n> `optional` **show\\\\_hidden**: `boolean`\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show_hidden`](BaseSearchOptions.md#show_hidden)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:80](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L80)\\n\\n***\\n\\n### - synchronous?\\n\\n> `optional` **synchronous**: `boolean`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:100](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L100)\\n\\n***\\n\\n### - top\\\\_k?\\n\\n> `optional` **top\\\\_k**: `number`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`top_k`](BaseSearchOptions.md#top_k)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:82](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L82)\\n\\n***\\n\\n### - vectorset?\\n\\n> `optional` **vectorset**: `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`vectorset`](BaseSearchOptions.md#vectorset)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:78](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L78)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"d6b2f3f31ba0af4fa58490cdf6abeb52\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ChatOptions \\n Interface: ChatOptions - \\n Extends \\n \\n BaseSearchOptions \\n \\n Properties \\n answer_json_schema? - \\n \\n optional answer_json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:114 - \\n \\n audit_metadata? \\n \\n optional audit_metadata: object \\n \\n Index - Signature \\n [key: string]: string \\n Inherited from \\n BaseSearchOptions.audit_metadata - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:81 \\n - \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:116 \\n \\n - citations? \\n \\n optional citations: boolean \\\\| none \\\\| default \\\\| - llm_footnotes \\n \\n It will return the text blocks that have been effectively - used to build each section of the answer. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:105 - \\n \\n debug? \\n \\n optional debug: boolean \\n \\n Inherited from \\n - BaseSearchOptions.debug \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:79 - \\n \\n extra_context? \\n \\n optional extra_context: string[] \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:115 \\n \\n extra_context_images? - \\n \\n optional extra_context_images: object[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:118 - \\n \\n ~~extracted?~~ \\n \\n optional extracted: ExtractedDataTypes[] \\n - \\n Deprecated \\n Inherited from \\n BaseSearchOptions.extracted \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:73 \\n \\n features? - \\n \\n optional features: Features[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:117 - \\n \\n field_type_filter? \\n \\n optional field_type_filter: FIELD_TYPE[] - \\n \\n Inherited from \\n BaseSearchOptions.field_type_filter \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:74 \\n \\n fields? - \\n \\n optional fields: string[] \\n \\n Inherited from \\n BaseSearchOptions.fields - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:62 \\n - \\n filter_expression? \\n \\n optional filter_expression: FilterExpression - \\n \\n Inherited from \\n BaseSearchOptions.filter_expression \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:64 \\n \\n filters? - \\n \\n optional filters: string[] \\\\| Filter[] \\n \\n Inherited from \\n - BaseSearchOptions.filters \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:63 - \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:108 \\n \\n - highlight? \\n \\n optional highlight: boolean \\n \\n Inherited from \\n - BaseSearchOptions.highlight \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:76 - \\n \\n keyword_filters? \\n \\n optional keyword_filters: string[] \\\\| - Filter[] \\n \\n Inherited from \\n BaseSearchOptions.keyword_filters \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:65 \\n \\n - max_tokens? \\n \\n optional max_tokens: number \\\\| object \\n \\n Defines - the maximum number of tokens that the model will take as context. \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 \\n \\n min_score? - \\n \\n optional min_score: number \\\\| MinScore \\n \\n Inherited from \\n - BaseSearchOptions.min_score \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:66 - \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:113 \\n \\n - prompt? \\n \\n optional prompt: string \\\\| Prompts \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/search/search.models.ts:101 \\n \\n query_image? - \\n \\n optional query_image: object \\n \\n b64encoded \\n \\n b64encoded: - string \\n \\n content_type \\n \\n content_type: string \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/search.models.ts:122 \\n \\n rag_images_strategies? - \\n \\n optional rag_images_strategies: RAGImageStrategy[] \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:107 \\n \\n rag_strategies? - \\n \\n optional rag_strategies: RAGStrategy[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:106 - \\n \\n range_creation_end? \\n \\n optional range_creation_end: string \\n - \\n Inherited from \\n BaseSearchOptions.range_creation_end \\n Defined in - \\n libs/sdk-core/src/lib/db/search/search.models.ts:68 \\n \\n range_creation_start? - \\n \\n optional range_creation_start: string \\n \\n Inherited from \\n BaseSearchOptions.range_creation_start - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:67 \\n - \\n range_modification_end? \\n \\n optional range_modification_end: string - \\n \\n Inherited from \\n BaseSearchOptions.range_modification_end \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:70 \\n \\n range_modification_start? - \\n \\n optional range_modification_start: string \\n \\n Inherited from \\n - BaseSearchOptions.range_modification_start \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:69 - \\n \\n rank_fusion? \\n \\n optional rank_fusion: RankFusion \\n \\n Inherited - from \\n BaseSearchOptions.rank_fusion \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:84 - \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:126 \\n \\n rephrase? - \\n \\n optional rephrase: boolean \\n \\n Inherited from \\n BaseSearchOptions.rephrase - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:77 \\n - \\n reranker? \\n \\n optional reranker: Reranker \\n \\n Inherited from \\n - BaseSearchOptions.reranker \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:83 - \\n \\n resource_filters? \\n \\n optional resource_filters: string[] \\n - \\n Inherited from \\n BaseSearchOptions.resource_filters \\n Defined in \\n - libs/sdk-core/src/lib/db/search/search.models.ts:75 \\n \\n search_configuration? - \\n \\n optional search_configuration: string \\n \\n Inherited from \\n BaseSearchOptions.search_configuration - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:86 \\n - \\n 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libs/sdk-core/src/lib/db/search/search.models.ts:82 \\n - \\n vectorset? \\n \\n optional vectorset: string \\n \\n Inherited from \\n - BaseSearchOptions.vectorset \\n Defined in \\n 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models\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-05-23T07:21:32.894218\",\"modified\":\"2026-06-09T08:07:43.359058\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - openai-api-compatible-models\\ntitle: Connect to any OpenAI API compatible - LLM\\n---\\n\\n# Connect to any OpenAI API compatible LLM\\n\\nAgentic RAG - allows you to connect to any OpenAI API compatible LLM. This means that you - can use any LLM that has an API compatible with the OpenAI API which has become - a standard in the industry.\\n\\nMany of the options for self-hosted LLMs, - open-source LLMs hosted by cloud providers or commercial LLMs are compatible - with the OpenAI API. This means that you can use them with Agentic RAG without - any modifications.\\n\\n## Configuration\\n\\nTo modify your knowledge box - configuration you can do so in three manners, through the API, the Nuclia - CLI / SDK or the Agentic RAG dashboard.\\n\\nThe Agentic RAG dashboard offers - the most user-friendly way to modify the configuration of your knowledge box - and we will use it in this example.\\n\\nWe will be setting up a connection - to the **Phi 4 Reasoning Plus** model, hosted by **OpenRouter** which offers - a wide range of open-source and commercial models compatible with the OpenAI - API. We can see more information about this specific model [here](https://openrouter.ai/microsoft/phi-4-reasoning-plus:free), - the API parameters are located under the **API** tab.\\n\\n1. **Open the AI - Models page** \\n In the left sidebar under **Advanced**, click **AI Models**.\\n2. - **Select \u201COpenAI API Compatible Model\u201D** \\n From the models - list, choose **OpenAI API Compatible Model**.\\n3. **Enable custom Key** \\n - \ Toggle the option for using you own `OpenAI API Compatible Key` if it is - not already enabled.\\n4. **Fill in the configuration parameters**\\n\\n - - **API Key**:\\n - Description: The API key for your LLM. This is the key - that you would use as an authorization header in the API. You may leave this - blank if the endpoint you are connecting to does not require an API key.\\n - \ - Example: We will set this to our OpenRouter API key.\\n - **API URL**:\\n - \ - Description: The URL of the API endpoint for your LLM. This may be - shared between multiple models.\\n - Example: For OpenRouter, it is the - same for all models: `https://openrouter.ai/api/v1`\\n - **Model**:\\n - - Description: The name of the model you want to use, it needs to exactly match - the name of the model in the API.\\n - Example: For Phi 4 Reasoning Plus - in the OpenRouter API, it is `microsoft/phi-4-reasoning-plus:free`.\\n - - **Maximum supported input tokens**:\\n - Description: The maximum number - of tokens that the model can accept as input. Be mindful that this takes into - account the tokens used in the prompt, query and context. Also take note that - some models may provide their context window as the total between input and - output tokens, while others may provide it as the input tokens only.\\n - - Example: For Phi 4 Reasoning Plus, the total context size is `32768` tokens, - as we want to leave room for the output, we will set the maximum supported - input tokens as `32768 - 1024 = 31744`.\\n - **Maximum supported output - tokens**:\\n - Description: The maximum number of tokens that the model - can generate as output. Again, we should keep in mind that this value summed - to the **Maximum supported input tokens** should not exceed the total context - size supported by the model.\\n - Example: For Phi 4 Reasoning Plus, the - maximum output tokens is specified at `32768`, but we already reserved `31744` - for the input tokens, so we will set this to `32768 - 31744 = 1024`.\\n - - **Model Features**:\\n - Description: Under this section you will find - multiple toggles related to features supported by the model, these vary from - model to model, but most often the default values are well suited to most - use cases. The most relevant toggle is for `Image Support` which allows you - to use images as input for the model.\\n - Example: Image input is not - supported by Phi 4 Reasoning Plus, so we will leave it disabled.\\n\\n5. **Save** - \ \\n Click **Save changes**.\\n\\n6. **Test your model** \\n Run a sample - query in Agentic RAG or via API/CLI. Adjust your prompt templates and token - settings as needed.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"37cd8aff748addd04a363fa50828d1fe\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: openai-api-compatible-models \\n title: Connect to any OpenAI API - compatible LLM \\n \\n Connect to any OpenAI API compatible LLM \\n Agentic - RAG allows you to connect to any OpenAI API compatible LLM. This means that - you can use any LLM that has an API compatible with the OpenAI API which has - become a standard in the industry. \\n Many of the options for self-hosted - LLMs, open-source LLMs hosted by cloud providers or commercial LLMs are compatible - with the OpenAI API. This means that you can use them with Agentic RAG without - any modifications. \\n Configuration \\n To modify your knowledge box configuration - you can do so in three manners, through the API, the Nuclia CLI / SDK or the - Agentic RAG dashboard. \\n The Agentic RAG dashboard offers the most user-friendly - way to modify the configuration of your knowledge box and we will use it in - this example. \\n We will be setting up a connection to the Phi 4 Reasoning - Plus model, hosted by OpenRouter which offers a wide range of open-source - and commercial models compatible with the OpenAI API. We can see more information - about this specific model here, the API parameters are located under the API - tab. \\n \\n Open the AI Models page \\n In the left sidebar under Advanced, - click AI Models. \\n Select OpenAI API Compatible Model \\n From the models - list, choose OpenAI API Compatible Model. \\n Enable custom Key \\n Toggle - the option for using you own OpenAI API Compatible Key if it is not already - enabled. \\n \\n Fill in the configuration parameters \\n \\n \\n API Key: - \\n \\n Description: The API key for your LLM. This is the key that you would - use as an authorization header in the API. You may leave this blank if the - endpoint you are connecting to does not require an API key. \\n Example: We - will set this to our OpenRouter API key. \\n \\n \\n API URL: \\n Description: - The URL of the API endpoint for your LLM. This may be shared between multiple - models. \\n Example: For OpenRouter, it is the same for all models: https://openrouter.ai/api/v1 - \\n \\n \\n Model: \\n Description: The name of the model you want to use, - it needs to exactly match the name of the model in the API. \\n Example: For - Phi 4 Reasoning Plus in the OpenRouter API, it is microsoft/phi-4-reasoning-plus:free. - \\n \\n \\n Maximum supported input tokens: \\n Description: The maximum number - of tokens that the model can accept as input. Be mindful that this takes into - account the tokens used in the prompt, query and context. Also take note that - some models may provide their context window as the total between input and - output tokens, while others may provide it as the input tokens only. \\n Example: - For Phi 4 Reasoning Plus, the total context size is 32768 tokens, as we want - to leave room for the output, we will set the maximum supported input tokens - as 32768 - 1024 = 31744. \\n \\n \\n Maximum supported output tokens: \\n - Description: The maximum number of tokens that the model can generate as output. - Again, we should keep in mind that this value summed to the Maximum supported - input tokens should not exceed the total context size supported by the model. - \\n Example: For Phi 4 Reasoning Plus, the maximum output tokens is specified - at 32768, but we already reserved 31744 for the input tokens, so we will set - this to 32768 - 31744 = 1024. \\n \\n \\n \\n Model Features: \\n \\n Description: - Under this section you will find multiple toggles related to features supported - by the model, these vary from model to model, but most often the default values - are well suited to most use cases. 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\u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / UsageType\\n\\n# - Enumeration: UsageType\\n\\n## Enumeration Members\\n\\n### AI\\\\_TOKENS\\\\_USED\\n\\n> - **AI\\\\_TOKENS\\\\_USED**: `\\\"ai_tokens_used\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:206](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L206)\\n\\n***\\n\\n### - BYTES\\\\_PROCESSED\\n\\n> **BYTES\\\\_PROCESSED**: `\\\"bytes_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:197](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L197)\\n\\n***\\n\\n### - CHARS\\\\_PROCESSED\\n\\n> **CHARS\\\\_PROCESSED**: `\\\"chars_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:198](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L198)\\n\\n***\\n\\n### - MEDIA\\\\_FILES\\\\_PROCESSED\\n\\n> **MEDIA\\\\_FILES\\\\_PROCESSED**: `\\\"media_files_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:200](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L200)\\n\\n***\\n\\n### - MEDIA\\\\_SECONDS\\\\_PROCESSED\\n\\n> **MEDIA\\\\_SECONDS\\\\_PROCESSED**: - `\\\"media_seconds_processed\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:199](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L199)\\n\\n***\\n\\n### - NUCLIA\\\\_TOKENS\\n\\n> **NUCLIA\\\\_TOKENS**: `\\\"nuclia_tokens_billed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:207](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L207)\\n\\n***\\n\\n### - PAGES\\\\_PROCESSED\\n\\n> **PAGES\\\\_PROCESSED**: `\\\"pages_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:201](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L201)\\n\\n***\\n\\n### - PARAGRAPHS\\\\_PROCESSED\\n\\n> **PARAGRAPHS\\\\_PROCESSED**: `\\\"paragraphs_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:202](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L202)\\n\\n***\\n\\n### - PRE\\\\_PROCESSING\\\\_TIME\\n\\n> **PRE\\\\_PROCESSING\\\\_TIME**: `\\\"pre_processing_time\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:194](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L194)\\n\\n***\\n\\n### - RESOURCES\\\\_PROCESSED\\n\\n> **RESOURCES\\\\_PROCESSED**: `\\\"resources_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:196](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L196)\\n\\n***\\n\\n### - SEARCHES\\\\_PERFORMED\\n\\n> **SEARCHES\\\\_PERFORMED**: `\\\"searches_performed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:204](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L204)\\n\\n***\\n\\n### - SLOW\\\\_PROCESSING\\\\_TIME\\n\\n> **SLOW\\\\_PROCESSING\\\\_TIME**: `\\\"slow_processing_time\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:195](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L195)\\n\\n***\\n\\n### - SUGGESTIONS\\\\_PERFORMED\\n\\n> **SUGGESTIONS\\\\_PERFORMED**: `\\\"suggestions_performed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:205](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L205)\\n\\n***\\n\\n### - TRAIN\\\\_SECONDS\\n\\n> **TRAIN\\\\_SECONDS**: `\\\"train_seconds\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:203](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L203)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"a6825b7bf9d5960444b0981f205811a3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / UsageType \\n Enumeration: UsageType \\n - Enumeration Members \\n AI_TOKENS_USED \\n \\n AI_TOKENS_USED: ai_tokens_used - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:206 \\n \\n BYTES_PROCESSED - \\n \\n BYTES_PROCESSED: bytes_processed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:197 - \\n \\n CHARS_PROCESSED \\n \\n CHARS_PROCESSED: chars_processed \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:198 \\n \\n MEDIA_FILES_PROCESSED - \\n \\n MEDIA_FILES_PROCESSED: media_files_processed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:200 \\n \\n MEDIA_SECONDS_PROCESSED - \\n \\n MEDIA_SECONDS_PROCESSED: media_seconds_processed \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n - NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 - \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED - \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n - \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 - \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED - \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 - \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED - \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: - train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":1833,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:54:13.123173Z\",\"last_understanding\":\"2026-07-14T12:54:12.864112Z\",\"last_extract\":\"2026-07-14T12:54:12.463871Z\",\"last_processing_start\":\"2026-07-14T12:54:12.433665Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - 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It explains that `max_tokens` sets limits on the number + of input tokens and the maximum number of tokens to generate. However, it + does not provide a direct link to the official documentation.\",\"answer\":\"Para + usar el par\xE1metro `max_tokens`, se debe establecer un l\xEDmite en el n\xFAmero + m\xE1ximo de tokens de entrada y en el n\xFAmero m\xE1ximo de tokens a generar. + Esto se puede hacer en el endpoint /ask. El par\xE1metro `max_tokens` limita + la longitud de la respuesta generada. Adem\xE1s, se puede usar `max_output_tokens` + para definir el n\xFAmero m\xE1ximo de tokens a generar. 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- headers: - Alt-Svc: - - h3=":443"; ma=2592000 - Content-Length: - - '11474' - access-control-expose-headers: - - X-NUCLIA-TRACE-ID - content-type: - - application/json - date: - - Wed, 15 Jul 2026 08:11:08 GMT - via: - - 1.1 google - x-envoy-upstream-service-time: - - '153' - x-nuclia-trace-id: - - 8f248de1a21918500f1489d14bc6efa2 - status: - code: 200 - message: OK -- request: - body: '{"user_id": "arag-ask", "texts": ["Explica c\u00f3mo usar el par\u00e1metro - `max_tokens` en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n - oficial."]}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '145' - Host: - - europe-1.dp.progress.cloud + - europe-1.dp.stashify.cloud User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: + - nuclia.py/4.11.5 + x-client-ident: + - default + x-message: + - 61239d46d4574621b88307ea3cf433d5 + x-origin: + - RAO + x-session: + - default_default_session + x-show-consumption: + - 'true' + x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/predict/run-agents-text + uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat response: body: - string: '{"results":[{"input_nuclia_tokens":0.0,"output_nuclia_tokens":0.0,"time":0.0001285076141357422,"payloads":[]}]}' + string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"link\":true,\"semantic_query\":\"Explica + el uso del par\xE1metro `max_tokens` para controlar la longitud de las respuestas + y proporciona un enlace a la documentaci\xF3n oficial.\",\"lexical_query\":\"Sut + mae defnyddio'r paramedr `max_tokens` i reoli hyd ymatebion?\",\"visual\":false,\"keywords_filter\":[\"max_tokens\",\"documentaci\xF3n\"],\"reason\":\"The + user is asking how to use the `max_tokens` parameter to control response length + and specifically requests a link to the official documentation. Therefore, + the semantic query should focus on explaining this parameter and requesting + a link, and the lexical query should ask the same in Welsh. Keywords like + 'max_tokens' and 'documentaci\xF3n' are crucial for retrieving relevant information.\",\"pre_queries\":[]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":36,\"output_tokens\":99,\"timings\":{\"generative\":1.6255864730046596},\"input_nuclia_tokens\":0.036,\"output_nuclia_tokens\":0.099}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0357,\"output\":0.099,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Length: - - '111' + Transfer-Encoding: + - chunked access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - - application/json + - application/x-ndjson date: - - Wed, 15 Jul 2026 08:11:14 GMT + - Wed, 05 Aug 2026 07:57:16 GMT + nuclia-learning-id: + - df8b44391e53433d82d28235efa1e958 + nuclia-learning-model: + - gemini-2.5-flash via: - 1.1 google x-envoy-upstream-service-time: - - '20' + - '1632' x-nuclia-trace-id: - - eb1ea9373075610b727005ee3ba6ae02 + - 544dc327d8fa657188be20294a318c9b status: code: 200 message: OK - request: - body: '{"query": "Sut mae defnyddio''r paramedr `max_tokens` yn Saesneg ac a yw''n - darparu dolen i''r ddogfennaeth swyddogol.", "filters": [], "show": ["basic", - "origin", "extra", "extracted", "values", "relations"], "extracted": ["text", - "metadata", "file", "link"], "security": {"groups": []}, "features": ["keyword"], - "reranker": "noop", "keyword_filters": ["max_tokens", "par\u00e1metro"]}' + body: '{"question": "\u00bfCu\u00e1l es el enlace a la documentaci\u00f3n oficial + sobre el uso del par\u00e1metro `max_tokens`?", "user_id": "arag-ask-rerank", + "context": {"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412": " max_tokens: + the maximum number of input tokens to put in the final context (including the + prompt, the retrieved results and the user question). \n max_output_tokens: + the maximum number of tokens to generate. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n", + "c27a1e5f5ddb4b118921345d713401b8/t/page/351-554": " full: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:386 \n \n max_messages? \n \n + optional max_messages: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:387 + \n \n name \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ConversationalStrategy\n", + "dd41482018924facb5dbb87a7d53f122/t/page/3310-3757": " ) \n time.sleep(wait_time) + \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( + Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers + = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_try_after_info(url, + headers) \n print(data) \n ``` \n These examples demonstrate how to handle rate + limits effectively, ensuring that your application respects the limits and retries + appropriately.\n\n\nLink: https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\n", + "dd41482018924facb5dbb87a7d53f122/t/page/1900-2653": " retries = 0 \n while + retries < max_retries: \n response = requests.get(url, headers=headers) \n if + response.status_code == 200: \n return response.json() \n elif response.status_code + == 429: \n wait_time = 2 retries # Exponential backoff: 2^retries \n print(f + Rate limit exceeded. Retrying in {wait_time} seconds... ) \n time.sleep(wait_time) + \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( + Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers + = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_exponential_backoff(url, + headers) \n print(data) \n ``` \n Example 2: Ingestion back pressure limits + \n Here''s an example of how to use the try_after key from the response to manage + rate limits: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\n", + "43004f553e534ffe9c9e735856bd9b23/t/page/480-703": " \n optional max_images: + string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \n \n + output_tokens \n \n output_tokens: object \n \n default_max? \n \n optional + default_max: number \n \n max \n \n max: number \n \n min? \n \n\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n", + "43004f553e534ffe9c9e735856bd9b23/t/page/212-480": " \n optional driver: string + \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 \n \n input_tokens + \n \n input_tokens: object \n \n max \n \n max: number \n \n min? \n \n optional + min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \n \n max_images? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n", + "e8525e64c5b44982b958d32cf6090613/t/page/2808-3011": " \n optional max_tokens: + number \\| object \n \n Defines the maximum number of tokens that the model + will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n", + "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221": " \n optional max_tokens: + number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", + "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709": " ::: \n :::warning \n + Enabling reasoning can use additional tokens, which may increase your usage + costs. \n You may need to increase max_tokens to give the LLM enough room to + reason and generate an answer. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n", + "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276": " \n SDK: \n \n ```python + \n from nuclia import sdk \n from nucliadb_models.search import AskRequest, + Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( \n query= My + question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( + \n display=True, # Show reasoning in the response \n effort= low , # Can be + low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can + use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning + Options: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n", + "f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299": "@nuclia/core \u2022 Docs \n + \n @nuclia/core / PageToken \n Interface: PageToken \n Properties \n height + \n \n height: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 + \n \n line \n \n line: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 + \n \n text \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageToken\n", + "44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668": " \n step: Information + about the current processing step \n module: The module being executed (e.g., + rephrase , basic_ask , remi ) \n title: Display title for the step \n value: + Result of the step \n reason: Explanation for the step \n timeit: Time taken + in seconds \n \n input_nuclia_tokens/output_nuclia_tokens: Token usage \n \n + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/rao\n", + "4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340": " Use the max_tokens parameter + on the /ask endpoint to set hard limits on: \n - Context size: Limits the amount + of retrieved information sent to the LLM \n - Answer length: Limits the length + of the generated response \n Important Considerations \n Context Limitations: + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", + "4039d76b0fff4962900836ab3fdec9f7/t/page/3340-4136": " - Restricting context + size may result in less relevant answers since the LLM has less information + to work with \n - Balance between cost control and answer quality \n Answer + Length Limitations: \n - The LLM might not complete its response if it hits + the token limit, potentially cutting sentences mid-way \n - Recommended approach: + Include length requirements in your prompt (e.g., Please answer in less than + 200 words ) rather than relying solely on hard limits \n - This allows the LLM + to naturally conclude its response within the desired length \n How to Monitor + Token Consumption \n Understanding Token Consumption Data \n You can receive + detailed token consumption information from the following endpoints that utilize + LLM models: ask, chat, remi, query, sentence, summarize, tokens, and rerank. + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", + "4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326": " \n Large context: Results + from using RAG strategies like Full resource or Neighbouring paragraphs , or + from using the extra_context parameter \n Long questions: More detailed or complex + questions require more input tokens \n Long prompts: Extensive system prompts + increase the input token count \n Detailed answers: Comprehensive responses + require more output tokens \n Images in context: When using multimodal models, + images included in the retrieved context significantly increase token consumption + \n \n How to Limit and Control Token Consumption \n Strategy 1: Optimize Your + Parameters \n The first approach to reducing token consumption is to fine-tune + your request parameters: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", + "4039d76b0fff4962900836ab3fdec9f7/t/page/5396-5615": " - input: Tokens used + for the prompt, context, and question \n - output: Tokens used for the generated + response \n - image: Tokens used for image processing (when applicable) \n Customer + Key Tokens (customer_key_tokens): \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", + "89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575": " \n \n Maximum supported + input tokens: \n Description: The maximum number of tokens that the model can + accept as input. Be mindful that this takes into account the tokens used in + the prompt, query and context. Also take note that some models may provide their + context window as the total between input and output tokens, while others may + provide it as the input tokens only. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", + "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043": " Description: The maximum + number of tokens that the model can generate as output. Again, we should keep + in mind that this value summed to the Maximum supported input tokens should + not exceed the total context size supported by the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", + "b6a6202b9f0d4611a980293ce53337d6/t/page/265-405": " last: boolean \n \n page + \n \n page: number \n \n size \n \n size: number \n \n Defined in \n libs/sdk-core/src/lib/db/training/training.models.ts:36\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/TrainingExecutions\n", + "42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696": " \n optional max_paragraph: + number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 \n \n + name? \n \n optional name: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/SplitStrategy\n"}}' headers: Accept: - '*/*' @@ -2467,1796 +846,351 @@ interactions: Connection: - 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\u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../../../globals.md) / [Ask](../README.md) - / ConsumptionAskResponseItem\\n\\n# Interface: ConsumptionAskResponseItem\\n\\n## - Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> **customer\\\\_key\\\\_tokens**: - [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L127)\\n\\n***\\n\\n### - normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L126)\\n\\n***\\n\\n### - type\\n\\n> **type**: `\\\"consumption\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:125](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L125)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"3d72cf5a8634c4719acbe4304e79b48d\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: - ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n - customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 - \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n - type \\n \\n type: consumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:125\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":397,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":397,\"key\":\"\"}]},{\"start\":397,\"end\":483,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":398,\"end\":483,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:48:23.234967Z\",\"last_understanding\":\"2026-07-14T12:48:22.068785Z\",\"last_extract\":\"2026-07-14T12:48:21.777104Z\",\"last_processing_start\":\"2026-07-14T12:48:21.755089Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\":{\"score\":0.599697470664978,\"score_type\":\"VECTOR\",\"order\":11,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: - ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n - customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 - \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n - type \\n \\n\",\"id\":\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":397,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"9f7036a7a6694700b72d52eb58a8326c\":{\"id\":\"9f7036a7a6694700b72d52eb58a8326c\",\"slug\":\"docs-rag-advanced-widget-features-md\",\"title\":\"docs - > rag > advanced > widget > features\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T14:32:26.204740\",\"modified\":\"2026-06-09T08:07:51.648767\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - features\\ntitle: Features\\n---\\n\\n# Widgets features\\n\\nThe Agentic - RAG widgets allows you to embed the Agentic RAG search experience directly - into your website or web application through a simple HTML snippet:\\n\\n```html\\n\\n\\n\\n```\\n\\nThe - easiest way to explore the different features of the widgets is to use the - [Agentic RAG Dashboard](https://rag.progress.cloud/) in the Widgets section - and to play with the different options.\\n\\nThe _Embed widget_ button will - generate the HTML snippet for you.\\n\\n## Widget types\\n\\nThere are 3 different - types of widgets:\\n\\n- **Embedded in page**: the search input is embedded - in a page and the results are displayed under the input. Once the initial - answer is displayed, the user can click on _Ask more_ to access the full chat - interface. Note: For the correct reading of the results, the width of the - widget container should not be less than 384px.\\n\\n Web components:\\n\\n - \ ```html\\n \\n \\n - \ ```\\n\\n- **Chat mode**: displays directly the full chat interface.\\n\\n - \ Web component:\\n\\n ```html\\n \\n ```\\n\\n- - **Popup modal**: the search inout and the results are displayed in a popup - modal.\\n\\n Web component:\\n\\n ```html\\n \\n - \ ```\\n\\n## The `features` parameter\\n\\nThe `features` parameter allows - you to customize the behavior of the widget. It is a comma-separated list - of features among the following:\\n\\n- `filter`: display a filter dropdown - in the search bar.\\n- `navigateToFile`: open the file in the browser when - clicking on the result (by default, the file is displayed in the viewer).\\n- - `navigateToLink`: open the link in the browser when clicking on the result - (by default, the link is displayed in the viewer).\\n- `permalink`: add the - search query and criteria to the URL, allowing the widget to re-render the - same results upon loading.\\n- `relations`: display an info card on the right - side of the widget listing all the relations of the entity mentioned in the - user query.\\n- `suggestions`: display a list of suggested resource titles - matching the user input.\\n- `suggestLabels`: display a list of suggestions - based on the labels when the user starts typing in the search bar.\\n- `autocompleteFromNERs`: - display a list of suggestions based on the NERs extracted from the user query - when the user starts typing in the search bar.\\n- `displayMetadata`: display - the metadata associated with the resource in the result rows.\\n- `answers`: - trigger the answer generation process when the user makes a search.\\n- `hideResults`: - hide the search results, only the generative answer will be displayed.\\n- - `hideThumbnails`: hide the thumbnails associated with the resource in the - result rows.\\n- `displayFieldList`: display a section listing all the fields - of the resource in the right sidebar of the viewer. This section is only visible - for resources containing multiple fields.\\n- `citations`: include citations - in the generative answer.\\n- `rephrase`: rephrase the user question in order - to optimize the quality of the search results.\\n- `debug`: display extra - buttons to download the last request full log of the debug metadata returned - by the API. It must not be used in production.\\n- `preferMarkdown`: require - the generative answer to be formatted in Markdown.\\n- `openNewTab`: open - the link in a new tab when clicking on the result.\\n- `orFilterLogic`: use - the OR logic for filters instead of the default AND logic.\\n- `noChatHistory`: - the previous questions and answers in the chat mode will not be passed as - context when generating a new answer.\\n- `showHidden`: display hidden resources - in the search results.\\n- `showAttachedImages`: display images attached to - the matching paragraphs in the search results.\\n\\n### Other parameters\\n\\n- - `backend`: the URL of the backend to use. Useful if you use your own proxy - to access the Agentic RAG API.\\n- `zone`: the zone to use.\\n- `knowledgebox`: - the Knowledge Box id.\\n- `placeholder`: the text displayed in the search - bar when it is empty.\\n- `lang`: the language of the widget. Currently supported: - `ca`, `fr`, `en`, `es`. Default: `en`.\\n- `apikey`: the API key to use. It - is not recommended to use it in production (the API key is meant to be injected - by your proxy).\\n- `account`: the account id.\\n- `state`: the publication - state of the Knowledge Box.\\n- `standalone`: set to `true` when using a standalone - NucliaDB instance.\\n- `proxy`: set to `true` when using a proxy to access - the Agentic RAG API.\\n- `mode`: set to `dark` to display the widget in dark - mode.\\n- `filters`: define the filters offered to the user in the search - bar among `labels`, `entities`, `created` and `labelFamilies`.\\n- `preselected_filters`: - define filters that will be applied by default to any query.\\n- `csspath`: - the path to the CSS file to use to customize the widget style.\\n- `prompt`: - the prompt to use for the generative model. It must use `{context}` and `{question}` - variables.\\n- `system_prompt`: the system prompt to use for the generative - model.\\n- `rephrase_prompt`: the prompt to use when optimizing the user query - to get the best search results.\\n- `generativemodel`: the generative model - to use for the answer generation.\\n- `rag_strategies`: the RAG strategies - to apply to the retrieved paragraphs.\\n- `rag_images_strategies`: the RAG - strategies to apply to the retrieved images.\\n- `not_enough_data_message`: - the message to display when there is not enough data to generate an answer.\\n- - `ask_to_resource`: the resource ID to use as context for the generative model.\\n- - `max_tokens`: the maximum number of input tokens to put in the final context - (including the prompt, the retrieved results and the user question).\\n- `max_output_tokens`: - the maximum number of tokens to generate.\\n- `max_paragraphs`: the maximum - number of paragraphs to pass in the context to the generative model (default: - 20).\\n- `query_prepend`: the hard-coded text to prepend to the user query.\\n- - `json_schema`: the JSON schema to use to get a JSON answer from the generative - model.\\n- `vectorset`: the embedding model to use for the semantic search.\\n- - `chat_placeholder`: the placeholder to display in the chat input.\\n- `audit_metadata`: - custom metatada to add in API calls for auditing purposes.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"8f3044c65d6a551153cea36353a2cdac\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: features \\n title: Features \\n \\n Widgets features \\n The Agentic - RAG widgets allows you to embed the Agentic RAG search experience directly - into your website or web application through a simple HTML snippet: \\n ```html - \\n \\n \\n \\n ``` \\n The easiest way to explore the different features - of the widgets is to use the Agentic RAG Dashboard in the Widgets section - and to play with the different options. \\n The Embed widget button will generate - the HTML snippet for you. \\n Widget types \\n There are 3 different types - of widgets: \\n \\n Embedded in page: the search input is embedded in a page - and the results are displayed under the input. Once the initial answer is - displayed, the user can click on Ask more to access the full chat interface. - Note: For the correct reading of the results, the width of the widget container - should not be less than 384px. \\n \\n Web components: \\n html \\n \\n \\n - \\n Chat mode: displays directly the full chat interface. \\n \\n Web component: - \\n html \\n \\n \\n Popup modal: the search inout and the results are displayed - in a popup modal. \\n \\n Web component: \\n html \\n \\n The features parameter - \\n The features parameter allows you to customize the behavior of the widget. - It is a comma-separated list of features among the following: \\n \\n filter: - display a filter dropdown in the search bar. \\n navigateToFile: open the - file in the browser when clicking on the result (by default, the file is displayed - in the viewer). \\n navigateToLink: open the link in the browser when clicking - on the result (by default, the link is displayed in the viewer). \\n permalink: - add the search query and criteria to the URL, allowing the widget to re-render - the same results upon loading. \\n relations: display an info card on the - right side of the widget listing all the relations of the entity mentioned - in the user query. \\n suggestions: display a list of suggested resource titles - matching the user input. \\n suggestLabels: display a list of suggestions - based on the labels when the user starts typing in the search bar. \\n autocompleteFromNERs: - display a list of suggestions based on the NERs extracted from the user query - when the user starts typing in the search bar. \\n displayMetadata: display - the metadata associated with the resource in the result rows. \\n answers: - trigger the answer generation process when the user makes a search. \\n hideResults: - hide the search results, only the generative answer will be displayed. \\n - hideThumbnails: hide the thumbnails associated with the resource in the result - rows. \\n displayFieldList: display a section listing all the fields of the - resource in the right sidebar of the viewer. This section is only visible - for resources containing multiple fields. \\n citations: include citations - in the generative answer. \\n rephrase: rephrase the user question in order - to optimize the quality of the search results. \\n debug: display extra buttons - to download the last request full log of the debug metadata returned by the - API. It must not be used in production. \\n preferMarkdown: require the generative - answer to be formatted in Markdown. \\n openNewTab: open the link in a new - tab when clicking on the result. \\n orFilterLogic: use the OR logic for filters - instead of the default AND logic. \\n noChatHistory: the previous questions - and answers in the chat mode will not be passed as context when generating - a new answer. \\n showHidden: display hidden resources in the search results. - \\n showAttachedImages: display images attached to the matching paragraphs - in the search results. \\n \\n Other parameters \\n \\n backend: the URL of - the backend to use. Useful if you use your own proxy to access the Agentic - RAG API. \\n zone: the zone to use. \\n knowledgebox: the Knowledge Box id. - \\n placeholder: the text displayed in the search bar when it is empty. \\n - lang: the language of the widget. Currently supported: ca, fr, en, es. Default: - en. \\n apikey: the API key to use. It is not recommended to use it in production - (the API key is meant to be injected by your proxy). \\n account: the account - id. \\n state: the publication state of the Knowledge Box. \\n standalone: - set to true when using a standalone NucliaDB instance. \\n proxy: set to true - when using a proxy to access the Agentic RAG API. \\n mode: set to dark to - display the widget in dark mode. \\n filters: define the filters offered to - the user in the search bar among labels, entities, created and labelFamilies. - \\n preselected_filters: define filters that will be applied by default to - any query. \\n csspath: the path to the CSS file to use to customize the widget - style. \\n prompt: the prompt to use for the generative model. It must use - {context} and {question} variables. \\n system_prompt: the system prompt to - use for the generative model. \\n rephrase_prompt: the prompt to use when - optimizing the user query to get the best search results. \\n generativemodel: - the generative model to use for the answer generation. \\n rag_strategies: - the RAG strategies to apply to the retrieved paragraphs. \\n rag_images_strategies: - the RAG strategies to apply to the retrieved images. \\n not_enough_data_message: - the message to display when there is not enough data to generate an answer. - \\n ask_to_resource: the resource ID to use as context for the generative - model. \\n max_tokens: the maximum number of input tokens to put in the final - context (including the prompt, the retrieved results and the user question). - \\n max_output_tokens: the maximum number of tokens to generate. \\n max_paragraphs: - the maximum number of paragraphs to pass in the context to the generative - model (default: 20). \\n query_prepend: the hard-coded text to prepend to - the user query. \\n json_schema: the JSON schema to use to get a JSON answer - from the generative model. \\n vectorset: the embedding model to use for the - semantic search. \\n chat_placeholder: the placeholder to display in the chat - input. \\n audit_metadata: custom metatada to add in API calls for auditing - purposes. \\n 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`number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L249)\\n\\n***\\n\\n### - line\\n\\n> **line**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L251)\\n\\n***\\n\\n### - text\\n\\n> **text**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L250)\\n\\n***\\n\\n### - width\\n\\n> **width**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L248)\\n\\n***\\n\\n### - x\\n\\n> **x**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L246)\\n\\n***\\n\\n### - y\\n\\n> **y**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"e72ffebe78398e6654aceec2addfd240\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n - Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 - \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 - \\n \\n text \\n \\n text: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:250 - \\n \\n width \\n \\n width: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:248 - \\n \\n x \\n \\n x: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:246 - \\n \\n y \\n \\n y: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:247\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":299,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":299,\"key\":\"\"}]},{\"start\":299,\"end\":592,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":300,\"end\":592,\"key\":\"\"}]},{\"start\":592,\"end\":677,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":593,\"end\":677,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:07.412857Z\",\"last_understanding\":\"2026-07-14T12:51:07.180359Z\",\"last_extract\":\"2026-07-14T12:51:06.857039Z\",\"last_processing_start\":\"2026-07-14T12:51:06.837097Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > PageToken\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > PageToken\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\":{\"score\":0.5957225561141968,\"score_type\":\"VECTOR\",\"order\":14,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n - Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 - \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 - \\n \\n text \\n \\n\",\"id\":\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":299,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"1b2a9e67b9f14a0cb81efaa05b8793b8\":{\"id\":\"1b2a9e67b9f14a0cb81efaa05b8793b8\",\"slug\":\"docs-develop-js-sdk-interfaces-AugmentedField-md\",\"title\":\"docs - > develop > js sdk > interfaces > AugmentedField\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:00:05.937520\",\"modified\":\"2026-07-14T12:49:32.163110\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/AugmentedField\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / AugmentedField\\n\\n# - Interface: AugmentedField\\n\\n## Properties\\n\\n### applied\\\\_data\\\\_augmentation\\n\\n> - **applied\\\\_data\\\\_augmentation**: [`AppliedDataAugmentation`](AppliedDataAugmentation.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:571](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L571)\\n\\n***\\n\\n### - input\\\\_nuclia\\\\_tokens\\n\\n> **input\\\\_nuclia\\\\_tokens**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:572](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L572)\\n\\n***\\n\\n### - metadata\\n\\n> **metadata**: [`FieldMetadata`](FieldMetadata.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:570](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L570)\\n\\n***\\n\\n### - output\\\\_nuclia\\\\_tokens\\n\\n> **output\\\\_nuclia\\\\_tokens**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:573](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L573)\\n\\n***\\n\\n### - time\\n\\n> **time**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:574](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L574)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"1e8e95b886439059ae4ec717c9bcf283\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / AugmentedField \\n Interface: AugmentedField - \\n Properties \\n applied_data_augmentation \\n \\n applied_data_augmentation: - AppliedDataAugmentation \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:571 - \\n \\n input_nuclia_tokens \\n \\n input_nuclia_tokens: number \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:572 \\n \\n metadata - \\n \\n metadata: FieldMetadata \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:570 - \\n \\n output_nuclia_tokens \\n \\n output_nuclia_tokens: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:573 \\n - \\n time \\n \\n time: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:574\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":641,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":641,\"key\":\"\"}]},{\"start\":641,\"end\":729,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":642,\"end\":729,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:49:33.585675Z\",\"last_understanding\":\"2026-07-14T12:49:33.340252Z\",\"last_extract\":\"2026-07-14T12:49:32.941746Z\",\"last_processing_start\":\"2026-07-14T12:49:32.917812Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > AugmentedField\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > AugmentedField\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"1b2a9e67b9f14a0cb81efaa05b8793b8/t/page/0-641\":{\"score\":0.5881041884422302,\"score_type\":\"VECTOR\",\"order\":19,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / AugmentedField \\n Interface: AugmentedField - \\n Properties \\n applied_data_augmentation \\n \\n applied_data_augmentation: - AppliedDataAugmentation \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:571 - \\n \\n input_nuclia_tokens \\n \\n input_nuclia_tokens: number \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:572 \\n \\n metadata - \\n \\n metadata: FieldMetadata \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:570 - \\n \\n output_nuclia_tokens \\n \\n output_nuclia_tokens: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:573 \\n - \\n time \\n \\n\",\"id\":\"1b2a9e67b9f14a0cb81efaa05b8793b8/t/page/0-641\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":641,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"44d05174f1954331b62f5e4026f2b01a\":{\"id\":\"44d05174f1954331b62f5e4026f2b01a\",\"slug\":\"docs-develop-python-sdk-14-rao-md\",\"title\":\"docs - > develop > python sdk > 14 rao\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-22T13:38:09.919472\",\"modified\":\"2026-06-09T08:08:04.176136\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/python-sdk/rao\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"# - Retrieval Agents Orchestrator\\n\\nInteract with Nuclia's Retrieval Agents - Orchestrator to have intelligent conversations over several knowledge sources - with persistent session management and real-time streaming responses.\\n\\n## - Prerequisites\\n\\nInstall the Nuclia SDK:\\n\\n```sh\\npip install nuclia\\n```\\n\\nEnsure - you have:\\n- A valid Nuclia authentication token (see [Authentication](02-auth.md))\\n- - Access to a configured Retrieval Agent\\n\\n## Overview\\n\\nThe nuclia.py - library provides several ways to interact with your Retrieval Agents Orchestrators:\\n\\n- - **Interactive CLI**: A rich, user-friendly terminal interface (recommended)\\n- - **Standard CLI**: Direct access to raw websocket messages for debugging\\n- - **Session Management**: Create and manage persistent conversation sessions\\n- - **Programmatic API**: Python SDK for building custom applications\\n\\n\\n## - Listing Available Agents\\n\\nDiscover what Retrieval Agents Orchestrators - you have access to.\\n\\n- CLI:\\n\\n ```sh\\n nuclia agents list\\n ```\\n\\n- - SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n - \ agents = NucliaAgents()\\n all_agents = agents.list()\\n\\n for agent - in all_agents:\\n print(f\\\"Agent: {agent.title} ({agent.id})\\\")\\n - \ print(f\\\" Slug: {agent.slug}\\\")\\n print(f\\\" Zone: {agent.zone}\\\")\\n - \ ```\\n\\n### Getting a Specific Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia - agents get --account=\\\"my-account\\\" --id=\\\"agent-uuid\\\" --zone=\\\"europe-1\\\"\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n - \ agents = NucliaAgents()\\n agent_details = agents.get(\\n account=\\\"my-account\\\",\\n - \ id=\\\"agent-uuid\\\",\\n zone=\\\"europe-1\\\"\\n )\\n print(agent_details)\\n - \ ```\\n\\n### Setting a Default Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia - agents default [AGENT_SLUG or AGENT_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n - \ from nuclia.sdk.agents import NucliaAgents\\n\\n agents = NucliaAgents()\\n - \ agents.default(\\\"my-agent\\\")\\n ```\\n\\nThis sets the default agent - for all subsequent operations.\\n\\n## Interactive CLI (Recommended)\\n\\nThe - interactive CLI provides a beautiful, real-time interface for conversing with - your Retrieval Agents Orchestrator.\\n\\n### Starting the Interactive CLI\\n\\n- - CLI:\\n\\n ```sh\\n nuclia agent cli interact\\n ```\\n\\n- SDK:\\n\\n - \ ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n - \ agent.cli.interact()\\n ```\\n\\nThis launches an interactive terminal - session where you can:\\n- Ask questions and see streaming responses\\n- View - processing steps in real-time\\n- Manage conversation sessions\\n- See retrieved - context and citations\\n\\n### Interactive CLI Commands\\n\\nThe CLI supports - several commands (prefix with `/`):\\n\\n| Command | Description |\\n|---------|-------------|\\n| - `/help` | Show available commands |\\n| `/new_session` | Create a new persistent - session |\\n| `/list_sessions` | List all your sessions |\\n| `/change_session` - | Switch to a different session, use 'ephemeral' for a temporary session |\\n| - `/clear` | Clear the screen |\\n| `/exit` | Exit the CLI |\\n\\nPlease note - that all commands related to sessions require a Retrieval Agent Orchestrator - with the option **Agent with memory** enabled during creation.\\n\\n## Session - Management\\n\\nSessions allow you to maintain conversation context across - multiple interactions.\\n\\n> This feature will only be available if you checked - **Agent with memory** during the creation of your Retrieval Agents Orchestrator.\\n\\n### - Creating a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent session new --name=\\\"My - Research Session\\\"\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent - import NucliaAgent\\n\\n agent = NucliaAgent()\\n session_uuid = agent.session.new(\\\"My - Research Session\\\")\\n print(f\\\"Created session: {session_uuid}\\\")\\n - \ ```\\n\\n### Listing Sessions\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent - session list\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent - import NucliaAgent\\n\\n agent = NucliaAgent()\\n sessions = agent.session.list()\\n - \ for session in sessions.resources:\\n print(f\\\"{session.title}: {session.id}\\\")\\n - \ ```\\n\\n### Getting a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent - session get --session_uuid=[SESSION_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n - \ from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n - \ session = agent.session.get(session_uuid)\\n print(f\\\"Session: {session.title}\\\")\\n - \ print(f\\\"Created: {session.created}\\\")\\n ```\\n\\n### Deleting a Session\\n\\n- - CLI:\\n\\n ```sh\\n nuclia agent session delete --session_uuid=[SESSION_UUID]\\n - \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n - \ agent = NucliaAgent()\\n agent.session.delete(session_uuid)\\n ```\\n\\n## - Interaction\\n\\nAside from the interactive CLI, you can interact with your - Retrieval Agents Orchestrator with the simple CLI or programmatically using - the SDK.\\n\\n### Basic Interaction\\n\\n\\n**CLI:**\\n```bash\\nnuclia agent - interact \\\"What is Eric known for?\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate - over streaming responses\\nfor response in agent.interact(\\n question=\\\"What - is Eric known for?\\\"\\n):\\n if response.operation == \\\"ANSWER\\\" - and response.answer:\\n print(response.answer)\\n elif response.step:\\n - \ print(f\\\"Processing: {response.step.module}\\\")\\n```\\n\\nNot - supplying a `session_uuid` when calling `interact` will use an ephemeral session - by default. To maintain context, provide a persistent session UUID.\\n\\n### - Using Persistent Sessions\\n\\n**CLI:**\\n```bash\\nnuclia agent sessions - new \\\"Customer Support Chat\\\"\\n# Note the session UUID returned\\nnuclia - agent interact \\\"What are your business hours?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\nnuclia - agent interact \\\"Are you open on weekends?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Create - a session\\nsession_uuid = agent.session.new(\\\"Customer Support Chat\\\")\\n\\n# - Have a conversation with context\\nfor response in agent.interact(\\n session_uuid=session_uuid,\\n - \ question=\\\"What are your business hours?\\\"\\n):\\n if response.answer:\\n - \ print(response.answer)\\n\\n# Follow-up question maintains context\\nfor - response in agent.interact(\\n session_uuid=session_uuid,\\n question=\\\"Are - you open on weekends?\\\"\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\n## - Understanding Response Types\\n\\nWhen interacting with an agent, you receive - a stream of `AragAnswer` objects with different operations:\\n\\n| Operation - | Description |\\n|-----------|-------------|\\n| `START` | Interaction has - begun |\\n| `ANSWER` | Processing step or partial answer |\\n| `DONE` | Interaction - complete |\\n| `ERROR` | An error occurred |\\n| `AGENT_REQUEST` | Agent needs - user feedback |\\n\\n### Response Attributes\\n\\nEach response may contain:\\n\\n- - **`step`**: Information about the current processing step\\n - `module`: - The module being executed (e.g., \\\"rephrase\\\", \\\"basic_ask\\\", \\\"remi\\\")\\n - \ - `title`: Display title for the step\\n - `value`: Result of the step\\n - \ - `reason`: Explanation for the step\\n - `timeit`: Time taken in seconds\\n - \ - `input_nuclia_tokens`/`output_nuclia_tokens`: Token usage\\n\\n- **`context`**: - Retrieved context from the knowledge base\\n - `chunks`: List of retrieved - text chunks with sources\\n - `summary`: Summary of the context or partial - answer\\n\\n- **`answer`**: The final answer text (Markdown formatted)\\n\\n- - **`generated_text`**: Intermediate generated text\\n\\n- **`possible_answer`**: - Alternative answer being considered\\n\\n- **`exception`**: Error details - if something went wrong\\n\\n### Processing Responses\\n\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\nfrom nuclia_models.agent.interaction - import AnswerOperation\\n\\nagent = NucliaAgent()\\n\\nfor response in agent.interact(question=\\\"Tell - me about AI\\\"):\\n if response.operation == AnswerOperation.START:\\n - \ print(\\\"Starting...\\\")\\n \\n elif response.step:\\n print(f\\\"Step: - {response.step.module} ({response.step.timeit:.2f}s)\\\")\\n \\n elif - response.context:\\n print(f\\\"Retrieved {len(response.context.chunks)} - chunks\\\")\\n for chunk in response.context.chunks:\\n print(f\\\" - \ - {chunk.title}: {chunk.text[:100]}...\\\")\\n \\n elif response.answer:\\n - \ print(f\\\"\\\\nFinal Answer:\\\\n{response.answer}\\\")\\n \\n - \ elif response.operation == AnswerOperation.DONE:\\n print(\\\"Complete!\\\")\\n - \ \\n elif response.operation == AnswerOperation.ERROR:\\n print(f\\\"Error: - {response.exception.detail if response.exception else 'Unknown'}\\\")\\n```\\n\\n## - Standard CLI for Raw Messages\\n\\nFor debugging or advanced use cases, you - can access raw websocket messages programmatically:\\n\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate - over all messages\\nfor message in agent.interact(\\n question=\\\"What - is RAO?\\\"\\n):\\n # message is an AragAnswer object with all raw data\\n - \ print(f\\\"Operation: {message.operation}\\\")\\n print(f\\\"Raw message: - {message.model_dump_json(indent=2)}\\\")\\n```\\n\\nThis gives you direct - access to all websocket message data for debugging or custom processing.\\n\\n## - Advanced Features\\n\\n### Agent Feedback Requests\\n\\nAgents can request - additional input from users during processing:\\n\\n```python\\nfrom nuclia.sdk.agent - import NucliaAgent\\nfrom nuclia_models.agent.interaction import AnswerOperation\\n\\nagent - = NucliaAgent()\\ngenerator = agent.interact(question=\\\"Help me with X\\\")\\n\\nfor - response in generator:\\n if response.operation == AnswerOperation.AGENT_REQUEST:\\n - \ # Agent is requesting user input\\n user_input = input(f\\\"Agent - asks: {response.feedback.question}\\\\n> \\\")\\n # Send response back\\n - \ generator.send(user_input)\\n elif response.answer:\\n print(response.answer)\\n```\\n\\n### - Error Handling\\n\\n```python\\nfrom nuclia.sdk.agent import NucliaAgent\\nfrom - nuclia.exceptions import RaoAPIException\\n\\nagent = NucliaAgent()\\n\\ntry:\\n - \ for response in agent.interact(question=\\\"Hello?\\\"):\\n if - response.exception:\\n print(f\\\"Agent error: {response.exception.detail}\\\")\\n - \ elif response.answer:\\n print(response.answer)\\nexcept - RaoAPIException as e:\\n print(f\\\"API error: {e.detail}\\\")\\nexcept - Exception as e:\\n print(f\\\"Unexpected error: {e}\\\")\\n```\\n\\n### - Passing Custom Headers to MCP\\n\\nIf your Retrieval Agents Orchestrator requires - custom headers for MCP Agents, you can pass them as follows:\\n\\n**CLI:**\\n```bash\\nnuclia - agent interact \\\"What is AI?\\\" --headers '{\\\"X-Custom-Header\\\": \\\"value\\\"}'\\n```\\n\\n**SDK:**\\n```python\\nfrom - nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\nfor response - in agent.interact(\\n question=\\\"What is AI?\\\",\\n headers={\\\"X-Custom-Header\\\": - \\\"value\\\"}\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\nPlease - ensure that the 'Allowed Headers' configuration in your MCP agent includes - any custom headers you wish to use.\\n\\n## Best Practices\\n\\n1. **Use Sessions - for Context**: Create sessions when you need multi-turn conversations with - context retention\\n2. **Use Ephemeral Sessions for One-offs**: Don't supply - a session UUID for using agents in a stateless manner.\\n3. **Stream for UX**: - Process responses as they arrive for better user experience\\n4. **Handle - All Operations**: Check for different operation types (START, ANSWER, DONE, - ERROR) when processing responses\\n5. **Clean Up Sessions**: Delete sessions - when done to avoid clutter\\n6. **Use Interactive CLI**: For manual testing - and exploration, the interactive CLI provides the best experience\\n\",\"format\":\"MARKDOWN\",\"md5\":\"bbaaf8cccd2b664ba4f7daf47d1f2bf4\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"Retrieval - Agents Orchestrator \\n Interact with Nuclia's Retrieval Agents Orchestrator - to have intelligent conversations over several knowledge sources with persistent - session management and real-time streaming responses. \\n Prerequisites \\n - Install the Nuclia SDK: \\n sh \\n pip install nuclia \\n Ensure you have: - \\n - A valid Nuclia authentication token (see Authentication) \\n - Access - to a configured Retrieval Agent \\n Overview \\n The nuclia.py library provides - several ways to interact with your Retrieval Agents Orchestrators: \\n \\n - Interactive CLI: A rich, user-friendly terminal interface (recommended) \\n - Standard CLI: Direct access to raw websocket messages for debugging \\n Session - Management: Create and manage persistent conversation sessions \\n Programmatic - API: Python SDK for building custom applications \\n \\n Listing Available - Agents \\n Discover what Retrieval Agents Orchestrators you have access to. - \\n \\n CLI: \\n \\n sh \\n nuclia agents list \\n \\n SDK: \\n \\n ```python - \\n from nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() - \\n all_agents = agents.list() \\n for agent in all_agents: \\n print(f Agent: - {agent.title} ({agent.id}) ) \\n print(f Slug: {agent.slug} ) \\n print(f - Zone: {agent.zone} ) \\n ``` \\n Getting a Specific Agent \\n \\n CLI: \\n - \\n sh \\n nuclia agents get --account= my-account --id= agent-uuid --zone= - europe-1 \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agents import - NucliaAgents \\n agents = NucliaAgents() \\n agent_details = agents.get( \\n - account= my-account , \\n id= agent-uuid , \\n zone= europe-1 \\n ) \\n print(agent_details) - \\n ``` \\n Setting a Default Agent \\n \\n CLI: \\n \\n sh \\n nuclia agents - default [AGENT_SLUG or AGENT_UUID] \\n \\n SDK: \\n \\n ```python \\n from - nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() \\n agents.default( - my-agent ) \\n ``` \\n This sets the default agent for all subsequent operations. - \\n Interactive CLI (Recommended) \\n The interactive CLI provides a beautiful, - real-time interface for conversing with your Retrieval Agents Orchestrator. - \\n Starting the Interactive CLI \\n \\n CLI: \\n \\n sh \\n nuclia agent - cli interact \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import - NucliaAgent \\n agent = NucliaAgent() \\n agent.cli.interact() \\n ``` \\n - This launches an interactive terminal session where you can: \\n - Ask questions - and see streaming responses \\n - View processing steps in real-time \\n - - Manage conversation sessions \\n - See retrieved context and citations \\n - Interactive CLI Commands \\n The CLI supports several commands (prefix with - /): \\n | Command | Description | \\n |---------|-------------| \\n | /help - | Show available commands | \\n | /new_session | Create a new persistent session - | \\n | /list_sessions | List all your sessions | \\n | /change_session | - Switch to a different session, use 'ephemeral' for a temporary session | \\n - | /clear | Clear the screen | \\n | /exit | Exit the CLI | \\n Please note - that all commands related to sessions require a Retrieval Agent Orchestrator - with the option Agent with memory enabled during creation. \\n Session Management - \\n Sessions allow you to maintain conversation context across multiple interactions. - \\n \\n This feature will only be available if you checked Agent with memory - during the creation of your Retrieval Agents Orchestrator. \\n \\n Creating - a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session new --name= My - Research Session \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent - import NucliaAgent \\n agent = NucliaAgent() \\n session_uuid = agent.session.new( - My Research Session ) \\n print(f Created session: {session_uuid} ) \\n ``` - \\n Listing Sessions \\n \\n CLI: \\n \\n sh \\n nuclia agent session list - \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import NucliaAgent - \\n agent = NucliaAgent() \\n sessions = agent.session.list() \\n for session - in sessions.resources: \\n print(f {session.title}: {session.id} ) \\n ``` - \\n Getting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session get - --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent - import NucliaAgent \\n agent = NucliaAgent() \\n session = agent.session.get(session_uuid) - \\n print(f Session: {session.title} ) \\n print(f Created: {session.created} - ) \\n ``` \\n Deleting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent - session delete --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python - \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n - agent.session.delete(session_uuid) \\n ``` \\n Interaction \\n Aside from - the interactive CLI, you can interact with your Retrieval Agents Orchestrator - with the simple CLI or programmatically using the SDK. \\n Basic Interaction - \\n CLI: \\n bash \\n nuclia agent interact What is Eric known for? \\n SDK: - \\n ```python \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() - \\n Iterate over streaming responses \\n for response in agent.interact( \\n - question= What is Eric known for? \\n ): \\n if response.operation == ANSWER - and response.answer: \\n print(response.answer) \\n elif response.step: \\n - print(f Processing: {response.step.module} ) \\n ``` \\n Not supplying a session_uuid - when calling interact will use an ephemeral session by default. To maintain - context, provide a persistent session UUID. \\n Using Persistent Sessions - \\n CLI: \\n ```bash \\n nuclia agent sessions new Customer Support Chat \\n - Note the session UUID returned \\n nuclia agent interact What are your business - hours? --session_uuid= SESSION_UUID \\n nuclia agent interact Are you open - on weekends? --session_uuid= SESSION_UUID \\n ``` \\n SDK: \\n ```python \\n - from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n Create - a session \\n session_uuid = agent.session.new( Customer Support Chat ) \\n - Have a conversation with context \\n for response in agent.interact( \\n session_uuid=session_uuid, - \\n question= What are your business hours? \\n ): \\n if response.answer: - \\n print(response.answer) \\n Follow-up question maintains context \\n for - response in agent.interact( \\n session_uuid=session_uuid, \\n question= Are - you open on weekends? \\n ): \\n if response.answer: \\n print(response.answer) - \\n ``` \\n Understanding Response Types \\n When interacting with an agent, - you receive a stream of AragAnswer objects with different operations: \\n - | Operation | Description | \\n |-----------|-------------| \\n | START | - Interaction has begun | \\n | ANSWER | Processing step or partial answer | - \\n | DONE | Interaction complete | \\n | ERROR | An error occurred | \\n - | AGENT_REQUEST | Agent needs user feedback | \\n Response Attributes \\n - Each response may contain: \\n \\n step: Information about the current processing - step \\n module: The module being executed (e.g., rephrase , basic_ask , remi - ) \\n title: Display title for the step \\n value: Result of the step \\n - reason: Explanation for the step \\n timeit: Time taken in seconds \\n \\n - input_nuclia_tokens/output_nuclia_tokens: Token usage \\n \\n \\n context: - Retrieved context from the knowledge base \\n \\n chunks: List of retrieved - text chunks with sources \\n \\n summary: Summary of the context or partial - answer \\n \\n \\n answer: The final answer text (Markdown formatted) \\n - \\n \\n generated_text: Intermediate generated text \\n \\n \\n possible_answer: - Alternative answer being considered \\n \\n \\n exception: Error details if - something went wrong \\n \\n \\n Processing Responses \\n ```python \\n from - nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction - import AnswerOperation \\n agent = NucliaAgent() \\n for response in agent.interact(question= - Tell me about AI ): \\n if response.operation == AnswerOperation.START: \\n - print( Starting... ) \\n elif response.step: \\n print(f Step: {response.step.module} - ({response.step.timeit:.2f}s) ) \\n \\n elif response.context: \\n print(f - Retrieved {len(response.context.chunks)} chunks ) \\n for chunk in response.context.chunks: - \\n print(f - {chunk.title}: {chunk.text[:100]}... ) \\n \\n elif response.answer: - \\n print(f \\\\nFinal Answer:\\\\n{response.answer} ) \\n \\n elif response.operation - == AnswerOperation.DONE: \\n print( Complete! ) \\n \\n elif response.operation - == AnswerOperation.ERROR: \\n print(f Error: {response.exception.detail if - response.exception else 'Unknown'} ) \\n \\n ``` \\n Standard CLI for Raw - Messages \\n For debugging or advanced use cases, you can access raw websocket - messages programmatically: \\n ```python \\n from nuclia.sdk.agent import - NucliaAgent \\n agent = NucliaAgent() \\n Iterate over all messages \\n for - message in agent.interact( \\n question= What is RAO? \\n ): \\n # message - is an AragAnswer object with all raw data \\n print(f Operation: {message.operation} - ) \\n print(f Raw message: {message.model_dump_json(indent=2)} ) \\n ``` \\n - This gives you direct access to all websocket message data for debugging or - custom processing. \\n Advanced Features \\n Agent Feedback Requests \\n Agents - can request additional input from users during processing: \\n ```python \\n - from nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction - import AnswerOperation \\n agent = NucliaAgent() \\n generator = agent.interact(question= - Help me with X ) \\n for response in generator: \\n if response.operation - == AnswerOperation.AGENT_REQUEST: \\n # Agent is requesting user input \\n - user_input = input(f Agent asks: {response.feedback.question}\\\\n> ) \\n - # Send response back \\n generator.send(user_input) \\n elif response.answer: - \\n print(response.answer) \\n ``` \\n Error Handling \\n ```python \\n from - nuclia.sdk.agent import NucliaAgent \\n from nuclia.exceptions import RaoAPIException - \\n agent = NucliaAgent() \\n try: \\n for response in agent.interact(question= - Hello? ): \\n if response.exception: \\n print(f Agent error: {response.exception.detail} - ) \\n elif response.answer: \\n print(response.answer) \\n except RaoAPIException - as e: \\n print(f API error: {e.detail} ) \\n except Exception as e: \\n print(f - Unexpected error: {e} ) \\n ``` \\n Passing Custom Headers to MCP \\n If your - Retrieval Agents Orchestrator requires custom headers for MCP Agents, you - can pass them as follows: \\n CLI: \\n bash \\n nuclia agent interact What - is AI? --headers '{ X-Custom-Header : value }' \\n SDK: \\n ```python \\n - from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n for - response in agent.interact( \\n question= What is AI? , \\n headers={ X-Custom-Header - : value } \\n ): \\n if response.answer: \\n print(response.answer) \\n ``` - \\n Please ensure that the 'Allowed Headers' configuration in your MCP agent - includes any custom headers you wish to use. \\n Best Practices \\n \\n Use - Sessions for Context: Create sessions when you need multi-turn conversations - with context retention \\n Use Ephemeral Sessions for One-offs: Don't supply - a session UUID for using agents in a stateless manner. \\n Stream for UX: - Process responses as they arrive for better user experience \\n Handle All - Operations: Check for different operation types (START, ANSWER, DONE, ERROR) - when processing responses \\n Clean Up Sessions: Delete sessions when done - to avoid clutter \\n Use Interactive CLI: For manual testing and exploration, - the interactive CLI provides the best experience \\n 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[`UsageMetric`](UsageMetric.md)\\n\\n## - Properties\\n\\n### details\\n\\n> **details**: [`NucliaTokensDetails`](NucliaTokensDetails.md)[]\\n\\n#### - Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`details`](UsageMetric.md#details)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:185](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L185)\\n\\n***\\n\\n### - name\\n\\n> **name**: `\\\"nuclia_tokens\\\"`\\n\\n#### Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`name`](UsageMetric.md#name)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:183](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L183)\\n\\n***\\n\\n### - value\\n\\n> **value**: `number`\\n\\n#### Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`value`](UsageMetric.md#value)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:184](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L184)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"af7b6aa34935b09fa5ddc2badd6da04f\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / NucliaTokensMetric \\n Interface: NucliaTokensMetric - \\n Extends \\n \\n UsageMetric \\n \\n Properties \\n details \\n \\n details: - NucliaTokensDetails[] \\n \\n Overrides \\n UsageMetric.details \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n name \\n \\n name: - nuclia_tokens \\n \\n Overrides \\n UsageMetric.name \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:183 - \\n \\n value \\n \\n value: number \\n \\n Overrides \\n UsageMetric.value - \\n Defined in \\n 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\\n\",\"id\":\"8b3e0ef630a346d1b591143309db87ec/t/page/0-281\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":281,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0d01e250360a4d6c91f3baf2de5e7d38\":{\"id\":\"0d01e250360a4d6c91f3baf2de5e7d38\",\"slug\":\"docs-develop-js-sdk-interfaces-ReasoningConfig-md\",\"title\":\"docs - > develop > js sdk > interfaces > 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budget\\\\_tokens?\\n\\n> - `optional` **budget\\\\_tokens**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:647](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L647)\\n\\n***\\n\\n### - effort?\\n\\n> `optional` **effort**: [`NumericReasoningEffort`](../enumerations/NumericReasoningEffort.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:648](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L648)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"940c8be17c938dcc14e4abb000b0f8b5\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ReasoningConfig \\n Interface: ReasoningConfig - \\n Properties \\n budget_tokens? \\n \\n optional budget_tokens: number \\n - \\n Defined in \\n 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AI\\\\_TOKENS\\\\_USED\\n\\n> - **AI\\\\_TOKENS\\\\_USED**: `\\\"ai_tokens_used\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:206](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L206)\\n\\n***\\n\\n### - BYTES\\\\_PROCESSED\\n\\n> **BYTES\\\\_PROCESSED**: `\\\"bytes_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:197](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L197)\\n\\n***\\n\\n### - CHARS\\\\_PROCESSED\\n\\n> **CHARS\\\\_PROCESSED**: `\\\"chars_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:198](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L198)\\n\\n***\\n\\n### - MEDIA\\\\_FILES\\\\_PROCESSED\\n\\n> **MEDIA\\\\_FILES\\\\_PROCESSED**: `\\\"media_files_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:200](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L200)\\n\\n***\\n\\n### - MEDIA\\\\_SECONDS\\\\_PROCESSED\\n\\n> **MEDIA\\\\_SECONDS\\\\_PROCESSED**: - `\\\"media_seconds_processed\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:199](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L199)\\n\\n***\\n\\n### - NUCLIA\\\\_TOKENS\\n\\n> **NUCLIA\\\\_TOKENS**: `\\\"nuclia_tokens_billed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:207](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L207)\\n\\n***\\n\\n### - PAGES\\\\_PROCESSED\\n\\n> **PAGES\\\\_PROCESSED**: `\\\"pages_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:201](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L201)\\n\\n***\\n\\n### - PARAGRAPHS\\\\_PROCESSED\\n\\n> **PARAGRAPHS\\\\_PROCESSED**: `\\\"paragraphs_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:202](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L202)\\n\\n***\\n\\n### - PRE\\\\_PROCESSING\\\\_TIME\\n\\n> **PRE\\\\_PROCESSING\\\\_TIME**: `\\\"pre_processing_time\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:194](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L194)\\n\\n***\\n\\n### - RESOURCES\\\\_PROCESSED\\n\\n> **RESOURCES\\\\_PROCESSED**: `\\\"resources_processed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:196](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L196)\\n\\n***\\n\\n### - SEARCHES\\\\_PERFORMED\\n\\n> **SEARCHES\\\\_PERFORMED**: `\\\"searches_performed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:204](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L204)\\n\\n***\\n\\n### - SLOW\\\\_PROCESSING\\\\_TIME\\n\\n> **SLOW\\\\_PROCESSING\\\\_TIME**: `\\\"slow_processing_time\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:195](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L195)\\n\\n***\\n\\n### - SUGGESTIONS\\\\_PERFORMED\\n\\n> **SUGGESTIONS\\\\_PERFORMED**: `\\\"suggestions_performed\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:205](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L205)\\n\\n***\\n\\n### - TRAIN\\\\_SECONDS\\n\\n> **TRAIN\\\\_SECONDS**: `\\\"train_seconds\\\"`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:203](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L203)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"a6825b7bf9d5960444b0981f205811a3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / UsageType \\n Enumeration: UsageType \\n - Enumeration Members \\n AI_TOKENS_USED \\n \\n AI_TOKENS_USED: ai_tokens_used - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:206 \\n \\n BYTES_PROCESSED - \\n \\n BYTES_PROCESSED: bytes_processed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:197 - \\n \\n CHARS_PROCESSED \\n \\n CHARS_PROCESSED: chars_processed \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:198 \\n \\n MEDIA_FILES_PROCESSED - \\n \\n MEDIA_FILES_PROCESSED: media_files_processed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:200 \\n \\n MEDIA_SECONDS_PROCESSED - \\n \\n MEDIA_SECONDS_PROCESSED: media_seconds_processed \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n - NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 - \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED - \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n - \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 - \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED - \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 - \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED - \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: - train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":1833,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:54:13.123173Z\",\"last_understanding\":\"2026-07-14T12:54:12.864112Z\",\"last_extract\":\"2026-07-14T12:54:12.463871Z\",\"last_processing_start\":\"2026-07-14T12:54:12.433665Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > enumerations > UsageType\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > enumerations > 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libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n - NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 - \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED - \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n - \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 - \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED - \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 - \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED - \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: - train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"id\":\"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0a003c3f724e45e392a9c8d1ce8800c1\":{\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1\",\"slug\":\"docs-develop-js-sdk-interfaces-Consumption-md\",\"title\":\"docs - > develop > js sdk > interfaces > Consumption\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:51:46.788864\",\"modified\":\"2026-07-14T12:51:15.300757\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / Consumption\\n\\n# - Interface: Consumption\\n\\n## Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> - **customer\\\\_key\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:230](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L230)\\n\\n***\\n\\n### - normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:229](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L229)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"654b0dfe17ab08959c78891dd24c3424\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption - \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n - \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":349,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:16.563837Z\",\"last_understanding\":\"2026-07-14T12:51:16.208384Z\",\"last_extract\":\"2026-07-14T12:51:15.984803Z\",\"last_processing_start\":\"2026-07-14T12:51:15.966495Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > Consumption\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > Consumption\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\":{\"score\":0.6083368062973022,\"score_type\":\"VECTOR\",\"order\":7,\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption - \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n - \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs - > rag > advanced > consumption.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-10-03T08:32:26.341394\",\"modified\":\"2026-06-09T08:18:16.730959\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - consumption\\ntitle: Token consumption\\n---\\n\\nimport Tabs from \\\"@theme/Tabs\\\";\\nimport - TabItem from \\\"@theme/TabItem\\\";\\n\\n# Token consumption\\n\\nAgentic - RAG is a license and consumption-based service. This means that you pay for - the computational resources you consume. The consumption is measured in **Agentic - RAG tokens**.\\nAll public 3rd-party LLMs base their pricing on the number - of tokens consumed. In the LLM world, a token is around 4-5 characters on - average, which might fit an entire word or be split into parts. The number - of tokens is proportional to the amount of text, measured in chunks of 4-5 - characters. It closely relates to words but not entirely. The longer a sentence - is, the more tokens it will consume to read or to generate it.\\nSince all - these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize - the cost across all of them.\\n\\n## How Tokens Are Consumed in RAG\\n\\nWhen - a user asks a question to your Knowledge Box, the token consumption process - follows these steps:\\n\\n1. **Question Processing**: The system finds the - most relevant paragraphs to answer the question\\n2. **Context Assembly**: - These paragraphs are used as context when calling the LLM model\\n3. **Prompt - Creation**: Agentic RAG assembles the **prompt**, **context**, and **question** - into a single string\\n4. **LLM Processing**: This complete string is sent - to the LLM, corresponding to a certain number of **input tokens**\\n5. **Answer - Generation**: The LLM generates the answer, which corresponds to a certain - number of **output tokens**\\n\\n**Total consumption** = Input tokens + Output - tokens + Image tokens\\n\\n### Factors That Impact Token Consumption\\n\\nToken - consumption is directly affected by:\\n\\n- **Large context**: Results from - using RAG strategies like \\\"Full resource\\\" or \\\"Neighbouring paragraphs\\\", - or from using the `extra_context` parameter\\n- **Long questions**: More detailed - or complex questions require more input tokens\\n- **Long prompts**: Extensive - system prompts increase the input token count\\n- **Detailed answers**: Comprehensive - responses require more output tokens\\n- **Images in context**: When using - multimodal models, images included in the retrieved context significantly - increase token consumption\\n\\n## How to Limit and Control Token Consumption\\n\\n### - Strategy 1: Optimize Your Parameters\\n\\nThe first approach to reducing token - consumption is to fine-tune your request parameters:\\n\\n- **Optimize prompts**: - Ensure your prompts are concise and focused, avoiding unnecessary verbosity\\n- - **Control resource scope**: When using the \\\"Full resource\\\" strategy, - use the `count` attribute to limit the number of resources returned\\n- **Tune - neighboring context**: For the \\\"Neighbouring paragraphs\\\" strategy, optimize - the `before` and `after` attributes to balance context quality with token - efficiency\\n- **Manage summary length**: When using the \\\"Hierarchical\\\" - strategy, ensure that resource summaries are appropriately sized\\n- **Choose - efficient models**: Select LLMs that offer better token efficiency (typically, - ChatGPT 4o-mini is more cost-effective than ChatGPT 4o)\\n\\n### Strategy - 2: Set Hard Limits\\n\\nYou can implement safeguards against excessive token - consumption:\\n\\nUse the `max_tokens` parameter on the [`/ask` endpoint](/docs/api#tag/Search/operation/ask_knowledgebox_endpoint_kb__kbid__ask_post) - to set hard limits on:\\n- **Context size**: Limits the amount of retrieved - information sent to the LLM\\n- **Answer length**: Limits the length of the - generated response\\n\\n#### Important Considerations\\n\\n**Context Limitations**:\\n- - Restricting context size may result in less relevant answers since the LLM - has less information to work with\\n- Balance between cost control and answer - quality\\n\\n**Answer Length Limitations**:\\n- The LLM might not complete - its response if it hits the token limit, potentially cutting sentences mid-way\\n- - **Recommended approach**: Include length requirements in your prompt (e.g., - \\\"Please answer in less than 200 words\\\") rather than relying solely on - hard limits\\n- This allows the LLM to naturally conclude its response within - the desired length\\n\\n## How to Monitor Token Consumption\\n\\n### Understanding - Token Consumption Data\\n\\nYou can receive detailed token consumption information - from the following endpoints that utilize LLM models: `ask`, `chat`, `remi`, - `query`, `sentence`, `summarize`, `tokens`, and `rerank`.\\n\\n:::note\\nThe - `rephrase` endpoint currently does not support token consumption monitoring.\\n:::\\n\\nTo - receive token consumption data, you must include the following header in your - request:\\n```\\nX-SHOW-CONSUMPTION: true\\n```\\n\\nThe token consumption - data is provided in different formats depending on the response type:\\n- - **Streaming responses** (`application/x-ndjson`): Token consumption appears - as a separate JSON chunk with type \\\"consumption\\\"\\n- **Standard responses** - (`application/json`): Token consumption is included in a \\\"consumption\\\" - field within the main response\\n\\n### Token Consumption Response Format\\n\\n\\n \\n ```json\\n {\\n \\\"item\\\": - {\\n \\\"type\\\": \\\"consumption\\\",\\n \\\"normalized_tokens\\\": - {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": - 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": - 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n - \ }\\n }\\n ```\\n \\n \\n ```json\\n {\\n \\\"consumption\\\": {\\n \\\"normalized_tokens\\\": - {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": - 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": - 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n - \ }\\n }\\n ```\\n \\n\\n\\n### Understanding - Token Types\\n\\n**Normalized Tokens** (`normalized_tokens`):\\n- These represent - the number of Agentic RAG tokens consumed and that you will be billed for\\n- - Values are normalized across different LLM providers for consistent billing\\n- - Include separate counts for:\\n - `input`: Tokens used for the prompt, context, - and question\\n - `output`: Tokens used for the generated response\\n - - `image`: Tokens used for image processing (when applicable)\\n\\n**Customer - Key Tokens** (`customer_key_tokens`):\\n- These represent tokens consumed - when using your own LLM API keys\\n- These tokens are **not billed** by Agentic - RAG since you're using your own API keys\\n- Values are also normalized for - comparison purposes across different providers\\n\",\"format\":\"MARKDOWN\",\"md5\":\"204fe47dbd7eb38d465d05fa7538e51e\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: consumption \\n title: Token consumption \\n \\n import Tabs from - @theme/Tabs ; \\n import TabItem from @theme/TabItem ; \\n Token consumption - \\n Agentic RAG is a license and consumption-based service. This means that - you pay for the computational resources you consume. The consumption is measured - in Agentic RAG tokens. \\n All public 3rd-party LLMs base their pricing on - the number of tokens consumed. In the LLM world, a token is around 4-5 characters - on average, which might fit an entire word or be split into parts. The number - of tokens is proportional to the amount of text, measured in chunks of 4-5 - characters. It closely relates to words but not entirely. The longer a sentence - is, the more tokens it will consume to read or to generate it. \\n Since all - these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize - the cost across all of them. \\n How Tokens Are Consumed in RAG \\n When a - user asks a question to your Knowledge Box, the token consumption process - follows these steps: \\n \\n Question Processing: The system finds the most - relevant paragraphs to answer the question \\n Context Assembly: These paragraphs - are used as context when calling the LLM model \\n Prompt Creation: Agentic - RAG assembles the prompt, context, and question into a single string \\n LLM - Processing: This complete string is sent to the LLM, corresponding to a certain - number of input tokens \\n Answer Generation: The LLM generates the answer, - which corresponds to a certain number of output tokens \\n \\n Total consumption - = Input tokens + Output tokens + Image tokens \\n Factors That Impact Token - Consumption \\n Token consumption is directly affected by: \\n \\n Large context: - Results from using RAG strategies like Full resource or Neighbouring paragraphs - , or from using the extra_context parameter \\n Long questions: More detailed - or complex questions require more input tokens \\n Long prompts: Extensive - system prompts increase the input token count \\n Detailed answers: Comprehensive - responses require more output tokens \\n Images in context: When using multimodal - models, images included in the retrieved context significantly increase token - consumption \\n \\n How to Limit and Control Token Consumption \\n Strategy - 1: Optimize Your Parameters \\n The first approach to reducing token consumption - is to fine-tune your request parameters: \\n \\n Optimize prompts: Ensure - your prompts are concise and focused, avoiding unnecessary verbosity \\n Control - resource scope: When using the Full resource strategy, use the count attribute - to limit the number of resources returned \\n Tune neighboring context: For - the Neighbouring paragraphs strategy, optimize the before and after attributes - to balance context quality with token efficiency \\n Manage summary length: - When using the Hierarchical strategy, ensure that resource summaries are appropriately - sized \\n Choose efficient models: Select LLMs that offer better token efficiency - (typically, ChatGPT 4o-mini is more cost-effective than ChatGPT 4o) \\n \\n - Strategy 2: Set Hard Limits \\n You can implement safeguards against excessive - token consumption: \\n Use the max_tokens parameter on the /ask endpoint to - set hard limits on: \\n - Context size: Limits the amount of retrieved information - sent to the LLM \\n - Answer length: Limits the length of the generated response - \\n Important Considerations \\n Context Limitations: \\n - Restricting context - size may result in less relevant answers since the LLM has less information - to work with \\n - Balance between cost control and answer quality \\n Answer - Length Limitations: \\n - The LLM might not complete its response if it hits - the token limit, potentially cutting sentences mid-way \\n - Recommended approach: - Include length requirements in your prompt (e.g., Please answer in less than - 200 words ) rather than relying solely on hard limits \\n - This allows the - LLM to naturally conclude its response within the desired length \\n How to - Monitor Token Consumption \\n Understanding Token Consumption Data \\n You - can receive detailed token consumption information from the following endpoints - that utilize LLM models: ask, chat, remi, query, sentence, summarize, tokens, - and rerank. \\n :::note \\n The rephrase endpoint currently does not support - token consumption monitoring. \\n ::: \\n To receive token consumption data, - you must include the following header in your request: \\n X-SHOW-CONSUMPTION: - true \\n The token consumption data is provided in different formats depending - on the response type: \\n - Streaming responses (application/x-ndjson): Token - consumption appears as a separate JSON chunk with type consumption \\n - Standard - responses (application/json): Token consumption is included in a consumption - field within the main response \\n Token Consumption Response Format \\n \\n - \\n json \\n { \\n item : { \\n type : consumption , \\n normalized_tokens - : { \\n input : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens - : { \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n - \\n \\n json \\n { \\n consumption : { \\n normalized_tokens : { \\n input - : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens : { - \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n \\n - \\n Understanding Token Types \\n Normalized Tokens (normalized_tokens): \\n - - These represent the number of Agentic RAG tokens consumed and that you will - be billed for \\n - Values are normalized across different LLM providers for - consistent billing \\n - Include separate counts for: \\n - input: Tokens - used for the prompt, context, and question \\n - output: Tokens used for the - generated response \\n - image: Tokens used for image processing (when applicable) - 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openai-api-compatible-models\\ntitle: Connect to any OpenAI API compatible - LLM\\n---\\n\\n# Connect to any OpenAI API compatible LLM\\n\\nAgentic RAG - allows you to connect to any OpenAI API compatible LLM. This means that you - can use any LLM that has an API compatible with the OpenAI API which has become - a standard in the industry.\\n\\nMany of the options for self-hosted LLMs, - open-source LLMs hosted by cloud providers or commercial LLMs are compatible - with the OpenAI API. This means that you can use them with Agentic RAG without - any modifications.\\n\\n## Configuration\\n\\nTo modify your knowledge box - configuration you can do so in three manners, through the API, the Nuclia - CLI / SDK or the Agentic RAG dashboard.\\n\\nThe Agentic RAG dashboard offers - the most user-friendly way to modify the configuration of your knowledge box - and we will use it in this example.\\n\\nWe will be setting up a connection - to the **Phi 4 Reasoning Plus** model, hosted by **OpenRouter** which offers - a wide range of open-source and commercial models compatible with the OpenAI - API. We can see more information about this specific model [here](https://openrouter.ai/microsoft/phi-4-reasoning-plus:free), - the API parameters are located under the **API** tab.\\n\\n1. **Open the AI - Models page** \\n In the left sidebar under **Advanced**, click **AI Models**.\\n2. - **Select \u201COpenAI API Compatible Model\u201D** \\n From the models - list, choose **OpenAI API Compatible Model**.\\n3. **Enable custom Key** \\n - \ Toggle the option for using you own `OpenAI API Compatible Key` if it is - not already enabled.\\n4. **Fill in the configuration parameters**\\n\\n - - **API Key**:\\n - Description: The API key for your LLM. This is the key - that you would use as an authorization header in the API. You may leave this - blank if the endpoint you are connecting to does not require an API key.\\n - \ - Example: We will set this to our OpenRouter API key.\\n - **API URL**:\\n - \ - Description: The URL of the API endpoint for your LLM. This may be - shared between multiple models.\\n - Example: For OpenRouter, it is the - same for all models: `https://openrouter.ai/api/v1`\\n - **Model**:\\n - - Description: The name of the model you want to use, it needs to exactly match - the name of the model in the API.\\n - Example: For Phi 4 Reasoning Plus - in the OpenRouter API, it is `microsoft/phi-4-reasoning-plus:free`.\\n - - **Maximum supported input tokens**:\\n - Description: The maximum number - of tokens that the model can accept as input. Be mindful that this takes into - account the tokens used in the prompt, query and context. Also take note that - some models may provide their context window as the total between input and - output tokens, while others may provide it as the input tokens only.\\n - - Example: For Phi 4 Reasoning Plus, the total context size is `32768` tokens, - as we want to leave room for the output, we will set the maximum supported - input tokens as `32768 - 1024 = 31744`.\\n - **Maximum supported output - tokens**:\\n - Description: The maximum number of tokens that the model - can generate as output. Again, we should keep in mind that this value summed - to the **Maximum supported input tokens** should not exceed the total context - size supported by the model.\\n - Example: For Phi 4 Reasoning Plus, the - maximum output tokens is specified at `32768`, but we already reserved `31744` - for the input tokens, so we will set this to `32768 - 31744 = 1024`.\\n - - **Model Features**:\\n - Description: Under this section you will find - multiple toggles related to features supported by the model, these vary from - model to model, but most often the default values are well suited to most - use cases. The most relevant toggle is for `Image Support` which allows you - to use images as input for the model.\\n - Example: Image input is not - supported by Phi 4 Reasoning Plus, so we will leave it disabled.\\n\\n5. **Save** - \ \\n Click **Save changes**.\\n\\n6. **Test your model** \\n Run a sample - query in Agentic RAG or via API/CLI. Adjust your prompt templates and token - settings as needed.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"37cd8aff748addd04a363fa50828d1fe\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: openai-api-compatible-models \\n title: Connect to any OpenAI API - compatible LLM \\n \\n Connect to any OpenAI API compatible LLM \\n Agentic - RAG allows you to connect to any OpenAI API compatible LLM. This means that - you can use any LLM that has an API compatible with the OpenAI API which has - become a standard in the industry. \\n Many of the options for self-hosted - LLMs, open-source LLMs hosted by cloud providers or commercial LLMs are compatible - with the OpenAI API. This means that you can use them with Agentic RAG without - any modifications. \\n Configuration \\n To modify your knowledge box configuration - you can do so in three manners, through the API, the Nuclia CLI / SDK or the - Agentic RAG dashboard. \\n The Agentic RAG dashboard offers the most user-friendly - way to modify the configuration of your knowledge box and we will use it in - this example. \\n We will be setting up a connection to the Phi 4 Reasoning - Plus model, hosted by OpenRouter which offers a wide range of open-source - and commercial models compatible with the OpenAI API. We can see more information - about this specific model here, the API parameters are located under the API - tab. \\n \\n Open the AI Models page \\n In the left sidebar under Advanced, - click AI Models. \\n Select OpenAI API Compatible Model \\n From the models - list, choose OpenAI API Compatible Model. \\n Enable custom Key \\n Toggle - the option for using you own OpenAI API Compatible Key if it is not already - enabled. \\n \\n Fill in the configuration parameters \\n \\n \\n API Key: - \\n \\n Description: The API key for your LLM. This is the key that you would - use as an authorization header in the API. You may leave this blank if the - endpoint you are connecting to does not require an API key. \\n Example: We - will set this to our OpenRouter API key. \\n \\n \\n API URL: \\n Description: - The URL of the API endpoint for your LLM. This may be shared between multiple - models. \\n Example: For OpenRouter, it is the same for all models: https://openrouter.ai/api/v1 - \\n \\n \\n Model: \\n Description: The name of the model you want to use, - it needs to exactly match the name of the model in the API. \\n Example: For - Phi 4 Reasoning Plus in the OpenRouter API, it is microsoft/phi-4-reasoning-plus:free. - \\n \\n \\n Maximum supported input tokens: \\n Description: The maximum number - of tokens that the model can accept as input. Be mindful that this takes into - account the tokens used in the prompt, query and context. 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The most relevant toggle is for Image Support - which allows you to use images as input for the model. \\n Example: Image - input is not supported by Phi 4 Reasoning Plus, so we will leave it disabled. - \\n \\n \\n \\n Save \\n Click Save changes. \\n \\n \\n Test your model \\n - Run a sample query in Agentic RAG or via API/CLI. 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Also take note that - some models may provide their context window as the total between input and - output tokens, while others may provide it as the input tokens only. \\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":8,\"start\":2202,\"end\":2575,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs - > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-07-14T12:49:58.922592\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ModelConfig\\n\\n# - Interface: ModelConfig\\n\\n## Properties\\n\\n### assume\\\\_role?\\n\\n> - `optional` **assume\\\\_role**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:592](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L592)\\n\\n***\\n\\n### - driver?\\n\\n> `optional` **driver**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:590](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L590)\\n\\n***\\n\\n### - input\\\\_tokens\\n\\n> **input\\\\_tokens**: `object`\\n\\n#### max\\n\\n> - **max**: `number`\\n\\n#### min?\\n\\n> `optional` **min**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:587](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L587)\\n\\n***\\n\\n### - max\\\\_images?\\n\\n> `optional` **max\\\\_images**: `string`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:591](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L591)\\n\\n***\\n\\n### - output\\\\_tokens\\n\\n> **output\\\\_tokens**: `object`\\n\\n#### default\\\\_max?\\n\\n> - `optional` **default\\\\_max**: `number`\\n\\n#### max\\n\\n> **max**: `number`\\n\\n#### - min?\\n\\n> `optional` **min**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:588](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L588)\\n\\n***\\n\\n### - prompt\\\\_id?\\n\\n> `optional` **prompt\\\\_id**: `string`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:589](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L589)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"0ce41cb0494bcb99176527165e321fec\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ModelConfig \\n Interface: ModelConfig - \\n Properties \\n assume_role? \\n \\n optional assume_role: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:592 \\n \\n driver? - \\n \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 - \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: - number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \\n \\n max_images? \\n \\n optional max_images: string \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \\n \\n output_tokens \\n - \\n output_tokens: object \\n \\n default_max? \\n \\n optional default_max: - number \\n \\n max \\n \\n max: number \\n \\n min? \\n \\n optional min: - number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:588 - \\n \\n prompt_id? \\n \\n optional prompt_id: string \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/kb/kb.models.ts:589\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":212,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":108,\"key\":\"\"},{\"start\":108,\"end\":212,\"key\":\"\"}]},{\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":215,\"end\":380,\"key\":\"\"},{\"start\":380,\"end\":480,\"key\":\"\"}]},{\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":483,\"end\":638,\"key\":\"\"},{\"start\":638,\"end\":703,\"key\":\"\"}]},{\"start\":703,\"end\":895,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":704,\"end\":806,\"key\":\"\"},{\"start\":806,\"end\":895,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:01.191702Z\",\"last_understanding\":\"2026-07-14T12:50:00.962823Z\",\"last_extract\":\"2026-07-14T12:50:00.418522Z\",\"last_processing_start\":\"2026-07-14T12:50:00.364723Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - 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\\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 - \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: - number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \\n \\n max_images? \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":1,\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"42a4cd5a30314e94aa079ed0cfe81381\":{\"id\":\"42a4cd5a30314e94aa079ed0cfe81381\",\"slug\":\"docs-develop-js-sdk-interfaces-SplitStrategy-md\",\"title\":\"docs - > develop > js sdk > interfaces > SplitStrategy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:02:38.468609\",\"modified\":\"2026-07-14T12:51:02.450318\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/SplitStrategy\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / SplitStrategy\\n\\n# - Interface: SplitStrategy\\n\\n## Properties\\n\\n### custom\\\\_split?\\n\\n> - `optional` **custom\\\\_split**: [`CustomSplitStrategy`](../enumerations/CustomSplitStrategy.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:537](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L537)\\n\\n***\\n\\n### - llm\\\\_split?\\n\\n> `optional` **llm\\\\_split**: [`SplitLLMConfig`](SplitLLMConfig.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:538](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L538)\\n\\n***\\n\\n### - manual\\\\_split?\\n\\n> `optional` **manual\\\\_split**: `object`\\n\\n#### - splitter\\n\\n> **splitter**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:539](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L539)\\n\\n***\\n\\n### - max\\\\_paragraph?\\n\\n> `optional` **max\\\\_paragraph**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:536](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L536)\\n\\n***\\n\\n### - name?\\n\\n> `optional` **name**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:535](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L535)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"d24d884112df2f67b327ac6d6302ddf1\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / SplitStrategy \\n Interface: SplitStrategy - \\n Properties \\n custom_split? \\n \\n optional custom_split: CustomSplitStrategy - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:537 \\n \\n - llm_split? \\n \\n optional llm_split: SplitLLMConfig \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/kb/kb.models.ts:538 \\n \\n manual_split? \\n \\n - optional manual_split: object \\n \\n splitter \\n \\n splitter: string \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:539 \\n \\n max_paragraph? - \\n \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 - \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":234,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":113,\"key\":\"\"},{\"start\":113,\"end\":234,\"key\":\"\"}]},{\"start\":234,\"end\":502,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":237,\"end\":356,\"key\":\"\"},{\"start\":356,\"end\":502,\"key\":\"\"}]},{\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":505,\"end\":612,\"key\":\"\"},{\"start\":612,\"end\":696,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:04.701538Z\",\"last_understanding\":\"2026-07-14T12:51:04.225754Z\",\"last_extract\":\"2026-07-14T12:51:03.819024Z\",\"last_processing_start\":\"2026-07-14T12:51:03.798124Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > SplitStrategy\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > SplitStrategy\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\":{\"score\":0.5957005620002747,\"score_type\":\"VECTOR\",\"order\":15,\"text\":\" - \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 - \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"id\":\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":2,\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"b14cf452a3434839a04c111f2ea4dc51\":{\"id\":\"b14cf452a3434839a04c111f2ea4dc51\",\"slug\":\"docs-develop-js-sdk-enums-UsageType-md\",\"title\":\"docs - > develop > js sdk > enums > UsageType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"tn\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:41.582110\",\"modified\":\"2026-06-09T08:13:34.112208\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/enums/UsageType\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[@nuclia/core](../README.md) - / [Exports](../modules.md) / UsageType\\n\\n# Enumeration: UsageType\\n\\n## - Table of contents\\n\\n### Enumeration Members\\n\\n- [AI\\\\_TOKENS\\\\_USED](UsageType.md#ai_tokens_used)\\n- - [BYTES\\\\_PROCESSED](UsageType.md#bytes_processed)\\n- [CHARS\\\\_PROCESSED](UsageType.md#chars_processed)\\n- - [MEDIA\\\\_FILES\\\\_PROCESSED](UsageType.md#media_files_processed)\\n- [MEDIA\\\\_SECONDS\\\\_PROCESSED](UsageType.md#media_seconds_processed)\\n- - [NUCLIA\\\\_TOKENS](UsageType.md#nuclia_tokens)\\n- [PAGES\\\\_PROCESSED](UsageType.md#pages_processed)\\n- - [PARAGRAPHS\\\\_PROCESSED](UsageType.md#paragraphs_processed)\\n- [PRE\\\\_PROCESSING\\\\_TIME](UsageType.md#pre_processing_time)\\n- - [RESOURCES\\\\_PROCESSED](UsageType.md#resources_processed)\\n- [SEARCHES\\\\_PERFORMED](UsageType.md#searches_performed)\\n- - [SLOW\\\\_PROCESSING\\\\_TIME](UsageType.md#slow_processing_time)\\n- [SUGGESTIONS\\\\_PERFORMED](UsageType.md#suggestions_performed)\\n- - [TRAIN\\\\_SECONDS](UsageType.md#train_seconds)\\n\\n## Enumeration Members\\n\\n### - AI\\\\_TOKENS\\\\_USED\\n\\n\u2022 **AI\\\\_TOKENS\\\\_USED** = ``\\\"ai_tokens_used\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:190](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L190)\\n\\n___\\n\\n### - BYTES\\\\_PROCESSED\\n\\n\u2022 **BYTES\\\\_PROCESSED** = ``\\\"bytes_processed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:181](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L181)\\n\\n___\\n\\n### - CHARS\\\\_PROCESSED\\n\\n\u2022 **CHARS\\\\_PROCESSED** = ``\\\"chars_processed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:182](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L182)\\n\\n___\\n\\n### - MEDIA\\\\_FILES\\\\_PROCESSED\\n\\n\u2022 **MEDIA\\\\_FILES\\\\_PROCESSED** - = ``\\\"media_files_processed\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:184](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L184)\\n\\n___\\n\\n### - MEDIA\\\\_SECONDS\\\\_PROCESSED\\n\\n\u2022 **MEDIA\\\\_SECONDS\\\\_PROCESSED** - = ``\\\"media_seconds_processed\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:183](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L183)\\n\\n___\\n\\n### - NUCLIA\\\\_TOKENS\\n\\n\u2022 **NUCLIA\\\\_TOKENS** = ``\\\"nuclia_tokens_billed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:191](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L191)\\n\\n___\\n\\n### - PAGES\\\\_PROCESSED\\n\\n\u2022 **PAGES\\\\_PROCESSED** = ``\\\"pages_processed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:185](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L185)\\n\\n___\\n\\n### - PARAGRAPHS\\\\_PROCESSED\\n\\n\u2022 **PARAGRAPHS\\\\_PROCESSED** = ``\\\"paragraphs_processed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:186](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L186)\\n\\n___\\n\\n### - PRE\\\\_PROCESSING\\\\_TIME\\n\\n\u2022 **PRE\\\\_PROCESSING\\\\_TIME** = - ``\\\"pre_processing_time\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:178](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L178)\\n\\n___\\n\\n### - RESOURCES\\\\_PROCESSED\\n\\n\u2022 **RESOURCES\\\\_PROCESSED** = ``\\\"resources_processed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:180](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L180)\\n\\n___\\n\\n### - SEARCHES\\\\_PERFORMED\\n\\n\u2022 **SEARCHES\\\\_PERFORMED** = ``\\\"searches_performed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:188](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L188)\\n\\n___\\n\\n### - SLOW\\\\_PROCESSING\\\\_TIME\\n\\n\u2022 **SLOW\\\\_PROCESSING\\\\_TIME** - = ``\\\"slow_processing_time\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:179](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L179)\\n\\n___\\n\\n### - SUGGESTIONS\\\\_PERFORMED\\n\\n\u2022 **SUGGESTIONS\\\\_PERFORMED** = ``\\\"suggestions_performed\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:189](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L189)\\n\\n___\\n\\n### - TRAIN\\\\_SECONDS\\n\\n\u2022 **TRAIN\\\\_SECONDS** = ``\\\"train_seconds\\\"``\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:187](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L187)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"232462bafe6a7eb30c1df7131403005e\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - / Exports / UsageType \\n Enumeration: UsageType \\n Table of contents \\n - Enumeration Members \\n \\n AI_TOKENS_USED \\n BYTES_PROCESSED \\n CHARS_PROCESSED - \\n MEDIA_FILES_PROCESSED \\n MEDIA_SECONDS_PROCESSED \\n NUCLIA_TOKENS \\n - PAGES_PROCESSED \\n PARAGRAPHS_PROCESSED \\n PRE_PROCESSING_TIME \\n RESOURCES_PROCESSED - \\n SEARCHES_PERFORMED \\n SLOW_PROCESSING_TIME \\n SUGGESTIONS_PERFORMED - \\n TRAIN_SECONDS \\n \\n Enumeration Members \\n AI_TOKENS_USED \\n \u2022 - AI_TOKENS_USED = ai_tokens_used \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:190 - \\n \\n BYTES_PROCESSED \\n \u2022 BYTES_PROCESSED = bytes_processed \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:181 \\n \\n CHARS_PROCESSED \\n - \u2022 CHARS_PROCESSED = chars_processed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:182 - \\n \\n MEDIA_FILES_PROCESSED \\n \u2022 MEDIA_FILES_PROCESSED = media_files_processed - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184 \\n \\n MEDIA_SECONDS_PROCESSED - \\n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \\n Defined in - \\n libs/sdk-core/src/lib/db/db.models.ts:183 \\n \\n NUCLIA_TOKENS \\n \u2022 - NUCLIA_TOKENS = nuclia_tokens_billed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:191 - \\n \\n PAGES_PROCESSED \\n \u2022 PAGES_PROCESSED = pages_processed \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n PARAGRAPHS_PROCESSED - \\n \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:186 \\n \\n PRE_PROCESSING_TIME \\n - 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\u2022 CHARS_PROCESSED = chars_processed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:182 - \\n \\n MEDIA_FILES_PROCESSED \\n \u2022 MEDIA_FILES_PROCESSED = media_files_processed - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184 \\n \\n MEDIA_SECONDS_PROCESSED - \\n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \\n Defined in - \\n libs/sdk-core/src/lib/db/db.models.ts:183 \\n \\n NUCLIA_TOKENS \\n \u2022 - NUCLIA_TOKENS = nuclia_tokens_billed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:191 - \\n \\n PAGES_PROCESSED \\n \u2022 PAGES_PROCESSED = pages_processed \\n Defined - in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n PARAGRAPHS_PROCESSED - \\n \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:186 \\n \\n PRE_PROCESSING_TIME \\n - \u2022 PRE_PROCESSING_TIME = pre_processing_time \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:178 - \\n \\n RESOURCES_PROCESSED \\n \u2022 RESOURCES_PROCESSED = resources_processed - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:180 \\n \\n SEARCHES_PERFORMED - \\n \u2022 SEARCHES_PERFORMED = searches_performed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:188 - \\n \\n SLOW_PROCESSING_TIME \\n \u2022 SLOW_PROCESSING_TIME = slow_processing_time - \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:179 \\n \\n SUGGESTIONS_PERFORMED - \\n \u2022 SUGGESTIONS_PERFORMED = suggestions_performed \\n Defined in \\n - libs/sdk-core/src/lib/db/db.models.ts:189 \\n \\n TRAIN_SECONDS \\n \u2022 - TRAIN_SECONDS = train_seconds \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:187\",\"id\":\"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":2139,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"dd41482018924facb5dbb87a7d53f122\":{\"id\":\"dd41482018924facb5dbb87a7d53f122\",\"slug\":\"docs-ingestion-how-to-rate-limiting-md\",\"title\":\"docs - > ingestion > how to > rate limiting\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:05.339624\",\"modified\":\"2026-06-09T08:18:12.259849\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: - rate-limiting\\ntitle: Manage rate limiting\\n---\\n\\n# Manage rate limiting\\n\\nRate - limits are an essential aspect of the Agentic RAG platform, ensuring fair - usage and optimal performance for all users interacting with Agentic RAG APIs. - This document outlines the rate limits enforced by Agentic RAG and provides - guidelines for handling rate-limited responses effectively.\\n\\n## Introduction\\n\\nAgentic - RAG can apply two types of limits to its APIs:\\n\\n- **Regular API rate limits**: - By default, the sum of all authenticated requests in a Agentic RAG account - cannot exceed 2400 requests per minute. Note that this limit can be customized - on a per-account basis. Please contact [Agentic RAG's support team](mailto:support@nuclia.com) - if you need an increase.\\n\\n- **Ingestion back pressure limits**: Agentic - RAG implements a back-pressure mechanism to manage ingestion pipeline overload. - This mainly affects endpoints for uploading data and creating or updating - resources.\\n\\n## Handling Rate-Limited Responses\\n\\nAgentic RAG adheres - to [the HTTP standard](https://datatracker.ietf.org/doc/html/rfc6585#section-4) - and will return a response with a `429` status codes when the limits are exceeded.\\n\\nThe - official Agentic RAG API clients already have built-in mechanisms for retrying - requests when rate limits are encountered:\\n\\n- [Nuclia Python client](/docs/develop/python-sdk/README)\\n- - [Nuclia JavaScript client](/docs/develop/js-sdk/)\\n\\nHowever, if you are - interacting directly with the API, we recommend using an [exponential backoff - retry strategy](https://en.wikipedia.org/wiki/Exponential_backoff) when limits - are reached.\\n\\nWhen ingestion back pressure rate limits are hit, the response - will include a `try_after` key with an estimated UTC time for retrying the - request. You can use this value for retry logic as an alternative to the exponential - backoff strategy.\\n\\n## Example 1: Regular API rate limits\\n\\nHere's an - example of how to implement an exponential backoff retry strategy in Python:\\n\\n```python\\nimport - time\\nimport requests\\n\\ndef make_request_with_exponential_backoff(url, - headers, max_retries=5):\\n retries = 0\\n while retries < max_retries:\\n - \ response = requests.get(url, headers=headers)\\n if response.status_code - == 200:\\n return response.json()\\n elif response.status_code - == 429:\\n wait_time = 2 ** retries # Exponential backoff: 2^retries\\n - \ print(f\\\"Rate limit exceeded. Retrying in {wait_time} seconds...\\\")\\n - \ time.sleep(wait_time)\\n retries += 1\\n else:\\n - \ response.raise_for_status()\\n raise Exception(\\\"Max retries - exceeded\\\")\\n\\n# Example usage\\nurl = \\\"https://your-endpoint\\\"\\nheaders - = {\\\"Authorization\\\": \\\"Bearer YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_exponential_backoff(url, - headers)\\nprint(data)\\n```\\n\\n## Example 2: Ingestion back pressure limits\\n\\nHere's - an example of how to use the try_after key from the response to manage rate - limits:\\n\\n```python\\nimport time\\nfrom datetime import datetime\\n\\nimport - requests\\n\\n\\ndef make_request_with_try_after_info(url, headers, max_retries=5):\\n - \ retries = 0\\n while retries < max_retries:\\n response = requests.get(url, - headers=headers)\\n response_body = response.json()\\n if response.status_code - == 200:\\n return response.json()\\n elif response.status_code - == 429 and \\\"try_after\\\" in response_body:\\n try_after = response_body[\\\"try_after\\\"]\\n - \ retry_time = datetime.strptime(try_after, \\\"%Y-%m-%dT%H:%M:%S.%fZ\\\")\\n - \ wait_time = (retry_time - datetime.utcnow()).total_seconds()\\n - \ print(\\n f\\\"Rate limit exceeded. Retrying at - {retry_time} (in {wait_time} seconds)...\\\"\\n )\\n time.sleep(wait_time)\\n - \ retries += 1\\n else:\\n response.raise_for_status()\\n - \ raise Exception(\\\"Max retries exceeded\\\")\\n\\n\\n# Example usage\\nurl - = \\\"https://your-endpoint\\\"\\nheaders = {\\\"Authorization\\\": \\\"Bearer - YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_try_after_info(url, headers)\\nprint(data)\\n```\\n\\nThese - examples demonstrate how to handle rate limits effectively, ensuring that - your application respects the limits and retries appropriately.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"ed11945857f4618eec7ed0d1b16ffa44\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" - \\n id: rate-limiting \\n title: Manage rate limiting \\n \\n Manage rate - limiting \\n Rate limits are an essential aspect of the Agentic RAG platform, - ensuring fair usage and optimal performance for all users interacting with - Agentic RAG APIs. This document outlines the rate limits enforced by Agentic - RAG and provides guidelines for handling rate-limited responses effectively. - \\n Introduction \\n Agentic RAG can apply two types of limits to its APIs: - \\n \\n \\n Regular API rate limits: By default, the sum of all authenticated - requests in a Agentic RAG account cannot exceed 2400 requests per minute. - Note that this limit can be customized on a per-account basis. Please contact - Agentic RAG's support team if you need an increase. \\n \\n \\n Ingestion - back pressure limits: Agentic RAG implements a back-pressure mechanism to - manage ingestion pipeline overload. This mainly affects endpoints for uploading - data and creating or updating resources. \\n \\n \\n Handling Rate-Limited - Responses \\n Agentic RAG adheres to the HTTP standard and will return a response - with a 429 status codes when the limits are exceeded. \\n The official Agentic - RAG API clients already have built-in mechanisms for retrying requests when - rate limits are encountered: \\n \\n Nuclia Python client \\n Nuclia JavaScript - client \\n \\n However, if you are interacting directly with the API, we recommend - using an exponential backoff retry strategy when limits are reached. \\n When - ingestion back pressure rate limits are hit, the response will include a try_after - key with an estimated UTC time for retrying the request. You can use this - value for retry logic as an alternative to the exponential backoff strategy. - \\n Example 1: Regular API rate limits \\n Here's an example of how to implement - an exponential backoff retry strategy in Python: \\n ```python \\n import - time \\n import requests \\n def make_request_with_exponential_backoff(url, - headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: - \\n response = requests.get(url, headers=headers) \\n if response.status_code - == 200: \\n return response.json() \\n elif response.status_code == 429: \\n - wait_time = 2 retries # Exponential backoff: 2^retries \\n print(f Rate limit - exceeded. Retrying in {wait_time} seconds... ) \\n time.sleep(wait_time) \\n - retries += 1 \\n else: \\n response.raise_for_status() \\n raise Exception( - Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint \\n - headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_exponential_backoff(url, - headers) \\n print(data) \\n ``` \\n Example 2: Ingestion back pressure limits - \\n Here's an example of how to use the try_after key from the response to - manage rate limits: \\n ```python \\n import time \\n from datetime import - datetime \\n import requests \\n def make_request_with_try_after_info(url, - headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: - \\n response = requests.get(url, headers=headers) \\n response_body = response.json() - \\n if response.status_code == 200: \\n return response.json() \\n elif response.status_code - == 429 and try_after in response_body: \\n try_after = response_body[ try_after - ] \\n retry_time = datetime.strptime(try_after, %Y-%m-%dT%H:%M:%S.%fZ ) \\n - wait_time = (retry_time - datetime.utcnow()).total_seconds() \\n print( \\n - f Rate limit exceeded. Retrying at {retry_time} (in {wait_time} seconds)... - \\n ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() - \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint - \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, - headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle - rate limits effectively, ensuring that your application respects the limits - and retries 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limiting\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\":{\"score\":0.590923011302948,\"score_type\":\"VECTOR\",\"order\":18,\"text\":\" - ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() - \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint - \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, - headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle - rate limits effectively, ensuring that your application respects the limits - and retries appropriately.\",\"id\":\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":9,\"start\":3310,\"end\":3757,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"50aac6f34b6d47de8e3b01f8b2de6e9c\":{\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c\",\"slug\":\"docs-develop-js-sdk-interfaces-PredictAnswerOptions-md\",\"title\":\"docs - > develop > js sdk > interfaces > PredictAnswerOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:11.443619\",\"modified\":\"2026-07-14T12:50:46.385594\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / PredictAnswerOptions\\n\\n# - Interface: PredictAnswerOptions\\n\\n## Properties\\n\\n### chat\\\\_history?\\n\\n> - `optional` **chat\\\\_history**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:242](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L242)\\n\\n***\\n\\n### - citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L249)\\n\\n***\\n\\n### - citations?\\n\\n> `optional` **citations**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L248)\\n\\n***\\n\\n### - context?\\n\\n> `optional` **context**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:243](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L243)\\n\\n***\\n\\n### - format\\\\_prompt?\\n\\n> `optional` **format\\\\_prompt**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:258](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L258)\\n\\n***\\n\\n### - generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L250)\\n\\n***\\n\\n### - json\\\\_schema?\\n\\n> `optional` **json\\\\_schema**: `object`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:257](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L257)\\n\\n***\\n\\n### - max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L251)\\n\\n***\\n\\n### - prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:256](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L256)\\n\\n***\\n\\n### - query\\\\_context?\\n\\n> `optional` **query\\\\_context**: `string`[] \\\\| - `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:244](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L244)\\n\\n***\\n\\n### - query\\\\_context\\\\_images?\\n\\n> `optional` **query\\\\_context\\\\_images**: - `object`\\n\\n#### b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> - **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:252](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L252)\\n\\n***\\n\\n### - query\\\\_context\\\\_order?\\n\\n> `optional` **query\\\\_context\\\\_order**: - `object`\\n\\n#### Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:245](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L245)\\n\\n***\\n\\n### - reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:260](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L260)\\n\\n***\\n\\n### - rerank\\\\_context?\\n\\n> `optional` **rerank\\\\_context**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:259](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L259)\\n\\n***\\n\\n### - retrieval?\\n\\n> `optional` **retrieval**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:240](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L240)\\n\\n***\\n\\n### - system?\\n\\n> `optional` **system**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:241](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L241)\\n\\n***\\n\\n### - truncate?\\n\\n> `optional` **truncate**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L246)\\n\\n***\\n\\n### - user\\\\_prompt?\\n\\n> `optional` **user\\\\_prompt**: `object`\\n\\n#### - prompt\\n\\n> **prompt**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"470be50f3c6aeeff5ae3310ed007b9b3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / PredictAnswerOptions \\n Interface: PredictAnswerOptions - \\n Properties \\n chat_history? \\n \\n optional chat_history: ContextEntry[] - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:242 \\n - \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:249 \\n \\n citations? - \\n \\n optional citations: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:248 - \\n \\n context? \\n \\n optional context: ContextEntry[] \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:243 \\n \\n format_prompt? - \\n \\n optional format_prompt: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:258 - \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 \\n \\n json_schema? - \\n \\n optional json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 - \\n \\n max_tokens? \\n \\n optional max_tokens: number \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 \\n \\n prefer_markdown? - \\n \\n optional prefer_markdown: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 - \\n \\n query_context? \\n \\n optional query_context: string[] \\\\| object - \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:244 \\n - \\n query_context_images? \\n \\n optional query_context_images: object \\n - \\n b64encoded \\n \\n b64encoded: string \\n \\n content_type \\n \\n content_type: - string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:252 - \\n \\n query_context_order? \\n \\n optional query_context_order: object - \\n \\n Index Signature \\n [key: string]: number \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:245 - \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:260 \\n \\n rerank_context? - \\n \\n optional rerank_context: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:259 - \\n \\n retrieval? \\n \\n optional retrieval: boolean \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/ask.models.ts:240 \\n \\n system? \\n - \\n optional system: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:241 - \\n \\n truncate? \\n \\n optional truncate: boolean \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/search/ask.models.ts:246 \\n \\n user_prompt? \\n - \\n optional user_prompt: object \\n \\n prompt \\n \\n prompt: string \\n - \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:247\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":257,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":127,\"key\":\"\"},{\"start\":127,\"end\":257,\"key\":\"\"}]},{\"start\":257,\"end\":491,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":260,\"end\":382,\"key\":\"\"},{\"start\":382,\"end\":491,\"key\":\"\"}]},{\"start\":491,\"end\":739,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":494,\"end\":617,\"key\":\"\"},{\"start\":617,\"end\":739,\"key\":\"\"}]},{\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":742,\"end\":864,\"key\":\"\"},{\"start\":864,\"end\":977,\"key\":\"\"}]},{\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":980,\"end\":1100,\"key\":\"\"},{\"start\":1100,\"end\":1221,\"key\":\"\"}]},{\"start\":1221,\"end\":1575,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1224,\"end\":1364,\"key\":\"\"},{\"start\":1364,\"end\":1575,\"key\":\"\"}]},{\"start\":1575,\"end\":1866,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1578,\"end\":1743,\"key\":\"\"},{\"start\":1743,\"end\":1866,\"key\":\"\"}]},{\"start\":1866,\"end\":2096,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1869,\"end\":1988,\"key\":\"\"},{\"start\":1988,\"end\":2096,\"key\":\"\"}]},{\"start\":2096,\"end\":2320,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2099,\"end\":2208,\"key\":\"\"},{\"start\":2208,\"end\":2320,\"key\":\"\"}]},{\"start\":2320,\"end\":2449,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2323,\"end\":2449,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:49.024021Z\",\"last_understanding\":\"2026-07-14T12:50:48.461687Z\",\"last_extract\":\"2026-07-14T12:50:47.086918Z\",\"last_processing_start\":\"2026-07-14T12:50:47.048628Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs - > develop > js sdk > interfaces > PredictAnswerOptions\",\"extracted\":{\"text\":{\"text\":\"docs - > develop > js sdk > interfaces > PredictAnswerOptions\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\":{\"score\":0.6482165455818176,\"score_type\":\"VECTOR\",\"order\":3,\"text\":\" - \\n optional max_tokens: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \\n \\n query_context? - \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":4,\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\":{\"score\":0.5993967652320862,\"score_type\":\"VECTOR\",\"order\":12,\"text\":\" - \\n optional generative_model: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 - \\n \\n json_schema? \\n \\n optional json_schema: object \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 \\n \\n max_tokens? - \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":3,\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs - > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-07-14T12:51:04.368823\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) - \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ChatOptions\\n\\n# - Interface: ChatOptions\\n\\n## Extends\\n\\n- [`BaseSearchOptions`](BaseSearchOptions.md)\\n\\n## - Properties\\n\\n### answer\\\\_json\\\\_schema?\\n\\n> `optional` **answer\\\\_json\\\\_schema**: - `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:114](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L114)\\n\\n***\\n\\n### - audit\\\\_metadata?\\n\\n> `optional` **audit\\\\_metadata**: `object`\\n\\n#### - Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `string`\\n\\n#### Inherited - from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`audit_metadata`](BaseSearchOptions.md#audit_metadata)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:81](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L81)\\n\\n***\\n\\n### - citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:116](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L116)\\n\\n***\\n\\n### - citations?\\n\\n> `optional` **citations**: `boolean` \\\\| `\\\"none\\\"` - \\\\| `\\\"default\\\"` \\\\| `\\\"llm_footnotes\\\"`\\n\\nIt will return - the text blocks that have been effectively used to build each section of the - answer.\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:105](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L105)\\n\\n***\\n\\n### - debug?\\n\\n> `optional` **debug**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`debug`](BaseSearchOptions.md#debug)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:79](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L79)\\n\\n***\\n\\n### - extra\\\\_context?\\n\\n> `optional` **extra\\\\_context**: `string`[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:115](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L115)\\n\\n***\\n\\n### - extra\\\\_context\\\\_images?\\n\\n> `optional` **extra\\\\_context\\\\_images**: - `object`[]\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:118](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L118)\\n\\n***\\n\\n### - ~~extracted?~~\\n\\n> `optional` **extracted**: [`ExtractedDataTypes`](../enumerations/ExtractedDataTypes.md)[]\\n\\n#### - Deprecated\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`extracted`](BaseSearchOptions.md#extracted)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:73](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L73)\\n\\n***\\n\\n### - features?\\n\\n> `optional` **features**: [`Features`](../namespaces/Ask/enumerations/Features.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:117](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L117)\\n\\n***\\n\\n### - field\\\\_type\\\\_filter?\\n\\n> `optional` **field\\\\_type\\\\_filter**: - [`FIELD_TYPE`](../enumerations/FIELD_TYPE.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`field_type_filter`](BaseSearchOptions.md#field_type_filter)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:74](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L74)\\n\\n***\\n\\n### - fields?\\n\\n> `optional` **fields**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`fields`](BaseSearchOptions.md#fields)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:62](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L62)\\n\\n***\\n\\n### - filter\\\\_expression?\\n\\n> `optional` **filter\\\\_expression**: [`FilterExpression`](FilterExpression.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filter_expression`](BaseSearchOptions.md#filter_expression)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:64](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L64)\\n\\n***\\n\\n### - filters?\\n\\n> `optional` **filters**: `string`[] \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filters`](BaseSearchOptions.md#filters)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:63](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L63)\\n\\n***\\n\\n### - generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:108](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L108)\\n\\n***\\n\\n### - highlight?\\n\\n> `optional` **highlight**: `boolean`\\n\\n#### Inherited - from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`highlight`](BaseSearchOptions.md#highlight)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:76](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L76)\\n\\n***\\n\\n### - keyword\\\\_filters?\\n\\n> `optional` **keyword\\\\_filters**: `string`[] - \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`keyword_filters`](BaseSearchOptions.md#keyword_filters)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:65](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L65)\\n\\n***\\n\\n### - max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number` \\\\| `object`\\n\\nDefines - the maximum number of tokens that the model will take as context.\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:112](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L112)\\n\\n***\\n\\n### - min\\\\_score?\\n\\n> `optional` **min\\\\_score**: `number` \\\\| [`MinScore`](MinScore.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`min_score`](BaseSearchOptions.md#min_score)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:66](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L66)\\n\\n***\\n\\n### - prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:113](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L113)\\n\\n***\\n\\n### - prompt?\\n\\n> `optional` **prompt**: `string` \\\\| [`Prompts`](Prompts.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:101](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L101)\\n\\n***\\n\\n### - query\\\\_image?\\n\\n> `optional` **query\\\\_image**: `object`\\n\\n#### - b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> - **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:122](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L122)\\n\\n***\\n\\n### - rag\\\\_images\\\\_strategies?\\n\\n> `optional` **rag\\\\_images\\\\_strategies**: - [`RAGImageStrategy`](../type-aliases/RAGImageStrategy.md)[]\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:107](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L107)\\n\\n***\\n\\n### - rag\\\\_strategies?\\n\\n> `optional` **rag\\\\_strategies**: [`RAGStrategy`](../type-aliases/RAGStrategy.md)[]\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:106](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L106)\\n\\n***\\n\\n### - range\\\\_creation\\\\_end?\\n\\n> `optional` **range\\\\_creation\\\\_end**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_end`](BaseSearchOptions.md#range_creation_end)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:68](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L68)\\n\\n***\\n\\n### - range\\\\_creation\\\\_start?\\n\\n> `optional` **range\\\\_creation\\\\_start**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_start`](BaseSearchOptions.md#range_creation_start)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:67](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L67)\\n\\n***\\n\\n### - range\\\\_modification\\\\_end?\\n\\n> `optional` **range\\\\_modification\\\\_end**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_end`](BaseSearchOptions.md#range_modification_end)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:70](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L70)\\n\\n***\\n\\n### - range\\\\_modification\\\\_start?\\n\\n> `optional` **range\\\\_modification\\\\_start**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_start`](BaseSearchOptions.md#range_modification_start)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:69](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L69)\\n\\n***\\n\\n### - rank\\\\_fusion?\\n\\n> `optional` **rank\\\\_fusion**: [`RankFusion`](RankFusion.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rank_fusion`](BaseSearchOptions.md#rank_fusion)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:84](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L84)\\n\\n***\\n\\n### - reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L126)\\n\\n***\\n\\n### - rephrase?\\n\\n> `optional` **rephrase**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rephrase`](BaseSearchOptions.md#rephrase)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:77](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L77)\\n\\n***\\n\\n### - reranker?\\n\\n> `optional` **reranker**: [`Reranker`](../enumerations/Reranker.md)\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`reranker`](BaseSearchOptions.md#reranker)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:83](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L83)\\n\\n***\\n\\n### - resource\\\\_filters?\\n\\n> `optional` **resource\\\\_filters**: `string`[]\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`resource_filters`](BaseSearchOptions.md#resource_filters)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:75](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L75)\\n\\n***\\n\\n### - search\\\\_configuration?\\n\\n> `optional` **search\\\\_configuration**: - `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`search_configuration`](BaseSearchOptions.md#search_configuration)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:86](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L86)\\n\\n***\\n\\n### - security?\\n\\n> `optional` **security**: `object`\\n\\n#### groups\\n\\n> - **groups**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`security`](BaseSearchOptions.md#security)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:85](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L85)\\n\\n***\\n\\n### - show?\\n\\n> `optional` **show**: [`ResourceProperties`](../enumerations/ResourceProperties.md)[]\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show`](BaseSearchOptions.md#show)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:71](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L71)\\n\\n***\\n\\n### - show\\\\_consumption?\\n\\n> `optional` **show\\\\_consumption**: `boolean`\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L127)\\n\\n***\\n\\n### - show\\\\_hidden?\\n\\n> `optional` **show\\\\_hidden**: `boolean`\\n\\n#### - Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show_hidden`](BaseSearchOptions.md#show_hidden)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:80](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L80)\\n\\n***\\n\\n### - synchronous?\\n\\n> `optional` **synchronous**: `boolean`\\n\\n#### Defined - in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:100](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L100)\\n\\n***\\n\\n### - top\\\\_k?\\n\\n> `optional` **top\\\\_k**: `number`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`top_k`](BaseSearchOptions.md#top_k)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:82](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L82)\\n\\n***\\n\\n### - vectorset?\\n\\n> `optional` **vectorset**: `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`vectorset`](BaseSearchOptions.md#vectorset)\\n\\n#### - Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:78](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L78)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"d6b2f3f31ba0af4fa58490cdf6abeb52\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core - \u2022 Docs \\n \\n @nuclia/core / ChatOptions \\n Interface: ChatOptions - \\n Extends \\n \\n BaseSearchOptions \\n \\n Properties \\n answer_json_schema? - \\n \\n optional answer_json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:114 - \\n \\n audit_metadata? \\n \\n optional audit_metadata: object \\n \\n Index - Signature \\n [key: string]: string \\n Inherited from \\n BaseSearchOptions.audit_metadata - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:81 \\n - \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:116 \\n \\n - citations? \\n \\n optional citations: boolean \\\\| none \\\\| default \\\\| - llm_footnotes \\n \\n It will return the text blocks that have been effectively - used to build each section of the answer. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:105 - \\n \\n debug? \\n \\n optional debug: boolean \\n \\n Inherited from \\n - BaseSearchOptions.debug \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:79 - \\n \\n extra_context? \\n \\n optional extra_context: string[] \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:115 \\n \\n extra_context_images? - \\n \\n optional extra_context_images: object[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:118 - \\n \\n ~~extracted?~~ \\n \\n optional extracted: ExtractedDataTypes[] \\n - \\n Deprecated \\n Inherited from \\n BaseSearchOptions.extracted \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:73 \\n \\n features? - \\n \\n optional features: Features[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:117 - \\n \\n field_type_filter? \\n \\n optional field_type_filter: FIELD_TYPE[] - \\n \\n Inherited from \\n BaseSearchOptions.field_type_filter \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:74 \\n \\n fields? - \\n \\n optional fields: string[] \\n \\n Inherited from \\n BaseSearchOptions.fields - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:62 \\n - \\n filter_expression? \\n \\n optional filter_expression: FilterExpression - \\n \\n Inherited from \\n BaseSearchOptions.filter_expression \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:64 \\n \\n filters? - \\n \\n optional filters: string[] \\\\| Filter[] \\n \\n Inherited from \\n - BaseSearchOptions.filters \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:63 - \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:108 \\n \\n - highlight? \\n \\n optional highlight: boolean \\n \\n Inherited from \\n - BaseSearchOptions.highlight \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:76 - \\n \\n keyword_filters? \\n \\n optional keyword_filters: string[] \\\\| - Filter[] \\n \\n Inherited from \\n BaseSearchOptions.keyword_filters \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:65 \\n \\n - max_tokens? \\n \\n optional max_tokens: number \\\\| object \\n \\n Defines - the maximum number of tokens that the model will take as context. \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 \\n \\n min_score? - \\n \\n optional min_score: number \\\\| MinScore \\n \\n Inherited from \\n - BaseSearchOptions.min_score \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:66 - \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n - Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:113 \\n \\n - prompt? \\n \\n optional prompt: string \\\\| Prompts \\n \\n Defined in \\n - libs/sdk-core/src/lib/db/search/search.models.ts:101 \\n \\n query_image? - \\n \\n optional query_image: object \\n \\n b64encoded \\n \\n b64encoded: - string \\n \\n content_type \\n \\n content_type: string \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/search.models.ts:122 \\n \\n rag_images_strategies? - \\n \\n optional rag_images_strategies: RAGImageStrategy[] \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:107 \\n \\n rag_strategies? - \\n \\n optional rag_strategies: RAGStrategy[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:106 - \\n \\n range_creation_end? \\n \\n optional range_creation_end: string \\n - \\n Inherited from \\n BaseSearchOptions.range_creation_end \\n Defined in - \\n libs/sdk-core/src/lib/db/search/search.models.ts:68 \\n \\n range_creation_start? - \\n \\n optional range_creation_start: string \\n \\n Inherited from \\n BaseSearchOptions.range_creation_start - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:67 \\n - \\n range_modification_end? \\n \\n optional range_modification_end: string - \\n \\n Inherited from \\n BaseSearchOptions.range_modification_end \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:70 \\n \\n range_modification_start? - \\n \\n optional range_modification_start: string \\n \\n Inherited from \\n - BaseSearchOptions.range_modification_start \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:69 - \\n \\n rank_fusion? \\n \\n optional rank_fusion: RankFusion \\n \\n Inherited - from \\n BaseSearchOptions.rank_fusion \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:84 - \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:126 \\n \\n rephrase? - \\n \\n optional rephrase: boolean \\n \\n Inherited from \\n BaseSearchOptions.rephrase - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:77 \\n - \\n reranker? \\n \\n optional reranker: Reranker \\n \\n Inherited from \\n - BaseSearchOptions.reranker \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:83 - \\n \\n resource_filters? \\n \\n optional resource_filters: string[] \\n - \\n Inherited from \\n BaseSearchOptions.resource_filters \\n Defined in \\n - libs/sdk-core/src/lib/db/search/search.models.ts:75 \\n \\n search_configuration? - \\n \\n optional search_configuration: string \\n \\n Inherited from \\n BaseSearchOptions.search_configuration - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:86 \\n - \\n security? \\n \\n optional security: object \\n \\n groups \\n \\n groups: - string[] \\n \\n Inherited from \\n BaseSearchOptions.security \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:85 \\n \\n show? \\n - \\n optional show: ResourceProperties[] \\n \\n Inherited from \\n BaseSearchOptions.show - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:71 \\n - \\n show_consumption? \\n \\n optional show_consumption: boolean \\n \\n Defined - in \\n libs/sdk-core/src/lib/db/search/search.models.ts:127 \\n \\n show_hidden? - \\n \\n optional show_hidden: boolean \\n \\n Inherited from \\n BaseSearchOptions.show_hidden - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:80 \\n - \\n synchronous? \\n \\n optional synchronous: boolean \\n \\n Defined in - \\n libs/sdk-core/src/lib/db/search/search.models.ts:100 \\n \\n top_k? \\n - \\n optional top_k: number \\n \\n Inherited from \\n BaseSearchOptions.top_k - \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:82 \\n - \\n vectorset? \\n \\n optional vectorset: string \\n \\n Inherited from \\n - BaseSearchOptions.vectorset \\n Defined in \\n 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headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Content-Length: - - '207667' + - '1448' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 15 Jul 2026 08:11:15 GMT + - Wed, 05 Aug 2026 07:57:20 GMT + nuclia-learning-model: + - bge-reranker-v2-m3 via: - 1.1 google x-envoy-upstream-service-time: - - '297' + - '90' x-nuclia-trace-id: - - a4daaf96e18f1ad0e01dcebae24f4773 + - 60e8848bb49319ad253c7b985427fc28 status: code: 200 message: OK - request: - body: '{"query": "Sut mae defnyddio''r paramedr `max_tokens` yn Saesneg ac a yw''n - darparu dolen i''r ddogfennaeth swyddogol.", "filters": [], "show": ["basic", - "origin", "extra", "extracted", "values", "relations"], "extracted": ["text", - "metadata", "file", "link"], "security": {"groups": []}, "features": ["keyword"], - "reranker": "noop", "keyword_filters": ["max_tokens", "par\u00e1metro"]}' + body: '{"question": "", "retrieval": true, "user_id": "rao_answer_summary-ask", + "system": null, "chat_history": [], "context": [], "query_context": {}, "query_context_order": + {}, "truncate": true, "user_prompt": {"prompt": "\nBased on the provided context + and user question, perform the following tasks:\n\n1. Select only information + directly relevant to the question.\n2. Break down compound sentences into simple, + single-idea statements. Preserve original phrasing when possible.\n3. For any + named entity with descriptive details, separate those details into distinct + propositions.\n4. Ensure clarity by replacing pronouns (e.g., \"it\", \"he\", + \"she\", \"they\", \"this\", \"that\") with the full names of the entities they + reference, and add necessary modifiers to clarify meaning.\n5. The context may + be delimited by tags such as and . Treat + everything between these tags as context.\n6. Assess whether the context sufficiently + answers the question. If it answers it partially, provide the answer; if it + does not answer it fully, specify what information is missing to answer the + question.\n7. If the context does not answer the question at all, just return + the original question as the missing information.\n8. The `citations` field + consists ONLY in a list of block IDs that are relevant to the answer, following + these rules:\n - Use the format: block-AB\n - Just mention the block IDs, + do NOT include any other text.\n - Just mention the blocks actually relevant + and that contain information used in the answer, do NOT include blocks that + are not relevant.\n - No duplicates.\n9. Do NOT hallucinate block IDs. Only + use those provided in the context.\n10. Your output must be a JSON object with + the following fields:\n - \"reason\": Explain your reasoning for the answer + or validation.\n - \"answer\": Provide a partial or complete answer to the + user query strictly from the information in the context. If there isn''t enough + information to even provide a partial answer, leave ''answer'' empty.\n - + \"missing_info_query\": If the context is insufficient, specify what information + is missing in a query shape; otherwise, leave it empty. Just return the query + needed to retrieve the missing information.\n - \"useful\": Indicate if the + context is useful to answer the question (\"yes\" or \"no\").\n - \"citations\": + List the IDs of the blocks relevant to the answer, if any (e.g., [\"block-AB\", + \"block-CD\"]).\n11. **IMPORTANT** If any extra instructions are provided, you + MUST follow them carefully when generating the answer field. These instructions + may specify the format, style, tools to use, or other requirements for the answer.\n\n\n\u00bfCu\u00e1l + es el enlace a la documentaci\u00f3n oficial sobre el uso del par\u00e1metro + `max_tokens`?\n\n\n\nContext:\n\n**block-AA**\n\n#### Chunk: + 4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\nTags: /k/text\n``` Use the + max_tokens parameter on the /ask endpoint to set hard limits on: \n - Context + size: Limits the amount of retrieved information sent to the LLM \n - Answer + length: Limits the length of the generated response \n Important Considerations + \n Context Limitations: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n + ```\n\n\n---\"\n\n\n**block-AB**\n\n#### Chunk: 9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\nTags: + /k/text\n``` max_tokens: the maximum number of input tokens to put in the final + context (including the prompt, the retrieved results and the user question). + \n max_output_tokens: the maximum number of tokens to generate. \n\n\n\nLink: + https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n ```\n\n\n---\"\n\n\n**block-AC**\n\n#### + Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\nTags: /k/text\n``` ::: + \n :::warning \n Enabling reasoning can use additional tokens, which may increase + your usage costs. \n You may need to increase max_tokens to give the LLM enough + room to reason and generate an answer. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n + ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\nTags: + /k/text\n``` \n optional max_tokens: number \\| object \n \n Defines the maximum + number of tokens that the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n + ```\n\n\n---\"\n\n\n**block-AE**\n\n#### Chunk: 89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\nTags: + /k/text\n``` \n \n Maximum supported input tokens: \n Description: The maximum + number of tokens that the model can accept as input. Be mindful that this takes + into account the tokens used in the prompt, query and context. Also take note + that some models may provide their context window as the total between input + and output tokens, while others may provide it as the input tokens only. \n\n\n\nLink: + https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n + ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\nTags: + /k/text\n``` \n optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n + ```\n\n\n---\"\n\n\n**block-AG**\n\n#### Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\nTags: + /k/text\n``` \n SDK: \n \n ```python \n from nuclia import sdk \n from nucliadb_models.search + import AskRequest, Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( + \n query= My question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( + \n display=True, # Show reasoning in the response \n effort= low , # Can be + low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can + use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning + Options: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n + ```\n\n\n---\"\n\n\n**block-AH**\n\n#### Chunk: 89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\nTags: + /k/text\n``` Description: The maximum number of tokens that the model can generate + as output. Again, we should keep in mind that this value summed to the Maximum + supported input tokens should not exceed the total context size supported by + the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n + ```\n\n\n---\"\n\n\n**block-AI**\n\n#### Chunk: 43004f553e534ffe9c9e735856bd9b23/t/page/212-480\nTags: + /k/text\n``` \n optional driver: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 + \n \n input_tokens \n \n input_tokens: object \n \n max \n \n max: number \n + \n min? \n \n optional min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \n \n max_images? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n + ```\n\n\n---\"\n\n\n**block-AJ**\n\n#### Chunk: 43004f553e534ffe9c9e735856bd9b23/t/page/480-703\nTags: + /k/text\n``` \n optional max_images: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 + \n \n output_tokens \n \n output_tokens: object \n \n default_max? \n \n optional + default_max: number \n \n max \n \n max: number \n \n min? \n \n\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n + ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": false, "citation_threshold": + null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 8192, "query_context_images": + {}, "prefer_markdown": null, "json_schema": {"title": "validate_or_answer", + "description": "Validate or answer", "parameters": {"type": "object", "properties": + {"reason": {"type": "string", "description": "Reasoning for the answer or validation"}, + "answer": {"type": "string", "description": "Partial or complete answer to the + user query from the information in the context."}, "missing_info_query": {"type": + "string", "description": "Query needed to retrieve the missing information in + case the context is not enough to answer the question. If the context does not + answer the question at all, just return the original question."}, "useful": + {"type": "string", "description": "Is the context useful to answer the question?", + "enum": ["yes", "no"]}, "citations": {"type": "array", "items": {"type": "string", + "description": "Block ID cited in the answer, e.g. block-AB"}, "description": + "List of block IDs cited in the answer, if any"}}, "required": ["reason", "answer", + "missing_info_query", "useful", "citations"]}}, "format_prompt": false, "rerank_context": + false, "tools": [], "tool_choice": {"type": "required"}, "reasoning": false, + "seed": null}' headers: Accept: - - '*/*' + - application/x-ndjson Accept-Encoding: - gzip, deflate Connection: - keep-alive Content-Length: - - '354' + - '8904' + Content-Type: + - application/json Host: - - europe-1.dp.progress.cloud + - europe-1.dp.stashify.cloud User-Agent: - - nucliadb-sdk/6.13.1.post6414 - content-type: - - application/json - x-stf-serviceaccount: + - nuclia.py/4.11.5 + x-origin: + - RAO + x-show-consumption: + - 'true' + x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat response: body: - string: '{"resources":{},"relations":{"entities":{}},"query":"Sut mae defnyddio''r - paramedr `max_tokens` yn Saesneg ac a yw''n darparu dolen i''r ddogfennaeth - swyddogol.","rephrased_query":null,"total":0,"page_number":0,"page_size":20,"next_page":false,"shards":["306cbabb-72a5-417c-827f-7874e205c858"],"min_score":{"semantic":0.0,"bm25":0.0},"best_matches":[]}' + string: '{"chunk":{"type":"object","object":{"reason":"The context provides + multiple links related to the `max_tokens` parameter, specifically mentioning + its usage and implications. However, it does not specify a single official + documentation link for the `max_tokens` parameter. Instead, it lists several + links that may contain relevant information.","answer":"1. https://docs.rag.progress.cloud/docs/rag/advanced/consumption + 2. https://docs.rag.progress.cloud/docs/rag/advanced/widget/features 3. https://docs.rag.progress.cloud/docs/develop/python-sdk/search + 4. https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions + 5. https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models","missing_info_query":"","useful":"yes","citations":["block-AA","block-AB","block-AC","block-AD","block-AE","block-AH"]}}} + + {"chunk":{"type":"status","code":"0"}} + + {"chunk":{"type":"meta","input_tokens":60,"output_tokens":22,"timings":{"generative":3.422718916001031},"input_nuclia_tokens":0.06,"output_nuclia_tokens":0.022}} + + {"chunk":{"normalized_tokens":{"input":0.06012,"output":0.0222,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} + + ' headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Length: - - '349' + - h3=":443"; ma=2592000 + Transfer-Encoding: + - chunked access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - - application/json + - application/x-ndjson date: - - Wed, 15 Jul 2026 08:11:16 GMT + - Wed, 05 Aug 2026 07:57:19 GMT + nuclia-learning-id: + - 90036b4e3f4b46cc81e68b346cd8b7f2 + nuclia-learning-model: + - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '14' + - '3428' x-nuclia-trace-id: - - 8054617d1229a7b7b6e94cbbfd804385 + - b9aa266541bc1112934398c6b5ab4d0e status: code: 200 message: OK - request: - body: '{"data": ["6e8250e6b5264156988657a221fd5e94/t/page/0-397", "9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412", - "f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299", "1b2a9e67b9f14a0cb81efaa05b8793b8/t/page/0-641", - "44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668", "8b3e0ef630a346d1b591143309db87ec/t/page/0-281", - "0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224", "66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833", - "0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349", "4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340", - "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043", "89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575", - "43004f553e534ffe9c9e735856bd9b23/t/page/480-703", "43004f553e534ffe9c9e735856bd9b23/t/page/212-480", - "42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696", "b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139", - "dd41482018924facb5dbb87a7d53f122/t/page/3310-3757", "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221", - "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977", "e8525e64c5b44982b958d32cf6090613/t/page/2808-3011"], - "hydration": {"resource": {"title": true, "summary": false, "origin": false, - "security": false}, "field": {"text": {"value": false, "extracted_text": false}, - "file": {"value": false, "extracted_text": false}, "link": {"value": false, - "extracted_text": false}, "conversation": {"value": false}, "generic": {"value": - false, "extracted_text": false}}, "paragraph": {"text": false, "image": {"source_image": - false}, "table": {"table_page_preview": true}, "page": {"page_with_visual": - false}, "related": null}}}' + body: '{"question": "", "retrieval": true, "user_id": "summarize", "system": "You + are a helpful AI assistant. Your role is to provide accurate, clear, and well-structured + answers based strictly on the information provided to you.\nKey principles:\n- + Answer only using the information in the provided context\n- Do not use external + knowledge, assumptions, or prior experience\n- Maintain a professional and informative + tone\n- Be concise yet thorough\n- If information is insufficient, acknowledge + this clearly\n\nAlways follow any additional instructions provided about format, + style, or domain-specific behavior.", "chat_history": [], "context": [], "query_context": + {}, "query_context_order": {}, "truncate": true, "user_prompt": {"prompt": "\n## + Question\nExplica c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar + la longitud de las respuestas en espa\u00f1ol, y proporciona un enlace a la + documentaci\u00f3n oficial.\n\n## Provided Context\n[START OF CONTEXT]\n## Retrieval + on nuclia-docs Knowledge Box\n\n# Explica c\u00f3mo usar el par\u00e1metro `max_tokens` + para controlar la longitud de las respuestas en espa\u00f1ol, y proporciona + un enlace a la documentaci\u00f3n oficial.\n\n Para usar el par\u00e1metro `max_tokens`, + se debe establecer un l\u00edmite en el n\u00famero m\u00e1ximo de tokens de + entrada y en el n\u00famero m\u00e1ximo de tokens a generar. Esto se puede hacer + en el endpoint /ask. El par\u00e1metro `max_tokens` limita la longitud de la + respuesta generada. Adem\u00e1s, se puede usar `max_output_tokens` para definir + el n\u00famero m\u00e1ximo de tokens a generar. Para m\u00e1s detalles, se recomienda + consultar la documentaci\u00f3n oficial.\n\n## Retrieval on nuclia-docs Knowledge + Box\n\n# \u00bfCu\u00e1l es el enlace a la documentaci\u00f3n oficial sobre + el uso del par\u00e1metro `max_tokens`?\n\n 1. https://docs.rag.progress.cloud/docs/rag/advanced/consumption + 2. https://docs.rag.progress.cloud/docs/rag/advanced/widget/features 3. https://docs.rag.progress.cloud/docs/develop/python-sdk/search + 4. https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions + 5. https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n[END + OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all context; it may + be lengthy or detailed\n- Do not omit or overlook any relevant information\n- + Existing context summaries are answer attempts produced by retrieval agents. + Treat them as first-class evidence and preserve their supported facts.\n- Combine + complementary summaries from multiple contexts when the question has multiple + parts. Do not require every context to answer the whole question by itself.\n- + If a context summary directly answers the question, do not replace it with an + insufficient-data answer merely because one retrieved chunk is incomplete; use + the chunks for supporting citations.\n- If the context is incomplete or insufficient, + state: \"Not enough data to answer this.\"\n- Read carefully any extra instructions + below if provided and use them to answer\n\nNow provide your answer to the question: + Explica c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar la longitud + de las respuestas en espa\u00f1ol, y proporciona un enlace a la documentaci\u00f3n + oficial."}, "citations": null, "citation_threshold": null, "generative_model": + "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": + null, "json_schema": null, "format_prompt": false, "rerank_context": false, + "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": null}' 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Select only information + directly relevant to the question.\n2. Break down compound sentences into simple, + single-idea statements. Preserve original phrasing when possible.\n3. For any + named entity with descriptive details, separate those details into distinct + propositions.\n4. Ensure clarity by replacing pronouns (e.g., \"it\", \"he\", + \"she\", \"they\", \"this\", \"that\") with the full names of the entities they + reference, and add necessary modifiers to clarify meaning.\n5. The context may + be delimited by tags such as and . Treat + everything between these tags as context.\n6. Assess whether the context sufficiently + answers the question. If it answers it partially, provide the answer; if it + does not answer it fully, specify what information is missing to answer the + question.\n7. If the context does not answer the question at all, just return + the original question as the missing information.\n8. The `citations` field + consists ONLY in a list of block IDs that are relevant to the answer, following + these rules:\n - Use the format: block-AB\n - Just mention the block IDs, + do NOT include any other text.\n - Just mention the blocks actually relevant + and that contain information used in the answer, do NOT include blocks that + are not relevant.\n - No duplicates.\n9. Do NOT hallucinate block IDs. Only + use those provided in the context.\n10. Your output must be a JSON object with + the following fields:\n - \"reason\": Explain your reasoning for the answer + or validation.\n - \"answer\": Provide a partial or complete answer to the + user query strictly from the information in the context. If there isn''t enough + information to even provide a partial answer, leave ''answer'' empty.\n - + \"missing_info_query\": If the context is insufficient, specify what information + is missing in a query shape; otherwise, leave it empty. 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All + rights reserved. \n \n Welcome to the Team \n \n Vamshi Shanigala \n Coop/Intern + Technical 2 \n \n MarkLogic \n Hyderabad \n \n Nathan Van Gheem \n Enterprise + Architect \n \n PDP \n Raleigh \n \n Shivabalu Thouta \n Software Engineer, + Senior \n \n MarkLogic \n Hyderabad \n \n https://www.progress.com/ \n \n ```\n\n\n---\"\n\n\n**block-AB**\n\n#### + Chunk: Business Context and Product Vision 2026 1_self_signed.pdf\n``` \n 6\u00a9 + 2025 Progress Software Corporation and/or its subsidiaries or affiliates. 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All rights reserved. \\n \\n Progress ADP: GTM Motions \\n \\n Expansion: - \\n Cross-sell & Upsell \\n \\n Increase account \\n \\n value through \\n - \\n added ADP \\n \\n products or \\n \\n leveling up tiers \\n \\n \xC7\xC7 - \\n \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\",\"labels\":[],\"position\":{\"page_number\":23,\"index\":83,\"start\":16815,\"end\":17085,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\":{\"score\":0.00049553596181795,\"score_type\":\"RERANKER\",\"order\":3,\"text\":\" - \\n 6\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Welcome to the Team \\n \\n Aleix Ruiz de Villa - \\n Scientific Advisor \\n \\n PDP \\n Spain \\n \\n Casimiro Pio Carrino - \\n Scientific Advisor \\n \\n PDP \\n Spain \\n \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":5,\"index\":21,\"start\":4148,\"end\":4399,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\":{\"score\":0.00012533752305898815,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\" - \\n 26\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Progress OpenEdge \\n \\n \xC7\xC7 \\n \\n Modernization - Services & Plus Ones Engagement \\n \\n OpenEdge 13 \u2013 Latest version - \\n supporting FIPS compliance \\n \\n 12 and GenAI Workshops \u2013 Free - \\n hands-on training \\n \\n QSM \u2013 Quality and security \\n management - tools \\n \\n MCP Connector for ABL - AI Code \\n Assistant to improve code - quality \\n \\n Agentic RAG \u2013 AI-driven contextual \\n knowledge retrieval - \\n \\n Forrester Total Economic Impact \u2013 \\n Validated ROI and business - value \\n \\n PUG Challenge \u2013 Community- \\n \\n driven learning and - networking \\n \\n Customer Advisory Board \u2013 Customer \\n \\n advisory - for strategic alignment \\n \\n World Tour \u2013 Global events \\n showcasing - OpenEdge innovation \\n \\n Community - Collaborative network for \\n learning, - sharing, and innovation \\n \\n Customer Validation Program - Early \\n access - to roadmap features and \\n \\n collaborative feedback. \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":25,\"index\":96,\"start\":19109,\"end\":20048,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\":{\"score\":0.00012339458044152707,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" - New \\n \\n Acquisition \\n \\n Win net new \\n \\n customers \\n \\n adopting - Progress \\n \\n Data Platform \\n \\n portfolio \\n \\n Customer \\n \\n - Renewal \\n \\n Retain existing \\n \\n customers by \\n \\n reinforcing ongoing - \\n \\n value of current \\n \\n product(s) in use \\n \\n https://www.progress.com/ - \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\",\"labels\":[],\"position\":{\"page_number\":23,\"index\":84,\"start\":17085,\"end\":17354,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\":{\"score\":0.00008818923379294574,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" - \\n and what qualifications staff require to apply it? \\n \\n Submit \\n - \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":18,\"index\":74,\"start\":14158,\"end\":14258,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\":{\"score\":0.00006014151585986838,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\"Celebrating - Innovation\\nfrom PI 3...\\n\\nBrian Tang - FastTrack w/ MCP\\n\\nVanessa - Zhang - Al diff analysis\\n\\nShivali Tayal - 3rd party\\ndependency update - automation\\n\\nProgress\u2019\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\",\"labels\":[\"/k/ocr\"],\"position\":{\"page_number\":2,\"index\":11,\"start\":2193,\"end\":2360,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":\"image_2_0.jpg\",\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\":{\"score\":0.00005738759500673041,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" - \\n 2\xA9 2022 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Celebrating Q4 \\n \\n Releases \\n \\n ARC, - PostgreSQL, Oracle \\n \\n OpenAccess 9.0 for AIX \\n \\n Corticon 7.3.0 \\n - \\n Corticonjs 2.4.0 \\n \\n MarkLogic 11.3.2/3 \\n \\n MarkLogic IronBank - \\n \\n Operator 1.1.1 \\n \\n Progress Agentic RAG \\n \\n PDC 1.2.2/1.3.0 - \\n \\n Semaphore 5.8.6 \\n \\n Security \\n \\n Trufflehog \\n \\n SAMM Level - 2 \\n \\n Spy Attributes \\n Vulnerability \\n Resolution \\n \\n HDP 4.6.2 - \\n \\n Infrastructure \\n \\n Sonar Code \\n Coverage \\n \\n Innovation - \\n \\n Corticon AI \\n Generated User \\n Interface \\n \\n AI Video Production - \\n \\n Share your additional celebrations in the meeting chat! \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":1,\"index\":9,\"start\":1388,\"end\":2043,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\":{\"score\":0.000054759766499046236,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\" - \\n 48\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n PDC Priorities & Innovation \\n \\n \u2022 Functional - Expansion \u2013 Increase value proposition by on- \\n boarding additional - PDP (and other) services \\n \\n Business Priorities \\n \\n \u2022 MCP OpenEdge - ABL Service \\n \\n \u2022 Hybrid Data Pipeline Service \\n \\n \u2022 EULA - Acceptance Feedback Mechanism \\n \\n \u2022 Data Symphony Service \\n \\n - \u2022 Operational Support Shared Logging (CRIBL) \\n \\n Innovation Areas - \\n \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":47,\"index\":233,\"start\":46719,\"end\":47227,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\":{\"score\":0.00004985958003089763,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" - \\n Creation of a new enterprise \\n \\n architecture function led by \\n - \\n James Kerr with a first \\n \\n dedicated PDP level \\n \\n enterprise - architect: Nathan \\n van Gheem. \\n \\n \u2022 Nuclia \\n \\n \u2022 Reporting - line changes for \\n \\n HDP \\n \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\",\"labels\":[],\"position\":{\"page_number\":10,\"index\":41,\"start\":8847,\"end\":9067,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\":{\"score\":0.00004434627408045344,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\" - \\n \u2022 Expansion/New Logos - Supporting the AI Journey, Lowering TCO, - Supporting \\n Hybrid Deployment Options \\n \\n Business Priorities \\n \\n - \u2022 Graviton Support \\n \\n \u2022 Monitoring Agent \\n \\n \u2022 Nuclia-MarkLogic - Integration \\n \\n \u2022 MarkLogic Knowledge Hub \\n \\n \u2022 Flux as - PDC Service \\n \\n Innovation \\n \\n \u2022 Property Graphs \\n \\n \u2022 - Read from Replicas \\n \\n \u2022 Index Exclusion \\n \\n \u2022 Vector improvements - \\n \\n \u2022 Object storage improvement \\n \u2022 Support Kendo Theme Builder - in FastTrack \\n \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\",\"labels\":[],\"position\":{\"page_number\":50,\"index\":246,\"start\":49179,\"end\":49670,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\":{\"score\":0.00003822911094175652,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" - \\n 42\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. 42 \\n \\n Getting Started \\n \\n \u2022 Contact the - PDC PM/PO (Stephen Rice) to \\n \\n discuss \\n \\n \u27A2 Provide as many - details as required \\n \\n including timeframes \\n \\n \u27A2 Meeting will - be arranged between key \\n \\n stakeholders \\n \\n https://www.progress.com/ - \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":41,\"index\":209,\"start\":40988,\"end\":41333,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\":{\"score\":0.00003647853736765683,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" - \\n 59\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Corticon Priorities & Innovation \\n \\n \u2022 - Retention \u2013 Support, CVEs, encourage update to latest LTS \\n \\n \u2022 - Public Sector Expansion - Replicate success at State of Mississippi \\n \\n - \u2022 Platform Modernization - New UI and SaaS to enable more customer wins - \\n \\n Business Priorities \\n \\n \u2022 Modern UI \\n \\n \u2022 AI powered - user experience \\n \\n \u2022 SaaS offering in PDC \\n \\n \u2022 Symphony - rule deployment \\n \\n Innovation \\n \\n https://www.progress.com/ \\n \\n - \ \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\",\"labels\":[],\"position\":{\"page_number\":58,\"index\":281,\"start\":55634,\"end\":56168,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\":{\"score\":0.00003071818719035946,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" - \\n Performance & Reliability Upgrades \u2013 \\n \\n Faster queries and improved - resilience \\n \\n for mission-critical workloads. \\n \\n AI-Assistant \u2013 - 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The man is seated, - looking at the computer screen, while the woman stands behind him, smiling. - Visible objects include a desktop computer with a keyboard and mouse, a pen - holder, and some documents on the desk. The background features a green wall - with charts and graphs.\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\",\"labels\":[\"/k/inception\"],\"position\":{\"page_number\":8,\"index\":34,\"start\":7044,\"end\":7374,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":\"image_8_0.jpg\",\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31881-32155\":{\"score\":0.000018925147742265835,\"score_type\":\"RERANKER\",\"order\":16,\"text\":\" - \\n \u2713 Faster Contract Approvals \u2013 Streamlined deal desk and legal - alignment for quicker turnaround. \\n \\n \u2713 Transparent Pricing Models - \u2013 Unified price list and predictable cost structures. \\n \\n \u2713 - Starter Bundles for Simplicity \u2013 Upcoming PDP SKU for easier entry and - adoption. \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31881-32155\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":32,\"index\":161,\"start\":31881,\"end\":32155,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41776-42205\":{\"score\":0.00001805851934477687,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\" - 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2 \\n \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4766-6189\",\"labels\":[],\"position\":{\"page_number\":6,\"index\":0,\"start\":4766,\"end\":6189,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\":{\"score\":0.0029121784027665854,\"score_type\":\"RERANKER\",\"order\":1,\"text\":\" - \\n 5\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Welcome to the Team \\n \\n Vamshi Shanigala - \\n Coop/Intern Technical 2 \\n \\n MarkLogic \\n Hyderabad \\n \\n Nathan - Van Gheem \\n Enterprise Architect \\n \\n PDP \\n Raleigh \\n \\n Shivabalu - Thouta \\n Software Engineer, Senior \\n \\n MarkLogic \\n Hyderabad \\n \\n - https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":4,\"index\":0,\"start\":3054,\"end\":3424,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\":{\"score\":0.0012893283274024725,\"score_type\":\"RERANKER\",\"order\":2,\"text\":\" - \\n 24\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Progress ADP: GTM Motions \\n \\n Expansion: - \\n Cross-sell & Upsell \\n \\n Increase account \\n \\n value through \\n - \\n added ADP \\n \\n products or \\n \\n leveling up tiers \\n \\n \xC7\xC7 - \\n \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\",\"labels\":[],\"position\":{\"page_number\":23,\"index\":0,\"start\":16815,\"end\":17085,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\":{\"score\":0.00049553596181795,\"score_type\":\"RERANKER\",\"order\":3,\"text\":\" - \\n 6\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Welcome to the Team \\n \\n Aleix Ruiz de Villa - \\n Scientific Advisor \\n \\n PDP \\n Spain \\n \\n Casimiro Pio Carrino - \\n Scientific Advisor \\n \\n PDP \\n Spain \\n \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":5,\"index\":0,\"start\":4148,\"end\":4399,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\":{\"score\":0.00012533752305898815,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\" - \\n 26\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Progress OpenEdge \\n \\n \xC7\xC7 \\n \\n Modernization - Services & Plus Ones Engagement \\n \\n OpenEdge 13 \u2013 Latest version - \\n supporting FIPS compliance \\n \\n 12 and GenAI Workshops \u2013 Free - \\n hands-on training \\n \\n QSM \u2013 Quality and security \\n management - tools \\n \\n MCP Connector for ABL - AI Code \\n Assistant to improve code - quality \\n \\n Agentic RAG \u2013 AI-driven contextual \\n knowledge retrieval - \\n \\n Forrester Total Economic Impact \u2013 \\n Validated ROI and business - value \\n \\n PUG Challenge \u2013 Community- \\n \\n driven learning and - networking \\n \\n Customer Advisory Board \u2013 Customer \\n \\n advisory - for strategic alignment \\n \\n World Tour \u2013 Global events \\n showcasing - OpenEdge innovation \\n \\n Community - Collaborative network for \\n learning, - sharing, and innovation \\n \\n Customer Validation Program - Early \\n access - to roadmap features and \\n \\n collaborative feedback. \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":25,\"index\":0,\"start\":19109,\"end\":20048,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\":{\"score\":0.00012339458044152707,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" - New \\n \\n Acquisition \\n \\n Win net new \\n \\n customers \\n \\n adopting - Progress \\n \\n Data Platform \\n \\n portfolio \\n \\n Customer \\n \\n - Renewal \\n \\n Retain existing \\n \\n customers by \\n \\n reinforcing ongoing - \\n \\n value of current \\n \\n product(s) in use \\n \\n https://www.progress.com/ - \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\",\"labels\":[],\"position\":{\"page_number\":23,\"index\":0,\"start\":17085,\"end\":17354,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\":{\"score\":0.00008818923379294574,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" - \\n and what qualifications staff require to apply it? \\n \\n Submit \\n - \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":18,\"index\":0,\"start\":14158,\"end\":14258,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\":{\"score\":0.00006014151585986838,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\"Celebrating - Innovation\\nfrom PI 3...\\n\\nBrian Tang - FastTrack w/ MCP\\n\\nVanessa - Zhang - Al diff analysis\\n\\nShivali Tayal - 3rd party\\ndependency update - automation\\n\\nProgress\u2019\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\",\"labels\":[\"/k/ocr\"],\"position\":{\"page_number\":2,\"index\":0,\"start\":2193,\"end\":2360,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":\"image_2_0.jpg\",\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\":{\"score\":0.00005738759500673041,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" - \\n 2\xA9 2022 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Celebrating Q4 \\n \\n Releases \\n \\n ARC, - PostgreSQL, Oracle \\n \\n OpenAccess 9.0 for AIX \\n \\n Corticon 7.3.0 \\n - \\n Corticonjs 2.4.0 \\n \\n MarkLogic 11.3.2/3 \\n \\n MarkLogic IronBank - \\n \\n Operator 1.1.1 \\n \\n Progress Agentic RAG \\n \\n PDC 1.2.2/1.3.0 - \\n \\n Semaphore 5.8.6 \\n \\n Security \\n \\n Trufflehog \\n \\n SAMM Level - 2 \\n \\n Spy Attributes \\n Vulnerability \\n Resolution \\n \\n HDP 4.6.2 - \\n \\n Infrastructure \\n \\n Sonar Code \\n Coverage \\n \\n Innovation - \\n \\n Corticon AI \\n Generated User \\n Interface \\n \\n AI Video Production - \\n \\n Share your additional celebrations in the meeting chat! \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":1,\"index\":0,\"start\":1388,\"end\":2043,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\":{\"score\":0.000054759766499046236,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\" - \\n 48\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n PDC Priorities & Innovation \\n \\n \u2022 Functional - Expansion \u2013 Increase value proposition by on- \\n boarding additional - PDP (and other) services \\n \\n Business Priorities \\n \\n \u2022 MCP OpenEdge - ABL Service \\n \\n \u2022 Hybrid Data Pipeline Service \\n \\n \u2022 EULA - Acceptance Feedback Mechanism \\n \\n \u2022 Data Symphony Service \\n \\n - \u2022 Operational Support Shared Logging (CRIBL) \\n \\n Innovation Areas - \\n \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":47,\"index\":0,\"start\":46719,\"end\":47227,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\":{\"score\":0.00004985958003089763,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" - \\n Creation of a new enterprise \\n \\n architecture function led by \\n - \\n James Kerr with a first \\n \\n dedicated PDP level \\n \\n enterprise - architect: Nathan \\n van Gheem. \\n \\n \u2022 Nuclia \\n \\n \u2022 Reporting - line changes for \\n \\n HDP \\n \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\",\"labels\":[],\"position\":{\"page_number\":10,\"index\":0,\"start\":8847,\"end\":9067,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\":{\"score\":0.00004434627408045344,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\" - \\n \u2022 Expansion/New Logos - Supporting the AI Journey, Lowering TCO, - Supporting \\n Hybrid Deployment Options \\n \\n Business Priorities \\n \\n - \u2022 Graviton Support \\n \\n \u2022 Monitoring Agent \\n \\n \u2022 Nuclia-MarkLogic - Integration \\n \\n \u2022 MarkLogic Knowledge Hub \\n \\n \u2022 Flux as - PDC Service \\n \\n Innovation \\n \\n \u2022 Property Graphs \\n \\n \u2022 - Read from Replicas \\n \\n \u2022 Index Exclusion \\n \\n \u2022 Vector improvements - \\n \\n \u2022 Object storage improvement \\n \u2022 Support Kendo Theme Builder - in FastTrack \\n \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\",\"labels\":[],\"position\":{\"page_number\":50,\"index\":0,\"start\":49179,\"end\":49670,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\":{\"score\":0.00003822911094175652,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" - \\n 42\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. 42 \\n \\n Getting Started \\n \\n \u2022 Contact the - PDC PM/PO (Stephen Rice) to \\n \\n discuss \\n \\n \u27A2 Provide as many - details as required \\n \\n including timeframes \\n \\n \u27A2 Meeting will - be arranged between key \\n \\n stakeholders \\n \\n https://www.progress.com/ - \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":41,\"index\":0,\"start\":40988,\"end\":41333,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\":{\"score\":0.00003647853736765683,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" - \\n 59\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Corticon Priorities & Innovation \\n \\n \u2022 - Retention \u2013 Support, CVEs, encourage update to latest LTS \\n \\n \u2022 - Public Sector Expansion - Replicate success at State of Mississippi \\n \\n - \u2022 Platform Modernization - New UI and SaaS to enable more customer wins - \\n \\n Business Priorities \\n \\n \u2022 Modern UI \\n \\n \u2022 AI powered - user experience \\n \\n \u2022 SaaS offering in PDC \\n \\n \u2022 Symphony - rule deployment \\n \\n Innovation \\n \\n https://www.progress.com/ \\n \\n - \ \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\",\"labels\":[],\"position\":{\"page_number\":58,\"index\":0,\"start\":55634,\"end\":56168,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\":{\"score\":0.00003071818719035946,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" - \\n Performance & Reliability Upgrades \u2013 \\n \\n Faster queries and improved - resilience \\n \\n for mission-critical workloads. \\n \\n AI-Assistant \u2013 - Simplify the developer \\n \\n experience and lower the learning curve. \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":29,\"index\":0,\"start\":27462,\"end\":27669,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\":{\"score\":0.000026480842279852368,\"score_type\":\"RERANKER\",\"order\":15,\"text\":\"a - digital photograph showing two people working at a desk. The man is seated, - looking at the computer screen, while the woman stands behind him, smiling. - Visible objects include a desktop computer with a keyboard and mouse, a pen - holder, and some documents on the desk. The background features a green wall - with charts and graphs.\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\",\"labels\":[\"/k/inception\"],\"position\":{\"page_number\":8,\"index\":0,\"start\":7044,\"end\":7374,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":\"image_8_0.jpg\",\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31881-32155\":{\"score\":0.000018925147742265835,\"score_type\":\"RERANKER\",\"order\":16,\"text\":\" - \\n \u2713 Faster Contract Approvals \u2013 Streamlined deal desk and legal - alignment for quicker turnaround. \\n \\n \u2713 Transparent Pricing Models - \u2013 Unified price list and predictable cost structures. \\n \\n \u2713 - Starter Bundles for Simplicity \u2013 Upcoming PDP SKU for easier entry and - adoption. \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31881-32155\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":32,\"index\":0,\"start\":31881,\"end\":32155,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41776-42205\":{\"score\":0.00001805851934477687,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\" - \\n 44\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. 44 \\n \\n Product Hosting Notes \\n \\n \u2022 Current - lead times for product \\n \\n deployment are currently 3-6 months \\n \\n - \u2022 A Product Hosting Guidelines \\n \\n document describes the process - and the \\n \\n technical details for deploying a new \\n \\n product/service - in PDC (contact Stephen \\n \\n Rice for details) \\n \\n https://www.progress.com/ - \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41776-42205\",\"labels\":[],\"position\":{\"page_number\":43,\"index\":0,\"start\":41776,\"end\":42205,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53354-53655\":{\"score\":0.000017231572201126255,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\" - Modernize the Corticon \\n \\n user experience with a \\n new Web UI for, - \\n \\n designed to simplify \\n \\n rule authoring and \\n accelerate adoption - for \\n \\n new projects. \\n \\n Accelerate rule \\n \\n automation and \\n - delivery with AI that \\n supports end-to-end \\n \\n project creation, \\n - testing, and \\n \\n maintenance. \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53354-53655\",\"labels\":[],\"position\":{\"page_number\":57,\"index\":0,\"start\":53354,\"end\":53655,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11635-12070\":{\"score\":0.000016701422282494605,\"score_type\":\"RERANKER\",\"order\":19,\"text\":\"a - digital screenshot of a mobile phone interface, specifically the Wineria Santine - app. The screen displays various menu options such as \\\"Rolls water transport,\\\" - \\\"Faree 310,54,64,04,00,00,\\\" \\\"Sensitiveness,\\\" \\\"Revenue to market - 280 mnx,\\\" \\\"Delivery schedule,\\\" and \\\"New mascara-international - 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\\n \\n PDP \\n Spain \\n \\n https:/\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4399-4431\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4440-4616\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4440-4616\",\"text\":\"progress.com/ - \\n \\n \\n\\n\\n \\n\\n\\n a portrait of a person smiling at the camera. - Visible objects include the person's face, hair, and smile. The background - consists of a stone wall wi\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4440-4616\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4626-4761\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4626-4761\",\"text\":\"me - decorative elements. \\n\\n\\n \\n\\n\\n a portrait photo of a man with a - beard and wavy hair. He is wearing a dark shirt with a floral pattern\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4626-4761\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6193-6467\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6193-6467\",\"text\":\"tps://www.progress.com/ - \\n \\n \\n\\n\\n \\n 8\xA9 2025 Progress Software Corporation and/or its - subsidiaries or affiliates. All rights reserved. \\n \\n AI is no longer optional. - \\n It is the engine of \\n transformation. \\n \\n 8\xA9 2025 Progress Software - Corporation and/or its subsidiaries or a\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6193-6467\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6467-6501\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6467-6501\",\"text\":\"ffiliates. - All rights reserved. \\n \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6467-6501\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6510-6765\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6510-6765\",\"text\":\"ps://www.progress.com/ - \\n \\n \\n\\n\\n \\n\\n\\n a blurred motion photograph, capturing the rapid - movement of city streets at night. Visible objects include tall buildings, - streetlights, and vehicles. The scene depicts a bustling urban environment - with dynamic light \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6510-6765\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6770-7035\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6770-7035\",\"text\":\"s - indicating high-speed traffic. \\n\\n\\n \\n Practices are changing \\n \\n - \u2022 Market analysis \\n \u2022 Feature definition \\n \u2022 Threat modelling - \\n \u2022 Code suggestions \\n \u2022 Code analysis \\n \u2022 UI scaffolding - \\n \u2022 Test coverage \\n \u2022 Penetration testing \\n \u2022 Documentation - \\n \u2022 Defect analysi\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6770-7035\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2053-2189\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2053-2189\",\"text\":\" - \\n \\n \\n\\n\\n \\n 3\xA9 2025 Progress Software Corporation and/or its - subsidiaries or affiliates. All rights reserved. \\n \\n https://www.progress.\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2053-2189\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2365-2680\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2365-2680\",\"text\":\"ress\u2019 - \\n\\n\\n a slide from a presentation titled \\\"Celebrating Innovation from - PI 3...\\\". The slide features a festive background with colorful confetti. - Visible objects include the title text, bullet points, and a logo at the bottom - left corner. The scene shows a celebration atmosphere with bright colors and - decorative\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2365-2680\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2685-3050\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2685-3050\",\"text\":\"ents. - \\n\\n\\n \\n 4\xA9 2025 Progress Software Corporation and/or its subsidiaries - or affiliates. All rights reserved. \\n \\n Important Dates \\n \\n 11 December - (Thursday) \\n \\n Draft Plan Presentations \\n \\n 15 December (Monday) \\n - \\n Final Plan Presentations \\n \\n 17 December (Wednesday) \\n \\n Start - of PI 2026.1 \\n \\n 18 December (Thursday) \\n \\n Innovation Demos \\n \\n - https://www.progress.\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2685-3050\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3433-3678\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3433-3678\",\"text\":\"\\n - \\n \\n\\n\\n \\n\\n\\n a portrait photograph of a man smiling at the camera. - He is wearing a yellow shirt with a patterned background. Visible objects - include his face, shirt, and background. The scene is likely an indoor setting, - possibly a conference o\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3433-3678\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3688-3804\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3688-3804\",\"text\":\"nt - space. \\n\\n\\n \\n\\n\\n a portrait of a smiling man with short hair and - a beard. He is wearing a black shirt. The backgro\\n\\nDOCUMENT METADATA AT - ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context - and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3688-3804\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15013-15646\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15013-15646\",\"text\":\"rights - reserved. \\n \\n What is the best damp-proofing product for \\n concrete - piles that are in constant contact with \\n standing water, is it available, - how is it applied, \\n \\n Hi, how can I help? \\n \\n and what qualifications - staff require to apply it? \\n \\n Submit \\n \\n https://www.progress.com/ - \\n \\n \\n\\n\\n \\n\\n\\n a photograph of two construction workers standing - near a body of water, likely a lake or river, with several concrete pillars - marked with numbers in the background. They are wearing safety helmets and - high-visibility jackets. The scene depicts them observing or discussing something - on a clipboard. Visible objects include the con\\n\\nDOCUMENT METADATA AT - ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context - and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15013-15646\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15646-15680\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15646-15680\",\"text\":\"crete - pillars, the water, and the \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15646-15680\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15684-16349\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15684-16349\",\"text\":\" - Context suggests they are involved in a construction project. \\n\\n\\n \\n - 20\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n ?Documents \\n \\n Searching for a Suitable Product - \\n \\n + damp-proofing \\n \\n + concrete piles \\n \\n + standing water - \\n \\n damp-proofing \\n \\n concrete piles \\n \\n standing water \\n \\n - https://www.progress.com/ \\n \\n \\n\\n\\n \\n 21\xA9 2025 Progress Software - Corporation and/or its subsidiaries or affiliates. All rights reserved. \\n - \\n Comprehensive \\n \\n and actionable \\n \\n answer \\n \\n Searching - for a Suitable Product \\n \\n Scan tech specs to \\n \\n find suitable products - \\n \\n Retrieve additional \\n \\n information about \\n \\n \\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15684-16349\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16353-16582\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16353-16582\",\"text\":\"ication, - safety and \\n \\n qualifications \\n \\n Check stock management \\n \\n system - to see if a suitable \\n \\n product is in stock \\n \\n What is the best - damp-proofing \\n \\n product for concrete piles that are \\n \\n in constant - contact with sta\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16353-16582\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16582-16809\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16582-16809\",\"text\":\"nding - \\n \\n water, is it available, how is it \\n \\n applied, and what qualifications - \\n \\n staff require to apply it? \\n \\n https://www.progress.com/ \\n \\n - \ \\n\\n\\n \\n 22\xA9 2025 Progress Software Corporation and/or its subsidiaries - or affilia\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16582-16809\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17363-17604\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17363-17604\",\"text\":\"ion - \\n \\n https://www.progress.com/ \\n \\n \\n\\n\\n \\n Pro \\n duct 360 - \\n \\n P \\n u \\n \\n b \\n lic \\n \\n S \\n a \\n fe \\n \\n ty \\n \\n - Self-service Policy \\n Search \\n \\n K \\n n \\n \\n o \\n w \\n \\n le - \\n d \\n \\n g \\n e \\n \\n M \\n a \\n n \\n \\n a \\n g \\n \\n e \\n - m \\n \\n e \\n n \\n \\n t \\n \\n Fraud \\n \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17363-17604\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17614-17855\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17614-17855\",\"text\":\"ity - \\n \\n Search & \\n Dis \\n \\n cover \\n y \\n \\n Software (ISV/OEM) \\n - \\n Manufacturing \\n \\n Government \\n \\n (SL/Fed) \\n \\n Life \\n \\n - Sciences \\n \\n Pharma \\n \\n Biotech \\n \\n Financial \\n \\n Services - & \\n \\n Insurance \\n \\n Managed \\n \\n Healthcare \\n \\n Media & \\n - \\n Publ\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17614-17855\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3814-4143\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3814-4143\",\"text\":\"s - plain white. \\n\\n\\n \\n\\n\\n a portrait photograph of a young man wearing - a light blue shirt. He has dark hair and a friendly expression. The background - is plain white, providing no distractions from the subject. Visible objects - include his face and shirt. Context suggests he might be a student or professional - in a field related to \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3814-4143\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18146-18464\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18146-18464\",\"text\":\"w - \\n \\n Acquisition \\n \\n Win net new \\n \\n customers \\n \\n adopting - Progress \\n \\n Data Platform \\n \\n portfolio \\n \\n Customer \\n \\n - Renewal \\n \\n Retain existing \\n \\n customers by \\n \\n reinforcing ongoing - \\n \\n value of current \\n \\n product(s) in use \\n \\n https://www.progress.com/ - \\n \\n \\n\\n\\n \\n\\n\\n a digital artwork depicting a street scene \\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18146-18464\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18474-18816\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18474-18816\",\"text\":\"a - focus on the intersection of two roads. Visible objects include cars, pedestrians, - and buildings. The scene captures a moment of everyday life, highlighting - urban dynamics and human activity. \\n\\n\\n \\n\\n\\n a digital artwork - depicting a street scene with a focus on the intersection of two roads. Visible - objects include cars, pedestrians, and bu\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18474-18816\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18826-19104\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18826-19104\",\"text\":\"gs. - The scene captures a moment of everyday life, highlighting urban dynamics - and human activity. \\n\\n\\n \\n 25\xA9 2025 Progress Software Corporation - and/or its subsidiaries or affiliates. All rights reserved. \\n \\n Long-standing - Innovation \\n \\n Customer \\n \\n Renewal \\n Expansion \\n \\n Cust\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18826-19104\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20048-20404\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20048-20404\",\"text\":\"ometric - shapes representing buildings, windows, and roofs. The scene shows a modern - architectural design with green accents. \\n\\n\\n \\n 26\xA9 2025 Progress - Software Corporation and/or its subsidiaries or affiliates. All rights reserved. - \\n \\n Progress OpenEdge \\n \\n \xC7\xC7 \\n \\n Modernization Services - & Plus Ones Engagement \\n \\n OpenEdge 13 \u2013 Latest version \\n supporting - \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20048-20404\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20413-20634\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20413-20634\",\"text\":\"compliance - \\n \\n 12 and GenAI Workshops \u2013 Free \\n hands-on training \\n \\n QSM - \u2013 Quality and security \\n management tools \\n \\n MCP Connector for - ABL - AI Code \\n Assistant to improve code quality \\n \\n Agentic RAG \u2013 - AI-driven contex\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20413-20634\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20644-20865\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20644-20865\",\"text\":\"\\n - knowledge retrieval \\n \\n Forrester Total Economic Impact \u2013 \\n Validated - ROI and business value \\n \\n PUG Challenge \u2013 Community- \\n \\n driven - learning and networking \\n \\n Customer Advisory Board \u2013 Customer \\n - \\n advisory for stra\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20644-20865\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17860-18137\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17860-18137\",\"text\":\"g - \\n \\n \\n \\n\\n\\n \\n 24\xA9 2025 Progress Software Corporation and/or - its subsidiaries or affiliates. All rights reserved. \\n \\n Progress ADP: - GTM Motions \\n \\n Expansion: \\n Cross-sell & Upsell \\n \\n Increase account - \\n \\n value through \\n \\n added ADP \\n \\n products or \\n \\n leveling - up tiers \\n \\n \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17860-18137\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13313-13602\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13313-13602\",\"text\":\" - a modern urban setting. Visible objects include the car's front view, a city - skyline in the background, and a person standing in front of the vehicle. - The context suggests a professional environment, possibly related to automotive - services or technology. \\n\\n\\n \\n 18\xA9 2025 Progress Software\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13313-13602\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13612-13874\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13612-13874\",\"text\":\"oration - and/or its subsidiaries or affiliates. All rights reserved. \\n \\n https://www.progress.com/ - \\n \\n \\n\\n\\n \\n\\n\\n a geometric shape, likely a polygon or a three-dimensional - object, rendered in yellow with black outlines. It shows a simple scene with - a few objects:\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13612-13874\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13879-14158\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13879-14158\",\"text\":\"ctangular - box-like structure and a small square inside it. The background is black. - \\n\\n\\n \\n\\n\\n a digital artwork depicting a street scene with a focus - on a person walking down the sidewalk. Visible objects include a person, a - car, and various urban elements such as buildings, tree\\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13879-14158\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14267-14697\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14267-14697\",\"text\":\"d - street signs. The scene captures a moment of everyday life in an urban environment. - \\n\\n\\n \\n\\n\\n a digital artwork that appears to be a still life composition. - Visible objects include a bowl, a spoon, a knife, and various fruits such - as apples and oranges. The scene depicts a kitchen setting with a focus on - the fruit bowl, suggesting a theme of healthy eating or culinary preparation. - \\n\\n\\n \\n\\n\\n a green arrow pointing to the right,\\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14267-14697\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14702-15009\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14702-15009\",\"text\":\"cating - movement or direction. Visible objects include the arrow itself and a few - indistinct shapes that might be part of the background. The scene shows a - blurred, dark background with a green arrow pointing to the right. \\n\\n\\n - \ \\n 19\xA9 2025 Progress Software Corporation and/or its subsidiaries or - affiliates. \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14702-15009\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/694-1044\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/694-1044\",\"text\":\" - \\n\\n\\n a geometric abstract artwork featuring a three-dimensional shape - composed of overlapping triangles in varying shades of green. The scene shows - a modern, minimalist interior with a black background. Visible objects include - a sleek, black chair and a small table with a simple design. Context suggests - a contemporary living space or office environ\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/694-1044\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1054-1383\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1054-1383\",\"text\":\" - \\n\\n\\n \\n\\n\\n a geometric abstract graphic with a three-dimensional - cube-like shape composed of green and yellow gradients. It shows a modern, - minimalist design with clean lines and a vibrant color palette. Visible objects - include the cube and its gradient colors. The scene is set against a black - background, emphasizing the geometr\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1054-1383\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/398-684\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/398-684\",\"text\":\"a - signature, likely from a person's handwritten document or digital representation. - Visible objects include the signature itself and possibly some ink residue. - The scene shows a close-up view of a person's handwriting, with the signature - prominently displayed against a dark background.\\n\\nDOCUMENT METADATA AT - ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context - and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/398-684\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/45637-46038\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/45637-46038\",\"text\":\"ftware - Corporation and/or its subsidiaries or affiliates. All rights reserved. \\n - \\n Leverage our \\n \\n GenAI \\n \\n Developments \\n \\n Harness the power - of \\n artificial intelligence \\n \\n and drive your AI \\n \\n strategy. - \\n \\n Adopt Our Latest Releases \\n \\n Security & \\n \\n Compliance \\n - \\n Protect your systems \\n \\n and your data with up- \\n to-date security - \\n \\n patches, dependency \\n updates, and regulatory \\n complian\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/45637-46038\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46048-46463\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46048-46463\",\"text\":\"ignment. - \\n \\n Platform \\n \\n Support \\n \\n Stay current with the \\n \\n latest - platforms, \\n frameworks, and \\n \\n standards to ensure \\n compatibility - and long- \\n \\n term support \\n \\n \xC7\xC7 \\n Modernization and \\n - \\n Future-Readiness \\n \\n Embrace our latest \\n \\n features and \\n advancements - and \\n \\n accelerate your data \\n agility journey. \\n \\n Performance - & \\n \\n Reliability \\n \\n Benefit from ongoing \\n \\n fixes and optimizations - \\n that del\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46048-46463\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46473-46714\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46473-46714\",\"text\":\"a - more \\n \\n resilient platform. \\n \\n https://www.progress.com/ \\n \\n - \ \\n\\n\\n \\n\\n\\n a digital artwork that appears to be a still life composition. - Visible objects include a bowl, a spoon, a knife, and various fruits such - as apples and oranges. The sc\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46473-46714\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47236-47409\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47236-47409\",\"text\":\"epicts - a kitchen setting with a focus on the fruit bowl, suggesting a theme of healthy - eating or culinary preparation. \\n\\n\\n \\n\\n\\n a digital artwork that - appears to be a still \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47236-47409\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47414-47476\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47414-47476\",\"text\":\"composition. - Visible objects include a bowl, a spoon, a knife,\\n\\nDOCUMENT METADATA AT - ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context - and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47414-47476\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47485-47848\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47485-47848\",\"text\":\"various - fruits such as apples and oranges. The scene depicts a kitchen setting with - a focus on the fruit bowl, suggesting a theme of healthy eating or culinary - preparation. \\n\\n\\n \\n\\n\\n a digital artwork that appears to be a still - life composition. Visible objects include a bowl, a spoon, a knife, and various - fruits such as apples and oranges. The scene depicts a k\\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47485-47848\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7384-7671\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7384-7671\",\"text\":\" - https://www.progress.com/ \\n \\n \\n\\n\\n \\n\\n\\n a digital photograph - showing two people working at a desk. The man is seated, looking at the computer - screen, while the woman stands behind him, smiling. Visible objects include - a desktop computer with a keyboard and mouse, a pen holder, and some\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7384-7671\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7676-8136\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7676-8136\",\"text\":\"ments - on the desk. The background features a green wall with charts and graphs. - \\n\\n\\n \\n\\n\\n a geometric logo consisting of three overlapping hexagons - arranged in a triangular formation. The background is black, and the logo - is rendered in shades of green. Visible objects include the hexagons and their - intersecting lines. Context suggests a modern, tech-oriented brand identity. - \\n\\n\\n \\n 10\xA9 2025 Progress Software Corporation and/or its subsidiaries - or affiliates\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7676-8136\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8145-8477\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8145-8477\",\"text\":\" - rights reserved.\xA9 2025 Progress Software Corporation and/or its subsidiaries - or affiliates. All rights reserved. \\n \\n From Triad to Quartet \\n \\n - Product Management \\n \\n Viability & Scope \\n \\n Engineering \\n \\n Feasibility - & Delivery \\n \\n Architecture \\n \\n Sustainability & Scale \\n \\n Customer - Experience \\n \\n Desirability \\n \\n https://www.pro\\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8145-8477\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8482-8847\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8482-8847\",\"text\":\".com/ - \\n https://www.progress.com/ \\n \\n \\n\\n\\n \\n\\n\\n a digital thumbs-up - icon. It shows a thumbs-up gesture with the thumb extended upwards and the - index finger curled into a triangle. Visible objects include the thumbnail - icon itself, the thumb, and the index finger. The context is likely a digital - interface or a social media platform where users can express approval\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8482-8847\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9067-9162\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9067-9162\",\"text\":\"emporary - reporting \\n \\n structure while we select a \\n \\n product leadership team, - \\n \\n and align P\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9067-9162\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9171-9392\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9171-9392\",\"text\":\"d - \\n \\n OpenEdge product \\n management and product \\n \\n operations. \\n - \\n Creation of a new enterprise \\n \\n architecture function led by \\n - \\n James Kerr with a first \\n \\n dedicated PDP level \\n \\n enterprise - architect: Nathan \\n van \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9171-9392\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9402-9623\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9402-9623\",\"text\":\". - \\n \\n \u2022 Nuclia \\n \\n \u2022 Reporting line changes for \\n \\n HDP - \\n \\n \u2022 Temporary structure for \\n \\n the documentation \\n function - \\n \\n https://www.progress.com/ \\n \\n \\n\\n\\n \\n\\n\\n a digital - artwork depicting a street scene with various el\\n\\nDOCUMENT METADATA AT - ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context - and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9402-9623\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48116-48383\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48116-48383\",\"text\":\" - oranges. The scene depicts a kitchen setting with a focus on the fruit bowl, - suggesting a theme of healthy eating or culinary preparation. \\n\\n\\n \\n\\n\\n - a digital artwork that appears to be a still life composition. Visible objects - include a bowl, a spoon, a knife, and v\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48116-48383\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48383-48609\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48383-48609\",\"text\":\"arious - fruits such as apples and oranges. The scene depicts a kitchen setting with - a focus on the fruit bowl, suggesting a theme of healthy eating or culinary - preparation. \\n\\n\\n \\n Integrate \\n Our Teams \\n \\n Our Products \\n - \\n Our \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48383-48609\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48609-48921\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48609-48921\",\"text\":\"Use - Cases \\n \\n https://www.progress.com/ \\n \\n \\n\\n\\n Software (ISV/OEM)\\nManufacturing\\n\\nLife\\nSciences\\nPharma\\nBiotech\\n\\n&\\nS\\n@\\n<\\noO\\n=\\no\\ni=)\\n3\\ncc\\n3\\nS\\nt\\n\\nFinancial\\nServices - &\\nInsurance\\n\\nManaged\\nHealthcare\\n\\nGovernment\\nim (SL/Fed)\\n\\nMedia - &\\nPublishing\\n\\nMayes oyand \\n\\n\\n a circular diagram with six segments, - each representing \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48609-48921\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48921-48955\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48921-48955\",\"text\":\"a - different aspect of security man\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48921-48955\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48959-49179\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48959-49179\",\"text\":\"ent. - The segments are labeled Product 360, Self-service Policy Search, Managed - Healthcare, Government (SL/Fed), Public Safety, Fraud Identity, and Financial - Services & Insurance. Visible objects include icons for Softwar\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48959-49179\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49679-49855\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49679-49855\",\"text\":\"V/OEM) - Manufacturing, Life Sciences Pharma Biotech, Media & Publishing, and Fraud - Identity. The scene shows a globe centered within the circle, surrounded by - these six segments\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49679-49855\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49860-49896\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49860-49896\",\"text\":\" - @uHHEERy\\n\\nquxx== \xA9\\n\\nERB EBB BEEBE B\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49860-49896\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49900-50107\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49900-50107\",\"text\":\" - wm \xAE\\n\\nSd\\n\\n@nunuun 8 \\n\\n\\n a flowchart or diagram that illustrates - the process of data integration. Visible objects include arrows representing - different stages, icons indicating various processes, and a circu\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49900-50107\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/50107-50141\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/50107-50141\",\"text\":\"lar - loop symbolizing a continuous \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/50107-50141\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/39868-40218\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/39868-40218\",\"text\":\"a - digital graphic artifact, likely representing a logo or branding element. - It shows a stylized green geometric shape with three arrows pointing upwards, - set against a white background. Visible objects include the green shapes and - arrows, as well as some black elements that could represent additional details - or text. The scene context suggests a mo\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/39868-40218\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40223-40271\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40223-40271\",\"text\":\" - tech-oriented environment, possibly related to \\n\\nDOCUMENT METADATA AT - ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context - and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40223-40271\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40275-40528\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40275-40528\",\"text\":\"nology - or innovation. \\n\\n\\n \\n\\n\\n a digital graphic artifact, likely a logo - or an icon. It shows a green geometric shape with three arrows pointing upwards, - set against a white background. Visible objects include the green shapes and - arrows, as well as som\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40275-40528\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40528-40589\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40528-40589\",\"text\":\"e - black elements that could represent additional details or t\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40528-40589\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40593-40984\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40593-40984\",\"text\":\" - The scene is minimalistic, focusing on the geometric shapes and their directional - emphasis. \\n\\n\\n \\n 33\xA9 2025 Progress Software Corporation and/or - its subsidiaries or affiliates. All rights reserved. \\n \\n Progress Data - Platform \\n \\n \xC7\xC7 \\n \\n \u2713 Simplified Licensing Terms \u2013 - Harmonized EULA and clear discounting guidelines. \\n \\n \u2713 Faster Contract - Approvals \u2013 Streamlined deal desk and legal alignme\\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40593-40984\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41337-41738\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41337-41738\",\"text\":\"ion - for faster provisioning and order accuracy. \\n \\n \u2713 Unified UI \u2013 - Improved experience across product set to increase efficiency and user engagement. - \\n \\n Customer Experience \\n \\n https://www.progress.com/ \\n \\n \\n\\n\\n - \ \\n\\n\\n a graphic illustration featuring three stylized icons: a wave - symbol, a green checkmark icon, and a smiley face icon. The scene shows a - modern digital interface with these icons, sugg\\n\\nDOCUMENT METADATA AT - ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context - and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41337-41738\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41738-41772\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41738-41772\",\"text\":\"esting - a focus on user feedback or\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41738-41772\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/42209-43142\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/42209-43142\",\"text\":\"althy - eating or culinary preparation. \\n\\n\\n \\n\\n\\n a digital image of a - landscape scene. Visible objects include trees, grass, rocks, and water. The - scene depicts a serene natural environment with lush greenery and calm waters. - \\n\\n\\n \\n 34\xA9 2025 Progress Software Corporation and/or its subsidiaries - or affiliates. All rights reserved. \\n \\n Intersection of \\n Moment-in-Time - \\n Pain and Long-term \\n Business Impact \\n \\n Long-Term \\n \\n Transformation - \\n Help to solve today's pains \\n \\n repeatedly \\n \\n until long-term - impact \\n \\n becomes instilled. \\n \\n AI-Driven \\n \\n Foundation \\n - Build a robust AI \\n \\n foundation that \\n \\n accelerates insights and - \\n \\n decision-making \\n for long-term success. \\n \\n Customer-Centric - \\n \\n Approach \\n Focus on meeting \\n \\n customers at their \\n \\n current - state to address \\n \\n immediate \\n pain points effectively. \\n \\n https://www.progress.com/ - \\n \\n \\n\\n\\n \\n\\n\\n a long-exposure photograph capturing the dynamic - movement of vehic\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/42209-43142\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43147-43615\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43147-43615\",\"text\":\"n - an intricate highway network at night. Visible objects include multiple intersecting - highways with light trails indicating the speed and flow of traffic. The scene - is set in a bustling urban area, likely a city center, with illuminated buildings - and streets in the background. \\n\\n\\n \\n Progress Data Platform: Vertical - Concentration \\n \\n \xC7\xC7 \\n \\n Manufacturing \\n \\n \xC7\xC7 \\n - \\n Healthcare \\n \\n \xC7\xC7 \\n \\n Government \\n \\n \xC7\xC7 \\n \\n - Media & \\n \\n Publishing \\n \\n \xC7\xC7 \\n \\n FinServ/ \\n \\n Insuranc\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43147-43615\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54700-54989\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54700-54989\",\"text\":\"ions - team with \\n advanced tools to better \\n assist clients and drive \\n \\n - revenue generation \\n \\n Continuous monitoring \\n \\n and enhancement of - \\n security measures to \\n \\n safeguard customer data \\n \\n integrity - \\n \\n https://www.progress.com/ \\n \\n \\n\\n\\n \\n\\n\\n a digital - artwork depicting a street sc\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54700-54989\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54999-55330\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54999-55330\",\"text\":\"ith - a focus on the intersection of two roads. Visible objects include cars, pedestrians, - and buildings. The scene captures a moment of everyday life, highlighting - urban dynamics and human activity. \\n\\n\\n \\n\\n\\n a digital artwork - depicting a street scene with a focus on the intersection of two roads. Visible - objects include cars, pede\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54999-55330\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55340-55629\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55340-55629\",\"text\":\"ns, - and buildings. The scene captures a moment of everyday life, highlighting - urban dynamics and human activity. \\n\\n\\n \\n\\n\\n a digital artwork - depicting a street scene with a focus on the intersection of two roads. Visible - objects include cars, pedestrians, and buildings. The scene captures \\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55340-55629\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56177-56491\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56177-56491\",\"text\":\"ent - of everyday life, highlighting urban dynamics and human activity. \\n\\n\\n - \ \\n\\n\\n a digital illustration featuring a gear-like blue background with - interconnected lines and nodes, symbolizing technology and data management. - In the foreground, there are two open books: one with a brain diagram on the - left and another\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56177-56491\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56501-56608\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56501-56608\",\"text\":\" - a yellow brain icon on the right. Below the books, there is a graph showing - data trends. The scene suggest\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56501-56608\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56613-56634\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56613-56634\",\"text\":\"ocus - on information t\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56613-56634\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26541-26922\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26541-26922\",\"text\":\" - alignment \\n \\n World Tour \u2013 Global events \\n showcasing OpenEdge - innovation \\n \\n Community - Collaborative network for \\n learning, sharing, - and innovation \\n \\n Customer Validation Program - Early \\n access to roadmap - features and \\n \\n collaborative feedback. \\n \\n AppMod \u2013 Separating - US from \\n \\n database and business logic and API \\n enablement \\n \\n - Managed Database Administration \\n (MDB\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26541-26922\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26932-27153\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26932-27153\",\"text\":\"Proactive - DB monitoring \\n \\n and expert management \\n \\n Security Assessment \u2013 - Identify \\n \\n vulnerabilities and strengthen \\n protection \\n \\n Cloud - Migration \u2013 Move OpenEdge \\n workloads to cloud \\n \\n https://www.progress.com/ - \\n\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26932-27153\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27158-27462\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27158-27462\",\"text\":\"\\n\\n - \ \\n\\n\\n a digital artwork depicting a street scene with various elements. - Visible objects include buildings, trees, and pedestrians. The scene captures - the essence of urban life, highlighting the blend of architecture and nature. - \\n\\n\\n \\n\\n\\n a digital artwork depicting a street scene with various - elements.\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27158-27462\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27669-27911\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27669-27911\",\"text\":\"or - its subsidiaries or affiliates. All rights reserved. \\n \\n The Solution: - Trusted, Intelligent Insights \\n \\n \xC7\xC7 \\n \\n MCP Server \\n \\n - AI You Can \\n \\n TRUST \\n \u2022 Unified Intelligence \\n \\n \u2022 Faster - Modernization \\n \\n \u2022 Trusted, Governed AI \\n \\n https://\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27669-27911\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27911-28181\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27911-28181\",\"text\":\"www.progress.com/ - \\n \\n \\n\\n\\n \\n\\n\\n a graphic representation of a light bulb with - bright yellow glow and sparkles around it. The scene shows a sunny day with - a clear blue sky, and the light bulb is placed on a surface with a few decorative - elements like stars and flowers. \\n\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27911-28181\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28181-28534\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28181-28534\",\"text\":\"\\n\\n - \ \\n\\n\\n a digital artwork depicting a street scene with a focus on the - intersection of two roads. Visible objects include cars, pedestrians, and - buildings. The scene captures a moment of everyday life, highlighting urban - dynamics and human activity. \\n\\n\\n \\n\\n\\n a logo, featuring a gear - with arrows pointing downwards. The gear is yellow with black teeth, \\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28181-28534\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28534-28568\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28534-28568\",\"text\":\"and - the arrows are blue. The backg\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28534-28568\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/30837-31265\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/30837-31265\",\"text\":\" - is green. Visible objects include the gear and arrows. Context shows a factory - setting with machinery and equipment. \\n\\n\\n \\n\\n\\n a digital artwork - depicting a street scene with a focus on the intersection of two roads. Visible - objects include cars, pedestrians, and buildings. The scene captures a moment - of everyday life, highlighting urban dynamics and human activity. \\n\\n\\n - \ \\n\\n\\n a stylized graphic representation of a motorcyclis\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/30837-31265\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31275-31654\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31275-31654\",\"text\":\"ing - fast, likely on a racetrack. Visible objects include the rider's silhouette, - the motorcycle, and dynamic motion lines indicating speed. The scene captures - the thrill and intensity of racing, emphasizing rapid movement and speed. - \\n\\n\\n \\n\\n\\n a digital artwork that depicts a street scene with various - elements. Visible objects include buildings, trees, and vehicles. The scene - ca\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31275-31654\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31659-31881\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31659-31881\",\"text\":\"s - the essence of urban life, highlighting the contrast between nature and architecture. - \\n\\n\\n \\n 28\xA9 2025 Progress Software Corporation and/or its subsidiaries - or affiliates. All rights reserved. \\n \\n Progress Corticon \\n \\n \xC7\xC7\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31659-31881\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32155-32457\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32155-32457\",\"text\":\"ity - with modern platforms \\n \\n Unified Data + Rules \u2013 Decision logic \\n - \\n with real-time, governed data for more \\n accurate outcomes \\n \\n Accelerated - Compliance \u2013 Regulatory \\n requirements faster and with greater \\n - \\n confidence \\n \\n Future-Ready Architecture for \\n \\n Scalability \u2013 - Modern, scalable \\n founda\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32155-32457\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32457-32515\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32457-32515\",\"text\":\"tion - for advanced analytics and AI \\n \\n Targeted U.S. State\\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32457-32515\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32524-32916\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32524-32916\",\"text\":\" - https://www.progress.com/ \\n \\n \\n\\n\\n \\n\\n\\n a digital artwork - depicting a street scene with various elements such as buildings, trees, and - vehicles. Visible objects include a building with a large window, a tree with - green leaves, and a car parked on the side of the road. The scene captures - a typical urban environment with a mix of architectural styles and natural - elements. \\n\\n\\n \\n\\n\\n a graphic\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32524-32916\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43620-43649\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43620-43649\",\"text\":\" - \xC7\xC7 \\n \\n Pharma \\n \\n \u2022 R&D \u2013 pr\\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43620-43649\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43653-43816\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43653-43816\",\"text\":\"t - \\n design, test, \\n \\n pricing, etc. \\n \\n \u2022 Knowledge \\n \\n management - \\n \\n \u2022 Supply chain \\n \\n management and \\n \\n logistics \\n \\n - \u2022 Safety \\n \\n \u2022 Compliance \\n \\n Provider: \\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43653-43816\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43820-43841\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43820-43841\",\"text\":\"Clinical - coding \\n \\n \u2022\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43820-43841\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52072-52252\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52072-52252\",\"text\":\"nes - \\n \\n document describes the process and the \\n \\n technical details for - deploying a new \\n \\n product/service in PDC (contact Stephen \\n \\n Rice - for details) \\n \\n https://www.progress.\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52072-52252\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52256-52411\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52256-52411\",\"text\":\" - \\n \\n \\n\\n\\n Alltools Edit\\n1c)\\n\\n= menu) \xA5y Product Hosting - Guideli. x @ \xA9 # Signin - a x\\nConvert E-Sign Findtextortoo Q 6% a 8\\n| - @\\nProduct Hosting Guidelines\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52256-52411\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52415-53028\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52415-53028\",\"text\":\"t - updated by | Stephen Rice | 3 Dec 2025 at 14:36 GMT i(k)\\n\\nZ.\\n\\n2\\n\\nContents\\n* - Introduction\\n+ Terminology and Overview\\n+ Product Hosting Features\\n+ - Is PDC the correct place to host your service?\\n+ PDC Product Deployment - Process\\n+ Exploration - Need is identified for product to be hosted\\n+ - Preparation - Product and PDC teams create implementati...\\n\\n+ Product - Updates - Product team implements required cha...\\n\\n+ PDC Review - PDC - team reviews design documentation an...\\n+ PDC Integration - PDC deploys - product and performs inte..\\n\\n+ Operations On-boarding - Operations team - is provided wi...\\n+ Retrospective - Revi\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52415-53028\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53032-53067\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53032-53067\",\"text\":\"rocess - and discuss how any issues..\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53032-53067\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53071-53354\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53071-53354\",\"text\":\"Technical - Requirements\\n\\n+ Reverse Proxy Support\\n\\n+ specif .\\n\\n+ Network Connections - Requirements\\n\\n+ Helm Charts\\n\\n+ Load Bala\\n\\n2 p \\n\\n\\n a screenshot - of a webpage titled \\\"Product Hosting Guidelines\\\". The page contains - a list of contents, including sections on introduction, product deplo\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53071-53354\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53655-53971\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53655-53971\",\"text\":\"r - images present. \\n\\n\\n \\n Product Innovation \\n \\n \\n \\n\\n\\n \\n - 46\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Progress \\n Data Cloud \\n \\n https://www.progress.com/ - \\n \\n \\n\\n\\n 3) Progress DataCloud \\n\\n\\n a logo for Progress DataCloud. - It shows a green square with a white \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53655-53971\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53971-54093\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53971-54093\",\"text\":\"arrow - pointing upwards, indicating progress or growth. Visible objects include the - green square and the white arrow. The s\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53971-54093\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54102-54391\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54102-54391\",\"text\":\"shows - a modern office environment with a desk, chair, and computer monitor. \\n\\n\\n - \ \\n 47\xA9 2025 Progress Software Corporation and/or its subsidiaries or - affiliates. All rights reserved. \\n \\n Platform \\n \\n Functionality \\n - \\n Support \\n \\n Support for additional \\n \\n PDP products and \\n services - as we\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54102-54391\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/10976-11113\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/10976-11113\",\"text\":\"eople - in a garage setting, likely a car repair shop. The woman is seated at a desk - writing on a clipboard, while the man stands behind he\\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/10976-11113\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11122-11484\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11122-11484\",\"text\":\"aning - slightly towards her. Visible objects include a vintage telephone, a metal - workbench with various tools and equipment, and a classic car parked in the - background. The context suggests a professional environment focused on automotive - repairs. \\n\\n\\n \\n 15\xA9 2025 Progress Software Corporation and/or its - subsidiaries or affiliates. All rights reserved. \\n \\n http\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11122-11484\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11489-11626\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11489-11626\",\"text\":\"ww.progress.com/ - \\n \\n \\n\\n\\n \\n\\n\\n a vintage photograph showing a woman working - at a computer desk in an automotive workshop. Visible objects\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11489-11626\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12075-12212\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12075-12212\",\"text\":\" - interface, specifically the Wineria Santine app. The screen displays various - menu options such as \\\"Rolls water transport,\\\" \\\"Faree 310,54\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12075-12212\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12216-12317\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12216-12317\",\"text\":\"04,00,00,\\\" - \\\"Sensitiveness,\\\" \\\"Revenue to market 280 mnx,\\\" \\\"Delivery schedule,\\\" - and \\\"New mascara-intern\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12216-12317\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12322-12628\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12322-12628\",\"text\":\"al - brands 06.\\\" Visible objects include a woman sitting on a bench holding - a smartphone, with storefronts in the background featuring signage in Hindi. - \\n\\n\\n \\n 17\xA9 2025 Progress Software Corporation and/or its subsidiaries - or affiliates. All rights reserved. \\n \\n https://www.progress.com/ \\n - \\n \\n\\n\\n AAPFOINFAE\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12322-12628\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12633-12770\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12633-12770\",\"text\":\"MFROMDE\\n\u201CTUsEBALI - NOW_16 2050 G-\u20ACARAEE\\n[DEWAUS EG TO NELIMAL LK\\nENIOY @0F9 UN JOURTEY. - \\n\\n\\n a digital interface displaying an image of a c\\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12633-12770\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4766-6189\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4766-6189\",\"text\":\"7\xA9 - 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Congrats getting to the next level! \\n \\n Employee - Location Scrum Team New Position \\n Abhishek Tiwari Hyderabad Mangalayan - QA Engineer, Senior 2 \\n \\n Ajoy Soni Hyderabad Avengers Software Engineer, - Senior 1 \\n \\n Amit Anchaliya Hyderabad Atlantis Software Engineer, Principal - 1 \\n \\n Anshuman Singh Hyderabad Conquerors Software Engineer, Senior 1 - \\n \\n Bing Zhu USA Light QA Engineer, Senior Principal \\n \\n Brahmananda - Gouni Hyderabad - Senior Manager, Software Engineering \\n \\n Brian Tang - USA Quicksilver Software Engineer, Principal \\n \\n Hari Krishna Tirunagari - Hyderabad Mangalayan QA Engineer, Principal 3 \\n \\n Hemanandh S Hyderabad - Avengers Software Engineer, Principal 3 \\n \\n Jonathan Miller USA Kalimba - Software Engineer, Senior \\n \\n Kunal Basarkar Hyderabad Avengers Software - Engineer, Senior Principal \\n \\n Nitesh Mehta Hyderabad Harmonica Software - Engineer, Senior Principal \\n \\n Saivenkat Chepuri Hyderabad Conquerors - Software Engineer, Principal 1 \\n \\n Sathyanarayana Gundoji Hyderabad Mangalayan - Software Engineer, Senior 1 \\n \\n Srikar Veeramallu Hyderabad Atlantis Software - Engineer, Principal 1 \\n \\n Stephen Brown USA Apollo Software Engineer, - Principal \\n \\n Sumit Pritmani Hyderabad Transformers Software Engineer, - Senior 2 \\n \\n Vikram Reddy Deva Hyderabad Avengers QA Engineer, Senior - 2 \\n \\n https://www.progress.com/\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4766-6189\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\",\"text\":\"5\xA9 - 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Welcome to the Team \\n \\n Vamshi Shanigala - \\n Coop/Intern Technical 2 \\n \\n MarkLogic \\n Hyderabad \\n \\n Nathan - Van Gheem \\n Enterprise Architect \\n \\n PDP \\n Raleigh \\n \\n Shivabalu - Thouta \\n Software Engineer, Senior \\n \\n MarkLogic \\n Hyderabad \\n \\n - https://www.progress.com/\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\",\"text\":\"24\xA9 - 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Progress ADP: GTM Motions \\n \\n Expansion: - \\n Cross-sell & Upsell \\n \\n Increase account \\n \\n value through \\n - \\n added ADP \\n \\n products or \\n \\n leveling up tiers \\n \\n \xC7\xC7\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\",\"text\":\"6\xA9 - 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Welcome to the Team \\n \\n Aleix Ruiz de Villa - \\n Scientific Advisor \\n \\n PDP \\n Spain \\n \\n Casimiro Pio Carrino - \\n Scientific Advisor \\n \\n PDP \\n Spain\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\",\"text\":\"26\xA9 - 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Progress OpenEdge \\n \\n \xC7\xC7 \\n \\n Modernization - Services & Plus Ones Engagement \\n \\n OpenEdge 13 \u2013 Latest version - \\n supporting FIPS compliance \\n \\n 12 and GenAI Workshops \u2013 Free - \\n hands-on training \\n \\n QSM \u2013 Quality and security \\n management - tools \\n \\n MCP Connector for ABL - AI Code \\n Assistant to improve code - quality \\n \\n Agentic RAG \u2013 AI-driven contextual \\n knowledge retrieval - \\n \\n Forrester Total Economic Impact \u2013 \\n Validated ROI and business - value \\n \\n PUG Challenge \u2013 Community- \\n \\n driven learning and - networking \\n \\n Customer Advisory Board \u2013 Customer \\n \\n advisory - for strategic alignment \\n \\n World Tour \u2013 Global events \\n showcasing - OpenEdge innovation \\n \\n Community - Collaborative network for \\n learning, - sharing, and innovation \\n \\n Customer Validation Program - Early \\n access - to roadmap features and \\n \\n collaborative feedback.\\n\\nDOCUMENT METADATA - AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business - Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\",\"text\":\"New - \\n \\n Acquisition \\n \\n Win net new \\n \\n customers \\n \\n adopting - Progress \\n \\n Data Platform \\n \\n portfolio \\n \\n Customer \\n \\n - Renewal \\n \\n Retain existing \\n \\n customers by \\n \\n reinforcing ongoing - \\n \\n value of current \\n \\n product(s) in use \\n \\n https://www.progress.com/\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\",\"text\":\"and - what qualifications staff require to apply it? \\n \\n Submit \\n \\n https://www.progress.com/\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\",\"text\":\"Celebrating - Innovation\\nfrom PI 3...\\n\\nBrian Tang - FastTrack w/ MCP\\n\\nVanessa - Zhang - Al diff analysis\\n\\nShivali Tayal - 3rd party\\ndependency update - automation\\n\\nProgress\u2019\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\",\"text\":\"2\xA9 - 2022 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Celebrating Q4 \\n \\n Releases \\n \\n ARC, - PostgreSQL, Oracle \\n \\n OpenAccess 9.0 for AIX \\n \\n Corticon 7.3.0 \\n - \\n Corticonjs 2.4.0 \\n \\n MarkLogic 11.3.2/3 \\n \\n MarkLogic IronBank - \\n \\n Operator 1.1.1 \\n \\n Progress Agentic RAG \\n \\n PDC 1.2.2/1.3.0 - \\n \\n Semaphore 5.8.6 \\n \\n Security \\n \\n Trufflehog \\n \\n SAMM Level - 2 \\n \\n Spy Attributes \\n Vulnerability \\n Resolution \\n \\n HDP 4.6.2 - \\n \\n Infrastructure \\n \\n Sonar Code \\n Coverage \\n \\n Innovation - \\n \\n Corticon AI \\n Generated User \\n Interface \\n \\n AI Video Production - \\n \\n Share your additional celebrations in the meeting chat!\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\",\"text\":\"48\xA9 - 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n PDC Priorities & Innovation \\n \\n \u2022 Functional - Expansion \u2013 Increase value proposition by on- \\n boarding additional - PDP (and other) services \\n \\n Business Priorities \\n \\n \u2022 MCP OpenEdge - ABL Service \\n \\n \u2022 Hybrid Data Pipeline Service \\n \\n \u2022 EULA - Acceptance Feedback Mechanism \\n \\n \u2022 Data Symphony Service \\n \\n - \u2022 Operational Support Shared Logging (CRIBL) \\n \\n Innovation Areas - \\n \\n https://www.progress.com/\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\",\"text\":\"Creation - of a new enterprise \\n \\n architecture function led by \\n \\n James Kerr - with a first \\n \\n dedicated PDP level \\n \\n enterprise architect: Nathan - \\n van Gheem. \\n \\n \u2022 Nuclia \\n \\n \u2022 Reporting line changes - for \\n \\n HDP\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\",\"text\":\"\u2022 - Expansion/New Logos - Supporting the AI Journey, Lowering TCO, Supporting - \\n Hybrid Deployment Options \\n \\n Business Priorities \\n \\n \u2022 Graviton - Support \\n \\n \u2022 Monitoring Agent \\n \\n \u2022 Nuclia-MarkLogic Integration - \\n \\n \u2022 MarkLogic Knowledge Hub \\n \\n \u2022 Flux as PDC Service - \\n \\n Innovation \\n \\n \u2022 Property Graphs \\n \\n \u2022 Read from - Replicas \\n \\n \u2022 Index Exclusion \\n \\n \u2022 Vector improvements - \\n \\n \u2022 Object storage improvement \\n \u2022 Support Kendo Theme Builder - in FastTrack \\n \\n https://www.progress.com/\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: - 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product - Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: - Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\",\"text\":\"42\xA9 - 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. 42 \\n \\n Getting Started \\n \\n \u2022 Contact the - PDC PM/PO (Stephen Rice) to \\n \\n discuss \\n \\n \u27A2 Provide as many - details as required \\n \\n including timeframes \\n \\n \u27A2 Meeting will - be arranged between key \\n \\n stakeholders \\n \\n https://www.progress.com/\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\",\"text\":\"59\xA9 - 2025 Progress Software Corporation and/or its subsidiaries or affiliates. - All rights reserved. \\n \\n Corticon Priorities & Innovation \\n \\n \u2022 - Retention \u2013 Support, CVEs, encourage update to latest LTS \\n \\n \u2022 - Public Sector Expansion - Replicate success at State of Mississippi \\n \\n - \u2022 Platform Modernization - New UI and SaaS to enable more customer wins - \\n \\n Business Priorities \\n \\n \u2022 Modern UI \\n \\n \u2022 AI powered - user experience \\n \\n \u2022 SaaS offering in PDC \\n \\n \u2022 Symphony - rule deployment \\n \\n Innovation \\n \\n https://www.progress.com/\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\",\"text\":\"Performance - & Reliability Upgrades \u2013 \\n \\n Faster queries and improved resilience - \\n \\n for mission-critical workloads. \\n \\n AI-Assistant \u2013 Simplify - the developer \\n \\n experience and lower the learning curve.\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\",\"text\":\"a - digital photograph showing two people working at a desk. The man is seated, - looking at the computer screen, while the woman stands behind him, smiling. - Visible objects include a desktop computer with a keyboard and mouse, a pen - holder, and some documents on the desk. The background features a green wall - with charts and graphs.\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 - 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 - 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test - folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: - sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: - sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: - fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31881-32155\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31881-32155\",\"text\":\"\u2713 - Faster Contract Approvals \u2013 Streamlined deal desk and legal alignment - for quicker turnaround. \\n \\n \u2713 Transparent Pricing Models \u2013 Unified - price list and predictable cost structures. \\n \\n \u2713 Starter Bundles - for Simplicity \u2013 Upcoming PDP SKU for easier entry and adoption.\\n\\nDOCUMENT - METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: - Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 - 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and - Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n - \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n - \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: 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2026 07:57:53 GMT nuclia-learning-id: - - d5de8633afd345d0b14bd067304be32b + - 228aaa2bbde34ab5aeec5879ac99ad8a + nuclia-learning-model: + - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '2575' + - '346' x-nuclia-trace-id: - - ff0273c5d7ddd3d7462448d4c88ef51b + - 9603c9f12264f172ba450a12759769cc status: code: 200 message: OK diff --git a/agents/nucliadb/tests/test_nucliadb.py b/agents/nucliadb/tests/test_nucliadb.py index 4806d94f..ee9505de 100644 --- a/agents/nucliadb/tests/test_nucliadb.py +++ b/agents/nucliadb/tests/test_nucliadb.py @@ -26,6 +26,13 @@ NucliaDBConnection, ) + +def ignore_nucliadb_api(request): + if request.path.startswith("/api/v1/kb/"): + return None + return request + + NUA_KEY = os.environ.get( "NUA_KEY", ) or cassette_nua_key("https://europe-1.dp.progress.cloud/") @@ -250,7 +257,7 @@ async def callback(obj: AragAnswer): @pytest.mark.asyncio -@pytest.mark.vcr(ignore_localhost=True, ignore_hosts=["europe-1.dp.progress.cloud"]) +@pytest.mark.vcr(ignore_localhost=True, before_record_request=ignore_nucliadb_api) async def test_nucliadb_agent_simple(): answers = [] @@ -276,7 +283,7 @@ async def callback(obj: AragAnswer): @pytest.mark.asyncio -@pytest.mark.vcr(ignore_localhost=True, ignore_hosts=["europe-1.dp.progress.cloud"]) +@pytest.mark.vcr(ignore_localhost=True, before_record_request=ignore_nucliadb_api) async def test_nucliadb_agent_simple_disable_ai_parameter_search(): question_memory = await arag_main( agent_id="default", @@ -294,7 +301,7 @@ async def test_nucliadb_agent_simple_disable_ai_parameter_search(): @pytest.mark.asyncio -@pytest.mark.vcr(ignore_localhost=True, ignore_hosts=["europe-1.dp.progress.cloud"]) +@pytest.mark.vcr(ignore_localhost=True, before_record_request=ignore_nucliadb_api) async def test_nucliadb_agent_basic_ask(): config = deepcopy(CONFIG_SIMPLE) diff --git a/agents/nucliadb/tests/test_sync.py b/agents/nucliadb/tests/test_sync.py index 334be20c..349d71bb 100644 --- a/agents/nucliadb/tests/test_sync.py +++ b/agents/nucliadb/tests/test_sync.py @@ -13,6 +13,12 @@ from hyperforge.minimal_fixtures import cassette_nua_key from hyperforge.pubsub import UserToAgentInteraction + +def ignore_nucliadb_api(request): + if request.path.startswith("/api/v1/kb/"): + return None + return request + NUA_KEY = os.environ.get( "NUA_KEY", ) or cassette_nua_key("https://europe-1.dp.progress.cloud/") @@ -23,7 +29,7 @@ ) or cassette_nua_key("https://europe-1.dp.progress.cloud/") pytestmark = [ - pytest.mark.vcr(ignore_localhost=True, ignore_hosts=["europe-1.dp.progress.cloud"]), + pytest.mark.vcr(ignore_localhost=True, before_record_request=ignore_nucliadb_api), pytest.mark.asyncio, ] From f002480bb02479bad9a987b70dcaef50bef9d1da Mon Sep 17 00:00:00 2001 From: Carles Onielfa Date: Wed, 5 Aug 2026 10:00:18 +0200 Subject: [PATCH 4/6] fmt --- agents/nucliadb/tests/test_sync.py | 1 + 1 file changed, 1 insertion(+) diff --git a/agents/nucliadb/tests/test_sync.py b/agents/nucliadb/tests/test_sync.py index 349d71bb..02e52e3d 100644 --- a/agents/nucliadb/tests/test_sync.py +++ b/agents/nucliadb/tests/test_sync.py @@ -19,6 +19,7 @@ def ignore_nucliadb_api(request): return None return request + NUA_KEY = os.environ.get( "NUA_KEY", ) or cassette_nua_key("https://europe-1.dp.progress.cloud/") From b77c0fc386b19cf207992ecc6266669bd6eeb4de Mon Sep 17 00:00:00 2001 From: Carles Onielfa Date: Wed, 5 Aug 2026 10:11:32 +0200 Subject: [PATCH 5/6] rerecord --- .../test_nucliadb_agent_basic_ask.yaml | 293 +++--- .../test_nucliadb_agent_simple.yaml | 597 +++++------ ...nt_simple_disable_ai_parameter_search.yaml | 969 +++++------------- .../cassettes/test_sync/test_sync_agent.yaml | 44 +- 4 files changed, 732 insertions(+), 1171 deletions(-) diff --git a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml index 9efdf529..2d2fcfc1 100644 --- a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml +++ b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml @@ -9,29 +9,29 @@ interactions: Connection: - keep-alive Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.dp.stashify.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: - string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"da1740fa-ab3e-4971-b374-7bb31b5dd325","account_id":"39f5fa6e-680a-475e-a757-812597e86d06","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' + string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"9e1317aa-e212-4a59-b794-afee535458a6","account_id":"07c2de7c-fa77-4374-a461-eea314da9dfd","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' headers: Alt-Svc: - - h3=":443"; ma=2592000 + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - '227' content-type: - application/json date: - - Wed, 05 Aug 2026 07:57:25 GMT + - Wed, 05 Aug 2026 08:09:49 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '7' + - '69' status: code: 200 message: OK @@ -77,13 +77,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-client-ident: - default x-message: - - 0dfefb8a0b7b40f6a89fc902c85a8d80 + - 7bd1cbc3b0ac4748a0cad7661bcf202b x-origin: - RAO x-session: @@ -93,19 +93,21 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"rephrased_question\":\"Explica - el uso de `max_tokens` en espa\xF1ol y proporciona un enlace a la documentaci\xF3n - oficial.\",\"rules\":[\"Responde en espa\xF1ol.\",\"Incluye un enlace a la - documentaci\xF3n oficial de `max_tokens`.\"],\"reason\":\"La pregunta original - es clara pero se puede mejorar ligeramente al especificar que se busca la - explicaci\xF3n y el enlace a la documentaci\xF3n de manera expl\xEDcita, adem\xE1s - de asegurar que la respuesta sea en espa\xF1ol.\"}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":7,\"output_tokens\":9,\"timings\":{\"generative\":0.8064458860026207},\"input_nuclia_tokens\":0.007,\"output_nuclia_tokens\":0.009}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0071,\"output\":0.0092,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" + c\xF3mo usar el par\xE1metro `max_tokens` en espa\xF1ol y proporciona un enlace + a la documentaci\xF3n oficial.\",\"rules\":[\"Responde en espa\xF1ol.\",\"Incluye + una explicaci\xF3n clara del uso de `max_tokens`.\",\"Proporciona un enlace + directo a la documentaci\xF3n relevante sobre `max_tokens`.\"],\"reason\":\"La + pregunta original es clara en su intenci\xF3n, pero se ha reformulado ligeramente + para mejorar la fluidez y asegurar que se especifica la necesidad de un enlace + a la documentaci\xF3n oficial, adem\xE1s de aclarar que la respuesta debe + ser en espa\xF1ol.\"}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":7,\"output_tokens\":11,\"timings\":{\"generative\":1.509255008000764},\"input_nuclia_tokens\":0.007,\"output_nuclia_tokens\":0.011}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0071,\"output\":0.01144,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -113,17 +115,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:25 GMT + - Wed, 05 Aug 2026 08:09:50 GMT nuclia-learning-id: - - 773cc8e292d24a8399e92e28cc05601f + - 93f79d882b0547fe98ace3244ab5a9e5 nuclia-learning-model: - gemini-2.5-flash-lite via: - 1.1 google x-envoy-upstream-service-time: - - '812' + - '1517' x-nuclia-trace-id: - - fc73b490383741aa83d36633cd9a6d98 + - 7a7703497744d2cbe1f374cdec214bfd status: code: 200 message: OK @@ -162,68 +164,66 @@ interactions: \"block-CD\"]).\n11. **IMPORTANT** If any extra instructions are provided, you MUST follow them carefully when generating the answer field. These instructions may specify the format, style, tools to use, or other requirements for the answer.\n\n\nExplica - el uso de `max_tokens` en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n - oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### Chunk: docs - > develop > js sdk > interfaces > PredictAnswerOptions\n``` \n optional max_tokens: - number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol y proporciona + un enlace a la documentaci\u00f3n oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### + Chunk: docs > rag > advanced > consumption.\n``` Use the max_tokens parameter + on the /ask endpoint to set hard limits on: \n - Context size: Limits the amount + of retrieved information sent to the LLM \n - Answer length: Limits the length + of the generated response \n Important Considerations \n Context Limitations: + \n ```\n\n\n---\"\n\n\n**block-AB**\n\n#### Chunk: docs > rag > advanced > openai + api compatible models\n``` Description: The maximum number of tokens that the + model can generate as output. Again, we should keep in mind that this value + summed to the Maximum supported input tokens should not exceed the total context + size supported by the model. \n ```\n\n\n---\"\n\n\n**block-AC**\n\n#### Chunk: + docs > develop > js sdk > interfaces > PredictAnswerOptions\n``` \n optional + generative_model: string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 + \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 + \n \n max_tokens? \n ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: docs > + develop > python sdk > 05 search\n``` \n SDK: \n \n ```python \n from nuclia + import sdk \n from nucliadb_models.search import AskRequest, Reasoning \n search + = sdk.NucliaSearch() \n query = AskRequest( \n query= My question with extra + reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( \n display=True, + # Show reasoning in the response \n effort= low , # Can be low , medium , or + high \n budget_tokens=1024 # How many tokens reasoning can use \n ), \n ) \n + search.ask(query=query) \n ``` \n Model Support for Reasoning Options: \n ```\n\n\n---\"\n\n\n**block-AE**\n\n#### + Chunk: docs > rag > advanced > widget > features\n``` max_tokens: the maximum + number of input tokens to put in the final context (including the prompt, the + retrieved results and the user question). \n max_output_tokens: the maximum + number of tokens to generate. \n ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: + docs > develop > js sdk > interfaces > PredictAnswerOptions\n``` \n optional + max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? - \n ```\n\n\n---\"\n\n\n**block-AB**\n\n#### Chunk: docs > rag > advanced > consumption.\n``` Use - the max_tokens parameter on the /ask endpoint to set hard limits on: \n - Context - size: Limits the amount of retrieved information sent to the LLM \n - Answer - length: Limits the length of the generated response \n Important Considerations - \n Context Limitations: \n ```\n\n\n---\"\n\n\n**block-AC**\n\n#### Chunk: docs - > rag > advanced > widget > features\n``` max_tokens: the maximum number of - input tokens to put in the final context (including the prompt, the retrieved - results and the user question). \n max_output_tokens: the maximum number of - tokens to generate. \n ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: docs - > develop > js sdk > interfaces > ChatOptions\n``` \n optional max_tokens: - number \\| object \n \n Defines the maximum number of tokens that the model - will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 - \n \n min_score? \n ```\n\n\n---\"\n\n\n**block-AE**\n\n#### Chunk: docs > rag - > advanced > openai api compatible models\n``` \n \n Maximum supported input - tokens: \n Description: The maximum number of tokens that the model can accept - as input. Be mindful that this takes into account the tokens used in the prompt, - query and context. Also take note that some models may provide their context - window as the total between input and output tokens, while others may provide - it as the input tokens only. \n ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: - docs > develop > python sdk > 05 search\n``` \n SDK: \n \n ```python \n from - nuclia import sdk \n from nucliadb_models.search import AskRequest, Reasoning - \n search = sdk.NucliaSearch() \n query = AskRequest( \n query= My question - with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( \n - display=True, # Show reasoning in the response \n effort= low , # Can be low - , medium , or high \n budget_tokens=1024 # How many tokens reasoning can use - \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning - Options: \n ```\n\n\n---\"\n\n\n**block-AG**\n\n#### Chunk: docs > develop > - js sdk > interfaces > PredictAnswerOptions\n``` \n optional generative_model: - string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 - \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 - \n \n max_tokens? \n ```\n\n\n---\"\n\n\n**block-AH**\n\n#### Chunk: docs > - develop > js sdk > interfaces > ChatOptions\n``` \n optional highlight: boolean - \n \n Inherited from \n BaseSearchOptions.highlight \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:76 - \n \n keyword_filters? \n \n optional keyword_filters: string[] \\| Filter[] - \n \n Inherited from \n BaseSearchOptions.keyword_filters \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:65 - \n \n max_tokens? \n ```\n\n\n---\"\n\n\n**block-AI**\n\n#### Chunk: docs > - rag > advanced > openai api compatible models\n``` Description: The maximum - number of tokens that the model can generate as output. Again, we should keep - in mind that this value summed to the Maximum supported input tokens should - not exceed the total context size supported by the model. \n ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": false, "citation_threshold": null, "generative_model": - "chatgpt-azure-4o-mini", "max_tokens": 8192, "query_context_images": {}, "prefer_markdown": - null, "json_schema": {"title": "validate_or_answer", "description": "Validate - or answer", "parameters": {"type": "object", "properties": {"reason": {"type": - "string", "description": "Reasoning for the answer or validation"}, "answer": - {"type": "string", "description": "Partial or complete answer to the user query - from the information in the context."}, "missing_info_query": {"type": "string", - "description": "Query needed to retrieve the missing information in case the - context is not enough to answer the question. If the context does not answer - the question at all, just return the original question."}, "useful": {"type": - "string", "description": "Is the context useful to answer the question?", "enum": - ["yes", "no"]}, "citations": {"type": "array", "items": {"type": "string", "description": - "Block ID cited in the answer, e.g. block-AB"}, "description": "List of block - IDs cited in the answer, if any"}}, "required": ["reason", "answer", "missing_info_query", - "useful", "citations"]}}, "format_prompt": false, "rerank_context": false, "tools": - [], "tool_choice": {"type": "required"}, "reasoning": false, "seed": null}' + \n ```\n\n\n---\"\n\n\n**block-AG**\n\n#### Chunk: docs > develop > python sdk + > 05 search\n``` ::: \n :::warning \n Enabling reasoning can use additional + tokens, which may increase your usage costs. \n You may need to increase max_tokens + to give the LLM enough room to reason and generate an answer. \n ```\n\n\n---\"\n\n\n**block-AH**\n\n#### + Chunk: docs > rag > advanced > openai api compatible models\n``` \n \n Maximum + supported input tokens: \n Description: The maximum number of tokens that the + model can accept as input. Be mindful that this takes into account the tokens + used in the prompt, query and context. Also take note that some models may provide + their context window as the total between input and output tokens, while others + may provide it as the input tokens only. \n ```\n\n\n---\"\n\n\n**block-AI**\n\n#### + Chunk: docs > develop > js sdk > interfaces > ChatOptions\n``` \n optional + max_tokens: number \\| object \n \n Defines the maximum number of tokens that + the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \n \n min_score? \n ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": + false, "citation_threshold": null, "generative_model": "chatgpt-azure-4o-mini", + "max_tokens": 8192, "query_context_images": {}, "prefer_markdown": null, "json_schema": + {"title": "validate_or_answer", "description": "Validate or answer", "parameters": + {"type": "object", "properties": {"reason": {"type": "string", "description": + "Reasoning for the answer or validation"}, "answer": {"type": "string", "description": + "Partial or complete answer to the user query from the information in the context."}, + "missing_info_query": {"type": "string", "description": "Query needed to retrieve + the missing information in case the context is not enough to answer the question. + If the context does not answer the question at all, just return the original + question."}, "useful": {"type": "string", "description": "Is the context useful + to answer the question?", "enum": ["yes", "no"]}, "citations": {"type": "array", + "items": {"type": "string", "description": "Block ID cited in the answer, e.g. + block-AB"}, "description": "List of block IDs cited in the answer, if any"}}, + "required": ["reason", "answer", "missing_info_query", "useful", "citations"]}}, + "format_prompt": false, "rerank_context": false, "tools": [], "tool_choice": + {"type": "required"}, "reasoning": false, "seed": null}' headers: Accept: - application/x-ndjson @@ -232,11 +232,11 @@ interactions: Connection: - keep-alive Content-Length: - - '7700' + - '7535' Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-origin: @@ -246,19 +246,20 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"reason\":\"The context - provides information about the `max_tokens` parameter, explaining its use - in limiting context size and answer length. However, it does not provide a - direct link to the official documentation.\",\"answer\":\"El par\xE1metro - `max_tokens` se utiliza en el endpoint /ask para establecer l\xEDmites estrictos - en el tama\xF1o del contexto y en la longitud de la respuesta generada. Esto - significa que `max_tokens` limita la cantidad de informaci\xF3n recuperada - que se env\xEDa al modelo de lenguaje y tambi\xE9n limita la longitud de la - respuesta generada.\",\"missing_info_query\":\"\xBFCu\xE1l es el enlace a - la documentaci\xF3n oficial sobre el uso de `max_tokens`?\",\"useful\":\"yes\",\"citations\":[\"block-AB\",\"block-AC\"]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":46,\"output_tokens\":18,\"timings\":{\"generative\":2.8625618090009084},\"input_nuclia_tokens\":0.046,\"output_nuclia_tokens\":0.018}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.04581,\"output\":0.018,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" + provides information on how to use the `max_tokens` parameter, including its + purpose and considerations. However, it does not provide a direct link to + the official documentation.\",\"answer\":\"El par\xE1metro `max_tokens` se + utiliza en el endpoint /ask para establecer l\xEDmites en el tama\xF1o del + contexto y en la longitud de la respuesta generada. Este par\xE1metro limita + la cantidad de informaci\xF3n recuperada que se env\xEDa al modelo de lenguaje + y tambi\xE9n limita la longitud de la respuesta generada. Es importante tener + en cuenta que el valor de `max_tokens` sumado a los tokens de entrada no debe + exceder el tama\xF1o total del contexto soportado por el modelo.\",\"missing_info_query\":\"\xBFCu\xE1l + es el enlace a la documentaci\xF3n oficial sobre el par\xE1metro `max_tokens`?\",\"useful\":\"yes\",\"citations\":[\"block-AA\",\"block-AB\",\"block-AE\"]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":45,\"output_tokens\":22,\"timings\":{\"generative\":5.024970737998956},\"input_nuclia_tokens\":0.045,\"output_nuclia_tokens\":0.022}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.04488,\"output\":0.0216,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 @@ -269,17 +270,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:30 GMT + - Wed, 05 Aug 2026 08:09:56 GMT nuclia-learning-id: - - 10e7401f850c48a0afd895ed84ffd566 + - 7a38f8e9dd32443ca290185b45ac590e nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '2868' + - '5033' x-nuclia-trace-id: - - 78c408e0a8923f91d8d7bd15ba9dcd88 + - 97bebbe9e4eb4a72b92e307f9d75058e status: code: 200 message: OK @@ -293,27 +294,30 @@ interactions: this clearly\n\nAlways follow any additional instructions provided about format, style, or domain-specific behavior.", "chat_history": [], "context": [], "query_context": {}, "query_context_order": {}, "truncate": true, "user_prompt": {"prompt": "\n## - Question\nExplica el uso de `max_tokens` en espa\u00f1ol y proporciona un enlace - a la documentaci\u00f3n oficial.\n\n## Provided Context\n[START OF CONTEXT]\n## - Retrieval on nuclia-docs Knowledge Box\n\n# Explica el uso de `max_tokens` en - espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n oficial.\n\n El - par\u00e1metro `max_tokens` se utiliza en el endpoint /ask para establecer l\u00edmites - estrictos en el tama\u00f1o del contexto y en la longitud de la respuesta generada. - Esto significa que `max_tokens` limita la cantidad de informaci\u00f3n recuperada - que se env\u00eda al modelo de lenguaje y tambi\u00e9n limita la longitud de - la respuesta generada.\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully - read all context; it may be lengthy or detailed\n- Do not omit or overlook any - relevant information\n- Existing context summaries are answer attempts produced - by retrieval agents. Treat them as first-class evidence and preserve their supported - facts.\n- Combine complementary summaries from multiple contexts when the question - has multiple parts. Do not require every context to answer the whole question - by itself.\n- If a context summary directly answers the question, do not replace - it with an insufficient-data answer merely because one retrieved chunk is incomplete; - use the chunks for supporting citations.\n- If the context is incomplete or - insufficient, state: \"Not enough data to answer this.\"\n- Read carefully any - extra instructions below if provided and use them to answer\n\nNow provide your - answer to the question: Explica el uso de `max_tokens` en espa\u00f1ol y proporciona - un enlace a la documentaci\u00f3n oficial."}, "citations": null, "citation_threshold": + Question\nExplica c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol + y proporciona un enlace a la documentaci\u00f3n oficial.\n\n## Provided Context\n[START + OF CONTEXT]\n## Retrieval on nuclia-docs Knowledge Box\n\n# Explica c\u00f3mo + usar el par\u00e1metro `max_tokens` en espa\u00f1ol y proporciona un enlace + a la documentaci\u00f3n oficial.\n\n El par\u00e1metro `max_tokens` se utiliza + en el endpoint /ask para establecer l\u00edmites en el tama\u00f1o del contexto + y en la longitud de la respuesta generada. Este par\u00e1metro limita la cantidad + de informaci\u00f3n recuperada que se env\u00eda al modelo de lenguaje y tambi\u00e9n + limita la longitud de la respuesta generada. Es importante tener en cuenta que + el valor de `max_tokens` sumado a los tokens de entrada no debe exceder el tama\u00f1o + total del contexto soportado por el modelo.\n[END OF CONTEXT]\n\n## Answering + Guidelines\n- Carefully read all context; it may be lengthy or detailed\n- Do + not omit or overlook any relevant information\n- Existing context summaries + are answer attempts produced by retrieval agents. Treat them as first-class + evidence and preserve their supported facts.\n- Combine complementary summaries + from multiple contexts when the question has multiple parts. Do not require + every context to answer the whole question by itself.\n- If a context summary + directly answers the question, do not replace it with an insufficient-data answer + merely because one retrieved chunk is incomplete; use the chunks for supporting + citations.\n- If the context is incomplete or insufficient, state: \"Not enough + data to answer this.\"\n- Read carefully any extra instructions below if provided + and use them to answer\n\nNow provide your answer to the question: Explica c\u00f3mo + usar el par\u00e1metro `max_tokens` en espa\u00f1ol y proporciona un enlace + a la documentaci\u00f3n oficial."}, "citations": null, "citation_threshold": null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": null, "json_schema": null, "format_prompt": false, "rerank_context": false, "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": @@ -326,17 +330,17 @@ interactions: Connection: - keep-alive Content-Length: - - '2627' + - '2807' Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-client-ident: - default x-message: - - 0dfefb8a0b7b40f6a89fc902c85a8d80 + - 7bd1cbc3b0ac4748a0cad7661bcf202b x-origin: - RAO x-session: @@ -346,7 +350,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"text\",\"text\":\"El\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" @@ -356,16 +360,14 @@ interactions: en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" endpoint\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" /\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ask\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" para\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" establecer\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - l\xEDmites\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" estrict\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"os\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - tama\xF1o\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" del\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - contexto\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" y\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - longitud\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" respuesta\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - gener\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ada\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - Esto\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" significa\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - que\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" `\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"max\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"_tokens\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"`\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + l\xEDmites\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" tama\xF1o\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + del\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" contexto\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + y\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" longitud\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + respuesta\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" gener\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ada\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + Este\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" par\xE1\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"metro\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" limita\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" cantidad\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" informaci\xF3n\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" recuper\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ada\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" @@ -377,14 +379,29 @@ interactions: limita\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" longitud\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" respuesta\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - gener\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ada\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".\\n\\n\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"Para\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + gener\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ada\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + Es\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" importante\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + tener\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + cuenta\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" que\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" valor\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" `\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"max\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"_tokens\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"`\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + sum\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ado\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + a\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" los\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + tokens\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + entrada\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" no\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + debe\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" exced\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"er\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" tama\xF1o\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + total\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" del\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + contexto\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" soport\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ado\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + por\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + modelo\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".\\n\\n\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"Para\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" m\xE1s\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" informaci\xF3n\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\",\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" puedes\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" consultar\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" documentaci\xF3n\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - oficial\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" [\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"a\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"qu\xED\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"](\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"https\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"://\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"nu\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"cl\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ia\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".com\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"/docs\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\").\"}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":13,\"output_tokens\":11,\"timings\":{\"generative_first_chunk\":0.5319892059997073,\"generative\":1.600093567998556},\"input_nuclia_tokens\":0.013,\"output_nuclia_tokens\":0.011}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.01266,\"output\":0.01068,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" + oficial\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".\"}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":14,\"output_tokens\":13,\"timings\":{\"generative_first_chunk\":0.4219976280000992,\"generative\":1.8003466689988272},\"input_nuclia_tokens\":0.014,\"output_nuclia_tokens\":0.013}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.01371,\"output\":0.01284,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - - h3=":443"; ma=2592000 + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -392,17 +409,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:34 GMT + - Wed, 05 Aug 2026 08:10:02 GMT nuclia-learning-id: - - 37d96ad3949b41f78aed6026d5f7a024 + - e0ff422b19b64a198069582d47d83673 nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '539' + - '428' x-nuclia-trace-id: - - f9874cc775afb70717e61b611916b70e + - c88e5e3b762a13f9ec00fc2ae1886269 status: code: 200 message: OK diff --git a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple.yaml b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple.yaml index b104faa5..12f68137 100644 --- a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple.yaml +++ b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple.yaml @@ -9,29 +9,29 @@ interactions: Connection: - keep-alive Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.dp.stashify.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: - string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"da1740fa-ab3e-4971-b374-7bb31b5dd325","account_id":"39f5fa6e-680a-475e-a757-812597e86d06","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' + string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"9e1317aa-e212-4a59-b794-afee535458a6","account_id":"07c2de7c-fa77-4374-a461-eea314da9dfd","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' headers: Alt-Svc: - - h3=":443"; ma=2592000 + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - '227' content-type: - application/json date: - - Wed, 05 Aug 2026 07:56:56 GMT + - Wed, 05 Aug 2026 08:09:26 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '190' + - '86' status: code: 200 message: OK @@ -77,13 +77,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-client-ident: - default x-message: - - 8ed74a70fcdc44fda2e5768a74ef5b19 + - be08982cb83945a7933a4f69a8a5c618 x-origin: - RAO x-session: @@ -93,22 +93,21 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"rephrased_question\":\"Explica - c\xF3mo usar el par\xE1metro `max_tokens` para controlar la longitud de las - respuestas en espa\xF1ol y proporciona un enlace a la documentaci\xF3n oficial.\",\"rules\":[\"La - respuesta debe estar en espa\xF1ol.\",\"Incluye una explicaci\xF3n clara de - la funci\xF3n de `max_tokens`.\",\"Proporciona un enlace directo a la documentaci\xF3n - relevante.\"],\"reason\":\"La pregunta original es un poco ambigua al decir - \\\"max_tokens.answer\\\". La reformulaci\xF3n aclara que se refiere al par\xE1metro - `max_tokens` para controlar la longitud de las respuestas. Tambi\xE9n se enfatiza - la necesidad de la respuesta en espa\xF1ol y el enlace a la documentaci\xF3n, - lo cual ya estaba impl\xEDcito pero se hace expl\xEDcito para mayor claridad.\"}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":7,\"output_tokens\":14,\"timings\":{\"generative\":1.0897292209992884},\"input_nuclia_tokens\":0.007,\"output_nuclia_tokens\":0.014}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0071,\"output\":0.01384,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" + c\xF3mo usar el par\xE1metro `max_tokens` en espa\xF1ol, incluyendo un enlace + a la documentaci\xF3n oficial.\",\"rules\":[\"Proporcionar una explicaci\xF3n + clara y concisa del uso de `max_tokens`.\",\"Incluir un enlace directo a la + documentaci\xF3n oficial que trate sobre `max_tokens`.\",\"La respuesta debe + estar en espa\xF1ol.\"],\"reason\":\"La pregunta original es clara en su intenci\xF3n, + pero la reformulaci\xF3n la hace m\xE1s directa y especifica la necesidad + de la documentaci\xF3n oficial y el idioma de respuesta, lo cual asegura que + el agente RAG se centre en los aspectos m\xE1s importantes de la solicitud.\"}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":7,\"output_tokens\":12,\"timings\":{\"generative\":1.108321628998965},\"input_nuclia_tokens\":0.007,\"output_nuclia_tokens\":0.012}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0071,\"output\":0.01232,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -116,17 +115,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:56:56 GMT + - Wed, 05 Aug 2026 08:09:27 GMT nuclia-learning-id: - - 838119e9aa2e412896d6d3f6fb031f57 + - 9ae8deaa701c4e8e9f79938c5d4b45bb nuclia-learning-model: - gemini-2.5-flash-lite via: - 1.1 google x-envoy-upstream-service-time: - - '1096' + - '1128' x-nuclia-trace-id: - - e960ac37fbef63af9c8e7b481a41d3f8 + - 193468b6e72ffcae7241e7afef4830ad status: code: 200 message: OK @@ -140,35 +139,35 @@ interactions: Connection: - keep-alive Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-stf-nuakey: - DUMMY method: GET - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/tokens?model=multilingual&text=Explica+c%C3%B3mo+usar+el+par%C3%A1metro+%60max_tokens%60+para+controlar+la+longitud+de+las+respuestas+en+espa%C3%B1ol+y+proporciona+un+enlace+a+la+documentaci%C3%B3n+oficial. + uri: https://europe-1.dp.progress.cloud/api/v1/predict/tokens?model=multilingual&text=Explica+c%C3%B3mo+usar+el+par%C3%A1metro+%60max_tokens%60+en+espa%C3%B1ol%2C+incluyendo+un+enlace+a+la+documentaci%C3%B3n+oficial. response: body: - string: "{\"tokens\":[{\"text\":\"espa\xF1ol\",\"ner\":\"LANGUAGE\",\"start\":92,\"end\":99}],\"time\":0.009359359741210938,\"input_tokens\":36}" + string: "{\"tokens\":[{\"text\":\"espa\xF1ol\",\"ner\":\"LANGUAGE\",\"start\":47,\"end\":54}],\"time\":0.09751224517822266,\"input_tokens\":28}" headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Content-Length: - - '115' + - '114' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 05 Aug 2026 07:56:58 GMT + - Wed, 05 Aug 2026 08:09:28 GMT nuclia-learning-model: - multilingual via: - 1.1 google x-envoy-upstream-service-time: - - '16' + - '114' x-nuclia-trace-id: - - b146c40f938c36e41f8ce06ba3cc8959 + - 84baf889a4ecb1a482bd247299b78b37 status: code: 200 message: OK @@ -178,46 +177,45 @@ interactions: {}, "truncate": true, "user_prompt": {"prompt": "\n\nInformation about the KB:\n\n# nuclia-docs\n\ndescription: Documentation of the Nuclia API, recipies, reference \n\nAnd given the question: Explica c\u00f3mo usar el par\u00e1metro `max_tokens` - para controlar la longitud de las respuestas en espa\u00f1ol y proporciona un - enlace a la documentaci\u00f3n oficial.\n\n## labels: {''pmm'': [''Videos'', - ''Partner Content'', ''Softcat'', ''Sales Enablement Assets'', ''KO 26'', ''Data - Sheets'', ''Progress Agentic RAG Training Materials 2026'']}\n\n## Facets:\n\n## - Content Types\nThe following content types are available in the KB:\n\n- /n/i: - 994\n- application/json: 1\n- text/markdown: 993\nThe following languages are - available in the KB:\n\n- ca: 4\n- cy: 1\n- da: 1\n- en: 974\n- eo: 4\n- la: - 7\n- nb: 1\n- tl: 1\n- yo: 1\n\n\n# Important rules to follow\n\n\nprompt=''Be - polite''\n"}, "citations": false, "citation_threshold": null, "generative_model": - "gemini-2.5-flash", "max_tokens": 8192, "query_context_images": {}, "prefer_markdown": - null, "json_schema": {"title": "ask_configuration", "description": "Configuration - extracted from reasoning engine", "parameters": {"type": "object", "properties": - {"link": {"type": "boolean", "description": "The user wants link reference to - the answer?"}, "knowledge_scan": {"type": "string", "description": "If the query - requires a knowledge aggregation or scan search to answer define the entities, - labels and relations to query in the KB. Example queries: How many ..."}, "semantic_query": - {"type": "string", "description": "Rephrase this question so its better for - semantic retrieval, and keep the rephrased question in the same language as - the original. Please define ONLY the question without any explanation. JUST - A SENTENCE. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST ONE SENTENCE"}, "lexical_query": - {"type": "string", "description": "Rephrase this question so its better for - lexical retrieval, translate the lexical rephrased question to cy. Please define - ONLY the question without any explanation. JUST A SENTENCE. DO NOT ADD ANY EXTRA - NOTES AT THE END, JUST ONE SENTENCE"}, "visual": {"type": "boolean", "description": - "Is required an analysis of an image to answer this question, answer with false - or true"}, "keywords_filter": {"type": "array", "items": {"type": "string"}, - "description": "Extract if any the keywords that should appear on the retrieved - results and its a must match, make sure that are keywords that are not common - words, and that are not the same as the question or answer. Please define ONLY - the keywords without any explanation. Only one or two words maximum. JUST A - LIST OF KEYWORDS. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST A LIST OF KEYWORDS"}, - "reason": {"type": "string"}, "entities": {"type": "array", "description": "Entities - related to the user question to query in the KB", "items": {"type": "string"}}, - "relations": {"type": "array", "description": "Relations related to the user - question to query in the KB", "items": {"type": "string"}}, "pre_queries": {"type": - "array", "items": {"type": "string"}, "description": "Pre queries to run before - the main query to gather more information"}}, "required": ["semantic_query", - "lexical_query", "visual", "keywords_filter", "reason", "pre_queries"]}}, "format_prompt": - false, "rerank_context": false, "tools": [], "tool_choice": {"type": "required"}, - "reasoning": false, "seed": null}' + en espa\u00f1ol, incluyendo un enlace a la documentaci\u00f3n oficial.\n\n## + labels: {''pmm'': [''Videos'', ''Partner Content'', ''Softcat'', ''Sales Enablement + Assets'', ''KO 26'', ''Data Sheets'', ''Progress Agentic RAG Training Materials + 2026'']}\n\n## Facets:\n\n## Content Types\nThe following content types are + available in the KB:\n\n- /n/i: 994\n- application/json: 1\n- text/markdown: + 993\nThe following languages are available in the KB:\n\n- ca: 4\n- cy: 1\n- + da: 1\n- en: 974\n- eo: 4\n- la: 7\n- nb: 1\n- tl: 1\n- yo: 1\n\n\n# Important + rules to follow\n\n\nprompt=''Be polite''\n"}, "citations": false, "citation_threshold": + null, "generative_model": "gemini-2.5-flash", "max_tokens": 8192, "query_context_images": + {}, "prefer_markdown": null, "json_schema": {"title": "ask_configuration", "description": + "Configuration extracted from reasoning engine", "parameters": {"type": "object", + "properties": {"link": {"type": "boolean", "description": "The user wants link + reference to the answer?"}, "knowledge_scan": {"type": "string", "description": + "If the query requires a knowledge aggregation or scan search to answer define + the entities, labels and relations to query in the KB. Example queries: How + many ..."}, "semantic_query": {"type": "string", "description": "Rephrase this + question so its better for semantic retrieval, and keep the rephrased question + in the same language as the original. Please define ONLY the question without + any explanation. JUST A SENTENCE. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST + ONE SENTENCE"}, "lexical_query": {"type": "string", "description": "Rephrase + this question so its better for lexical retrieval, translate the lexical rephrased + question to cy. Please define ONLY the question without any explanation. JUST + A SENTENCE. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST ONE SENTENCE"}, "visual": + {"type": "boolean", "description": "Is required an analysis of an image to answer + this question, answer with false or true"}, "keywords_filter": {"type": "array", + "items": {"type": "string"}, "description": "Extract if any the keywords that + should appear on the retrieved results and its a must match, make sure that + are keywords that are not common words, and that are not the same as the question + or answer. Please define ONLY the keywords without any explanation. Only one + or two words maximum. JUST A LIST OF KEYWORDS. DO NOT ADD ANY EXTRA NOTES AT + THE END, JUST A LIST OF KEYWORDS"}, "reason": {"type": "string"}, "entities": + {"type": "array", "description": "Entities related to the user question to query + in the KB", "items": {"type": "string"}}, "relations": {"type": "array", "description": + "Relations related to the user question to query in the KB", "items": {"type": + "string"}}, "pre_queries": {"type": "array", "items": {"type": "string"}, "description": + "Pre queries to run before the main query to gather more information"}}, "required": + ["semantic_query", "lexical_query", "visual", "keywords_filter", "reason", "pre_queries"]}}, + "format_prompt": false, "rerank_context": false, "tools": [], "tool_choice": + {"type": "required"}, "reasoning": false, "seed": null}' headers: Accept: - application/x-ndjson @@ -226,17 +224,17 @@ interactions: Connection: - keep-alive Content-Length: - - '3420' + - '3373' Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-client-ident: - default x-message: - - 8ed74a70fcdc44fda2e5768a74ef5b19 + - be08982cb83945a7933a4f69a8a5c618 x-origin: - RAO x-session: @@ -246,17 +244,16 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: - string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"link\":true,\"semantic_query\":\"Explica - el uso del par\xE1metro `max_tokens` para controlar la longitud de las respuestas - y proporciona un enlace a la documentaci\xF3n oficial.\",\"lexical_query\":\"Sut - i ddefnyddio'r paramedr `max_tokens` i reoli hyd ymatebion a darparu dolen - i'r ddogfennaeth swyddogol?\",\"visual\":false,\"keywords_filter\":[\"max_tokens\",\"longitud\",\"respuestas\"],\"reason\":\"The - user is asking how to use a specific parameter (`max_tokens`) to control the - length of responses and wants a link to the official documentation. This requires - a semantic search for the parameter's usage and a link.\",\"pre_queries\":[]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":36,\"output_tokens\":97,\"timings\":{\"generative\":1.6855239240012452},\"input_nuclia_tokens\":0.036,\"output_nuclia_tokens\":0.097}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.03564,\"output\":0.097,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" + string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"link\":true,\"semantic_query\":\"Expl\xEDcame + c\xF3mo utilizar el par\xE1metro `max_tokens` y d\xF3nde encontrar su documentaci\xF3n + oficial.\",\"lexical_query\":\"Sut hawl defnyddio'r paramedr `max_tokens` + yn y ddogfennaeth swyddogol?\",\"visual\":false,\"keywords_filter\":[\"max_tokens\",\"par\xE1metro\"],\"reason\":\"La + pregunta pide una explicaci\xF3n sobre el uso de `max_tokens` y un enlace + a la documentaci\xF3n oficial, por lo que la recuperaci\xF3n sem\xE1ntica + y l\xE9xica debe enfocarse en esos t\xE9rminos.\",\"entities\":[],\"relations\":[],\"pre_queries\":[]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":35,\"output_tokens\":86,\"timings\":{\"generative\":1.704163222995703},\"input_nuclia_tokens\":0.035,\"output_nuclia_tokens\":0.086}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.03522,\"output\":0.0865,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - h3=":443"; ma=2592000 @@ -267,103 +264,55 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:56:58 GMT + - Wed, 05 Aug 2026 08:09:28 GMT nuclia-learning-id: - - a7e8d9326fd649fdaf69d8c6dd824a2e + - 11c37d9ef4b74b36971d4441fdcf9fa8 nuclia-learning-model: - gemini-2.5-flash via: - 1.1 google x-envoy-upstream-service-time: - - '1692' + - '1722' x-nuclia-trace-id: - - 96862f234d56fe6dab0110cbd5a26d36 + - 623be6c00fe1043b6ce09bd614b8e13c status: code: 200 message: OK - request: - body: '{"question": "Explica c\u00f3mo usar el par\u00e1metro `max_tokens` para - controlar la longitud de las respuestas en espa\u00f1ol y proporciona un enlace - a la documentaci\u00f3n oficial.", "user_id": "arag-ask-rerank", "context": - {"c27a1e5f5ddb4b118921345d713401b8/t/page/351-554": " full: boolean \n \n Defined - in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:386 \n \n max_messages? \n \n - optional max_messages: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:387 - \n \n name \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ConversationalStrategy\n", - "dd41482018924facb5dbb87a7d53f122/t/page/3310-3757": " ) \n time.sleep(wait_time) - \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( - Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers - = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_try_after_info(url, - headers) \n print(data) \n ``` \n These examples demonstrate how to handle rate - limits effectively, ensuring that your application respects the limits and retries - appropriately.\n\n\nLink: https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\n", - "dd41482018924facb5dbb87a7d53f122/t/page/1900-2653": " retries = 0 \n while - retries < max_retries: \n response = requests.get(url, headers=headers) \n if - response.status_code == 200: \n return response.json() \n elif response.status_code - == 429: \n wait_time = 2 retries # Exponential backoff: 2^retries \n print(f - Rate limit exceeded. Retrying in {wait_time} seconds... ) \n time.sleep(wait_time) - \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( - Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers - = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_exponential_backoff(url, - headers) \n print(data) \n ``` \n Example 2: Ingestion back pressure limits - \n Here''s an example of how to use the try_after key from the response to manage - rate limits: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\n", - "4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340": " Use the max_tokens parameter - on the /ask endpoint to set hard limits on: \n - Context size: Limits the amount - of retrieved information sent to the LLM \n - Answer length: Limits the length - of the generated response \n Important Considerations \n Context Limitations: - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", - "4039d76b0fff4962900836ab3fdec9f7/t/page/3340-4136": " - Restricting context - size may result in less relevant answers since the LLM has less information - to work with \n - Balance between cost control and answer quality \n Answer - Length Limitations: \n - The LLM might not complete its response if it hits - the token limit, potentially cutting sentences mid-way \n - Recommended approach: - Include length requirements in your prompt (e.g., Please answer in less than - 200 words ) rather than relying solely on hard limits \n - This allows the LLM - to naturally conclude its response within the desired length \n How to Monitor - Token Consumption \n Understanding Token Consumption Data \n You can receive - detailed token consumption information from the following endpoints that utilize - LLM models: ask, chat, remi, query, sentence, summarize, tokens, and rerank. - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", - "4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326": " \n Large context: Results - from using RAG strategies like Full resource or Neighbouring paragraphs , or - from using the extra_context parameter \n Long questions: More detailed or complex - questions require more input tokens \n Long prompts: Extensive system prompts - increase the input token count \n Detailed answers: Comprehensive responses - require more output tokens \n Images in context: When using multimodal models, - images included in the retrieved context significantly increase token consumption - \n \n How to Limit and Control Token Consumption \n Strategy 1: Optimize Your - Parameters \n The first approach to reducing token consumption is to fine-tune - your request parameters: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", - "4039d76b0fff4962900836ab3fdec9f7/t/page/5396-5615": " - input: Tokens used - for the prompt, context, and question \n - output: Tokens used for the generated - response \n - image: Tokens used for image processing (when applicable) \n Customer - Key Tokens (customer_key_tokens): \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", - "b6a6202b9f0d4611a980293ce53337d6/t/page/265-405": " last: boolean \n \n page - \n \n page: number \n \n size \n \n size: number \n \n Defined in \n libs/sdk-core/src/lib/db/training/training.models.ts:36\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/TrainingExecutions\n", - "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709": " ::: \n :::warning \n - Enabling reasoning can use additional tokens, which may increase your usage - costs. \n You may need to increase max_tokens to give the LLM enough room to - reason and generate an answer. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n", - "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276": " \n SDK: \n \n ```python - \n from nuclia import sdk \n from nucliadb_models.search import AskRequest, - Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( \n query= My - question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( - \n display=True, # Show reasoning in the response \n effort= low , # Can be - low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can - use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning - Options: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n", - "44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668": " \n step: Information - about the current processing step \n module: The module being executed (e.g., - rephrase , basic_ask , remi ) \n title: Display title for the step \n value: - Result of the step \n reason: Explanation for the step \n timeit: Time taken - in seconds \n \n input_nuclia_tokens/output_nuclia_tokens: Token usage \n \n - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/rao\n", - "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221": " \n optional max_tokens: - number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined - in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", + body: '{"question": "Explica c\u00f3mo usar el par\u00e1metro `max_tokens` en + espa\u00f1ol, incluyendo un enlace a la documentaci\u00f3n oficial.", "user_id": + "arag-ask-rerank", "context": {"666b3a9d01f74323b6ca6c9939834bec/t/page/0-1386": + "@nuclia/core / Exports / StatsType \n Enumeration: StatsType \n Deprecated + \n Table of contents \n Enumeration Members \n \n AI_TOKENS_USED \n BYTES \n + CHARS \n DOCS_NO_MEDIA \n MEDIA_SECONDS \n PAGES \n PROCESSING_TIME \n RESOURCES + \n SEARCHES \n SUGGESTIONS \n TRAIN_SECONDS \n \n Enumeration Members \n AI_TOKENS_USED + \n \u2022 AI_TOKENS_USED = ai_tokens_used \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:206 + \n \n BYTES \n \u2022 BYTES = bytes \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:200 + \n \n CHARS \n \u2022 CHARS = chars \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:198 + \n \n DOCS_NO_MEDIA \n \u2022 DOCS_NO_MEDIA = docs_no_media \n Defined in \n + libs/sdk-core/src/lib/db/db.models.ts:205 \n \n MEDIA_SECONDS \n \u2022 MEDIA_SECONDS + = media_seconds \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:199 \n + \n PAGES \n \u2022 PAGES = pages \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:202 + \n \n PROCESSING_TIME \n \u2022 PROCESSING_TIME = processing_time \n Defined + in \n libs/sdk-core/src/lib/db/db.models.ts:196 \n \n RESOURCES \n \u2022 RESOURCES + = resources \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:201 \n \n + SEARCHES \n \u2022 SEARCHES = searches \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:197 + \n \n SUGGESTIONS \n \u2022 SUGGESTIONS = suggestions \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:204 + \n \n TRAIN_SECONDS \n \u2022 TRAIN_SECONDS = train_seconds \n Defined in \n + libs/sdk-core/src/lib/db/db.models.ts:203\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/enums/StatsType\n", + "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043": " Description: The maximum + number of tokens that the model can generate as output. Again, we should keep + in mind that this value summed to the Maximum supported input tokens should + not exceed the total context size supported by the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", + "9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412": " max_tokens: the maximum + number of input tokens to put in the final context (including the prompt, the + retrieved results and the user question). \n max_output_tokens: the maximum + number of tokens to generate. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n", + "0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349": "@nuclia/core \u2022 Docs \n + \n @nuclia/core / Consumption \n Interface: Consumption \n Properties \n customer_key_tokens + \n \n customer_key_tokens: TokenConsumption \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:230 + \n \n normalized_tokens \n \n normalized_tokens: TokenConsumption \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:229\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Consumption\n", "43004f553e534ffe9c9e735856bd9b23/t/page/480-703": " \n optional max_images: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \n \n output_tokens \n \n output_tokens: object \n \n default_max? \n \n optional @@ -374,32 +323,105 @@ interactions: \n \n input_tokens: object \n \n max \n \n max: number \n \n min? \n \n optional min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 \n \n max_images? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n", + "e8525e64c5b44982b958d32cf6090613/t/page/2808-3011": " \n optional max_tokens: + number \\| object \n \n Defines the maximum number of tokens that the model + will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n", + "e8525e64c5b44982b958d32cf6090613/t/page/2450-2808": " \n optional highlight: + boolean \n \n Inherited from \n BaseSearchOptions.highlight \n Defined in \n + libs/sdk-core/src/lib/db/search/search.models.ts:76 \n \n keyword_filters? \n + \n optional keyword_filters: string[] \\| Filter[] \n \n Inherited from \n BaseSearchOptions.keyword_filters + \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:65 \n \n max_tokens? + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n", + "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221": " \n optional max_tokens: + number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", + "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977": " \n optional generative_model: + string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 + \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 + \n \n max_tokens? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", "f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299": "@nuclia/core \u2022 Docs \n \n @nuclia/core / PageToken \n Interface: PageToken \n Properties \n height \n \n height: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 \n \n line \n \n line: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 \n \n text \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageToken\n", - "9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412": " max_tokens: the maximum - number of input tokens to put in the final context (including the prompt, the - retrieved results and the user question). \n max_output_tokens: the maximum - number of tokens to generate. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n", - "e8525e64c5b44982b958d32cf6090613/t/page/2808-3011": " \n optional max_tokens: - number \\| object \n \n Defines the maximum number of tokens that the model - will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 - \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n", - "89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575": " \n \n Maximum supported - input tokens: \n Description: The maximum number of tokens that the model can - accept as input. Be mindful that this takes into account the tokens used in - the prompt, query and context. Also take note that some models may provide their - context window as the total between input and output tokens, while others may - provide it as the input tokens only. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", - "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043": " Description: The maximum - number of tokens that the model can generate as output. Again, we should keep - in mind that this value summed to the Maximum supported input tokens should - not exceed the total context size supported by the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", - "42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696": " \n optional max_paragraph: - number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 \n \n - name? \n \n optional name: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\n\n\nLink: + "24ad6997e1fe4a109d67d7802a083678/a/title/0-55": "docs > develop > js sdk > + interfaces > TokenConsumption\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/TokenConsumption\n", + "6e8250e6b5264156988657a221fd5e94/t/page/0-397": "@nuclia/core \u2022 Docs \n + \n @nuclia/core / Ask / ConsumptionAskResponseItem \n Interface: ConsumptionAskResponseItem + \n Properties \n customer_key_tokens \n \n customer_key_tokens: TokenConsumption + \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:127 \n \n + normalized_tokens \n \n normalized_tokens: TokenConsumption \n \n Defined in + \n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \n \n type \n \n\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/namespaces/Ask/interfaces/ConsumptionAskResponseItem\n", + "7b41750917e349598c846526162ebb68/a/title/0-58": "docs > develop > js sdk > + interfaces > NucliaTokensDetails\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/NucliaTokensDetails\n", + "4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340": " Use the max_tokens parameter + on the /ask endpoint to set hard limits on: \n - Context size: Limits the amount + of retrieved information sent to the LLM \n - Answer length: Limits the length + of the generated response \n Important Considerations \n Context Limitations: + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", + "328ed5b87692439a881303c7c1d4eefc/a/title/0-52": "docs > develop > js sdk > + interfaces > Ask.AskTokens\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Ask.AskTokens\n", + "66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833": "@nuclia/core \u2022 Docs + \n \n @nuclia/core / UsageType \n Enumeration: UsageType \n Enumeration Members + \n AI_TOKENS_USED \n \n AI_TOKENS_USED: ai_tokens_used \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:208 + \n \n BYTES_PROCESSED \n \n BYTES_PROCESSED: bytes_processed \n \n Defined in + \n libs/sdk-core/src/lib/db/db.models.ts:199 \n \n CHARS_PROCESSED \n \n CHARS_PROCESSED: + chars_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:200 + \n \n MEDIA_FILES_PROCESSED \n \n MEDIA_FILES_PROCESSED: media_files_processed + \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:202 \n \n MEDIA_SECONDS_PROCESSED + \n \n MEDIA_SECONDS_PROCESSED: media_seconds_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:201 + \n \n NUCLIA_TOKENS \n \n NUCLIA_TOKENS: nuclia_tokens_billed \n \n Defined + in \n libs/sdk-core/src/lib/db/db.models.ts:209 \n \n PAGES_PROCESSED \n \n + PAGES_PROCESSED: pages_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:203 + \n \n PARAGRAPHS_PROCESSED \n \n PARAGRAPHS_PROCESSED: paragraphs_processed + \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:204 \n \n PRE_PROCESSING_TIME + \n \n PRE_PROCESSING_TIME: pre_processing_time \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:196 + \n \n RESOURCES_PROCESSED \n \n RESOURCES_PROCESSED: resources_processed \n + \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:198 \n \n SEARCHES_PERFORMED + \n \n SEARCHES_PERFORMED: searches_performed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:206 + \n \n SLOW_PROCESSING_TIME \n \n SLOW_PROCESSING_TIME: slow_processing_time + \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:197 \n \n SUGGESTIONS_PERFORMED + \n \n SUGGESTIONS_PERFORMED: suggestions_performed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:207 + \n \n TRAIN_SECONDS \n \n TRAIN_SECONDS: train_seconds \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:205\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/enumerations/UsageType\n", + "0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224": "@nuclia/core \u2022 Docs \n + \n @nuclia/core / ReasoningConfig \n Interface: ReasoningConfig \n Properties + \n budget_tokens? \n \n optional budget_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 + \n \n effort? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ReasoningConfig\n", + "b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139": "@nuclia/core / Exports / + UsageType \n Enumeration: UsageType \n Table of contents \n Enumeration Members + \n \n AI_TOKENS_USED \n BYTES_PROCESSED \n CHARS_PROCESSED \n MEDIA_FILES_PROCESSED + \n MEDIA_SECONDS_PROCESSED \n NUCLIA_TOKENS \n PAGES_PROCESSED \n PARAGRAPHS_PROCESSED + \n PRE_PROCESSING_TIME \n RESOURCES_PROCESSED \n SEARCHES_PERFORMED \n SLOW_PROCESSING_TIME + \n SUGGESTIONS_PERFORMED \n TRAIN_SECONDS \n \n Enumeration Members \n AI_TOKENS_USED + \n \u2022 AI_TOKENS_USED = ai_tokens_used \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:190 + \n \n BYTES_PROCESSED \n \u2022 BYTES_PROCESSED = bytes_processed \n Defined + in \n libs/sdk-core/src/lib/db/db.models.ts:181 \n \n CHARS_PROCESSED \n \u2022 + CHARS_PROCESSED = chars_processed \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:182 + \n \n MEDIA_FILES_PROCESSED \n \u2022 MEDIA_FILES_PROCESSED = media_files_processed + \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:184 \n \n MEDIA_SECONDS_PROCESSED + \n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \n Defined in \n + libs/sdk-core/src/lib/db/db.models.ts:183 \n \n NUCLIA_TOKENS \n \u2022 NUCLIA_TOKENS + = nuclia_tokens_billed \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:191 + \n \n PAGES_PROCESSED \n \u2022 PAGES_PROCESSED = pages_processed \n Defined + in \n libs/sdk-core/src/lib/db/db.models.ts:185 \n \n PARAGRAPHS_PROCESSED \n + \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:186 + \n \n PRE_PROCESSING_TIME \n \u2022 PRE_PROCESSING_TIME = pre_processing_time + \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:178 \n \n RESOURCES_PROCESSED + \n \u2022 RESOURCES_PROCESSED = resources_processed \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:180 + \n \n SEARCHES_PERFORMED \n \u2022 SEARCHES_PERFORMED = searches_performed \n + Defined in \n libs/sdk-core/src/lib/db/db.models.ts:188 \n \n SLOW_PROCESSING_TIME + \n \u2022 SLOW_PROCESSING_TIME = slow_processing_time \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:179 + \n \n SUGGESTIONS_PERFORMED \n \u2022 SUGGESTIONS_PERFORMED = suggestions_performed + \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:189 \n \n TRAIN_SECONDS + \n \u2022 TRAIN_SECONDS = train_seconds \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:187\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/enums/UsageType\n", "42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696": + " \n optional max_paragraph: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 + \n \n name? \n \n optional name: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/SplitStrategy\n"}}' headers: Accept: @@ -409,39 +431,39 @@ interactions: Connection: - keep-alive Content-Length: - - '9962' + - '12751' Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/rerank + uri: https://europe-1.dp.progress.cloud/api/v1/predict/rerank response: body: - string: '{"context_scores":{"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340":0.8265718221664429,"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412":0.3453260064125061,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276":0.13741667568683624,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709":0.11536139249801636,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221":0.09619516134262085,"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011":0.08525123447179794,"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757":0.033148519694805145,"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043":0.0326513797044754,"43004f553e534ffe9c9e735856bd9b23/t/page/212-480":0.020964240655303,"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575":0.02025469020009041,"4039d76b0fff4962900836ab3fdec9f7/t/page/3340-4136":0.012771867215633392,"dd41482018924facb5dbb87a7d53f122/t/page/1900-2653":0.011508149094879627,"4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326":0.009485713206231594,"43004f553e534ffe9c9e735856bd9b23/t/page/480-703":0.009055264294147491,"4039d76b0fff4962900836ab3fdec9f7/t/page/5396-5615":0.005797401536256075,"c27a1e5f5ddb4b118921345d713401b8/t/page/351-554":0.003350423648953438,"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696":0.0013096056645736098,"44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668":0.000661517377011478,"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299":0.0003514382697176188,"b6a6202b9f0d4611a980293ce53337d6/t/page/265-405":0.0001956353517016396}}' + string: '{"context_scores":{"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412":0.46481049060821533,"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340":0.4441126585006714,"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011":0.18639107048511505,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221":0.15830442309379578,"e8525e64c5b44982b958d32cf6090613/t/page/2450-2808":0.1296229362487793,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977":0.11797800660133362,"43004f553e534ffe9c9e735856bd9b23/t/page/212-480":0.09434341639280319,"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043":0.06853749603033066,"43004f553e534ffe9c9e735856bd9b23/t/page/480-703":0.041695769876241684,"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139":0.029256708920001984,"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833":0.023419944569468498,"666b3a9d01f74323b6ca6c9939834bec/t/page/0-1386":0.015663648024201393,"328ed5b87692439a881303c7c1d4eefc/a/title/0-52":0.006744989659637213,"7b41750917e349598c846526162ebb68/a/title/0-58":0.005426943302154541,"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349":0.004231587518006563,"24ad6997e1fe4a109d67d7802a083678/a/title/0-55":0.0037072529084980488,"6e8250e6b5264156988657a221fd5e94/t/page/0-397":0.0032730652019381523,"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696":0.003039649687707424,"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224":0.0016356753185391426,"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299":0.0014895173953846097}}' headers: Alt-Svc: - - h3=":443"; ma=2592000 + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - - '1454' + - '1428' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 05 Aug 2026 07:57:01 GMT + - Wed, 05 Aug 2026 08:09:31 GMT nuclia-learning-model: - bge-reranker-v2-m3 via: - 1.1 google x-envoy-upstream-service-time: - - '95' + - '170' x-nuclia-trace-id: - - 338f5c8e8ab5c4e13ad42dc6fa176198 + - d4ee701a6eec616fe4d6fda69c8a5f81 status: code: 200 message: OK @@ -480,40 +502,46 @@ interactions: \"block-CD\"]).\n11. **IMPORTANT** If any extra instructions are provided, you MUST follow them carefully when generating the answer field. These instructions may specify the format, style, tools to use, or other requirements for the answer.\n\n\nExplica - c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar la longitud de - las respuestas en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n - oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### Chunk: 4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\nTags: + c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol, incluyendo un + enlace a la documentaci\u00f3n oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### + Chunk: 9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\nTags: /k/text\n``` max_tokens: + the maximum number of input tokens to put in the final context (including the + prompt, the retrieved results and the user question). \n max_output_tokens: + the maximum number of tokens to generate. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n + ```\n\n\n---\"\n\n\n**block-AB**\n\n#### Chunk: 4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\nTags: /k/text\n``` Use the max_tokens parameter on the /ask endpoint to set hard limits on: \n - Context size: Limits the amount of retrieved information sent to the LLM \n - Answer length: Limits the length of the generated response \n Important Considerations \n Context Limitations: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n - ```\n\n\n---\"\n\n\n**block-AB**\n\n#### Chunk: 9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\nTags: - /k/text\n``` max_tokens: the maximum number of input tokens to put in the final - context (including the prompt, the retrieved results and the user question). - \n max_output_tokens: the maximum number of tokens to generate. \n\n\n\nLink: - https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n ```\n\n\n---\"\n\n\n**block-AC**\n\n#### - Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\nTags: /k/text\n``` \n - SDK: \n \n ```python \n from nuclia import sdk \n from nucliadb_models.search - import AskRequest, Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( - \n query= My question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( - \n display=True, # Show reasoning in the response \n effort= low , # Can be - low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can - use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning - Options: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n - ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\nTags: - /k/text\n``` ::: \n :::warning \n Enabling reasoning can use additional tokens, - which may increase your usage costs. \n You may need to increase max_tokens - to give the LLM enough room to reason and generate an answer. \n\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n ```\n\n\n---\"\n\n\n**block-AE**\n\n#### - Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\nTags: /k/text\n``` \n - optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined - in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n - ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\nTags: + ```\n\n\n---\"\n\n\n**block-AC**\n\n#### Chunk: e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\nTags: /k/text\n``` \n optional max_tokens: number \\| object \n \n Defines the maximum number of tokens that the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n + ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\nTags: + /k/text\n``` \n optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? + \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n + ```\n\n\n---\"\n\n\n**block-AE**\n\n#### Chunk: e8525e64c5b44982b958d32cf6090613/t/page/2450-2808\nTags: + /k/text\n``` \n optional highlight: boolean \n \n Inherited from \n BaseSearchOptions.highlight + \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:76 \n \n keyword_filters? + \n \n optional keyword_filters: string[] \\| Filter[] \n \n Inherited from \n + BaseSearchOptions.keyword_filters \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:65 + \n \n max_tokens? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n + ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\nTags: + /k/text\n``` \n optional generative_model: string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 + \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 + \n \n max_tokens? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n + ```\n\n\n---\"\n\n\n**block-AG**\n\n#### Chunk: 43004f553e534ffe9c9e735856bd9b23/t/page/212-480\nTags: + /k/text\n``` \n optional driver: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 + \n \n input_tokens \n \n input_tokens: object \n \n max \n \n max: number \n + \n min? \n \n optional min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \n \n max_images? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n + ```\n\n\n---\"\n\n\n**block-AH**\n\n#### Chunk: 89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\nTags: + /k/text\n``` Description: The maximum number of tokens that the model can generate + as output. Again, we should keep in mind that this value summed to the Maximum + supported input tokens should not exceed the total context size supported by + the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": false, "citation_threshold": null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 8192, "query_context_images": {}, "prefer_markdown": null, "json_schema": {"title": "validate_or_answer", @@ -539,11 +567,11 @@ interactions: Connection: - keep-alive Content-Length: - - '6987' + - '7833' Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-origin: @@ -553,19 +581,19 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"reason\":\"The context - provides information on how to use the `max_tokens` parameter to control the - length of responses. It specifies that `max_tokens` sets limits on the answer - length and context size. Additionally, it includes links to the official documentation - for further details.\",\"answer\":\"Para usar el par\xE1metro `max_tokens`, - se debe establecer un l\xEDmite en la longitud de la respuesta generada. El - par\xE1metro `max_tokens` se utiliza en el endpoint /ask para limitar la longitud - de la respuesta generada. Tambi\xE9n se puede usar para limitar el tama\xF1o - del contexto. Para m\xE1s detalles, puedes consultar la documentaci\xF3n oficial - en el siguiente enlace: https://docs.rag.progress.cloud/docs/rag/advanced/consumption.\",\"missing_info_query\":\"\",\"useful\":\"yes\",\"citations\":[\"block-AA\",\"block-AB\"]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":45,\"output_tokens\":20,\"timings\":{\"generative\":4.430337170000712},\"input_nuclia_tokens\":0.045,\"output_nuclia_tokens\":0.02}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.04521,\"output\":0.0198,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" + provides detailed information about the `max_tokens` parameter, including + its purpose and links to official documentation. It explains that `max_tokens` + sets limits on context size and answer length, which directly addresses the + user's question about how to use this parameter.\",\"answer\":\"El par\xE1metro + `max_tokens` define el n\xFAmero m\xE1ximo de tokens que el modelo tomar\xE1 + como contexto. Se utiliza en el endpoint /ask para establecer l\xEDmites en + el tama\xF1o del contexto y en la longitud de la respuesta generada. Para + m\xE1s detalles, puedes consultar la documentaci\xF3n oficial en el siguiente + enlace: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features.\",\"missing_info_query\":\"\",\"useful\":\"yes\",\"citations\":[\"block-AA\",\"block-AB\",\"block-AC\"]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":52,\"output_tokens\":19,\"timings\":{\"generative\":3.9760479599935934},\"input_nuclia_tokens\":0.052,\"output_nuclia_tokens\":0.019}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.05154,\"output\":0.01872,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - h3=":443"; ma=2592000 @@ -576,17 +604,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:01 GMT + - Wed, 05 Aug 2026 08:09:31 GMT nuclia-learning-id: - - 3332506d9f554b70b464562c52d6c050 + - 34a5830fe85e4f48beb6484f9bf088cd nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '4436' + - '3985' x-nuclia-trace-id: - - dec9ad587d2e1065b9b2e8fd2594ebc4 + - 7298286281d01765ed4d9710e840871c status: code: 200 message: OK @@ -600,17 +628,15 @@ interactions: this clearly\n\nAlways follow any additional instructions provided about format, style, or domain-specific behavior.", "chat_history": [], "context": [], "query_context": {}, "query_context_order": {}, "truncate": true, "user_prompt": {"prompt": "\n## - Question\nExplica c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar - la longitud de las respuestas en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n - oficial.\n\n## Provided Context\n[START OF CONTEXT]\n## Retrieval on nuclia-docs - Knowledge Box\n\n# Explica c\u00f3mo usar el par\u00e1metro `max_tokens` para - controlar la longitud de las respuestas en espa\u00f1ol y proporciona un enlace - a la documentaci\u00f3n oficial.\n\n Para usar el par\u00e1metro `max_tokens`, - se debe establecer un l\u00edmite en la longitud de la respuesta generada. El - par\u00e1metro `max_tokens` se utiliza en el endpoint /ask para limitar la longitud - de la respuesta generada. Tambi\u00e9n se puede usar para limitar el tama\u00f1o - del contexto. Para m\u00e1s detalles, puedes consultar la documentaci\u00f3n - oficial en el siguiente enlace: https://docs.rag.progress.cloud/docs/rag/advanced/consumption.\n[END + Question\nExplica c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol, + incluyendo un enlace a la documentaci\u00f3n oficial.\n\n## Provided Context\n[START + OF CONTEXT]\n## Retrieval on nuclia-docs Knowledge Box\n\n# Explica c\u00f3mo + usar el par\u00e1metro `max_tokens` en espa\u00f1ol, incluyendo un enlace a + la documentaci\u00f3n oficial.\n\n El par\u00e1metro `max_tokens` define el + n\u00famero m\u00e1ximo de tokens que el modelo tomar\u00e1 como contexto. Se + utiliza en el endpoint /ask para establecer l\u00edmites en el tama\u00f1o del + contexto y en la longitud de la respuesta generada. Para m\u00e1s detalles, + puedes consultar la documentaci\u00f3n oficial en el siguiente enlace: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features.\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all context; it may be lengthy or detailed\n- Do not omit or overlook any relevant information\n- Existing context summaries are answer attempts produced by retrieval agents. @@ -622,12 +648,12 @@ interactions: the chunks for supporting citations.\n- If the context is incomplete or insufficient, state: \"Not enough data to answer this.\"\n- Read carefully any extra instructions below if provided and use them to answer\n\nNow provide your answer to the question: - Explica c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar la longitud - de las respuestas en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n - oficial."}, "citations": null, "citation_threshold": null, "generative_model": - "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": - null, "json_schema": null, "format_prompt": false, "rerank_context": false, - "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": null}' + Explica c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol, incluyendo + un enlace a la documentaci\u00f3n oficial."}, "citations": null, "citation_threshold": + null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": + {}, "prefer_markdown": null, "json_schema": null, "format_prompt": false, "rerank_context": + false, "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": + null}' headers: Accept: - application/x-ndjson @@ -636,17 +662,17 @@ interactions: Connection: - keep-alive Content-Length: - - '2903' + - '2713' Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-client-ident: - default x-message: - - 8ed74a70fcdc44fda2e5768a74ef5b19 + - be08982cb83945a7933a4f69a8a5c618 x-origin: - RAO x-session: @@ -656,30 +682,29 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: - string: "{\"chunk\":{\"type\":\"text\",\"text\":\"Para\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - usar\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + string: "{\"chunk\":{\"type\":\"text\",\"text\":\"El\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" par\xE1\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"metro\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - `\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"max\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"_tokens\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"`,\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - se\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" debe\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - establecer\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" un\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - l\xEDmite\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + `\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"max\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"_tokens\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"`\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + define\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + n\xFAmero\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" m\xE1ximo\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" tokens\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + que\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + modelo\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" tom\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ar\xE1\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + como\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" contexto\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + Se\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" utiliza\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + endpoint\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" /\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ask\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + para\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" establecer\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + l\xEDmites\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" tama\xF1o\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + del\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" contexto\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + y\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" longitud\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" respuesta\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" gener\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ada\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - Este\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" par\xE1\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"metro\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - se\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" utiliza\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - endpoint\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" /\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ask\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - para\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" limitar\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - tanto\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - longitud\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - la\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" respuesta\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - como\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - tama\xF1o\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" del\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - contexto\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" \\n\\n\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"Para\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" m\xE1s\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" detalles\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\",\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" puedes\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" consultar\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" @@ -688,10 +713,10 @@ interactions: el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" siguiente\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" enlace\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\":\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" [\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"Document\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"aci\xF3n\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - oficial\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"](\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"https\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"://\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"docs\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".r\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ag\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".progress\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".cloud\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"/docs\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"/r\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ag\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"/\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"advanced\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"/\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"cons\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"umption\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\").\"}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":14,\"output_tokens\":10,\"timings\":{\"generative_first_chunk\":0.704960907001805,\"generative\":1.8514365820010426},\"input_nuclia_tokens\":0.014,\"output_nuclia_tokens\":0.01}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0141,\"output\":0.01008,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" + oficial\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"](\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"https\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"://\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"docs\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".r\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ag\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".progress\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\".cloud\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"/docs\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"/r\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"ag\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"/\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"advanced\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"/widget\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"/features\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\").\"}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":13,\"output_tokens\":10,\"timings\":{\"generative_first_chunk\":0.5052020049915882,\"generative\":2.3873363719903864},\"input_nuclia_tokens\":0.013,\"output_nuclia_tokens\":0.01}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.01308,\"output\":0.00984,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -699,17 +724,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:06 GMT + - Wed, 05 Aug 2026 08:09:36 GMT nuclia-learning-id: - - 969ce81ad5f24d799cf1bfae4efb53a4 + - c6f18ca3532e4d3e908e7993e16d843d nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '711' + - '515' x-nuclia-trace-id: - - cead86b163db939c5ca30c224ebd395c + - 7ba9eff357ef774e3eaf5989655dc566 status: code: 200 message: OK diff --git a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple_disable_ai_parameter_search.yaml b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple_disable_ai_parameter_search.yaml index 24bc8cfb..29c623ce 100644 --- a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple_disable_ai_parameter_search.yaml +++ b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple_disable_ai_parameter_search.yaml @@ -9,16 +9,16 @@ interactions: Connection: - keep-alive Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.dp.stashify.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: - string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"da1740fa-ab3e-4971-b374-7bb31b5dd325","account_id":"39f5fa6e-680a-475e-a757-812597e86d06","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' + string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"9e1317aa-e212-4a59-b794-afee535458a6","account_id":"07c2de7c-fa77-4374-a461-eea314da9dfd","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 @@ -27,11 +27,11 @@ interactions: content-type: - application/json date: - - Wed, 05 Aug 2026 07:57:08 GMT + - Wed, 05 Aug 2026 08:09:38 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '8' + - '5' status: code: 200 message: OK @@ -77,13 +77,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-client-ident: - default x-message: - - 61239d46d4574621b88307ea3cf433d5 + - 07ebf4168bab4cffacebc2b72e8be648 x-origin: - RAO x-session: @@ -93,17 +93,17 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"rephrased_question\":\"Explica - c\xF3mo usar el par\xE1metro `max_tokens` para controlar la longitud de las - respuestas en espa\xF1ol, y proporciona un enlace a la documentaci\xF3n oficial.\",\"rules\":[\"La - explicaci\xF3n debe ser en espa\xF1ol.\",\"Incluir un enlace a la documentaci\xF3n - relevante sobre `max_tokens`.\"],\"reason\":\"La pregunta original es un poco - informal. La rephrased question es m\xE1s precisa al especificar que se busca - entender el uso de `max_tokens` para controlar la longitud de las respuestas - y solicita expl\xEDcitamente la documentaci\xF3n.\"}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":7,\"output_tokens\":11,\"timings\":{\"generative\":1.0181801019989507},\"input_nuclia_tokens\":0.007,\"output_nuclia_tokens\":0.011}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0071,\"output\":0.01072,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" + c\xF3mo usar el par\xE1metro `max_tokens` en espa\xF1ol y proporciona un enlace + a la documentaci\xF3n oficial.\",\"rules\":[\"The answer must be in Spanish.\",\"Include + a link to the official documentation regarding `max_tokens`.\"],\"reason\":\"The + original question is understandable but could be more precise. The rephrased + question explicitly asks for an explanation of how to use `max_tokens` and + requests the documentation link, which were implied but not directly stated. + This ensures the agent focuses on both aspects.\"}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":7,\"output_tokens\":11,\"timings\":{\"generative\":0.9138043400016613},\"input_nuclia_tokens\":0.007,\"output_nuclia_tokens\":0.011}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0071,\"output\":0.01056,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - h3=":443"; ma=2592000 @@ -114,17 +114,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:08 GMT + - Wed, 05 Aug 2026 08:09:38 GMT nuclia-learning-id: - - 79b52474b9e94b588660fbe120b34419 + - e274305487174fd883f2260f026d1e90 nuclia-learning-model: - gemini-2.5-flash-lite via: - 1.1 google x-envoy-upstream-service-time: - - '1024' + - '919' x-nuclia-trace-id: - - ee3215934bb78a3b69e3599aa83b80d3 + - a71ef65098cdd571bd4b3fc4f5dfd839 status: code: 200 message: OK @@ -138,455 +138,16 @@ interactions: Connection: - keep-alive Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-stf-nuakey: - DUMMY method: GET - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/tokens?model=multilingual&text=Explica+c%C3%B3mo+usar+el+par%C3%A1metro+%60max_tokens%60+para+controlar+la+longitud+de+las+respuestas+en+espa%C3%B1ol%2C+y+proporciona+un+enlace+a+la+documentaci%C3%B3n+oficial. + uri: https://europe-1.dp.progress.cloud/api/v1/predict/tokens?model=multilingual&text=Explica+c%C3%B3mo+usar+el+par%C3%A1metro+%60max_tokens%60+en+espa%C3%B1ol+y+proporciona+un+enlace+a+la+documentaci%C3%B3n+oficial. response: body: - string: "{\"tokens\":[{\"text\":\"espa\xF1ol\",\"ner\":\"LANGUAGE\",\"start\":92,\"end\":99}],\"time\":0.07348251342773438,\"input_tokens\":37}" - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Length: - - '114' - access-control-expose-headers: - - X-NUCLIA-TRACE-ID - content-type: - - application/json - date: - - Wed, 05 Aug 2026 07:57:10 GMT - nuclia-learning-model: - - multilingual - via: - - 1.1 google - x-envoy-upstream-service-time: - - '83' - x-nuclia-trace-id: - - b6a9847aaed4241fe27300136f248784 - status: - code: 200 - message: OK -- request: - body: '{"question": "", "retrieval": true, "user_id": "arag-ask", "system": null, - "chat_history": [], "context": [], "query_context": {}, "query_context_order": - {}, "truncate": true, "user_prompt": {"prompt": "\n\nInformation about the KB:\n\n# - nuclia-docs\n\ndescription: Documentation of the Nuclia API, recipies, reference - \n\nAnd given the question: Explica c\u00f3mo usar el par\u00e1metro `max_tokens` - para controlar la longitud de las respuestas en espa\u00f1ol, y proporciona - un enlace a la documentaci\u00f3n oficial.\n\n## labels: {''pmm'': [''Videos'', - ''Partner Content'', ''Softcat'', ''Sales Enablement Assets'', ''KO 26'', ''Data - Sheets'', ''Progress Agentic RAG Training Materials 2026'']}\n\n## Facets:\n\n## - Content Types\nThe following content types are available in the KB:\n\n- /n/i: - 994\n- application/json: 1\n- text/markdown: 993\nThe following languages are - available in the KB:\n\n- ca: 4\n- cy: 1\n- da: 1\n- en: 974\n- eo: 4\n- la: - 7\n- nb: 1\n- tl: 1\n- yo: 1\n\n\n# Important rules to follow\n\n\nprompt=''Be - polite''\n"}, "citations": false, "citation_threshold": null, "generative_model": - "gemini-2.5-flash", "max_tokens": 8192, "query_context_images": {}, "prefer_markdown": - null, "json_schema": {"title": "ask_configuration", "description": "Configuration - extracted from reasoning engine", "parameters": {"type": "object", "properties": - {"link": {"type": "boolean", "description": "The user wants link reference to - the answer?"}, "knowledge_scan": {"type": "string", "description": "If the query - requires a knowledge aggregation or scan search to answer define the entities, - labels and relations to query in the KB. 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DO NOT ADD ANY EXTRA NOTES AT THE END, JUST A LIST OF KEYWORDS"}, - "reason": {"type": "string"}, "entities": {"type": "array", "description": "Entities - related to the user question to query in the KB", "items": {"type": "string"}}, - "relations": {"type": "array", "description": "Relations related to the user - question to query in the KB", "items": {"type": "string"}}, "pre_queries": {"type": - "array", "items": {"type": "string"}, "description": "Pre queries to run before - the main query to gather more information"}}, "required": ["semantic_query", - "lexical_query", "visual", "keywords_filter", "reason", "pre_queries"]}}, "format_prompt": - false, "rerank_context": false, "tools": [], "tool_choice": {"type": "required"}, - "reasoning": false, "seed": null}' - headers: - Accept: - - application/x-ndjson - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '3421' - Content-Type: - - application/json - Host: - - europe-1.dp.stashify.cloud - User-Agent: - - nuclia.py/4.11.5 - x-client-ident: - - default - x-message: - - 61239d46d4574621b88307ea3cf433d5 - x-origin: - - RAO - x-session: - - default_default_session - x-show-consumption: - - 'true' - x-stf-nuakey: - - DUMMY - method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat - response: - body: - string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"semantic_query\":\"Explica - el uso del par\xE1metro `max_tokens` para controlar la longitud de las respuestas - y proporciona un enlace a la documentaci\xF3n oficial.\",\"lexical_query\":\"Sut - mae'r paramedr `max_tokens` yn rheoli hyd ymatebion?\",\"visual\":false,\"keywords_filter\":[\"max_tokens\",\"longitud\"],\"reason\":\"The - user is asking for an explanation of how to use the `max_tokens` parameter - to control response length and a link to official documentation, which can - be directly answered by a knowledge base search.\",\"pre_queries\":[]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":36,\"output_tokens\":77,\"timings\":{\"generative\":1.7809446820028825},\"input_nuclia_tokens\":0.036,\"output_nuclia_tokens\":0.077}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0357,\"output\":0.077,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" - headers: - Alt-Svc: - - h3=":443"; ma=2592000 - Transfer-Encoding: - - chunked - access-control-expose-headers: - - X-NUCLIA-TRACE-ID - content-type: - - application/x-ndjson - date: - - Wed, 05 Aug 2026 07:57:10 GMT - nuclia-learning-id: - - 69c65dd846b848dc883284335a452d8d - nuclia-learning-model: - - gemini-2.5-flash - via: - - 1.1 google - x-envoy-upstream-service-time: - - '1786' - x-nuclia-trace-id: - - 9ac36e1828ae63fa42d77b222840f9b8 - status: - code: 200 - message: OK -- request: - body: '{"question": "Explica c\u00f3mo usar el par\u00e1metro `max_tokens` para - controlar la longitud de las respuestas en espa\u00f1ol, y proporciona un enlace - a la documentaci\u00f3n oficial.", "user_id": "arag-ask-rerank", "context": - {"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412": " max_tokens: the maximum - number of input tokens to put in the final context (including the prompt, the - retrieved results and the user question). \n max_output_tokens: the maximum - number of tokens to generate. \n\n", "c27a1e5f5ddb4b118921345d713401b8/t/page/351-554": - " full: boolean \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:386 - \n \n max_messages? \n \n optional max_messages: number \n \n Defined in \n - libs/sdk-core/src/lib/db/kb/kb.models.ts:387 \n \n name \n \n\n", "dd41482018924facb5dbb87a7d53f122/t/page/3310-3757": - " ) \n time.sleep(wait_time) \n retries += 1 \n else: \n response.raise_for_status() - \n raise Exception( Max retries exceeded ) \n Example usage \n url = https://your-endpoint - \n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_try_after_info(url, - headers) \n print(data) \n ``` \n These examples demonstrate how to handle rate - limits effectively, ensuring that your application respects the limits and retries - appropriately.\n", "dd41482018924facb5dbb87a7d53f122/t/page/1900-2653": " retries - = 0 \n while retries < max_retries: \n response = requests.get(url, headers=headers) - \n if response.status_code == 200: \n return response.json() \n elif response.status_code - == 429: \n wait_time = 2 retries # Exponential backoff: 2^retries \n print(f - Rate limit exceeded. Retrying in {wait_time} seconds... ) \n time.sleep(wait_time) - \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( - Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers - = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_exponential_backoff(url, - headers) \n print(data) \n ``` \n Example 2: Ingestion back pressure limits - \n Here''s an example of how to use the try_after key from the response to manage - rate limits: \n\n", "43004f553e534ffe9c9e735856bd9b23/t/page/480-703": " \n - optional max_images: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 - \n \n output_tokens \n \n output_tokens: object \n \n default_max? \n \n optional - default_max: number \n \n max \n \n max: number \n \n min? \n \n\n", "43004f553e534ffe9c9e735856bd9b23/t/page/212-480": - " \n optional driver: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 - \n \n input_tokens \n \n input_tokens: object \n \n max \n \n max: number \n - \n min? \n \n optional min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \n \n max_images? \n\n", "e8525e64c5b44982b958d32cf6090613/t/page/2808-3011": - " \n optional max_tokens: number \\| object \n \n Defines the maximum number - of tokens that the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 - \n \n min_score? \n\n", "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221": - " \n optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined - in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? - \n\n", "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709": " ::: \n :::warning - \n Enabling reasoning can use additional tokens, which may increase your usage - costs. \n You may need to increase max_tokens to give the LLM enough room to - reason and generate an answer. \n\n", "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276": - " \n SDK: \n \n ```python \n from nuclia import sdk \n from nucliadb_models.search - import AskRequest, Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( - \n query= My question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( - \n display=True, # Show reasoning in the response \n effort= low , # Can be - low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can - use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning - Options: \n\n", "f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299": "@nuclia/core - \u2022 Docs \n \n @nuclia/core / PageToken \n Interface: PageToken \n Properties - \n height \n \n height: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 - \n \n line \n \n line: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 - \n \n text \n \n\n", "44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668": " - \n step: Information about the current processing step \n module: The module - being executed (e.g., rephrase , basic_ask , remi ) \n title: Display title - for the step \n value: Result of the step \n reason: Explanation for the step - \n timeit: Time taken in seconds \n \n input_nuclia_tokens/output_nuclia_tokens: - Token usage \n \n \n\n", "4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340": - " Use the max_tokens parameter on the /ask endpoint to set hard limits on: \n - - Context size: Limits the amount of retrieved information sent to the LLM \n - - Answer length: Limits the length of the generated response \n Important Considerations - \n Context Limitations: \n\n", "4039d76b0fff4962900836ab3fdec9f7/t/page/3340-4136": - " - Restricting context size may result in less relevant answers since the LLM - has less information to work with \n - Balance between cost control and answer - quality \n Answer Length Limitations: \n - The LLM might not complete its response - if it hits the token limit, potentially cutting sentences mid-way \n - Recommended - approach: Include length requirements in your prompt (e.g., Please answer in - less than 200 words ) rather than relying solely on hard limits \n - This allows - the LLM to naturally conclude its response within the desired length \n How - to Monitor Token Consumption \n Understanding Token Consumption Data \n You - can receive detailed token consumption information from the following endpoints - that utilize LLM models: ask, chat, remi, query, sentence, summarize, tokens, - and rerank. \n\n", "4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326": " \n - Large context: Results from using RAG strategies like Full resource or Neighbouring - paragraphs , or from using the extra_context parameter \n Long questions: More - detailed or complex questions require more input tokens \n Long prompts: Extensive - system prompts increase the input token count \n Detailed answers: Comprehensive - responses require more output tokens \n Images in context: When using multimodal - models, images included in the retrieved context significantly increase token - consumption \n \n How to Limit and Control Token Consumption \n Strategy 1: - Optimize Your Parameters \n The first approach to reducing token consumption - is to fine-tune your request parameters: \n\n", "4039d76b0fff4962900836ab3fdec9f7/t/page/5396-5615": - " - input: Tokens used for the prompt, context, and question \n - output: Tokens - used for the generated response \n - image: Tokens used for image processing - (when applicable) \n Customer Key Tokens (customer_key_tokens): \n\n", "89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575": - " \n \n Maximum supported input tokens: \n Description: The maximum number of - tokens that the model can accept as input. Be mindful that this takes into account - the tokens used in the prompt, query and context. Also take note that some models - may provide their context window as the total between input and output tokens, - while others may provide it as the input tokens only. \n\n", "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043": - " Description: The maximum number of tokens that the model can generate as output. - Again, we should keep in mind that this value summed to the Maximum supported - input tokens should not exceed the total context size supported by the model. - \n\n", "b6a6202b9f0d4611a980293ce53337d6/t/page/265-405": " last: boolean \n - \n page \n \n page: number \n \n size \n \n size: number \n \n Defined in \n - libs/sdk-core/src/lib/db/training/training.models.ts:36\n", "42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696": - " \n optional max_paragraph: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 - \n \n name? \n \n optional name: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\n"}}' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '8322' - Content-Type: - - application/json - Host: - - europe-1.dp.stashify.cloud - User-Agent: - - nuclia.py/4.11.5 - x-stf-nuakey: - - DUMMY - method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/rerank - response: - body: - string: '{"context_scores":{"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340":0.8020908832550049,"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412":0.295738160610199,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709":0.10284407436847687,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276":0.07068779319524765,"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757":0.06816437840461731,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221":0.054098695516586304,"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011":0.02876158617436886,"4039d76b0fff4962900836ab3fdec9f7/t/page/3340-4136":0.018725162371993065,"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043":0.015130727551877499,"dd41482018924facb5dbb87a7d53f122/t/page/1900-2653":0.014172366820275784,"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575":0.013955709524452686,"43004f553e534ffe9c9e735856bd9b23/t/page/212-480":0.011072159744799137,"4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326":0.009974921122193336,"43004f553e534ffe9c9e735856bd9b23/t/page/480-703":0.005469274707138538,"4039d76b0fff4962900836ab3fdec9f7/t/page/5396-5615":0.002453428227454424,"c27a1e5f5ddb4b118921345d713401b8/t/page/351-554":0.0015247863484546542,"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696":0.0009075025445781648,"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299":0.0005463420529849827,"44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668":0.00039666122756898403,"b6a6202b9f0d4611a980293ce53337d6/t/page/265-405":6.868318450869992e-05}}' - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Content-Length: - - '1462' - access-control-expose-headers: - - X-NUCLIA-TRACE-ID - content-type: - - application/json - date: - - Wed, 05 Aug 2026 07:57:13 GMT - nuclia-learning-model: - - bge-reranker-v2-m3 - via: - - 1.1 google - x-envoy-upstream-service-time: - - '87' - x-nuclia-trace-id: - - 6805c19285258a2a8bf63f879102da69 - status: - code: 200 - message: OK -- request: - body: '{"question": "", "retrieval": true, "user_id": "rao_answer_summary-ask", - "system": null, "chat_history": [], "context": [], "query_context": {}, "query_context_order": - {}, "truncate": true, "user_prompt": {"prompt": "\nBased on the provided context - and user question, perform the following tasks:\n\n1. Select only information - directly relevant to the question.\n2. Break down compound sentences into simple, - single-idea statements. Preserve original phrasing when possible.\n3. For any - named entity with descriptive details, separate those details into distinct - propositions.\n4. Ensure clarity by replacing pronouns (e.g., \"it\", \"he\", - \"she\", \"they\", \"this\", \"that\") with the full names of the entities they - reference, and add necessary modifiers to clarify meaning.\n5. The context may - be delimited by tags such as and . Treat - everything between these tags as context.\n6. Assess whether the context sufficiently - answers the question. If it answers it partially, provide the answer; if it - does not answer it fully, specify what information is missing to answer the - question.\n7. If the context does not answer the question at all, just return - the original question as the missing information.\n8. The `citations` field - consists ONLY in a list of block IDs that are relevant to the answer, following - these rules:\n - Use the format: block-AB\n - Just mention the block IDs, - do NOT include any other text.\n - Just mention the blocks actually relevant - and that contain information used in the answer, do NOT include blocks that - are not relevant.\n - No duplicates.\n9. Do NOT hallucinate block IDs. Only - use those provided in the context.\n10. Your output must be a JSON object with - the following fields:\n - \"reason\": Explain your reasoning for the answer - or validation.\n - \"answer\": Provide a partial or complete answer to the - user query strictly from the information in the context. If there isn''t enough - information to even provide a partial answer, leave ''answer'' empty.\n - - \"missing_info_query\": If the context is insufficient, specify what information - is missing in a query shape; otherwise, leave it empty. Just return the query - needed to retrieve the missing information.\n - \"useful\": Indicate if the - context is useful to answer the question (\"yes\" or \"no\").\n - \"citations\": - List the IDs of the blocks relevant to the answer, if any (e.g., [\"block-AB\", - \"block-CD\"]).\n11. **IMPORTANT** If any extra instructions are provided, you - MUST follow them carefully when generating the answer field. These instructions - may specify the format, style, tools to use, or other requirements for the answer.\n\n\nExplica - c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar la longitud de - las respuestas en espa\u00f1ol, y proporciona un enlace a la documentaci\u00f3n - oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### Chunk: 4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\nTags: - /k/text\n``` Use the max_tokens parameter on the /ask endpoint to set hard - limits on: \n - Context size: Limits the amount of retrieved information sent - to the LLM \n - Answer length: Limits the length of the generated response \n - Important Considerations \n Context Limitations: \n\n ```\n\n\n---\"\n\n\n**block-AB**\n\n#### - Chunk: 9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\nTags: /k/text\n``` max_tokens: - the maximum number of input tokens to put in the final context (including the - prompt, the retrieved results and the user question). \n max_output_tokens: - the maximum number of tokens to generate. \n\n ```\n\n\n---\"\n\n\n**block-AC**\n\n#### - Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\nTags: /k/text\n``` ::: - \n :::warning \n Enabling reasoning can use additional tokens, which may increase - your usage costs. \n You may need to increase max_tokens to give the LLM enough - room to reason and generate an answer. \n\n ```\n\n\n---\"\n\n\n**block-AD**\n\n#### - Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\nTags: /k/text\n``` \n - SDK: \n \n ```python \n from nuclia import sdk \n from nucliadb_models.search - import AskRequest, Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( - \n query= My question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( - \n display=True, # Show reasoning in the response \n effort= low , # Can be - low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can - use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning - Options: \n\n ```\n\n\n---\"\n\n\n**block-AE**\n\n#### Chunk: dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\nTags: - /k/text\n``` ) \n time.sleep(wait_time) \n retries += 1 \n else: \n response.raise_for_status() - \n raise Exception( Max retries exceeded ) \n Example usage \n url = https://your-endpoint - \n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_try_after_info(url, - headers) \n print(data) \n ``` \n These examples demonstrate how to handle rate - limits effectively, ensuring that your application respects the limits and retries - appropriately.\n ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\nTags: - /k/text\n``` \n optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined - in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? - \n\n ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": false, "citation_threshold": - null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 8192, "query_context_images": - {}, "prefer_markdown": null, "json_schema": {"title": "validate_or_answer", - "description": "Validate or answer", "parameters": {"type": "object", "properties": - {"reason": {"type": "string", "description": "Reasoning for the answer or validation"}, - "answer": {"type": "string", "description": "Partial or complete answer to the - user query from the information in the context."}, "missing_info_query": {"type": - "string", "description": "Query needed to retrieve the missing information in - case the context is not enough to answer the question. If the context does not - answer the question at all, just return the original question."}, "useful": - {"type": "string", "description": "Is the context useful to answer the question?", - "enum": ["yes", "no"]}, "citations": {"type": "array", "items": {"type": "string", - "description": "Block ID cited in the answer, e.g. block-AB"}, "description": - "List of block IDs cited in the answer, if any"}}, "required": ["reason", "answer", - "missing_info_query", "useful", "citations"]}}, "format_prompt": false, "rerank_context": - false, "tools": [], "tool_choice": {"type": "required"}, "reasoning": false, - "seed": null}' - headers: - Accept: - - application/x-ndjson - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Content-Length: - - '6755' - Content-Type: - - application/json - Host: - - europe-1.dp.stashify.cloud - User-Agent: - - nuclia.py/4.11.5 - x-origin: - - RAO - x-show-consumption: - - 'true' - x-stf-nuakey: - - DUMMY - method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat - response: - body: - string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"reason\":\"The context - provides information on how to use the `max_tokens` parameter to control the - length of responses. It explains that `max_tokens` sets limits on the number - of input tokens and the maximum number of tokens to generate. However, it - does not provide a direct link to the official documentation.\",\"answer\":\"Para - usar el par\xE1metro `max_tokens`, se debe establecer un l\xEDmite en el n\xFAmero - m\xE1ximo de tokens de entrada y en el n\xFAmero m\xE1ximo de tokens a generar. - Esto se puede hacer en el endpoint /ask. El par\xE1metro `max_tokens` limita - la longitud de la respuesta generada. Adem\xE1s, se puede usar `max_output_tokens` - para definir el n\xFAmero m\xE1ximo de tokens a generar. Para m\xE1s detalles, - se recomienda consultar la documentaci\xF3n oficial.\",\"missing_info_query\":\"\xBFCu\xE1l - es el enlace a la documentaci\xF3n oficial sobre el uso del par\xE1metro `max_tokens`?\",\"useful\":\"yes\",\"citations\":[\"block-AA\",\"block-AB\"]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":44,\"output_tokens\":23,\"timings\":{\"generative\":2.894688597996719},\"input_nuclia_tokens\":0.044,\"output_nuclia_tokens\":0.023}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0435,\"output\":0.0234,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" - headers: - Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Transfer-Encoding: - - chunked - access-control-expose-headers: - - X-NUCLIA-TRACE-ID - content-type: - - application/x-ndjson - date: - - Wed, 05 Aug 2026 07:57:13 GMT - nuclia-learning-id: - - 3bb0cab631904c55a4e35287b76679b4 - nuclia-learning-model: - - chatgpt-azure-4o-mini - via: - - 1.1 google - x-envoy-upstream-service-time: - - '2902' - x-nuclia-trace-id: - - 179642b7fc3ee7faf6d49e35be5e2e35 - status: - code: 200 - message: OK -- request: - body: '' - headers: - Accept: - - '*/*' - Accept-Encoding: - - gzip, deflate - Connection: - - keep-alive - Host: - - europe-1.dp.stashify.cloud - User-Agent: - - nuclia.py/4.11.5 - x-stf-nuakey: - - DUMMY - method: GET - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/tokens?model=multilingual&text=Explica+c%C3%B3mo+usar+el+par%C3%A1metro+%60max_tokens%60+para+controlar+la+longitud+de+las+respuestas+en+espa%C3%B1ol%2C+y+proporciona+un+enlace+a+la+documentaci%C3%B3n+oficial. - response: - body: - string: "{\"tokens\":[{\"text\":\"espa\xF1ol\",\"ner\":\"LANGUAGE\",\"start\":92,\"end\":99}],\"time\":0.011320114135742188,\"input_tokens\":37}" + string: "{\"tokens\":[{\"text\":\"espa\xF1ol\",\"ner\":\"LANGUAGE\",\"start\":47,\"end\":54}],\"time\":0.008693933486938477,\"input_tokens\":28}" headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 @@ -597,15 +158,15 @@ interactions: content-type: - application/json date: - - Wed, 05 Aug 2026 07:57:17 GMT + - Wed, 05 Aug 2026 08:09:40 GMT nuclia-learning-model: - multilingual via: - 1.1 google x-envoy-upstream-service-time: - - '18' + - '17' x-nuclia-trace-id: - - 904fd0725cb28e0f4a67bb1285014b2a + - a453460ebff452852b5a65cb128ff5b0 status: code: 200 message: OK @@ -615,46 +176,45 @@ interactions: {}, "truncate": true, "user_prompt": {"prompt": "\n\nInformation about the KB:\n\n# nuclia-docs\n\ndescription: Documentation of the Nuclia API, recipies, reference \n\nAnd given the question: Explica c\u00f3mo usar el par\u00e1metro `max_tokens` - para controlar la longitud de las respuestas en espa\u00f1ol, y proporciona - un enlace a la documentaci\u00f3n oficial.\n\n## labels: {''pmm'': [''Videos'', - ''Partner Content'', ''Softcat'', ''Sales Enablement Assets'', ''KO 26'', ''Data - Sheets'', ''Progress Agentic RAG Training Materials 2026'']}\n\n## Facets:\n\n## - Content Types\nThe following content types are available in the KB:\n\n- /n/i: - 994\n- application/json: 1\n- text/markdown: 993\nThe following languages are - available in the KB:\n\n- ca: 4\n- cy: 1\n- da: 1\n- en: 974\n- eo: 4\n- la: - 7\n- nb: 1\n- tl: 1\n- yo: 1\n\n\n# Important rules to follow\n\n\nprompt=''Be - polite''\n"}, "citations": false, "citation_threshold": null, "generative_model": - "gemini-2.5-flash", "max_tokens": 8192, "query_context_images": {}, "prefer_markdown": - null, "json_schema": {"title": "ask_configuration", "description": "Configuration - extracted from reasoning engine", "parameters": {"type": "object", "properties": - {"link": {"type": "boolean", "description": "The user wants link reference to - the answer?"}, "knowledge_scan": {"type": "string", "description": "If the query - requires a knowledge aggregation or scan search to answer define the entities, - labels and relations to query in the KB. Example queries: How many ..."}, "semantic_query": - {"type": "string", "description": "Rephrase this question so its better for - semantic retrieval, and keep the rephrased question in the same language as - the original. Please define ONLY the question without any explanation. JUST - A SENTENCE. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST ONE SENTENCE"}, "lexical_query": - {"type": "string", "description": "Rephrase this question so its better for - lexical retrieval, translate the lexical rephrased question to cy. Please define - ONLY the question without any explanation. JUST A SENTENCE. DO NOT ADD ANY EXTRA - NOTES AT THE END, JUST ONE SENTENCE"}, "visual": {"type": "boolean", "description": - "Is required an analysis of an image to answer this question, answer with false - or true"}, "keywords_filter": {"type": "array", "items": {"type": "string"}, - "description": "Extract if any the keywords that should appear on the retrieved - results and its a must match, make sure that are keywords that are not common - words, and that are not the same as the question or answer. Please define ONLY - the keywords without any explanation. Only one or two words maximum. JUST A - LIST OF KEYWORDS. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST A LIST OF KEYWORDS"}, - "reason": {"type": "string"}, "entities": {"type": "array", "description": "Entities - related to the user question to query in the KB", "items": {"type": "string"}}, - "relations": {"type": "array", "description": "Relations related to the user - question to query in the KB", "items": {"type": "string"}}, "pre_queries": {"type": - "array", "items": {"type": "string"}, "description": "Pre queries to run before - the main query to gather more information"}}, "required": ["semantic_query", - "lexical_query", "visual", "keywords_filter", "reason", "pre_queries"]}}, "format_prompt": - false, "rerank_context": false, "tools": [], "tool_choice": {"type": "required"}, - "reasoning": false, "seed": null}' + en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n oficial.\n\n## + labels: {''pmm'': [''Videos'', ''Partner Content'', ''Softcat'', ''Sales Enablement + Assets'', ''KO 26'', ''Data Sheets'', ''Progress Agentic RAG Training Materials + 2026'']}\n\n## Facets:\n\n## Content Types\nThe following content types are + available in the KB:\n\n- /n/i: 994\n- application/json: 1\n- text/markdown: + 993\nThe following languages are available in the KB:\n\n- ca: 4\n- cy: 1\n- + da: 1\n- en: 974\n- eo: 4\n- la: 7\n- nb: 1\n- tl: 1\n- yo: 1\n\n\n# Important + rules to follow\n\n\nprompt=''Be polite''\n"}, "citations": false, "citation_threshold": + null, "generative_model": "gemini-2.5-flash", "max_tokens": 8192, "query_context_images": + {}, "prefer_markdown": null, "json_schema": {"title": "ask_configuration", "description": + "Configuration extracted from reasoning engine", "parameters": {"type": "object", + "properties": {"link": {"type": "boolean", "description": "The user wants link + reference to the answer?"}, "knowledge_scan": {"type": "string", "description": + "If the query requires a knowledge aggregation or scan search to answer define + the entities, labels and relations to query in the KB. Example queries: How + many ..."}, "semantic_query": {"type": "string", "description": "Rephrase this + question so its better for semantic retrieval, and keep the rephrased question + in the same language as the original. Please define ONLY the question without + any explanation. JUST A SENTENCE. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST + ONE SENTENCE"}, "lexical_query": {"type": "string", "description": "Rephrase + this question so its better for lexical retrieval, translate the lexical rephrased + question to cy. Please define ONLY the question without any explanation. JUST + A SENTENCE. DO NOT ADD ANY EXTRA NOTES AT THE END, JUST ONE SENTENCE"}, "visual": + {"type": "boolean", "description": "Is required an analysis of an image to answer + this question, answer with false or true"}, "keywords_filter": {"type": "array", + "items": {"type": "string"}, "description": "Extract if any the keywords that + should appear on the retrieved results and its a must match, make sure that + are keywords that are not common words, and that are not the same as the question + or answer. Please define ONLY the keywords without any explanation. Only one + or two words maximum. JUST A LIST OF KEYWORDS. DO NOT ADD ANY EXTRA NOTES AT + THE END, JUST A LIST OF KEYWORDS"}, "reason": {"type": "string"}, "entities": + {"type": "array", "description": "Entities related to the user question to query + in the KB", "items": {"type": "string"}}, "relations": {"type": "array", "description": + "Relations related to the user question to query in the KB", "items": {"type": + "string"}}, "pre_queries": {"type": "array", "items": {"type": "string"}, "description": + "Pre queries to run before the main query to gather more information"}}, "required": + ["semantic_query", "lexical_query", "visual", "keywords_filter", "reason", "pre_queries"]}}, + "format_prompt": false, "rerank_context": false, "tools": [], "tool_choice": + {"type": "required"}, "reasoning": false, "seed": null}' headers: Accept: - application/x-ndjson @@ -663,17 +223,17 @@ interactions: Connection: - keep-alive Content-Length: - - '3421' + - '3375' Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-client-ident: - default x-message: - - 61239d46d4574621b88307ea3cf433d5 + - 07ebf4168bab4cffacebc2b72e8be648 x-origin: - RAO x-session: @@ -683,21 +243,19 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"link\":true,\"semantic_query\":\"Explica - el uso del par\xE1metro `max_tokens` para controlar la longitud de las respuestas - y proporciona un enlace a la documentaci\xF3n oficial.\",\"lexical_query\":\"Sut - mae defnyddio'r paramedr `max_tokens` i reoli hyd ymatebion?\",\"visual\":false,\"keywords_filter\":[\"max_tokens\",\"documentaci\xF3n\"],\"reason\":\"The - user is asking how to use the `max_tokens` parameter to control response length - and specifically requests a link to the official documentation. Therefore, - the semantic query should focus on explaining this parameter and requesting - a link, and the lexical query should ask the same in Welsh. Keywords like - 'max_tokens' and 'documentaci\xF3n' are crucial for retrieving relevant information.\",\"pre_queries\":[]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":36,\"output_tokens\":99,\"timings\":{\"generative\":1.6255864730046596},\"input_nuclia_tokens\":0.036,\"output_nuclia_tokens\":0.099}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0357,\"output\":0.099,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" + el uso del par\xE1metro max_tokens y proporciona un enlace a su documentaci\xF3n + oficial.\",\"lexical_query\":\"Sut mae defnyddio'r paramedr max_tokens ac + a yw dolen i'r ddogfennaeth swyddogol ar gael?\",\"visual\":false,\"keywords_filter\":[\"max_tokens\",\"par\xE1metro\"],\"reason\":\"The + user is asking for an explanation of a specific parameter and a link to its + official documentation. This requires semantic and lexical search capabilities, + along with the ability to provide a link if available in the knowledge base.\",\"entities\":[\"max_tokens\"],\"relations\":[],\"pre_queries\":[]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":35,\"output_tokens\":95,\"timings\":{\"generative\":1.9877514440013329},\"input_nuclia_tokens\":0.035,\"output_nuclia_tokens\":0.095}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.03522,\"output\":0.095,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -705,49 +263,32 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:16 GMT + - Wed, 05 Aug 2026 08:09:40 GMT nuclia-learning-id: - - df8b44391e53433d82d28235efa1e958 + - 0a090a761a1f43e3802839819646990f nuclia-learning-model: - gemini-2.5-flash via: - 1.1 google x-envoy-upstream-service-time: - - '1632' + - '1993' x-nuclia-trace-id: - - 544dc327d8fa657188be20294a318c9b + - 86509b3f428f5321d6ae0b3152ba4b26 status: code: 200 message: OK - request: - body: '{"question": "\u00bfCu\u00e1l es el enlace a la documentaci\u00f3n oficial - sobre el uso del par\u00e1metro `max_tokens`?", "user_id": "arag-ask-rerank", - "context": {"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412": " max_tokens: - the maximum number of input tokens to put in the final context (including the - prompt, the retrieved results and the user question). \n max_output_tokens: + body: '{"question": "Explica c\u00f3mo usar el par\u00e1metro `max_tokens` en + espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n oficial.", "user_id": + "arag-ask-rerank", "context": {"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412": + " max_tokens: the maximum number of input tokens to put in the final context + (including the prompt, the retrieved results and the user question). \n max_output_tokens: the maximum number of tokens to generate. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n", - "c27a1e5f5ddb4b118921345d713401b8/t/page/351-554": " full: boolean \n \n Defined - in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:386 \n \n max_messages? \n \n - optional max_messages: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:387 - \n \n name \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ConversationalStrategy\n", - "dd41482018924facb5dbb87a7d53f122/t/page/3310-3757": " ) \n time.sleep(wait_time) - \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( - Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers - = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_try_after_info(url, - headers) \n print(data) \n ``` \n These examples demonstrate how to handle rate - limits effectively, ensuring that your application respects the limits and retries - appropriately.\n\n\nLink: https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\n", - "dd41482018924facb5dbb87a7d53f122/t/page/1900-2653": " retries = 0 \n while - retries < max_retries: \n response = requests.get(url, headers=headers) \n if - response.status_code == 200: \n return response.json() \n elif response.status_code - == 429: \n wait_time = 2 retries # Exponential backoff: 2^retries \n print(f - Rate limit exceeded. Retrying in {wait_time} seconds... ) \n time.sleep(wait_time) - \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( - Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers - = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_exponential_backoff(url, - headers) \n print(data) \n ``` \n Example 2: Ingestion back pressure limits - \n Here''s an example of how to use the try_after key from the response to manage - rate limits: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\n", + "0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349": "@nuclia/core \u2022 Docs \n + \n @nuclia/core / Consumption \n Interface: Consumption \n Properties \n customer_key_tokens + \n \n customer_key_tokens: TokenConsumption \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:230 + \n \n normalized_tokens \n \n normalized_tokens: TokenConsumption \n \n Defined + in \n libs/sdk-core/src/lib/db/search/ask.models.ts:229\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Consumption\n", "43004f553e534ffe9c9e735856bd9b23/t/page/480-703": " \n optional max_images: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \n \n output_tokens \n \n output_tokens: object \n \n default_max? \n \n optional @@ -758,6 +299,13 @@ interactions: \n \n input_tokens: object \n \n max \n \n max: number \n \n min? \n \n optional min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 \n \n max_images? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n", + "dd41482018924facb5dbb87a7d53f122/t/page/3310-3757": " ) \n time.sleep(wait_time) + \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( + Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers + = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_try_after_info(url, + headers) \n print(data) \n ``` \n These examples demonstrate how to handle rate + limits effectively, ensuring that your application respects the limits and retries + appropriately.\n\n\nLink: https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\n", "e8525e64c5b44982b958d32cf6090613/t/page/2808-3011": " \n optional max_tokens: number \\| object \n \n Defines the maximum number of tokens that the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 @@ -767,23 +315,28 @@ interactions: \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", - "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709": " ::: \n :::warning \n - Enabling reasoning can use additional tokens, which may increase your usage - costs. \n You may need to increase max_tokens to give the LLM enough room to - reason and generate an answer. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n", - "220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276": " \n SDK: \n \n ```python - \n from nuclia import sdk \n from nucliadb_models.search import AskRequest, - Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( \n query= My - question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( - \n display=True, # Show reasoning in the response \n effort= low , # Can be - low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can - use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning - Options: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n", + "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977": " \n optional generative_model: + string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 + \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 + \n \n max_tokens? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", "f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299": "@nuclia/core \u2022 Docs \n \n @nuclia/core / PageToken \n Interface: PageToken \n Properties \n height \n \n height: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 \n \n line \n \n line: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 \n \n text \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageToken\n", + "0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224": "@nuclia/core \u2022 Docs \n + \n @nuclia/core / ReasoningConfig \n Interface: ReasoningConfig \n Properties + \n budget_tokens? \n \n optional budget_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 + \n \n effort? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ReasoningConfig\n", + "24ad6997e1fe4a109d67d7802a083678/a/title/0-55": "docs > develop > js sdk > + interfaces > TokenConsumption\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/TokenConsumption\n", + "6e8250e6b5264156988657a221fd5e94/t/page/0-397": "@nuclia/core \u2022 Docs \n + \n @nuclia/core / Ask / ConsumptionAskResponseItem \n Interface: ConsumptionAskResponseItem + \n Properties \n customer_key_tokens \n \n customer_key_tokens: TokenConsumption + \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:127 \n \n + normalized_tokens \n \n normalized_tokens: TokenConsumption \n \n Defined in + \n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \n \n type \n \n\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/namespaces/Ask/interfaces/ConsumptionAskResponseItem\n", "44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668": " \n step: Information about the current processing step \n module: The module being executed (e.g., rephrase , basic_ask , remi ) \n title: Display title for the step \n value: @@ -795,45 +348,50 @@ interactions: of retrieved information sent to the LLM \n - Answer length: Limits the length of the generated response \n Important Considerations \n Context Limitations: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", - "4039d76b0fff4962900836ab3fdec9f7/t/page/3340-4136": " - Restricting context - size may result in less relevant answers since the LLM has less information - to work with \n - Balance between cost control and answer quality \n Answer - Length Limitations: \n - The LLM might not complete its response if it hits - the token limit, potentially cutting sentences mid-way \n - Recommended approach: - Include length requirements in your prompt (e.g., Please answer in less than - 200 words ) rather than relying solely on hard limits \n - This allows the LLM - to naturally conclude its response within the desired length \n How to Monitor - Token Consumption \n Understanding Token Consumption Data \n You can receive - detailed token consumption information from the following endpoints that utilize - LLM models: ask, chat, remi, query, sentence, summarize, tokens, and rerank. - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", - "4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326": " \n Large context: Results - from using RAG strategies like Full resource or Neighbouring paragraphs , or - from using the extra_context parameter \n Long questions: More detailed or complex - questions require more input tokens \n Long prompts: Extensive system prompts - increase the input token count \n Detailed answers: Comprehensive responses - require more output tokens \n Images in context: When using multimodal models, - images included in the retrieved context significantly increase token consumption - \n \n How to Limit and Control Token Consumption \n Strategy 1: Optimize Your - Parameters \n The first approach to reducing token consumption is to fine-tune - your request parameters: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", - "4039d76b0fff4962900836ab3fdec9f7/t/page/5396-5615": " - input: Tokens used - for the prompt, context, and question \n - output: Tokens used for the generated - response \n - image: Tokens used for image processing (when applicable) \n Customer - Key Tokens (customer_key_tokens): \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", + "8b3e0ef630a346d1b591143309db87ec/t/page/0-281": "@nuclia/core \u2022 Docs \n + \n @nuclia/core / NucliaTokensMetric \n Interface: NucliaTokensMetric \n Extends + \n \n UsageMetric \n \n Properties \n details \n \n details: NucliaTokensDetails[] + \n \n Overrides \n UsageMetric.details \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:187 + \n \n name \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/NucliaTokensMetric\n", + "66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833": "@nuclia/core \u2022 Docs + \n \n @nuclia/core / UsageType \n Enumeration: UsageType \n Enumeration Members + \n AI_TOKENS_USED \n \n AI_TOKENS_USED: ai_tokens_used \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:208 + \n \n BYTES_PROCESSED \n \n BYTES_PROCESSED: bytes_processed \n \n Defined in + \n libs/sdk-core/src/lib/db/db.models.ts:199 \n \n CHARS_PROCESSED \n \n CHARS_PROCESSED: + chars_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:200 + \n \n MEDIA_FILES_PROCESSED \n \n MEDIA_FILES_PROCESSED: media_files_processed + \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:202 \n \n MEDIA_SECONDS_PROCESSED + \n \n MEDIA_SECONDS_PROCESSED: media_seconds_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:201 + \n \n NUCLIA_TOKENS \n \n NUCLIA_TOKENS: nuclia_tokens_billed \n \n Defined + in \n libs/sdk-core/src/lib/db/db.models.ts:209 \n \n PAGES_PROCESSED \n \n + PAGES_PROCESSED: pages_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:203 + \n \n PARAGRAPHS_PROCESSED \n \n PARAGRAPHS_PROCESSED: paragraphs_processed + \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:204 \n \n PRE_PROCESSING_TIME + \n \n PRE_PROCESSING_TIME: pre_processing_time \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:196 + \n \n RESOURCES_PROCESSED \n \n RESOURCES_PROCESSED: resources_processed \n + \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:198 \n \n SEARCHES_PERFORMED + \n \n SEARCHES_PERFORMED: searches_performed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:206 + \n \n SLOW_PROCESSING_TIME \n \n SLOW_PROCESSING_TIME: slow_processing_time + \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:197 \n \n SUGGESTIONS_PERFORMED + \n \n SUGGESTIONS_PERFORMED: suggestions_performed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:207 + \n \n TRAIN_SECONDS \n \n TRAIN_SECONDS: train_seconds \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:205\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/enumerations/UsageType\n", + "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043": " Description: The maximum + number of tokens that the model can generate as output. Again, we should keep + in mind that this value summed to the Maximum supported input tokens should + not exceed the total context size supported by the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", "89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575": " \n \n Maximum supported input tokens: \n Description: The maximum number of tokens that the model can accept as input. Be mindful that this takes into account the tokens used in the prompt, query and context. Also take note that some models may provide their context window as the total between input and output tokens, while others may provide it as the input tokens only. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", - "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043": " Description: The maximum - number of tokens that the model can generate as output. Again, we should keep - in mind that this value summed to the Maximum supported input tokens should - not exceed the total context size supported by the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", - "b6a6202b9f0d4611a980293ce53337d6/t/page/265-405": " last: boolean \n \n page - \n \n page: number \n \n size \n \n size: number \n \n Defined in \n libs/sdk-core/src/lib/db/training/training.models.ts:36\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/TrainingExecutions\n", + "4194605cdfbd414f8fa762630d555bc1/t/page/0-358": "@nuclia/core \u2022 Docs \n + \n @nuclia/core / PageStructure \n Interface: PageStructure \n Properties \n + page \n \n page: object \n \n height \n \n height: number \n \n width \n \n + width: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:238 + \n \n tokens \n \n tokens: PageToken[] \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:242\n\n\nLink: + https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageStructure\n", "42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696": " \n optional max_paragraph: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 \n \n name? \n \n optional name: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\n\n\nLink: @@ -846,39 +404,39 @@ interactions: Connection: - keep-alive Content-Length: - - '9897' + - '10388' Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/rerank + uri: https://europe-1.dp.progress.cloud/api/v1/predict/rerank response: body: - string: '{"context_scores":{"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340":0.87169349193573,"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412":0.7346909642219543,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709":0.4891679286956787,"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011":0.48352646827697754,"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575":0.338733047246933,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221":0.29879820346832275,"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276":0.29665425419807434,"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043":0.20577459037303925,"43004f553e534ffe9c9e735856bd9b23/t/page/212-480":0.2045007199048996,"43004f553e534ffe9c9e735856bd9b23/t/page/480-703":0.19605544209480286,"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757":0.01711088791489601,"4039d76b0fff4962900836ab3fdec9f7/t/page/5396-5615":0.017045317217707634,"dd41482018924facb5dbb87a7d53f122/t/page/1900-2653":0.0076066721230745316,"c27a1e5f5ddb4b118921345d713401b8/t/page/351-554":0.007577241398394108,"44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668":0.007260866463184357,"4039d76b0fff4962900836ab3fdec9f7/t/page/3340-4136":0.005001672077924013,"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696":0.00466365460306406,"4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326":0.0031115086749196053,"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299":0.002992665395140648,"b6a6202b9f0d4611a980293ce53337d6/t/page/265-405":0.0013302015140652657}}' + string: '{"context_scores":{"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340":0.5153226852416992,"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412":0.5087576508522034,"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011":0.16411417722702026,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221":0.14128142595291138,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977":0.09859886020421982,"43004f553e534ffe9c9e735856bd9b23/t/page/212-480":0.08787643909454346,"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043":0.08108211308717728,"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575":0.07463503628969193,"43004f553e534ffe9c9e735856bd9b23/t/page/480-703":0.04084571450948715,"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757":0.020844316110014915,"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833":0.017442485317587852,"24ad6997e1fe4a109d67d7802a083678/a/title/0-55":0.0034970103297382593,"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349":0.0031480707693845034,"4194605cdfbd414f8fa762630d555bc1/t/page/0-358":0.002822832902893424,"6e8250e6b5264156988657a221fd5e94/t/page/0-397":0.0026316740550100803,"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696":0.0023688741493970156,"44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668":0.0017821963410824537,"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224":0.0016356753185391426,"8b3e0ef630a346d1b591143309db87ec/t/page/0-281":0.001560889184474945,"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299":0.0010608151787891984}}' headers: Alt-Svc: - h3=":443"; ma=2592000 Content-Length: - - '1448' + - '1436' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 05 Aug 2026 07:57:20 GMT + - Wed, 05 Aug 2026 08:09:44 GMT nuclia-learning-model: - bge-reranker-v2-m3 via: - 1.1 google x-envoy-upstream-service-time: - - '90' + - '155' x-nuclia-trace-id: - - 60e8848bb49319ad253c7b985427fc28 + - 490d79e7ba3417a95ff3cf0b74409013 status: code: 200 message: OK @@ -916,11 +474,11 @@ interactions: List the IDs of the blocks relevant to the answer, if any (e.g., [\"block-AB\", \"block-CD\"]).\n11. **IMPORTANT** If any extra instructions are provided, you MUST follow them carefully when generating the answer field. These instructions - may specify the format, style, tools to use, or other requirements for the answer.\n\n\n\u00bfCu\u00e1l - es el enlace a la documentaci\u00f3n oficial sobre el uso del par\u00e1metro - `max_tokens`?\n\n\n\nContext:\n\n**block-AA**\n\n#### Chunk: - 4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\nTags: /k/text\n``` Use the - max_tokens parameter on the /ask endpoint to set hard limits on: \n - Context + may specify the format, style, tools to use, or other requirements for the answer.\n\n\nExplica + c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol y proporciona + un enlace a la documentaci\u00f3n oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### + Chunk: 4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\nTags: /k/text\n``` Use + the max_tokens parameter on the /ask endpoint to set hard limits on: \n - Context size: Limits the amount of retrieved information sent to the LLM \n - Answer length: Limits the length of the generated response \n Important Considerations \n Context Limitations: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n @@ -929,49 +487,36 @@ interactions: context (including the prompt, the retrieved results and the user question). \n max_output_tokens: the maximum number of tokens to generate. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n ```\n\n\n---\"\n\n\n**block-AC**\n\n#### - Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\nTags: /k/text\n``` ::: - \n :::warning \n Enabling reasoning can use additional tokens, which may increase - your usage costs. \n You may need to increase max_tokens to give the LLM enough - room to reason and generate an answer. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n - ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\nTags: - /k/text\n``` \n optional max_tokens: number \\| object \n \n Defines the maximum - number of tokens that the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 + Chunk: e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\nTags: /k/text\n``` \n + optional max_tokens: number \\| object \n \n Defines the maximum number of tokens + that the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n - ```\n\n\n---\"\n\n\n**block-AE**\n\n#### Chunk: 89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\nTags: - /k/text\n``` \n \n Maximum supported input tokens: \n Description: The maximum - number of tokens that the model can accept as input. Be mindful that this takes - into account the tokens used in the prompt, query and context. Also take note - that some models may provide their context window as the total between input - and output tokens, while others may provide it as the input tokens only. \n\n\n\nLink: - https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n - ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\nTags: + ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\nTags: /k/text\n``` \n optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n - ```\n\n\n---\"\n\n\n**block-AG**\n\n#### Chunk: 220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\nTags: - /k/text\n``` \n SDK: \n \n ```python \n from nuclia import sdk \n from nucliadb_models.search - import AskRequest, Reasoning \n search = sdk.NucliaSearch() \n query = AskRequest( - \n query= My question with extra reasoning effort , \n max_tokens=5000, \n reasoning=Reasoning( - \n display=True, # Show reasoning in the response \n effort= low , # Can be - low , medium , or high \n budget_tokens=1024 # How many tokens reasoning can - use \n ), \n ) \n search.ask(query=query) \n ``` \n Model Support for Reasoning - Options: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/search\n - ```\n\n\n---\"\n\n\n**block-AH**\n\n#### Chunk: 89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\nTags: - /k/text\n``` Description: The maximum number of tokens that the model can generate - as output. Again, we should keep in mind that this value summed to the Maximum - supported input tokens should not exceed the total context size supported by - the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n - ```\n\n\n---\"\n\n\n**block-AI**\n\n#### Chunk: 43004f553e534ffe9c9e735856bd9b23/t/page/212-480\nTags: + ```\n\n\n---\"\n\n\n**block-AE**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\nTags: + /k/text\n``` \n optional generative_model: string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 + \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 + \n \n max_tokens? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n + ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: 43004f553e534ffe9c9e735856bd9b23/t/page/212-480\nTags: /k/text\n``` \n optional driver: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 \n \n input_tokens \n \n input_tokens: object \n \n max \n \n max: number \n \n min? \n \n optional min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 \n \n max_images? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n - ```\n\n\n---\"\n\n\n**block-AJ**\n\n#### Chunk: 43004f553e534ffe9c9e735856bd9b23/t/page/480-703\nTags: - /k/text\n``` \n optional max_images: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 - \n \n output_tokens \n \n output_tokens: object \n \n default_max? \n \n optional - default_max: number \n \n max \n \n max: number \n \n min? \n \n\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n + ```\n\n\n---\"\n\n\n**block-AG**\n\n#### Chunk: 89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\nTags: + /k/text\n``` Description: The maximum number of tokens that the model can generate + as output. Again, we should keep in mind that this value summed to the Maximum + supported input tokens should not exceed the total context size supported by + the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n + ```\n\n\n---\"\n\n\n**block-AH**\n\n#### Chunk: 89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\nTags: + /k/text\n``` \n \n Maximum supported input tokens: \n Description: The maximum + number of tokens that the model can accept as input. Be mindful that this takes + into account the tokens used in the prompt, query and context. Also take note + that some models may provide their context window as the total between input + and output tokens, while others may provide it as the input tokens only. \n\n\n\nLink: + https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": false, "citation_threshold": null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 8192, "query_context_images": {}, "prefer_markdown": null, "json_schema": {"title": "validate_or_answer", @@ -997,11 +542,11 @@ interactions: Connection: - keep-alive Content-Length: - - '8904' + - '7839' Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-origin: @@ -1011,25 +556,17 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: - string: '{"chunk":{"type":"object","object":{"reason":"The context provides - multiple links related to the `max_tokens` parameter, specifically mentioning - its usage and implications. However, it does not specify a single official - documentation link for the `max_tokens` parameter. Instead, it lists several - links that may contain relevant information.","answer":"1. https://docs.rag.progress.cloud/docs/rag/advanced/consumption - 2. https://docs.rag.progress.cloud/docs/rag/advanced/widget/features 3. https://docs.rag.progress.cloud/docs/develop/python-sdk/search - 4. https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions - 5. https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models","missing_info_query":"","useful":"yes","citations":["block-AA","block-AB","block-AC","block-AD","block-AE","block-AH"]}}} - - {"chunk":{"type":"status","code":"0"}} - - {"chunk":{"type":"meta","input_tokens":60,"output_tokens":22,"timings":{"generative":3.422718916001031},"input_nuclia_tokens":0.06,"output_nuclia_tokens":0.022}} - - {"chunk":{"normalized_tokens":{"input":0.06012,"output":0.0222,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} - - ' + string: "{\"chunk\":{\"type\":\"object\",\"object\":{\"reason\":\"The context + provides information on how to use the `max_tokens` parameter, including its + purpose and limitations. It also includes links to official documentation + for further details.\",\"answer\":\"El par\xE1metro `max_tokens` se utiliza + en el endpoint /ask para establecer l\xEDmites en el tama\xF1o del contexto + y en la longitud de la respuesta generada. El `max_tokens` define el n\xFAmero + m\xE1ximo de tokens que el modelo tomar\xE1 como contexto. Para m\xE1s informaci\xF3n, + puedes consultar la documentaci\xF3n oficial en el siguiente enlace: https://docs.rag.progress.cloud/docs/rag/advanced/consumption.\",\"missing_info_query\":\"\",\"useful\":\"yes\",\"citations\":[\"block-AA\",\"block-AB\",\"block-AC\"]}}}\n{\"chunk\":{\"type\":\"status\",\"code\":\"0\"}}\n{\"chunk\":{\"type\":\"meta\",\"input_tokens\":52,\"output_tokens\":17,\"timings\":{\"generative\":3.5389355920051457},\"input_nuclia_tokens\":0.052,\"output_nuclia_tokens\":0.017}}\n{\"chunk\":{\"normalized_tokens\":{\"input\":0.0516,\"output\":0.01716,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0},\"type\":\"consumption\"}}\n" headers: Alt-Svc: - h3=":443"; ma=2592000 @@ -1040,17 +577,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:19 GMT + - Wed, 05 Aug 2026 08:09:43 GMT nuclia-learning-id: - - 90036b4e3f4b46cc81e68b346cd8b7f2 + - 85d649724f454c8dbbd7db4737b3ee45 nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '3428' + - '3548' x-nuclia-trace-id: - - b9aa266541bc1112934398c6b5ab4d0e + - fa7657ec4de46355d5b27e8688cbfbf8 status: code: 200 message: OK @@ -1064,23 +601,16 @@ interactions: this clearly\n\nAlways follow any additional instructions provided about format, style, or domain-specific behavior.", "chat_history": [], "context": [], "query_context": {}, "query_context_order": {}, "truncate": true, "user_prompt": {"prompt": "\n## - Question\nExplica c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar - la longitud de las respuestas en espa\u00f1ol, y proporciona un enlace a la - documentaci\u00f3n oficial.\n\n## Provided Context\n[START OF CONTEXT]\n## Retrieval - on nuclia-docs Knowledge Box\n\n# Explica c\u00f3mo usar el par\u00e1metro `max_tokens` - para controlar la longitud de las respuestas en espa\u00f1ol, y proporciona - un enlace a la documentaci\u00f3n oficial.\n\n Para usar el par\u00e1metro `max_tokens`, - se debe establecer un l\u00edmite en el n\u00famero m\u00e1ximo de tokens de - entrada y en el n\u00famero m\u00e1ximo de tokens a generar. Esto se puede hacer - en el endpoint /ask. El par\u00e1metro `max_tokens` limita la longitud de la - respuesta generada. Adem\u00e1s, se puede usar `max_output_tokens` para definir - el n\u00famero m\u00e1ximo de tokens a generar. Para m\u00e1s detalles, se recomienda - consultar la documentaci\u00f3n oficial.\n\n## Retrieval on nuclia-docs Knowledge - Box\n\n# \u00bfCu\u00e1l es el enlace a la documentaci\u00f3n oficial sobre - el uso del par\u00e1metro `max_tokens`?\n\n 1. https://docs.rag.progress.cloud/docs/rag/advanced/consumption - 2. https://docs.rag.progress.cloud/docs/rag/advanced/widget/features 3. https://docs.rag.progress.cloud/docs/develop/python-sdk/search - 4. https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions - 5. https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n[END + Question\nExplica c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol + y proporciona un enlace a la documentaci\u00f3n oficial.\n\n## Provided Context\n[START + OF CONTEXT]\n## Retrieval on nuclia-docs Knowledge Box\n\n# Explica c\u00f3mo + usar el par\u00e1metro `max_tokens` en espa\u00f1ol y proporciona un enlace + a la documentaci\u00f3n oficial.\n\n El par\u00e1metro `max_tokens` se utiliza + en el endpoint /ask para establecer l\u00edmites en el tama\u00f1o del contexto + y en la longitud de la respuesta generada. El `max_tokens` define el n\u00famero + m\u00e1ximo de tokens que el modelo tomar\u00e1 como contexto. Para m\u00e1s + informaci\u00f3n, puedes consultar la documentaci\u00f3n oficial en el siguiente + enlace: https://docs.rag.progress.cloud/docs/rag/advanced/consumption.\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all context; it may be lengthy or detailed\n- Do not omit or overlook any relevant information\n- Existing context summaries are answer attempts produced by retrieval agents. @@ -1092,12 +622,12 @@ interactions: the chunks for supporting citations.\n- If the context is incomplete or insufficient, state: \"Not enough data to answer this.\"\n- Read carefully any extra instructions below if provided and use them to answer\n\nNow provide your answer to the question: - Explica c\u00f3mo usar el par\u00e1metro `max_tokens` para controlar la longitud - de las respuestas en espa\u00f1ol, y proporciona un enlace a la documentaci\u00f3n - oficial."}, "citations": null, "citation_threshold": null, "generative_model": - "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": {}, "prefer_markdown": - null, "json_schema": null, "format_prompt": false, "rerank_context": false, - "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": null}' + Explica c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol y proporciona + un enlace a la documentaci\u00f3n oficial."}, "citations": null, "citation_threshold": + null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 5000, "query_context_images": + {}, "prefer_markdown": null, "json_schema": null, "format_prompt": false, "rerank_context": + false, "tools": [], "tool_choice": {"type": "auto"}, "reasoning": false, "seed": + null}' headers: Accept: - application/x-ndjson @@ -1106,17 +636,17 @@ interactions: Connection: - keep-alive Content-Length: - - '3418' + - '2735' Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-client-ident: - default x-message: - - 61239d46d4574621b88307ea3cf433d5 + - 07ebf4168bab4cffacebc2b72e8be648 x-origin: - RAO x-session: @@ -1126,53 +656,42 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: - string: "{\"chunk\":{\"type\":\"text\",\"text\":\"Para\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - usar\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + string: "{\"chunk\":{\"type\":\"text\",\"text\":\"El\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" par\xE1\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"metro\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - `\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"max\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"_tokens\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"`,\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - se\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" debe\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - establecer\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" un\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - l\xEDmite\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" n\xFAmero\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - m\xE1ximo\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - tokens\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" de\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - entrada\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" y\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + `\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"max\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"_tokens\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\"`\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" + se\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" utiliza\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" en\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" el\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - n\xFAmero\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" m\xE1ximo\"}}\n{\"chunk\":{\"type\":\"text\",\"text\":\" - 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- h3=":443"; ma=2592000 + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -1180,17 +699,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:23 GMT + - Wed, 05 Aug 2026 08:09:47 GMT nuclia-learning-id: - - a61fac6e4e5d4d33826c1c73f5e35dc1 + - 6955d10112104e769187c9bc24435e61 nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '477' + - '380' x-nuclia-trace-id: - - fcf1f24c12bd61843eb1d7408122aa08 + - 607c73b6b59bb8f8405d883716c732c1 status: code: 200 message: OK diff --git a/agents/nucliadb/tests/cassettes/test_sync/test_sync_agent.yaml b/agents/nucliadb/tests/cassettes/test_sync/test_sync_agent.yaml index 6d0d58b0..2f00417b 100644 --- a/agents/nucliadb/tests/cassettes/test_sync/test_sync_agent.yaml +++ b/agents/nucliadb/tests/cassettes/test_sync/test_sync_agent.yaml @@ -9,29 +9,29 @@ interactions: Connection: - keep-alive Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-nuclia-nuakey: - DUMMY method: GET - uri: https://europe-1.dp.stashify.cloud/api/authorizer/info + uri: https://europe-1.dp.progress.cloud/api/authorizer/info response: body: - string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"da1740fa-ab3e-4971-b374-7bb31b5dd325","account_id":"39f5fa6e-680a-475e-a757-812597e86d06","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' + string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"9e1317aa-e212-4a59-b794-afee535458a6","account_id":"07c2de7c-fa77-4374-a461-eea314da9dfd","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' headers: Alt-Svc: - - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + - h3=":443"; ma=2592000 Content-Length: - '227' content-type: - application/json date: - - Wed, 05 Aug 2026 07:57:43 GMT + - Wed, 05 Aug 2026 08:10:11 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '6' + - '7' status: code: 200 message: OK @@ -110,7 +110,7 @@ interactions: Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-origin: @@ -120,7 +120,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"object","object":{"reason":"The context provides @@ -134,14 +134,14 @@ interactions: {"chunk":{"type":"status","code":"0"}} - {"chunk":{"type":"meta","input_tokens":27,"output_tokens":17,"timings":{"generative":3.083326596999541},"input_nuclia_tokens":0.027,"output_nuclia_tokens":0.017}} + {"chunk":{"type":"meta","input_tokens":27,"output_tokens":17,"timings":{"generative":3.321704932997818},"input_nuclia_tokens":0.027,"output_nuclia_tokens":0.017}} {"chunk":{"normalized_tokens":{"input":0.02733,"output":0.0174,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} ' headers: Alt-Svc: - - h3=":443"; ma=2592000 + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: @@ -149,17 +149,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:50 GMT + - Wed, 05 Aug 2026 08:10:16 GMT nuclia-learning-id: - - 9df2841d21204feab276782bd70217e6 + - 4d979db5b03242838ffb37473c21713c nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '3089' + - '3327' x-nuclia-trace-id: - - 683ad4b937701608fa28f585ab2c960a + - b582eba985fe0e6bdd7c4e0465372858 status: code: 200 message: OK @@ -207,13 +207,13 @@ interactions: Content-Type: - application/json Host: - - europe-1.dp.stashify.cloud + - europe-1.dp.progress.cloud User-Agent: - nuclia.py/4.11.5 x-client-ident: - default x-message: - - 4fa44307ec264607b2e493bc8735a2bc + - 8984acd31c4d459ead3b940fcae2da3e x-origin: - RAO x-session: @@ -223,7 +223,7 @@ interactions: x-stf-nuakey: - DUMMY method: POST - uri: https://europe-1.dp.stashify.cloud/api/v1/predict/chat + uri: https://europe-1.dp.progress.cloud/api/v1/predict/chat response: body: string: '{"chunk":{"type":"text","text":"New"}} @@ -432,7 +432,7 @@ interactions: {"chunk":{"type":"status","code":"0"}} - {"chunk":{"type":"meta","input_tokens":12,"output_tokens":12,"timings":{"generative_first_chunk":0.3386507480026921,"generative":1.6827171629993245},"input_nuclia_tokens":0.012,"output_nuclia_tokens":0.012}} + {"chunk":{"type":"meta","input_tokens":12,"output_tokens":12,"timings":{"generative_first_chunk":0.6097889899974689,"generative":1.8998295229976065},"input_nuclia_tokens":0.012,"output_nuclia_tokens":0.012}} {"chunk":{"normalized_tokens":{"input":0.01176,"output":0.01236,"image":0.0},"customer_key_tokens":{"input":0.0,"output":0.0,"image":0.0},"type":"consumption"}} @@ -447,17 +447,17 @@ interactions: content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 07:57:53 GMT + - Wed, 05 Aug 2026 08:10:19 GMT nuclia-learning-id: - - 228aaa2bbde34ab5aeec5879ac99ad8a + - d62db6e7ca50459ea209701d038d5370 nuclia-learning-model: - chatgpt-azure-4o-mini via: - 1.1 google x-envoy-upstream-service-time: - - '346' + - '621' x-nuclia-trace-id: - - 9603c9f12264f172ba450a12759769cc + - a75f3ef14029a9e0ffe13538b7ef022a status: code: 200 message: OK From 96e4bcec0077357d5a174975fd2871b53a38effa Mon Sep 17 00:00:00 2001 From: Carles Onielfa Date: Wed, 5 Aug 2026 10:22:30 +0200 Subject: [PATCH 6/6] revert nucliadb --- .../test_nucliadb_agent_basic_ask.yaml | 994 ++-- .../test_nucliadb_agent_simple.yaml | 2759 ++++++++-- ...nt_simple_disable_ai_parameter_search.yaml | 4563 +++++++++++++++-- .../cassettes/test_sync/test_sync_agent.yaml | 2428 +++++++-- agents/nucliadb/tests/test_nucliadb.py | 35 +- agents/nucliadb/tests/test_sync.py | 13 +- 6 files changed, 9039 insertions(+), 1753 deletions(-) diff --git a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml index 2d2fcfc1..26812c1d 100644 --- a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml +++ b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_basic_ask.yaml @@ -1,4 +1,48 @@ interactions: +- request: + body: '{"prefixes": [{"prefix": "/n/i"}]}' + headers: + Accept: + - '*/*' + Accept-Encoding: + - gzip, deflate + Connection: + - keep-alive + Content-Length: + - '32' + Host: + - europe-1.nuclia.cloud + User-Agent: + - nucliadb-sdk/6.13.1.post6414 + content-type: + - application/json + x-stf-serviceaccount: + - DUMMY + method: POST + uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets + response: + body: + string: '{"facets":{"/n/i":986,"/n/i/application":1,"/n/i/application/json":1,"/n/i/text":985,"/n/i/text/markdown":985}}' + headers: + Alt-Svc: + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + Content-Length: + - '111' + access-control-expose-headers: + - X-NUCLIA-TRACE-ID + content-type: + - application/json + date: + - Wed, 15 Jul 2026 08:11:22 GMT + via: + - 1.1 google + x-envoy-upstream-service-time: + - '15' + x-nuclia-trace-id: + - 5fb40576d4d8cf1a6cb3c5e23df20600 + status: + code: 200 + message: OK - request: body: '' headers: @@ -9,417 +53,751 @@ interactions: Connection: - keep-alive Host: - - europe-1.dp.progress.cloud + - europe-1.nuclia.cloud User-Agent: - - nuclia.py/4.11.5 - x-nuclia-nuakey: + - nucliadb-sdk/6.13.1.post6414 + content-type: + - application/json + x-stf-serviceaccount: - DUMMY method: GET - uri: https://europe-1.dp.progress.cloud/api/authorizer/info + uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b response: body: - string: '{"auth":"nua_key","user":{"identity_type":"nua_key","user_id":"9e1317aa-e212-4a59-b794-afee535458a6","account_id":"07c2de7c-fa77-4374-a461-eea314da9dfd","account_type":"v3enterprise","allow_kb_management":false},"ip_info":null}' + string: '{"slug":"nuclia-docs","uuid":"df8b4c24-2807-4888-ad6c-ae97357a638b","config":{"uuid":null,"slug":"4f9285c7-7151-4431-94e6-3f1fb0d66aca:nuclia-docs","title":"Nuclia + Docs","description":"","learning_configuration":null,"external_index_provider":null,"configured_external_index_provider":{"type":"unset"},"similarity":null,"hidden_resources_enabled":false,"hidden_resources_hide_on_creation":false,"enforce_security":false},"model":null}' headers: Alt-Svc: - 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Allowlist these if you restrict inbound traffic to your infrastructure. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n :::note \\n The current list of IP addresses is also available in machine-readable + format: JSON | YAML. These lists may change over time, so we recommend periodically + fetching and applying updates to your firewall rules to ensure uninterrupted + service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall + restricts network traffic, you may need to allowlist the following IP addresses. + They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | + --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 + | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 + | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- + | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n + | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 + | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | + 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 + | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 + | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United + States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- + | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 + | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS + PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately + through an AWS endpoint service (AWS PrivateLink) instead of over the public + internet, allowing connections to be established from your VPC without traversing + public IP addresses. This option is not available through self-service configuration. + Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests + on. Allowlist these if you restrict outbound traffic from your infrastructure + and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent + \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful + tool that enhances the capabilities of traditional retrieval-augmented generation + (RAG) systems. Regular RAG's fixed search-then-generate process is limiting + for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Different models can be chosen for different tasks: \\n \\n Context validation + happens when the Prune context option is enabled (recommended), we recommend + using a fast model - planning or the execution model (depending on the planning + mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Note: the rephrasing model is only used in more complex workflow, it can + be ignored in the present case. \\n Finally, add a Summarize agent in the + Generation step to generate a final answer from the retrieved information. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The Smart Agent plans the answer: picks the most appropriate sources, splits + the question into sub-questions, evaluates relevancy, and iterates autonomously + until the information is sufficient. \\n Basic usage \\n To set up a Smart + Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, + etc.) in the Sources section of the left menu. Then, create a new workflow + in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Chat mode \\n If you want to use the Smart Agent in a chat interface, you + need the following: \\n \\n Enable the Session history option in the Smart + Agent configuration. This will allow the Smart Agent to take into account + the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Then connect your sources as Registered Agents to the Smart Agent. It is very + important that you provide an extensive description of each registered agent, + so that the Smart Agent can understand what each source is about and when + to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n reactive: The Smart Agent will decide what to do first, and will plan + the next steps based on the information it retrieves. It is expected to be + faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, + and will execute them. It will be slower but more accurate when processing + complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also select the proper function for each registered agent, depending on the + type of source (MCP agents will not need one, the functions are provided dynamically + by the MCP server). \\n In the Smart Agent configuration, you can select the + planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In the Summarize Agent, enable the Conversational mode. This will allow the + Summarize Agent to generate a final answer that will not repeat the information + already provided in the previous conversation, and will be more natural for + a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Custom frontend \\n You can also create a custom frontend for your Retrieval + Agent. This allows you to have full control over the user interface and user + experience. \\n You can directly implement the API calls to your Retrieval + Agent in your frontend code (see the Websocket API section for more details), + or you can use the JavaScript SDK provided by Agentic to simplify the integration. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based + system (for example Claude Cowork or Copilot), it is reachable throught MCP. + \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval + Agent can be deployed in different ways, depending on your needs and the environment + you are working in. \\n Ready-to-use widget \\n The easiest way to deploy + your Retrieval Agent is to use the ready-to-use widget. You can embed it in + your website or application, and it will provide a chat user interface for + interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Go to the Widgets section in the left menu, and click on Create widget to + create a new widget. You can customize its appearance, and then copy the generated + code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 - Transfer-Encoding: - - chunked + Content-Length: + - '12993' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - - application/x-ndjson + - application/json date: - - Wed, 05 Aug 2026 08:09:56 GMT - nuclia-learning-id: - - 7a38f8e9dd32443ca290185b45ac590e - nuclia-learning-model: - - chatgpt-azure-4o-mini + - Wed, 15 Jul 2026 08:11:22 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '5033' + - '48' x-nuclia-trace-id: - - 97bebbe9e4eb4a72b92e307f9d75058e + - e2a8c7b44674b9bad737fc35b812a917 status: code: 200 message: OK - request: - body: '{"question": "", "retrieval": true, "user_id": "summarize", "system": "You - are a helpful AI assistant. 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Allowlist these if you restrict inbound traffic to your infrastructure. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n :::note \\n The current list of IP addresses is also available in machine-readable + format: JSON | YAML. These lists may change over time, so we recommend periodically + fetching and applying updates to your firewall rules to ensure uninterrupted + service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall + restricts network traffic, you may need to allowlist the following IP addresses. + They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | + --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 + | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 + | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- + | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n + | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 + | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | + 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 + | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 + | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United + States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- + | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 + | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS + PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately + through an AWS endpoint service (AWS PrivateLink) instead of over the public + internet, allowing connections to be established from your VPC without traversing + public IP addresses. This option is not available through self-service configuration. + Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests + on. Allowlist these if you restrict outbound traffic from your infrastructure + and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent + \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful + tool that enhances the capabilities of traditional retrieval-augmented generation + (RAG) systems. Regular RAG's fixed search-then-generate process is limiting + for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Different models can be chosen for different tasks: \\n \\n Context validation + happens when the Prune context option is enabled (recommended), we recommend + using a fast model - planning or the execution model (depending on the planning + mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Note: the rephrasing model is only used in more complex workflow, it can + be ignored in the present case. \\n Finally, add a Summarize agent in the + Generation step to generate a final answer from the retrieved information. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The Smart Agent plans the answer: picks the most appropriate sources, splits + the question into sub-questions, evaluates relevancy, and iterates autonomously + until the information is sufficient. \\n Basic usage \\n To set up a Smart + Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, + etc.) in the Sources section of the left menu. Then, create a new workflow + in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Chat mode \\n If you want to use the Smart Agent in a chat interface, you + need the following: \\n \\n Enable the Session history option in the Smart + Agent configuration. This will allow the Smart Agent to take into account + the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Then connect your sources as Registered Agents to the Smart Agent. It is very + important that you provide an extensive description of each registered agent, + so that the Smart Agent can understand what each source is about and when + to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n reactive: The Smart Agent will decide what to do first, and will plan + the next steps based on the information it retrieves. It is expected to be + faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, + and will execute them. It will be slower but more accurate when processing + complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also select the proper function for each registered agent, depending on the + type of source (MCP agents will not need one, the functions are provided dynamically + by the MCP server). \\n In the Smart Agent configuration, you can select the + planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In the Summarize Agent, enable the Conversational mode. This will allow the + Summarize Agent to generate a final answer that will not repeat the information + already provided in the previous conversation, and will be more natural for + a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Custom frontend \\n You can also create a custom frontend for your Retrieval + Agent. This allows you to have full control over the user interface and user + experience. \\n You can directly implement the API calls to your Retrieval + Agent in your frontend code (see the Websocket API section for more details), + or you can use the JavaScript SDK provided by Agentic to simplify the integration. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based + system (for example Claude Cowork or Copilot), it is reachable throught MCP. + \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval + Agent can be deployed in different ways, depending on your needs and the environment + you are working in. \\n Ready-to-use widget \\n The easiest way to deploy + your Retrieval Agent is to use the ready-to-use widget. You can embed it in + your website or application, and it will provide a chat user interface for + interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Go to the Widgets section in the left menu, and click on Create widget to + create a new widget. 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strategies\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-09-12T08:39:42.634556\",\"modified\":\"2026-06-09T08:18:07.009807\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"1cf976a5ca5947cd89a2f2a047b71ce9/t/page/963-1239\":{\"score\":0.00431468803435564,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" + Key components of a split strategy include: \\n \\n Max paragraph size: Sets + the maximum size (in characters or tokens) for each chunk. \\n Custom split: + Determines the method used for splitting: \\n Manual splitting: Splits content + based on a specified delimiter (default is \\\\n ). 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ConsumptionAskResponseItem\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:47:37.548412\",\"modified\":\"2026-07-14T12:48:09.327828\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\":{\"score\":0.0019418168812990189,\"score_type\":\"RERANKER\",\"order\":18,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: + ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n + customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 + \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n + type \\n \\n\",\"id\":\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":397,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"89cc367c149e4f6eab0e06a743d1edba\":{\"id\":\"89cc367c149e4f6eab0e06a743d1edba\",\"slug\":\"docs-rag-advanced-openai-api-compatible-models-md\",\"title\":\"docs + > rag > advanced > openai api compatible models\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-05-23T07:21:32.894218\",\"modified\":\"2026-06-09T08:07:43.359058\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\":{\"score\":0.023197626695036888,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" + Description: The maximum number of tokens that the model can generate as output. + Again, we should keep in mind that this value summed to the Maximum supported + input tokens should not exceed the total context size supported by the model. + \\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":2804,\"end\":3043,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\":{\"score\":0.022499969229102135,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" + \\n \\n Maximum supported input tokens: \\n Description: The maximum number + of tokens that the model can accept as input. Be mindful that this takes into + account the tokens used in the prompt, query and context. Also take note that + some models may provide their context window as the total between input and + output tokens, while others may provide it as the input tokens only. \\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":2202,\"end\":2575,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"0a003c3f724e45e392a9c8d1ce8800c1\":{\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1\",\"slug\":\"docs-develop-js-sdk-interfaces-Consumption-md\",\"title\":\"docs + > develop > js sdk > interfaces > Consumption\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:51:46.788864\",\"modified\":\"2026-07-14T12:51:15.300757\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\":{\"score\":0.0018675660248845816,\"score_type\":\"RERANKER\",\"order\":19,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption + \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n + \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-07-14T12:49:58.922592\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\":{\"score\":0.06359858065843582,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" + \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 + \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: + number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \\n \\n max_images? \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\":{\"score\":0.03126191347837448,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" + \\n optional max_images: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 + \\n \\n output_tokens \\n \\n output_tokens: object \\n \\n default_max? \\n + \\n optional default_max: number \\n \\n max \\n \\n max: number \\n \\n min? + \\n \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs + > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-07-14T12:51:04.368823\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\":{\"score\":0.08647765219211578,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\" + \\n optional max_tokens: number \\\\| object \\n \\n Defines the maximum number + of tokens that the model will take as context. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \\n \\n min_score? \\n\",\"id\":\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2808,\"end\":3011,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"e8525e64c5b44982b958d32cf6090613/t/page/2450-2808\":{\"score\":0.053502149879932404,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\" + \\n optional highlight: boolean \\n \\n Inherited from \\n BaseSearchOptions.highlight + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:76 \\n + \\n keyword_filters? \\n \\n optional keyword_filters: string[] \\\\| Filter[] + \\n \\n Inherited from \\n BaseSearchOptions.keyword_filters \\n Defined in + \\n libs/sdk-core/src/lib/db/search/search.models.ts:65 \\n \\n max_tokens? + \\n\",\"id\":\"e8525e64c5b44982b958d32cf6090613/t/page/2450-2808\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2450,\"end\":2808,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"220eb37c167f4eb9bb8e9454e7ba8cf5\":{\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5\",\"slug\":\"docs-develop-python-sdk-05-search-md\",\"title\":\"docs + > develop > python sdk > 05 search\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:48:33.723913\",\"modified\":\"2026-06-09T08:08:04.866092\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\":{\"score\":0.09982066601514816,\"score_type\":\"RERANKER\",\"order\":3,\"text\":\" + \\n SDK: \\n \\n ```python \\n from nuclia import sdk \\n from nucliadb_models.search + import AskRequest, Reasoning \\n search = sdk.NucliaSearch() \\n query = AskRequest( + \\n query= My question with extra reasoning effort , \\n max_tokens=5000, + \\n reasoning=Reasoning( \\n display=True, # Show reasoning in the response + \\n effort= low , # Can be low , medium , or high \\n budget_tokens=1024 # + How many tokens reasoning can use \\n ), \\n ) \\n search.ask(query=query) + \\n ``` \\n Model Support for Reasoning Options: \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":1790,\"end\":2276,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\":{\"score\":0.05582314357161522,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" + ::: \\n :::warning \\n Enabling reasoning can use additional tokens, which + may increase your usage costs. \\n You may need to increase max_tokens to + give the LLM enough room to reason and generate an answer. \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":2505,\"end\":2709,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs + > rag > advanced > consumption.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-10-03T08:32:26.341394\",\"modified\":\"2026-06-09T08:18:16.730959\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\":{\"score\":0.456288605928421,\"score_type\":\"RERANKER\",\"order\":0,\"text\":\" + Use the max_tokens parameter on the /ask endpoint to set hard limits on: \\n + - Context size: Limits the amount of retrieved information sent to the LLM + \\n - Answer length: Limits the length of the generated response \\n Important + Considerations \\n Context Limitations: \\n\",\"id\":\"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":3075,\"end\":3340,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"66b6f0dbd883413e98fbbf5b59f049b9\":{\"id\":\"66b6f0dbd883413e98fbbf5b59f049b9\",\"slug\":\"docs-develop-js-sdk-enumerations-UsageType-md\",\"title\":\"docs + > develop > js sdk > enumerations > UsageType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"tl\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T09:59:02.349911\",\"modified\":\"2026-07-14T12:54:11.386825\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833\":{\"score\":0.029986508190631866,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / UsageType \\n Enumeration: UsageType \\n + Enumeration Members \\n AI_TOKENS_USED \\n \\n AI_TOKENS_USED: ai_tokens_used + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:206 \\n \\n BYTES_PROCESSED + \\n \\n BYTES_PROCESSED: bytes_processed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:197 + \\n \\n CHARS_PROCESSED \\n \\n CHARS_PROCESSED: chars_processed \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:198 \\n \\n MEDIA_FILES_PROCESSED + \\n \\n MEDIA_FILES_PROCESSED: media_files_processed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:200 \\n \\n MEDIA_SECONDS_PROCESSED + \\n \\n MEDIA_SECONDS_PROCESSED: media_seconds_processed \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n + NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 + \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED + \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n + \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 + \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED + \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 + \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED + \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: + train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"id\":\"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"50aac6f34b6d47de8e3b01f8b2de6e9c\":{\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c\",\"slug\":\"docs-develop-js-sdk-interfaces-PredictAnswerOptions-md\",\"title\":\"docs + > develop > js sdk > interfaces > PredictAnswerOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:11.443619\",\"modified\":\"2026-07-14T12:50:46.385594\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\":{\"score\":0.1041124165058136,\"score_type\":\"RERANKER\",\"order\":2,\"text\":\" + \\n optional max_tokens: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \\n \\n query_context? + \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false},\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\":{\"score\":0.04401864856481552,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" + \\n optional generative_model: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 + \\n \\n json_schema? \\n \\n optional json_schema: object \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 \\n \\n max_tokens? + \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"b14cf452a3434839a04c111f2ea4dc51\":{\"id\":\"b14cf452a3434839a04c111f2ea4dc51\",\"slug\":\"docs-develop-js-sdk-enums-UsageType-md\",\"title\":\"docs + > develop > js sdk > enums > UsageType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"tn\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:41.582110\",\"modified\":\"2026-06-09T08:13:34.112208\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139\":{\"score\":0.042562730610370636,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\"@nuclia/core + / Exports / UsageType \\n Enumeration: UsageType \\n Table of contents \\n + Enumeration Members \\n \\n AI_TOKENS_USED \\n BYTES_PROCESSED \\n CHARS_PROCESSED + \\n MEDIA_FILES_PROCESSED \\n MEDIA_SECONDS_PROCESSED \\n NUCLIA_TOKENS \\n + PAGES_PROCESSED \\n PARAGRAPHS_PROCESSED \\n PRE_PROCESSING_TIME \\n RESOURCES_PROCESSED + \\n SEARCHES_PERFORMED \\n SLOW_PROCESSING_TIME \\n SUGGESTIONS_PERFORMED + \\n TRAIN_SECONDS \\n \\n Enumeration Members \\n AI_TOKENS_USED \\n \u2022 + AI_TOKENS_USED = ai_tokens_used \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:190 + \\n \\n BYTES_PROCESSED \\n \u2022 BYTES_PROCESSED = bytes_processed \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:181 \\n \\n CHARS_PROCESSED \\n + \u2022 CHARS_PROCESSED = chars_processed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:182 + \\n \\n MEDIA_FILES_PROCESSED \\n \u2022 MEDIA_FILES_PROCESSED = media_files_processed + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184 \\n \\n MEDIA_SECONDS_PROCESSED + \\n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \\n Defined in + \\n libs/sdk-core/src/lib/db/db.models.ts:183 \\n \\n NUCLIA_TOKENS \\n \u2022 + NUCLIA_TOKENS = nuclia_tokens_billed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:191 + \\n \\n PAGES_PROCESSED \\n \u2022 PAGES_PROCESSED = pages_processed \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n PARAGRAPHS_PROCESSED + \\n \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:186 \\n \\n PRE_PROCESSING_TIME \\n + \u2022 PRE_PROCESSING_TIME = pre_processing_time \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:178 + \\n \\n RESOURCES_PROCESSED \\n \u2022 RESOURCES_PROCESSED = resources_processed + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:180 \\n \\n SEARCHES_PERFORMED + \\n \u2022 SEARCHES_PERFORMED = searches_performed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:188 + \\n \\n SLOW_PROCESSING_TIME \\n \u2022 SLOW_PROCESSING_TIME = slow_processing_time + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:179 \\n \\n SUGGESTIONS_PERFORMED + \\n \u2022 SUGGESTIONS_PERFORMED = suggestions_performed \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:189 \\n \\n TRAIN_SECONDS \\n \u2022 + TRAIN_SECONDS = train_seconds \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:187\",\"id\":\"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":2139,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"ecabb0862fa24c8fb8e01d4930a3f7a2\":{\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2\",\"slug\":\"docs-develop-js-sdk-variables-MAX_FACETS_PER_REQUEST-md\",\"title\":\"docs + > develop > js sdk > variables > MAX_FACETS_PER_REQUEST\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:18.992004\",\"modified\":\"2026-07-14T12:54:35.795661\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/a/title\":{\"paragraphs\":{\"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60\":{\"score\":0.00220838887616992,\"score_type\":\"RERANKER\",\"order\":17,\"text\":\"docs + > develop > js sdk > variables > MAX_FACETS_PER_REQUEST\",\"id\":\"ecabb0862fa24c8fb8e01d4930a3f7a2/a/title/0-60\",\"labels\":[],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":60,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"is_a_table\":false}}}}},\"9f7036a7a6694700b72d52eb58a8326c\":{\"id\":\"9f7036a7a6694700b72d52eb58a8326c\",\"slug\":\"docs-rag-advanced-widget-features-md\",\"title\":\"docs + > rag > advanced > widget > features\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T14:32:26.204740\",\"modified\":\"2026-06-09T08:07:51.648767\",\"last_seqid\":0,\"queue\":\"private\",\"hidden\":false,\"fields\":{\"/t/page\":{\"paragraphs\":{\"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\":{\"score\":0.40833574533462524,\"score_type\":\"RERANKER\",\"order\":1,\"text\":\" + max_tokens: the maximum number of input tokens to put in the final context + (including the prompt, the retrieved results and the user question). \\n max_output_tokens: + the maximum number of tokens to generate. 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Again, we should keep - in mind that this value summed to the Maximum supported input tokens should - not exceed the total context size supported by the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", - "9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412": " max_tokens: the maximum - number of input tokens to put in the final context (including the prompt, the - retrieved results and the user question). \n max_output_tokens: the maximum - number of tokens to generate. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n", - "0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349": "@nuclia/core \u2022 Docs \n - \n @nuclia/core / Consumption \n Interface: Consumption \n Properties \n customer_key_tokens - \n \n customer_key_tokens: TokenConsumption \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:230 - \n \n normalized_tokens \n \n normalized_tokens: TokenConsumption \n \n Defined - in \n libs/sdk-core/src/lib/db/search/ask.models.ts:229\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Consumption\n", - "43004f553e534ffe9c9e735856bd9b23/t/page/480-703": " \n optional max_images: - string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \n \n - output_tokens \n \n output_tokens: object \n \n default_max? 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\n - \n optional keyword_filters: string[] \\| Filter[] \n \n Inherited from \n BaseSearchOptions.keyword_filters - \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:65 \n \n max_tokens? - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n", - "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221": " \n optional max_tokens: - number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined - in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", - "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977": " \n optional generative_model: - string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 - \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 - \n \n max_tokens? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", - "f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299": "@nuclia/core \u2022 Docs \n - \n @nuclia/core / PageToken \n Interface: PageToken \n Properties \n height - \n \n height: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 - \n \n line \n \n line: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 - \n \n text \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageToken\n", - "24ad6997e1fe4a109d67d7802a083678/a/title/0-55": "docs > develop > js sdk > - interfaces > TokenConsumption\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/TokenConsumption\n", - "6e8250e6b5264156988657a221fd5e94/t/page/0-397": "@nuclia/core \u2022 Docs \n - \n @nuclia/core / Ask / ConsumptionAskResponseItem \n Interface: ConsumptionAskResponseItem - \n Properties \n customer_key_tokens \n \n customer_key_tokens: TokenConsumption - \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:127 \n \n - normalized_tokens \n \n normalized_tokens: TokenConsumption \n \n Defined in - \n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \n \n type \n \n\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/namespaces/Ask/interfaces/ConsumptionAskResponseItem\n", - "7b41750917e349598c846526162ebb68/a/title/0-58": "docs > develop > js sdk > - interfaces > NucliaTokensDetails\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/NucliaTokensDetails\n", - "4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340": " Use the max_tokens parameter - on the /ask endpoint to set hard limits on: \n - Context size: Limits the amount - of retrieved information sent to the LLM \n - Answer length: Limits the length - of the generated response \n Important Considerations \n Context Limitations: - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", - "328ed5b87692439a881303c7c1d4eefc/a/title/0-52": "docs > develop > js sdk > - interfaces > Ask.AskTokens\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Ask.AskTokens\n", - "66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833": "@nuclia/core \u2022 Docs - \n \n @nuclia/core / UsageType \n Enumeration: UsageType \n Enumeration Members - \n AI_TOKENS_USED \n \n AI_TOKENS_USED: ai_tokens_used \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:208 - \n \n BYTES_PROCESSED \n \n BYTES_PROCESSED: bytes_processed \n \n Defined in - \n libs/sdk-core/src/lib/db/db.models.ts:199 \n \n CHARS_PROCESSED \n \n CHARS_PROCESSED: - chars_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:200 - \n \n MEDIA_FILES_PROCESSED \n \n MEDIA_FILES_PROCESSED: media_files_processed - \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:202 \n \n MEDIA_SECONDS_PROCESSED - \n \n MEDIA_SECONDS_PROCESSED: media_seconds_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:201 - \n \n NUCLIA_TOKENS \n \n NUCLIA_TOKENS: nuclia_tokens_billed \n \n Defined - in \n libs/sdk-core/src/lib/db/db.models.ts:209 \n \n PAGES_PROCESSED \n \n - PAGES_PROCESSED: pages_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:203 - \n \n PARAGRAPHS_PROCESSED \n \n PARAGRAPHS_PROCESSED: paragraphs_processed - \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:204 \n \n PRE_PROCESSING_TIME - \n \n PRE_PROCESSING_TIME: pre_processing_time \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:196 - \n \n RESOURCES_PROCESSED \n \n RESOURCES_PROCESSED: resources_processed \n - \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:198 \n \n SEARCHES_PERFORMED - \n \n SEARCHES_PERFORMED: searches_performed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:206 - \n \n SLOW_PROCESSING_TIME \n \n SLOW_PROCESSING_TIME: slow_processing_time - \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:197 \n \n SUGGESTIONS_PERFORMED - \n \n SUGGESTIONS_PERFORMED: suggestions_performed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:207 - \n \n TRAIN_SECONDS \n \n TRAIN_SECONDS: train_seconds \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:205\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/enumerations/UsageType\n", - "0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224": "@nuclia/core \u2022 Docs \n - \n @nuclia/core / ReasoningConfig \n Interface: ReasoningConfig \n Properties - \n budget_tokens? \n \n optional budget_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 - \n \n effort? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ReasoningConfig\n", - "b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139": "@nuclia/core / Exports / - UsageType \n Enumeration: UsageType \n Table of contents \n Enumeration Members - \n \n AI_TOKENS_USED \n BYTES_PROCESSED \n CHARS_PROCESSED \n MEDIA_FILES_PROCESSED - \n MEDIA_SECONDS_PROCESSED \n NUCLIA_TOKENS \n PAGES_PROCESSED \n PARAGRAPHS_PROCESSED - \n PRE_PROCESSING_TIME \n RESOURCES_PROCESSED \n SEARCHES_PERFORMED \n SLOW_PROCESSING_TIME - \n SUGGESTIONS_PERFORMED \n TRAIN_SECONDS \n \n Enumeration Members \n AI_TOKENS_USED - \n \u2022 AI_TOKENS_USED = ai_tokens_used \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:190 - \n \n BYTES_PROCESSED \n \u2022 BYTES_PROCESSED = bytes_processed \n Defined - in \n libs/sdk-core/src/lib/db/db.models.ts:181 \n \n CHARS_PROCESSED \n \u2022 - CHARS_PROCESSED = chars_processed \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:182 - \n \n MEDIA_FILES_PROCESSED \n \u2022 MEDIA_FILES_PROCESSED = media_files_processed - \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:184 \n \n MEDIA_SECONDS_PROCESSED - \n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \n Defined in \n - libs/sdk-core/src/lib/db/db.models.ts:183 \n \n NUCLIA_TOKENS \n \u2022 NUCLIA_TOKENS - = nuclia_tokens_billed \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:191 - \n \n PAGES_PROCESSED \n \u2022 PAGES_PROCESSED = pages_processed \n Defined - in \n libs/sdk-core/src/lib/db/db.models.ts:185 \n \n PARAGRAPHS_PROCESSED \n - \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:186 - \n \n PRE_PROCESSING_TIME \n \u2022 PRE_PROCESSING_TIME = pre_processing_time - \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:178 \n \n RESOURCES_PROCESSED - \n \u2022 RESOURCES_PROCESSED = resources_processed \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:180 - \n \n SEARCHES_PERFORMED \n \u2022 SEARCHES_PERFORMED = searches_performed \n - Defined in \n libs/sdk-core/src/lib/db/db.models.ts:188 \n \n SLOW_PROCESSING_TIME - \n \u2022 SLOW_PROCESSING_TIME = slow_processing_time \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:179 - \n \n SUGGESTIONS_PERFORMED \n \u2022 SUGGESTIONS_PERFORMED = suggestions_performed - \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:189 \n \n TRAIN_SECONDS - \n \u2022 TRAIN_SECONDS = train_seconds \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:187\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/enums/UsageType\n", "42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696": - " \n optional max_paragraph: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 - \n \n name? \n \n optional name: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/SplitStrategy\n"}}' + body: '{"features": ["keyword"], "faceted": ["/classification.labels"]}' headers: Accept: - '*/*' @@ -431,310 +231,2203 @@ interactions: Connection: - keep-alive Content-Length: - - '12751' - Content-Type: + - '61' + Host: + - europe-1.nuclia.cloud + User-Agent: + - nucliadb-sdk/6.13.1.post6414 + content-type: - application/json + x-stf-serviceaccount: + - DUMMY + method: POST + uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + response: + body: + string: "{\"resources\":{\"007b445866574d7ca69891d388663cc6\":{\"id\":\"007b445866574d7ca69891d388663cc6\",\"slug\":\"docs-management-security-5-public-ips-md\",\"title\":\"docs + > management > security > 5 public ips\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-03T09:28:57.937064\",\"modified\":\"2026-07-03T09:28:57.937076\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs + > agentic > deploy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-29T13:39:02.557258\",\"modified\":\"2026-06-29T13:39:02.557276\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"b28e388104644fc5bba68c0cd44e01d4\":{\"id\":\"b28e388104644fc5bba68c0cd44e01d4\",\"slug\":\"docs-agentic-how-to-agentic-retrieval-md\",\"title\":\"docs + > agentic > how to > agentic retrieval\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-29T13:39:03.379512\",\"modified\":\"2026-06-29T13:39:03.379525\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Outbound \u2014 the source IP addresses that Progress Agentic RAG uses when + making connections to your systems (e.g., webhooks, sync agents, or other + integrations). Allowlist these if you restrict inbound traffic to your infrastructure. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n :::note \\n The current list of IP addresses is also available in machine-readable + format: JSON | YAML. These lists may change over time, so we recommend periodically + fetching and applying updates to your firewall rules to ensure uninterrupted + service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall + restricts network traffic, you may need to allowlist the following IP addresses. + They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | + --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 + | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 + | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- + | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n + | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 + | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | + 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 + | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 + | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United + States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- + | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 + | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS + PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately + through an AWS endpoint service (AWS PrivateLink) instead of over the public + internet, allowing connections to be established from your VPC without traversing + public IP addresses. This option is not available through self-service configuration. + Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests + on. Allowlist these if you restrict outbound traffic from your infrastructure + and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent + \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful + tool that enhances the capabilities of traditional retrieval-augmented generation + (RAG) systems. Regular RAG's fixed search-then-generate process is limiting + for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Different models can be chosen for different tasks: \\n \\n Context validation + happens when the Prune context option is enabled (recommended), we recommend + using a fast model - planning or the execution model (depending on the planning + mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Note: the rephrasing model is only used in more complex workflow, it can + be ignored in the present case. \\n Finally, add a Summarize agent in the + Generation step to generate a final answer from the retrieved information. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The Smart Agent plans the answer: picks the most appropriate sources, splits + the question into sub-questions, evaluates relevancy, and iterates autonomously + until the information is sufficient. \\n Basic usage \\n To set up a Smart + Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, + etc.) in the Sources section of the left menu. Then, create a new workflow + in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Chat mode \\n If you want to use the Smart Agent in a chat interface, you + need the following: \\n \\n Enable the Session history option in the Smart + Agent configuration. This will allow the Smart Agent to take into account + the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Then connect your sources as Registered Agents to the Smart Agent. It is very + important that you provide an extensive description of each registered agent, + so that the Smart Agent can understand what each source is about and when + to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n reactive: The Smart Agent will decide what to do first, and will plan + the next steps based on the information it retrieves. It is expected to be + faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, + and will execute them. It will be slower but more accurate when processing + complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also select the proper function for each registered agent, depending on the + type of source (MCP agents will not need one, the functions are provided dynamically + by the MCP server). \\n In the Smart Agent configuration, you can select the + planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In the Summarize Agent, enable the Conversational mode. This will allow the + Summarize Agent to generate a final answer that will not repeat the information + already provided in the previous conversation, and will be more natural for + a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Custom frontend \\n You can also create a custom frontend for your Retrieval + Agent. This allows you to have full control over the user interface and user + experience. \\n You can directly implement the API calls to your Retrieval + Agent in your frontend code (see the Websocket API section for more details), + or you can use the JavaScript SDK provided by Agentic to simplify the integration. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based + system (for example Claude Cowork or Copilot), it is reachable throught MCP. + \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval + Agent can be deployed in different ways, depending on your needs and the environment + you are working in. \\n Ready-to-use widget \\n The easiest way to deploy + your Retrieval Agent is to use the ready-to-use widget. You can embed it in + your website or application, and it will provide a chat user interface for + interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Go to the Widgets section in the left menu, and click on Create widget to + create a new widget. 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Allowlist these if you restrict inbound traffic to your infrastructure. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n :::note \\n The current list of IP addresses is also available in machine-readable + format: JSON | YAML. These lists may change over time, so we recommend periodically + fetching and applying updates to your firewall rules to ensure uninterrupted + service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall + restricts network traffic, you may need to allowlist the following IP addresses. + They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | + --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 + | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 + | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- + | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n + | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 + | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | + 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 + | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 + | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United + States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- + | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 + | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS + PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately + through an AWS endpoint service (AWS PrivateLink) instead of over the public + internet, allowing connections to be established from your VPC without traversing + public IP addresses. This option is not available through self-service configuration. + Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests + on. Allowlist these if you restrict outbound traffic from your infrastructure + and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent + \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful + tool that enhances the capabilities of traditional retrieval-augmented generation + (RAG) systems. Regular RAG's fixed search-then-generate process is limiting + for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Different models can be chosen for different tasks: \\n \\n Context validation + happens when the Prune context option is enabled (recommended), we recommend + using a fast model - planning or the execution model (depending on the planning + mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Note: the rephrasing model is only used in more complex workflow, it can + be ignored in the present case. \\n Finally, add a Summarize agent in the + Generation step to generate a final answer from the retrieved information. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The Smart Agent plans the answer: picks the most appropriate sources, splits + the question into sub-questions, evaluates relevancy, and iterates autonomously + until the information is sufficient. \\n Basic usage \\n To set up a Smart + Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, + etc.) in the Sources section of the left menu. Then, create a new workflow + in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Chat mode \\n If you want to use the Smart Agent in a chat interface, you + need the following: \\n \\n Enable the Session history option in the Smart + Agent configuration. This will allow the Smart Agent to take into account + the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Then connect your sources as Registered Agents to the Smart Agent. It is very + important that you provide an extensive description of each registered agent, + so that the Smart Agent can understand what each source is about and when + to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n reactive: The Smart Agent will decide what to do first, and will plan + the next steps based on the information it retrieves. It is expected to be + faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, + and will execute them. It will be slower but more accurate when processing + complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also select the proper function for each registered agent, depending on the + type of source (MCP agents will not need one, the functions are provided dynamically + by the MCP server). \\n In the Smart Agent configuration, you can select the + planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In the Summarize Agent, enable the Conversational mode. This will allow the + Summarize Agent to generate a final answer that will not repeat the information + already provided in the previous conversation, and will be more natural for + a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Custom frontend \\n You can also create a custom frontend for your Retrieval + Agent. This allows you to have full control over the user interface and user + experience. \\n You can directly implement the API calls to your Retrieval + Agent in your frontend code (see the Websocket API section for more details), + or you can use the JavaScript SDK provided by Agentic to simplify the integration. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based + system (for example Claude Cowork or Copilot), it is reachable throught MCP. + \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval + Agent can be deployed in different ways, depending on your needs and the environment + you are working in. \\n Ready-to-use widget \\n The easiest way to deploy + your Retrieval Agent is to use the ready-to-use widget. You can embed it in + your website or application, and it will provide a chat user interface for + interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Go to the Widgets section in the left menu, and click on Create widget to + create a new widget. You can customize its appearance, and then copy the generated + code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{\"/k\":{\"/k/text\":5294}},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"fulltext\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-resources\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-search\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-rag-lab\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"account-arag\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-kv-schemas\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"user-profile\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-users\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-widgets\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-remi-analytics\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"agent-users\",\"labels\":[]}],\"facets\":{},\"query\":\"\",\"total\":2013,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - - '1428' + - '16898' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 05 Aug 2026 08:09:31 GMT - nuclia-learning-model: - - bge-reranker-v2-m3 + - Wed, 15 Jul 2026 08:10:51 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '170' + - '67' x-nuclia-trace-id: - - d4ee701a6eec616fe4d6fda69c8a5f81 + - d477b16749982203d03ea7babb4155fd status: code: 200 message: OK - request: - body: '{"question": "", "retrieval": true, "user_id": "rao_answer_summary-ask", - "system": null, "chat_history": [], "context": [], "query_context": {}, "query_context_order": - {}, "truncate": true, "user_prompt": {"prompt": "\nBased on the provided context - and user question, perform the following tasks:\n\n1. Select only information - directly relevant to the question.\n2. Break down compound sentences into simple, - single-idea statements. Preserve original phrasing when possible.\n3. For any - named entity with descriptive details, separate those details into distinct - propositions.\n4. Ensure clarity by replacing pronouns (e.g., \"it\", \"he\", - \"she\", \"they\", \"this\", \"that\") with the full names of the entities they - reference, and add necessary modifiers to clarify meaning.\n5. The context may - be delimited by tags such as and . Treat - everything between these tags as context.\n6. Assess whether the context sufficiently - answers the question. If it answers it partially, provide the answer; if it - does not answer it fully, specify what information is missing to answer the - question.\n7. If the context does not answer the question at all, just return - the original question as the missing information.\n8. The `citations` field - consists ONLY in a list of block IDs that are relevant to the answer, following - these rules:\n - Use the format: block-AB\n - Just mention the block IDs, - do NOT include any other text.\n - Just mention the blocks actually relevant - and that contain information used in the answer, do NOT include blocks that - are not relevant.\n - No duplicates.\n9. Do NOT hallucinate block IDs. Only - use those provided in the context.\n10. Your output must be a JSON object with - the following fields:\n - \"reason\": Explain your reasoning for the answer - or validation.\n - \"answer\": Provide a partial or complete answer to the - user query strictly from the information in the context. If there isn''t enough - information to even provide a partial answer, leave ''answer'' empty.\n - - \"missing_info_query\": If the context is insufficient, specify what information - is missing in a query shape; otherwise, leave it empty. Just return the query - needed to retrieve the missing information.\n - \"useful\": Indicate if the - context is useful to answer the question (\"yes\" or \"no\").\n - \"citations\": - List the IDs of the blocks relevant to the answer, if any (e.g., [\"block-AB\", - \"block-CD\"]).\n11. **IMPORTANT** If any extra instructions are provided, you - MUST follow them carefully when generating the answer field. These instructions - may specify the format, style, tools to use, or other requirements for the answer.\n\n\nExplica - c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol, incluyendo un - enlace a la documentaci\u00f3n oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### - Chunk: 9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\nTags: /k/text\n``` max_tokens: - the maximum number of input tokens to put in the final context (including the - prompt, the retrieved results and the user question). \n max_output_tokens: - the maximum number of tokens to generate. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n - ```\n\n\n---\"\n\n\n**block-AB**\n\n#### Chunk: 4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\nTags: - /k/text\n``` Use the max_tokens parameter on the /ask endpoint to set hard - limits on: \n - Context size: Limits the amount of retrieved information sent - to the LLM \n - Answer length: Limits the length of the generated response \n - Important Considerations \n Context Limitations: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n - ```\n\n\n---\"\n\n\n**block-AC**\n\n#### Chunk: e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\nTags: - /k/text\n``` \n optional max_tokens: number \\| object \n \n Defines the maximum - number of tokens that the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 - \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n - ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\nTags: - /k/text\n``` \n optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined - in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n - ```\n\n\n---\"\n\n\n**block-AE**\n\n#### Chunk: e8525e64c5b44982b958d32cf6090613/t/page/2450-2808\nTags: - /k/text\n``` \n optional highlight: boolean \n \n Inherited from \n BaseSearchOptions.highlight - \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:76 \n \n keyword_filters? - \n \n optional keyword_filters: string[] \\| Filter[] \n \n Inherited from \n - BaseSearchOptions.keyword_filters \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:65 - \n \n max_tokens? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n - ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\nTags: - /k/text\n``` \n optional generative_model: string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 - \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 - \n \n max_tokens? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n - ```\n\n\n---\"\n\n\n**block-AG**\n\n#### Chunk: 43004f553e534ffe9c9e735856bd9b23/t/page/212-480\nTags: - /k/text\n``` \n optional driver: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 - \n \n input_tokens \n \n input_tokens: object \n \n max \n \n max: number \n - \n min? \n \n optional min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \n \n max_images? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n - ```\n\n\n---\"\n\n\n**block-AH**\n\n#### Chunk: 89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\nTags: - /k/text\n``` Description: The maximum number of tokens that the model can generate - as output. Again, we should keep in mind that this value summed to the Maximum - supported input tokens should not exceed the total context size supported by - the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n - ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": false, "citation_threshold": - null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 8192, "query_context_images": - {}, "prefer_markdown": null, "json_schema": {"title": "validate_or_answer", - "description": "Validate or answer", "parameters": {"type": "object", "properties": - {"reason": {"type": "string", "description": "Reasoning for the answer or validation"}, - "answer": {"type": "string", "description": "Partial or complete answer to the - user query from the information in the context."}, "missing_info_query": {"type": - "string", "description": "Query needed to retrieve the missing information in - case the context is not enough to answer the question. 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ConsumptionAskResponseItem\\n\\n# Interface: ConsumptionAskResponseItem\\n\\n## + Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> **customer\\\\_key\\\\_tokens**: + [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L127)\\n\\n***\\n\\n### + normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L126)\\n\\n***\\n\\n### + type\\n\\n> **type**: `\\\"consumption\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:125](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L125)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"3d72cf5a8634c4719acbe4304e79b48d\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: + ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n + customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 + \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n + type \\n \\n type: consumption \\n \\n Defined in \\n 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Ask > interfaces > ConsumptionAskResponseItem\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\":{\"score\":0.6163696646690369,\"score_type\":\"VECTOR\",\"order\":8,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: + ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n + customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 + \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n + type \\n 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features\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T14:32:26.204740\",\"modified\":\"2026-06-09T08:07:51.648767\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + features\\ntitle: Features\\n---\\n\\n# Widgets features\\n\\nThe Agentic + RAG widgets allows you to embed the Agentic RAG search experience directly + into your website or web application through a simple HTML snippet:\\n\\n```html\\n\\n\\n\\n```\\n\\nThe + easiest way to explore the different features of the widgets is to use the + [Agentic RAG Dashboard](https://rag.progress.cloud/) in the Widgets section + and to play with the different options.\\n\\nThe _Embed widget_ button will + generate the HTML snippet for you.\\n\\n## Widget types\\n\\nThere are 3 different + types of widgets:\\n\\n- **Embedded in page**: the search input is embedded + in a page and the results are displayed under the input. Once the initial + answer is displayed, the user can click on _Ask more_ to access the full chat + interface. Note: For the correct reading of the results, the width of the + widget container should not be less than 384px.\\n\\n Web components:\\n\\n + \ ```html\\n \\n \\n + \ ```\\n\\n- **Chat mode**: displays directly the full chat interface.\\n\\n + \ Web component:\\n\\n ```html\\n \\n ```\\n\\n- + **Popup modal**: the search inout and the results are displayed in a popup + modal.\\n\\n Web component:\\n\\n ```html\\n \\n + \ ```\\n\\n## The `features` parameter\\n\\nThe `features` parameter allows + you to customize the behavior of the widget. It is a comma-separated list + of features among the following:\\n\\n- `filter`: display a filter dropdown + in the search bar.\\n- `navigateToFile`: open the file in the browser when + clicking on the result (by default, the file is displayed in the viewer).\\n- + `navigateToLink`: open the link in the browser when clicking on the result + (by default, the link is displayed in the viewer).\\n- `permalink`: add the + search query and criteria to the URL, allowing the widget to re-render the + same results upon loading.\\n- `relations`: display an info card on the right + side of the widget listing all the relations of the entity mentioned in the + user query.\\n- `suggestions`: display a list of suggested resource titles + matching the user input.\\n- `suggestLabels`: display a list of suggestions + based on the labels when the user starts typing in the search bar.\\n- `autocompleteFromNERs`: + display a list of suggestions based on the NERs extracted from the user query + when the user starts typing in the search bar.\\n- `displayMetadata`: display + the metadata associated with the resource in the result rows.\\n- `answers`: + trigger the answer generation process when the user makes a search.\\n- `hideResults`: + hide the search results, only the generative answer will be displayed.\\n- + `hideThumbnails`: hide the thumbnails associated with the resource in the + result rows.\\n- `displayFieldList`: display a section listing all the fields + of the resource in the right sidebar of the viewer. This section is only visible + for resources containing multiple fields.\\n- `citations`: include citations + in the generative answer.\\n- `rephrase`: rephrase the user question in order + to optimize the quality of the search results.\\n- `debug`: display extra + buttons to download the last request full log of the debug metadata returned + by the API. It must not be used in production.\\n- `preferMarkdown`: require + the generative answer to be formatted in Markdown.\\n- `openNewTab`: open + the link in a new tab when clicking on the result.\\n- `orFilterLogic`: use + the OR logic for filters instead of the default AND logic.\\n- `noChatHistory`: + the previous questions and answers in the chat mode will not be passed as + context when generating a new answer.\\n- `showHidden`: display hidden resources + in the search results.\\n- `showAttachedImages`: display images attached to + the matching paragraphs in the search results.\\n\\n### Other parameters\\n\\n- + `backend`: the URL of the backend to use. Useful if you use your own proxy + to access the Agentic RAG API.\\n- `zone`: the zone to use.\\n- `knowledgebox`: + the Knowledge Box id.\\n- `placeholder`: the text displayed in the search + bar when it is empty.\\n- `lang`: the language of the widget. Currently supported: + `ca`, `fr`, `en`, `es`. Default: `en`.\\n- `apikey`: the API key to use. It + is not recommended to use it in production (the API key is meant to be injected + by your proxy).\\n- `account`: the account id.\\n- `state`: the publication + state of the Knowledge Box.\\n- `standalone`: set to `true` when using a standalone + NucliaDB instance.\\n- `proxy`: set to `true` when using a proxy to access + the Agentic RAG API.\\n- `mode`: set to `dark` to display the widget in dark + mode.\\n- `filters`: define the filters offered to the user in the search + bar among `labels`, `entities`, `created` and `labelFamilies`.\\n- `preselected_filters`: + define filters that will be applied by default to any query.\\n- `csspath`: + the path to the CSS file to use to customize the widget style.\\n- `prompt`: + the prompt to use for the generative model. It must use `{context}` and `{question}` + variables.\\n- `system_prompt`: the system prompt to use for the generative + model.\\n- `rephrase_prompt`: the prompt to use when optimizing the user query + to get the best search results.\\n- `generativemodel`: the generative model + to use for the answer generation.\\n- `rag_strategies`: the RAG strategies + to apply to the retrieved paragraphs.\\n- `rag_images_strategies`: the RAG + strategies to apply to the retrieved images.\\n- `not_enough_data_message`: + the message to display when there is not enough data to generate an answer.\\n- + `ask_to_resource`: the resource ID to use as context for the generative model.\\n- + `max_tokens`: the maximum number of input tokens to put in the final context + (including the prompt, the retrieved results and the user question).\\n- `max_output_tokens`: + the maximum number of tokens to generate.\\n- `max_paragraphs`: the maximum + number of paragraphs to pass in the context to the generative model (default: + 20).\\n- `query_prepend`: the hard-coded text to prepend to the user query.\\n- + `json_schema`: the JSON schema to use to get a JSON answer from the generative + model.\\n- `vectorset`: the embedding model to use for the semantic search.\\n- + `chat_placeholder`: the placeholder to display in the chat input.\\n- `audit_metadata`: + custom metatada to add in API calls for auditing purposes.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"8f3044c65d6a551153cea36353a2cdac\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: features \\n title: Features \\n \\n Widgets features \\n The Agentic + RAG widgets allows you to embed the Agentic RAG search experience directly + into your website or web application through a simple HTML snippet: \\n ```html + \\n \\n \\n \\n ``` \\n The easiest way to explore the different features + of the widgets is to use the Agentic RAG Dashboard in the Widgets section + and to play with the different options. \\n The Embed widget button will generate + the HTML snippet for you. \\n Widget types \\n There are 3 different types + of widgets: \\n \\n Embedded in page: the search input is embedded in a page + and the results are displayed under the input. Once the initial answer is + displayed, the user can click on Ask more to access the full chat interface. + Note: For the correct reading of the results, the width of the widget container + should not be less than 384px. \\n \\n Web components: \\n html \\n \\n \\n + \\n Chat mode: displays directly the full chat interface. \\n \\n Web component: + \\n html \\n \\n \\n Popup modal: the search inout and the results are displayed + in a popup modal. \\n \\n Web component: \\n html \\n \\n The features parameter + \\n The features parameter allows you to customize the behavior of the widget. + It is a comma-separated list of features among the following: \\n \\n filter: + display a filter dropdown in the search bar. \\n navigateToFile: open the + file in the browser when clicking on the result (by default, the file is displayed + in the viewer). \\n navigateToLink: open the link in the browser when clicking + on the result (by default, the link is displayed in the viewer). \\n permalink: + add the search query and criteria to the URL, allowing the widget to re-render + the same results upon loading. \\n relations: display an info card on the + right side of the widget listing all the relations of the entity mentioned + in the user query. \\n suggestions: display a list of suggested resource titles + matching the user input. \\n suggestLabels: display a list of suggestions + based on the labels when the user starts typing in the search bar. \\n autocompleteFromNERs: + display a list of suggestions based on the NERs extracted from the user query + when the user starts typing in the search bar. \\n displayMetadata: display + the metadata associated with the resource in the result rows. \\n answers: + trigger the answer generation process when the user makes a search. \\n hideResults: + hide the search results, only the generative answer will be displayed. \\n + hideThumbnails: hide the thumbnails associated with the resource in the result + rows. \\n displayFieldList: display a section listing all the fields of the + resource in the right sidebar of the viewer. This section is only visible + for resources containing multiple fields. \\n citations: include citations + in the generative answer. \\n rephrase: rephrase the user question in order + to optimize the quality of the search results. \\n debug: display extra buttons + to download the last request full log of the debug metadata returned by the + API. It must not be used in production. \\n preferMarkdown: require the generative + answer to be formatted in Markdown. \\n openNewTab: open the link in a new + tab when clicking on the result. \\n orFilterLogic: use the OR logic for filters + instead of the default AND logic. \\n noChatHistory: the previous questions + and answers in the chat mode will not be passed as context when generating + a new answer. \\n showHidden: display hidden resources in the search results. + \\n showAttachedImages: display images attached to the matching paragraphs + in the search results. \\n \\n Other parameters \\n \\n backend: the URL of + the backend to use. Useful if you use your own proxy to access the Agentic + RAG API. \\n zone: the zone to use. \\n knowledgebox: the Knowledge Box id. + \\n placeholder: the text displayed in the search bar when it is empty. \\n + lang: the language of the widget. Currently supported: ca, fr, en, es. Default: + en. \\n apikey: the API key to use. It is not recommended to use it in production + (the API key is meant to be injected by your proxy). \\n account: the account + id. \\n state: the publication state of the Knowledge Box. \\n standalone: + set to true when using a standalone NucliaDB instance. \\n proxy: set to true + when using a proxy to access the Agentic RAG API. \\n mode: set to dark to + display the widget in dark mode. \\n filters: define the filters offered to + the user in the search bar among labels, entities, created and labelFamilies. + \\n preselected_filters: define filters that will be applied by default to + any query. \\n csspath: the path to the CSS file to use to customize the widget + style. \\n prompt: the prompt to use for the generative model. It must use + {context} and {question} variables. \\n system_prompt: the system prompt to + use for the generative model. \\n rephrase_prompt: the prompt to use when + optimizing the user query to get the best search results. \\n generativemodel: + the generative model to use for the answer generation. \\n rag_strategies: + the RAG strategies to apply to the retrieved paragraphs. \\n rag_images_strategies: + the RAG strategies to apply to the retrieved images. \\n not_enough_data_message: + the message to display when there is not enough data to generate an answer. + \\n ask_to_resource: the resource ID to use as context for the generative + model. \\n max_tokens: the maximum number of input tokens to put in the final + context (including the prompt, the retrieved results and the user question). + \\n max_output_tokens: the maximum number of tokens to generate. \\n max_paragraphs: + the maximum number of paragraphs to pass in the context to the generative + model (default: 20). \\n query_prepend: the hard-coded text to prepend to + the user query. \\n json_schema: the JSON schema to use to get a JSON answer + from the generative model. \\n vectorset: the embedding model to use for the + semantic search. \\n chat_placeholder: the placeholder to display in the chat + input. \\n audit_metadata: custom metatada to add in API calls for auditing + purposes. \\n 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features\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\":{\"score\":0.7432252764701843,\"score_type\":\"VECTOR\",\"order\":0,\"text\":\" + max_tokens: the maximum number of input tokens to put in the final context + (including the prompt, the retrieved results and the user question). \\n max_output_tokens: + the maximum number of tokens to generate. \\n\",\"id\":\"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":20,\"start\":5203,\"end\":5412,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"f02da6c4bdf34596a89a8106f4b0ea9f\":{\"id\":\"f02da6c4bdf34596a89a8106f4b0ea9f\",\"slug\":\"docs-develop-js-sdk-interfaces-PageToken-md\",\"title\":\"docs + > develop > js sdk > interfaces > PageToken\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:49:28.645864\",\"modified\":\"2026-07-14T12:51:05.803476\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageToken\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / PageToken\\n\\n# + Interface: PageToken\\n\\n## Properties\\n\\n### height\\n\\n> **height**: + `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L249)\\n\\n***\\n\\n### + line\\n\\n> **line**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L251)\\n\\n***\\n\\n### + text\\n\\n> **text**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L250)\\n\\n***\\n\\n### + width\\n\\n> **width**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L248)\\n\\n***\\n\\n### + x\\n\\n> **x**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L246)\\n\\n***\\n\\n### + y\\n\\n> **y**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"e72ffebe78398e6654aceec2addfd240\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n + Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 + \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 + \\n \\n text \\n \\n text: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:250 + \\n \\n width \\n \\n width: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:248 + \\n \\n x \\n \\n x: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:246 + \\n \\n y \\n \\n y: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:247\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":299,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":299,\"key\":\"\"}]},{\"start\":299,\"end\":592,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":300,\"end\":592,\"key\":\"\"}]},{\"start\":592,\"end\":677,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":593,\"end\":677,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:07.412857Z\",\"last_understanding\":\"2026-07-14T12:51:07.180359Z\",\"last_extract\":\"2026-07-14T12:51:06.857039Z\",\"last_processing_start\":\"2026-07-14T12:51:06.837097Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > PageToken\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > PageToken\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\":{\"score\":0.599377453327179,\"score_type\":\"VECTOR\",\"order\":17,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n + Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 + \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 + \\n \\n text \\n \\n\",\"id\":\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":299,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"220eb37c167f4eb9bb8e9454e7ba8cf5\":{\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5\",\"slug\":\"docs-develop-python-sdk-05-search-md\",\"title\":\"docs + > develop > python sdk > 05 search\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:48:33.723913\",\"modified\":\"2026-06-09T08:08:04.866092\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/python-sdk/search\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"# + Search and answer generation\\n\\n## Search\\n\\nNuclia supports 2 different + search endpoints:\\n\\n- `search`: returns several result sets according the + different search techniques (full-text, fuzzy, semantic).\\n- `find`: returns + a single result set where all different results are merged into a hierarchical + structure.\\n\\nBoth endpoints support the same query parameters.\\n\\n- CLI:\\n\\n + \ ```bash\\n nuclia kb search search --query=\\\"My search\\\"\\n nuclia + kb search find --query=\\\"My search\\\" --filters=\\\"['/icon/application/pdf','/classification.labels/region/Asia']\\\"\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n search = + sdk.NucliaSearch()\\n search.search(query=\\\"My search\\\", filters=['/icon/application/pdf', + '/classification.labels/region/Asia'])\\n search.find(query=\\\"My search\\\")\\n + \ ```\\n\\nGet JSON output:\\n\\n```bash\\nnuclia kb search find --query=\\\"My + search\\\" --json\\n```\\n\\nGet YAML output:\\n\\n```bash\\nnuclia kb search + search --query=\\\"My search\\\" --yaml\\n```\\n\\n## Generative answer\\n\\nBased + on a `find` request, Nuclia uses a generative AI to answer the question based + on the context without hallucinations and with the find result and relations.\\n\\n- + CLI:\\n\\n ```bash\\n nuclia kb search ask --query=\\\"My question\\\"\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n search = + sdk.NucliaSearch()\\n search.ask(query=\\\"My question\\\")\\n ```\\n\\n + \ You can also use the `AskRequest` item to configure the request with all + the parameters supported:\\n\\n ```python\\n from nuclia import sdk\\n from + nucliadb_models.search import AskRequest\\n\\n search = sdk.NucliaSearch()\\n + \ query = AskRequest(query=\\\"My question\\\", prefer_markdown=True, citations=True)\\n + \ search.ask(query=query)\\n ```\\n\\n### Reasoning\\n\\nSome LLMs support + reasoning. In some models, reasoning is enabled by default, while in others + it must be explicitly requested. You can control this behavior using the reasoning + parameter.\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n from + nucliadb_models.search import AskRequest, Reasoning\\n\\n search = sdk.NucliaSearch()\\n + \ query = AskRequest(\\n query=\\\"My question with extra reasoning effort\\\",\\n + \ max_tokens=5000,\\n reasoning=Reasoning(\\n display=True, # + Show reasoning in the response\\n effort=\\\"low\\\", # Can be + \\\"low\\\", \\\"medium\\\", or \\\"high\\\"\\n budget_tokens=1024 + # How many tokens reasoning can use\\n ),\\n )\\n search.ask(query=query)\\n + \ ```\\n\\nModel Support for Reasoning Options:\\n\\n* **OpenAI models** \u2192 + support `effort` only.\\n* **Google & Anthropic models** \u2192 support `budget_tokens` + only.\\n\\n:::tip\\nIf you send just one of these values (`effort` or `budget_tokens`), + Nuclia will automatically fill in the other for you.\\n:::\\n\\n:::warning\\n* + Enabling reasoning can use additional tokens, which may increase your usage + costs.\\n* You may need to increase `max_tokens` to give the LLM enough room + to reason and generate an answer.\\n:::\\n\\n## Filtering\\n\\nAny endpoint + that involves search (`search`, `find` and `ask`) also support more advanced + filtering expressions. Expressions can have one of the following operators:\\n\\n- + `all`: this is the default. Will make search return results containing all + specified filter labels.\\n- `any`: returns results containing at least one + of the labels.\\n- `none`: returns results that do not contain any of the + labels.\\n- `not_all`: returns results that do not contain all specified labels.\\n\\nNote + that multiple expressions can be chained in the `filters` parameter and the + conjunction of all of them will be computed.\\n\\nHere are some examples:\\n\\n- + CLI:\\n\\n ```bash\\n nuclia kb search find --query=\\\"My search\\\" --filters=\\\"[{'any':['/icon/application/pdf','/icon/image/mp4']}]\\\"\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n from nucliadb_models.search + import Filter\\n\\n search = sdk.NucliaSearch()\\n search.ask(\\n query=\\\"My + question\\\",\\n filters=[Filter(any=['/classification.labels/region/Europe','/classification.labels/region/Asia'])],\\n + \ )\\n ```\\n\\n## Using RAG strategies\\n\\nRAG strategies can be used to + improve the quality of the answers by extending the search results passed + to the LLM as context.\\n\\n- CLI:\\n\\n ```bash\\n nuclia kb search ask + --query=\\\"My question\\\" --rag_strategies='[{\\\"name\\\":\\\"hierarchy\\\"}]'\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n search = + sdk.NucliaSearch()\\n search.ask(query=\\\"My question\\\", rag_strategies=[{\\\"name\\\": + \\\"hierarchy\\\"}])\\n ```\\n\\nSee the [RAG strategies documentation](https://docs.rag.progress.cloud/docs/rag/rag-strategy) + for more information.\\n\\n## Complex queries\\n\\nThe Python SDK allows to + use all the options supported by the `/find` and `/ask` endpoints,\\nbut not + all of the options can be passed as specific parameter.\\nIn these cases, + you can just pass your query as a dictionnary in the `query` parameter.\\n\\n- + CLI:\\n\\n ```bash\\n nuclia kb search find --query='{\\\"query\\\": \\\"My + search\\\", \\\"filters\\\": [\\\"/icon/application/pdf\\\", \\\"/classification.labels/region/Asia\\\"]}'\\n + \ nuclia kb search ask --query='{\\\"query\\\": \\\"My search\\\",\\\"top_k\\\": + 5}'\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n search + = sdk.NucliaSearch()\\n search.find(query={\\\"query\\\": \\\"My search\\\", + \\\"filters\\\": [\\\"/icon/application/pdf\\\", \\\"/classification.labels/region/Asia\\\"]})\\n + \ search.ask(query={\\\"query\\\": \\\"My search\\\",\\\"top_k\\\": 5})\\n + \ ```\\n\\n## Graph queries\\n\\nThe Python SDK allows graph queries supported + by the `/graph` endpoint. Although\\na bit cumbersome, the knowledge graph + can be queried as in this example:\\n\\n- CLI:\\n\\n ```bash\\n nuclia kb + search graph --query='{\\\"query\\\": {\\\"prop\\\": \\\"path\\\", \\\"source\\\": + {\\\"value\\\": \\\"Rust\\\"}, \\\"destination\\\": {\\\"value\\\": \\\"Python\\\"}}}'\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia import sdk\\n search = + sdk.NucliaSearch()\\n search.graph(\\n query={\\n \\\"query\\\": + {\\n \\\"prop\\\": \\\"path\\\",\\n \\\"source\\\": + {\\\"value\\\": \\\"Rust\\\"},\\n \\\"destination\\\": {\\\"value\\\": + \\\"Python\\\"}\\n }\\n }\\n )\\n ```\\n\\nFor more information + about graph querying, please refer to [Nuclia's graph\\ndoc](https://docs.rag.progress.cloud/docs/rag/advanced/graph) + or the [API reference](https://docs.rag.progress.cloud/docs/api#tag/Search/operation/graph_search_knowledgebox_kb__kbid__graph_post)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"57ed2bd023399aee08015a57a948ebf2\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"Search + and answer generation \\n Search \\n Nuclia supports 2 different search endpoints: + \\n \\n search: returns several result sets according the different search + techniques (full-text, fuzzy, semantic). \\n find: returns a single result + set where all different results are merged into a hierarchical structure. + \\n \\n Both endpoints support the same query parameters. \\n \\n CLI: \\n + \\n bash \\n nuclia kb search search --query= My search \\n nuclia kb search + find --query= My search --filters= ['/icon/application/pdf','/classification.labels/region/Asia'] + \\n \\n SDK: \\n \\n python \\n from nuclia import sdk \\n search = sdk.NucliaSearch() + \\n search.search(query= My search , filters=['/icon/application/pdf', '/classification.labels/region/Asia']) + \\n search.find(query= My search ) \\n Get JSON output: \\n bash \\n nuclia + kb search find --query= My search --json \\n Get YAML output: \\n bash \\n + nuclia kb search search --query= My search --yaml \\n Generative answer \\n + Based on a find request, Nuclia uses a generative AI to answer the question + based on the context without hallucinations and with the find result and relations. + \\n \\n CLI: \\n \\n bash \\n nuclia kb search ask --query= My question \\n + \\n SDK: \\n \\n python \\n from nuclia import sdk \\n search = sdk.NucliaSearch() + \\n search.ask(query= My question ) \\n You can also use the AskRequest item + to configure the request with all the parameters supported: \\n ```python + \\n from nuclia import sdk \\n from nucliadb_models.search import AskRequest + \\n search = sdk.NucliaSearch() \\n query = AskRequest(query= My question + , prefer_markdown=True, citations=True) \\n search.ask(query=query) \\n ``` + \\n Reasoning \\n Some LLMs support reasoning. In some models, reasoning is + enabled by default, while in others it must be explicitly requested. You can + control this behavior using the reasoning parameter. \\n \\n SDK: \\n \\n + ```python \\n from nuclia import sdk \\n from nucliadb_models.search import + AskRequest, Reasoning \\n search = sdk.NucliaSearch() \\n query = AskRequest( + \\n query= My question with extra reasoning effort , \\n max_tokens=5000, + \\n reasoning=Reasoning( \\n display=True, # Show reasoning in the response + \\n effort= low , # Can be low , medium , or high \\n budget_tokens=1024 # + How many tokens reasoning can use \\n ), \\n ) \\n search.ask(query=query) + \\n ``` \\n Model Support for Reasoning Options: \\n \\n OpenAI models \u2192 + support effort only. \\n Google & Anthropic models \u2192 support budget_tokens + only. \\n \\n :::tip \\n If you send just one of these values (effort or budget_tokens), + Nuclia will automatically fill in the other for you. \\n ::: \\n :::warning + \\n Enabling reasoning can use additional tokens, which may increase your + usage costs. \\n You may need to increase max_tokens to give the LLM enough + room to reason and generate an answer. \\n ::: \\n Filtering \\n Any endpoint + that involves search (search, find and ask) also support more advanced filtering + expressions. Expressions can have one of the following operators: \\n \\n + all: this is the default. Will make search return results containing all specified + filter labels. \\n any: returns results containing at least one of the labels. + \\n none: returns results that do not contain any of the labels. \\n not_all: + returns results that do not contain all specified labels. \\n \\n Note that + multiple expressions can be chained in the filters parameter and the conjunction + of all of them will be computed. \\n Here are some examples: \\n \\n CLI: + \\n \\n bash \\n nuclia kb search find --query= My search --filters= [{'any':['/icon/application/pdf','/icon/image/mp4']}] + \\n \\n SDK: \\n \\n ```python \\n from nuclia import sdk \\n from nucliadb_models.search + import Filter \\n search = sdk.NucliaSearch() \\n search.ask( \\n query= My + question , \\n filters=[Filter(any=['/classification.labels/region/Europe','/classification.labels/region/Asia'])], + \\n ) \\n ``` \\n Using RAG strategies \\n RAG strategies can be used to improve + the quality of the answers by extending the search results passed to the LLM + as context. \\n \\n CLI: \\n \\n bash \\n nuclia kb search ask --query= My + question --rag_strategies='[{ name : hierarchy }]' \\n \\n SDK: \\n \\n python + \\n from nuclia import sdk \\n search = sdk.NucliaSearch() \\n search.ask(query= + My question , rag_strategies=[{ name : hierarchy }]) \\n See the RAG strategies + documentation for more information. \\n Complex queries \\n The Python SDK + allows to use all the options supported by the /find and /ask endpoints, \\n + but not all of the options can be passed as specific parameter. \\n In these + cases, you can just pass your query as a dictionnary in the query parameter. + \\n \\n CLI: \\n \\n bash \\n nuclia kb search find --query='{ query : My + search , filters : [ /icon/application/pdf , /classification.labels/region/Asia + ]}' \\n nuclia kb search ask --query='{ query : My search , top_k : 5}' \\n + \\n SDK: \\n \\n python \\n from nuclia import sdk \\n search = sdk.NucliaSearch() + \\n search.find(query={ query : My search , filters : [ /icon/application/pdf + , /classification.labels/region/Asia ]}) \\n search.ask(query={ query : My + search , top_k : 5}) \\n Graph queries \\n The Python SDK allows graph queries + supported by the /graph endpoint. Although \\n a bit cumbersome, the knowledge + graph can be queried as in this example: \\n \\n CLI: \\n \\n bash \\n nuclia + kb search graph --query='{ query : { prop : path , source : { value : Rust + }, destination : { value : Python }}}' \\n \\n SDK: \\n \\n python \\n from + nuclia import sdk \\n search = sdk.NucliaSearch() \\n search.graph( \\n query={ + \\n query : { \\n prop : path , \\n source : { value : Rust }, \\n destination + : { value : Python } \\n } \\n } \\n ) \\n For more information about graph + querying, please refer to Nuclia's graph \\n doc or the API 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+ > develop > python sdk > 05 search\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > python sdk > 05 search\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\":{\"score\":0.6185709238052368,\"score_type\":\"VECTOR\",\"order\":7,\"text\":\" + \\n SDK: \\n \\n ```python \\n from nuclia import sdk \\n from nucliadb_models.search + import AskRequest, Reasoning \\n search = sdk.NucliaSearch() \\n query = AskRequest( + \\n query= My question with extra reasoning effort , \\n max_tokens=5000, + \\n reasoning=Reasoning( \\n display=True, # Show reasoning in the response + \\n effort= low , # Can be low , medium , or high \\n budget_tokens=1024 # + How many tokens reasoning can use \\n ), \\n ) \\n search.ask(query=query) + \\n ``` \\n Model Support for Reasoning Options: \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/1790-2276\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":6,\"start\":1790,\"end\":2276,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\":{\"score\":0.5997583270072937,\"score_type\":\"VECTOR\",\"order\":16,\"text\":\" + ::: \\n :::warning \\n Enabling reasoning can use additional tokens, which + may increase your usage costs. \\n You may need to increase max_tokens to + give the LLM enough room to reason and generate an answer. \\n\",\"id\":\"220eb37c167f4eb9bb8e9454e7ba8cf5/t/page/2505-2709\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":8,\"start\":2505,\"end\":2709,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"44d05174f1954331b62f5e4026f2b01a\":{\"id\":\"44d05174f1954331b62f5e4026f2b01a\",\"slug\":\"docs-develop-python-sdk-14-rao-md\",\"title\":\"docs + > develop > python sdk > 14 rao\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-22T13:38:09.919472\",\"modified\":\"2026-06-09T08:08:04.176136\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/python-sdk/rao\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"# + Retrieval Agents Orchestrator\\n\\nInteract with Nuclia's Retrieval Agents + Orchestrator to have intelligent conversations over several knowledge sources + with persistent session management and real-time streaming responses.\\n\\n## + Prerequisites\\n\\nInstall the Nuclia SDK:\\n\\n```sh\\npip install nuclia\\n```\\n\\nEnsure + you have:\\n- A valid Nuclia authentication token (see [Authentication](02-auth.md))\\n- + Access to a configured Retrieval Agent\\n\\n## Overview\\n\\nThe nuclia.py + library provides several ways to interact with your Retrieval Agents Orchestrators:\\n\\n- + **Interactive CLI**: A rich, user-friendly terminal interface (recommended)\\n- + **Standard CLI**: Direct access to raw websocket messages for debugging\\n- + **Session Management**: Create and manage persistent conversation sessions\\n- + **Programmatic API**: Python SDK for building custom applications\\n\\n\\n## + Listing Available Agents\\n\\nDiscover what Retrieval Agents Orchestrators + you have access to.\\n\\n- CLI:\\n\\n ```sh\\n nuclia agents list\\n ```\\n\\n- + SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n + \ agents = NucliaAgents()\\n all_agents = agents.list()\\n\\n for agent + in all_agents:\\n print(f\\\"Agent: {agent.title} ({agent.id})\\\")\\n + \ print(f\\\" Slug: {agent.slug}\\\")\\n print(f\\\" Zone: {agent.zone}\\\")\\n + \ ```\\n\\n### Getting a Specific Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia + agents get --account=\\\"my-account\\\" --id=\\\"agent-uuid\\\" --zone=\\\"europe-1\\\"\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n + \ agents = NucliaAgents()\\n agent_details = agents.get(\\n account=\\\"my-account\\\",\\n + \ id=\\\"agent-uuid\\\",\\n zone=\\\"europe-1\\\"\\n )\\n print(agent_details)\\n + \ ```\\n\\n### Setting a Default Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia + agents default [AGENT_SLUG or AGENT_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n + \ from nuclia.sdk.agents import NucliaAgents\\n\\n agents = NucliaAgents()\\n + \ agents.default(\\\"my-agent\\\")\\n ```\\n\\nThis sets the default agent + for all subsequent operations.\\n\\n## Interactive CLI (Recommended)\\n\\nThe + interactive CLI provides a beautiful, real-time interface for conversing with + your Retrieval Agents Orchestrator.\\n\\n### Starting the Interactive CLI\\n\\n- + CLI:\\n\\n ```sh\\n nuclia agent cli interact\\n ```\\n\\n- SDK:\\n\\n + \ ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n + \ agent.cli.interact()\\n ```\\n\\nThis launches an interactive terminal + session where you can:\\n- Ask questions and see streaming responses\\n- View + processing steps in real-time\\n- Manage conversation sessions\\n- See retrieved + context and citations\\n\\n### Interactive CLI Commands\\n\\nThe CLI supports + several commands (prefix with `/`):\\n\\n| Command | Description |\\n|---------|-------------|\\n| + `/help` | Show available commands |\\n| `/new_session` | Create a new persistent + session |\\n| `/list_sessions` | List all your sessions |\\n| `/change_session` + | Switch to a different session, use 'ephemeral' for a temporary session |\\n| + `/clear` | Clear the screen |\\n| `/exit` | Exit the CLI |\\n\\nPlease note + that all commands related to sessions require a Retrieval Agent Orchestrator + with the option **Agent with memory** enabled during creation.\\n\\n## Session + Management\\n\\nSessions allow you to maintain conversation context across + multiple interactions.\\n\\n> This feature will only be available if you checked + **Agent with memory** during the creation of your Retrieval Agents Orchestrator.\\n\\n### + Creating a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent session new --name=\\\"My + Research Session\\\"\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent + import NucliaAgent\\n\\n agent = NucliaAgent()\\n session_uuid = agent.session.new(\\\"My + Research Session\\\")\\n print(f\\\"Created session: {session_uuid}\\\")\\n + \ ```\\n\\n### Listing Sessions\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent + session list\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent + import NucliaAgent\\n\\n agent = NucliaAgent()\\n sessions = agent.session.list()\\n + \ for session in sessions.resources:\\n print(f\\\"{session.title}: {session.id}\\\")\\n + \ ```\\n\\n### Getting a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent + session get --session_uuid=[SESSION_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n + \ from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n + \ session = agent.session.get(session_uuid)\\n print(f\\\"Session: {session.title}\\\")\\n + \ print(f\\\"Created: {session.created}\\\")\\n ```\\n\\n### Deleting a Session\\n\\n- + CLI:\\n\\n ```sh\\n nuclia agent session delete --session_uuid=[SESSION_UUID]\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n + \ agent = NucliaAgent()\\n agent.session.delete(session_uuid)\\n ```\\n\\n## + Interaction\\n\\nAside from the interactive CLI, you can interact with your + Retrieval Agents Orchestrator with the simple CLI or programmatically using + the SDK.\\n\\n### Basic Interaction\\n\\n\\n**CLI:**\\n```bash\\nnuclia agent + interact \\\"What is Eric known for?\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate + over streaming responses\\nfor response in agent.interact(\\n question=\\\"What + is Eric known for?\\\"\\n):\\n if response.operation == \\\"ANSWER\\\" + and response.answer:\\n print(response.answer)\\n elif response.step:\\n + \ print(f\\\"Processing: {response.step.module}\\\")\\n```\\n\\nNot + supplying a `session_uuid` when calling `interact` will use an ephemeral session + by default. To maintain context, provide a persistent session UUID.\\n\\n### + Using Persistent Sessions\\n\\n**CLI:**\\n```bash\\nnuclia agent sessions + new \\\"Customer Support Chat\\\"\\n# Note the session UUID returned\\nnuclia + agent interact \\\"What are your business hours?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\nnuclia + agent interact \\\"Are you open on weekends?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Create + a session\\nsession_uuid = agent.session.new(\\\"Customer Support Chat\\\")\\n\\n# + Have a conversation with context\\nfor response in agent.interact(\\n session_uuid=session_uuid,\\n + \ question=\\\"What are your business hours?\\\"\\n):\\n if response.answer:\\n + \ print(response.answer)\\n\\n# Follow-up question maintains context\\nfor + response in agent.interact(\\n session_uuid=session_uuid,\\n question=\\\"Are + you open on weekends?\\\"\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\n## + Understanding Response Types\\n\\nWhen interacting with an agent, you receive + a stream of `AragAnswer` objects with different operations:\\n\\n| Operation + | Description |\\n|-----------|-------------|\\n| `START` | Interaction has + begun |\\n| `ANSWER` | Processing step or partial answer |\\n| `DONE` | Interaction + complete |\\n| `ERROR` | An error occurred |\\n| `AGENT_REQUEST` | Agent needs + user feedback |\\n\\n### Response Attributes\\n\\nEach response may contain:\\n\\n- + **`step`**: Information about the current processing step\\n - `module`: + The module being executed (e.g., \\\"rephrase\\\", \\\"basic_ask\\\", \\\"remi\\\")\\n + \ - `title`: Display title for the step\\n - `value`: Result of the step\\n + \ - `reason`: Explanation for the step\\n - `timeit`: Time taken in seconds\\n + \ - `input_nuclia_tokens`/`output_nuclia_tokens`: Token usage\\n\\n- **`context`**: + Retrieved context from the knowledge base\\n - `chunks`: List of retrieved + text chunks with sources\\n - `summary`: Summary of the context or partial + answer\\n\\n- **`answer`**: The final answer text (Markdown formatted)\\n\\n- + **`generated_text`**: Intermediate generated text\\n\\n- **`possible_answer`**: + Alternative answer being considered\\n\\n- **`exception`**: Error details + if something went wrong\\n\\n### Processing Responses\\n\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\nfrom nuclia_models.agent.interaction + import AnswerOperation\\n\\nagent = NucliaAgent()\\n\\nfor response in agent.interact(question=\\\"Tell + me about AI\\\"):\\n if response.operation == AnswerOperation.START:\\n + \ print(\\\"Starting...\\\")\\n \\n elif response.step:\\n print(f\\\"Step: + {response.step.module} ({response.step.timeit:.2f}s)\\\")\\n \\n elif + response.context:\\n print(f\\\"Retrieved {len(response.context.chunks)} + chunks\\\")\\n for chunk in response.context.chunks:\\n print(f\\\" + \ - {chunk.title}: {chunk.text[:100]}...\\\")\\n \\n elif response.answer:\\n + \ print(f\\\"\\\\nFinal Answer:\\\\n{response.answer}\\\")\\n \\n + \ elif response.operation == AnswerOperation.DONE:\\n print(\\\"Complete!\\\")\\n + \ \\n elif response.operation == AnswerOperation.ERROR:\\n print(f\\\"Error: + {response.exception.detail if response.exception else 'Unknown'}\\\")\\n```\\n\\n## + Standard CLI for Raw Messages\\n\\nFor debugging or advanced use cases, you + can access raw websocket messages programmatically:\\n\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate + over all messages\\nfor message in agent.interact(\\n question=\\\"What + is RAO?\\\"\\n):\\n # message is an AragAnswer object with all raw data\\n + \ print(f\\\"Operation: {message.operation}\\\")\\n print(f\\\"Raw message: + {message.model_dump_json(indent=2)}\\\")\\n```\\n\\nThis gives you direct + access to all websocket message data for debugging or custom processing.\\n\\n## + Advanced Features\\n\\n### Agent Feedback Requests\\n\\nAgents can request + additional input from users during processing:\\n\\n```python\\nfrom nuclia.sdk.agent + import NucliaAgent\\nfrom nuclia_models.agent.interaction import AnswerOperation\\n\\nagent + = NucliaAgent()\\ngenerator = agent.interact(question=\\\"Help me with X\\\")\\n\\nfor + response in generator:\\n if response.operation == AnswerOperation.AGENT_REQUEST:\\n + \ # Agent is requesting user input\\n user_input = input(f\\\"Agent + asks: {response.feedback.question}\\\\n> \\\")\\n # Send response back\\n + \ generator.send(user_input)\\n elif response.answer:\\n print(response.answer)\\n```\\n\\n### + Error Handling\\n\\n```python\\nfrom nuclia.sdk.agent import NucliaAgent\\nfrom + nuclia.exceptions import RaoAPIException\\n\\nagent = NucliaAgent()\\n\\ntry:\\n + \ for response in agent.interact(question=\\\"Hello?\\\"):\\n if + response.exception:\\n print(f\\\"Agent error: {response.exception.detail}\\\")\\n + \ elif response.answer:\\n print(response.answer)\\nexcept + RaoAPIException as e:\\n print(f\\\"API error: {e.detail}\\\")\\nexcept + Exception as e:\\n print(f\\\"Unexpected error: {e}\\\")\\n```\\n\\n### + Passing Custom Headers to MCP\\n\\nIf your Retrieval Agents Orchestrator requires + custom headers for MCP Agents, you can pass them as follows:\\n\\n**CLI:**\\n```bash\\nnuclia + agent interact \\\"What is AI?\\\" --headers '{\\\"X-Custom-Header\\\": \\\"value\\\"}'\\n```\\n\\n**SDK:**\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\nfor response + in agent.interact(\\n question=\\\"What is AI?\\\",\\n headers={\\\"X-Custom-Header\\\": + \\\"value\\\"}\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\nPlease + ensure that the 'Allowed Headers' configuration in your MCP agent includes + any custom headers you wish to use.\\n\\n## Best Practices\\n\\n1. **Use Sessions + for Context**: Create sessions when you need multi-turn conversations with + context retention\\n2. **Use Ephemeral Sessions for One-offs**: Don't supply + a session UUID for using agents in a stateless manner.\\n3. **Stream for UX**: + Process responses as they arrive for better user experience\\n4. **Handle + All Operations**: Check for different operation types (START, ANSWER, DONE, + ERROR) when processing responses\\n5. **Clean Up Sessions**: Delete sessions + when done to avoid clutter\\n6. **Use Interactive CLI**: For manual testing + and exploration, the interactive CLI provides the best experience\\n\",\"format\":\"MARKDOWN\",\"md5\":\"bbaaf8cccd2b664ba4f7daf47d1f2bf4\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"Retrieval + Agents Orchestrator \\n Interact with Nuclia's Retrieval Agents Orchestrator + to have intelligent conversations over several knowledge sources with persistent + session management and real-time streaming responses. \\n Prerequisites \\n + Install the Nuclia SDK: \\n sh \\n pip install nuclia \\n Ensure you have: + \\n - A valid Nuclia authentication token (see Authentication) \\n - Access + to a configured Retrieval Agent \\n Overview \\n The nuclia.py library provides + several ways to interact with your Retrieval Agents Orchestrators: \\n \\n + Interactive CLI: A rich, user-friendly terminal interface (recommended) \\n + Standard CLI: Direct access to raw websocket messages for debugging \\n Session + Management: Create and manage persistent conversation sessions \\n Programmatic + API: Python SDK for building custom applications \\n \\n Listing Available + Agents \\n Discover what Retrieval Agents Orchestrators you have access to. + \\n \\n CLI: \\n \\n sh \\n nuclia agents list \\n \\n SDK: \\n \\n ```python + \\n from nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() + \\n all_agents = agents.list() \\n for agent in all_agents: \\n print(f Agent: + {agent.title} ({agent.id}) ) \\n print(f Slug: {agent.slug} ) \\n print(f + Zone: {agent.zone} ) \\n ``` \\n Getting a Specific Agent \\n \\n CLI: \\n + \\n sh \\n nuclia agents get --account= my-account --id= agent-uuid --zone= + europe-1 \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agents import + NucliaAgents \\n agents = NucliaAgents() \\n agent_details = agents.get( \\n + account= my-account , \\n id= agent-uuid , \\n zone= europe-1 \\n ) \\n print(agent_details) + \\n ``` \\n Setting a Default Agent \\n \\n CLI: \\n \\n sh \\n nuclia agents + default [AGENT_SLUG or AGENT_UUID] \\n \\n SDK: \\n \\n ```python \\n from + nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() \\n agents.default( + my-agent ) \\n ``` \\n This sets the default agent for all subsequent operations. + \\n Interactive CLI (Recommended) \\n The interactive CLI provides a beautiful, + real-time interface for conversing with your Retrieval Agents Orchestrator. + \\n Starting the Interactive CLI \\n \\n CLI: \\n \\n sh \\n nuclia agent + cli interact \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import + NucliaAgent \\n agent = NucliaAgent() \\n agent.cli.interact() \\n ``` \\n + This launches an interactive terminal session where you can: \\n - Ask questions + and see streaming responses \\n - View processing steps in real-time \\n - + Manage conversation sessions \\n - See retrieved context and citations \\n + Interactive CLI Commands \\n The CLI supports several commands (prefix with + /): \\n | Command | Description | \\n |---------|-------------| \\n | /help + | Show available commands | \\n | /new_session | Create a new persistent session + | \\n | /list_sessions | List all your sessions | \\n | /change_session | + Switch to a different session, use 'ephemeral' for a temporary session | \\n + | /clear | Clear the screen | \\n | /exit | Exit the CLI | \\n Please note + that all commands related to sessions require a Retrieval Agent Orchestrator + with the option Agent with memory enabled during creation. \\n Session Management + \\n Sessions allow you to maintain conversation context across multiple interactions. + \\n \\n This feature will only be available if you checked Agent with memory + during the creation of your Retrieval Agents Orchestrator. \\n \\n Creating + a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session new --name= My + Research Session \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent + import NucliaAgent \\n agent = NucliaAgent() \\n session_uuid = agent.session.new( + My Research Session ) \\n print(f Created session: {session_uuid} ) \\n ``` + \\n Listing Sessions \\n \\n CLI: \\n \\n sh \\n nuclia agent session list + \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import NucliaAgent + \\n agent = NucliaAgent() \\n sessions = agent.session.list() \\n for session + in sessions.resources: \\n print(f {session.title}: {session.id} ) \\n ``` + \\n Getting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session get + --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent + import NucliaAgent \\n agent = NucliaAgent() \\n session = agent.session.get(session_uuid) + \\n print(f Session: {session.title} ) \\n print(f Created: {session.created} + ) \\n ``` \\n Deleting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent + session delete --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python + \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n + agent.session.delete(session_uuid) \\n ``` \\n Interaction \\n Aside from + the interactive CLI, you can interact with your Retrieval Agents Orchestrator + with the simple CLI or programmatically using the SDK. \\n Basic Interaction + \\n CLI: \\n bash \\n nuclia agent interact What is Eric known for? \\n SDK: + \\n ```python \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() + \\n Iterate over streaming responses \\n for response in agent.interact( \\n + question= What is Eric known for? \\n ): \\n if response.operation == ANSWER + and response.answer: \\n print(response.answer) \\n elif response.step: \\n + print(f Processing: {response.step.module} ) \\n ``` \\n Not supplying a session_uuid + when calling interact will use an ephemeral session by default. To maintain + context, provide a persistent session UUID. \\n Using Persistent Sessions + \\n CLI: \\n ```bash \\n nuclia agent sessions new Customer Support Chat \\n + Note the session UUID returned \\n nuclia agent interact What are your business + hours? --session_uuid= SESSION_UUID \\n nuclia agent interact Are you open + on weekends? --session_uuid= SESSION_UUID \\n ``` \\n SDK: \\n ```python \\n + from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n Create + a session \\n session_uuid = agent.session.new( Customer Support Chat ) \\n + Have a conversation with context \\n for response in agent.interact( \\n session_uuid=session_uuid, + \\n question= What are your business hours? \\n ): \\n if response.answer: + \\n print(response.answer) \\n Follow-up question maintains context \\n for + response in agent.interact( \\n session_uuid=session_uuid, \\n question= Are + you open on weekends? \\n ): \\n if response.answer: \\n print(response.answer) + \\n ``` \\n Understanding Response Types \\n When interacting with an agent, + you receive a stream of AragAnswer objects with different operations: \\n + | Operation | Description | \\n |-----------|-------------| \\n | START | + Interaction has begun | \\n | ANSWER | Processing step or partial answer | + \\n | DONE | Interaction complete | \\n | ERROR | An error occurred | \\n + | AGENT_REQUEST | Agent needs user feedback | \\n Response Attributes \\n + Each response may contain: \\n \\n step: Information about the current processing + step \\n module: The module being executed (e.g., rephrase , basic_ask , remi + ) \\n title: Display title for the step \\n value: Result of the step \\n + reason: Explanation for the step \\n timeit: Time taken in seconds \\n \\n + input_nuclia_tokens/output_nuclia_tokens: Token usage \\n \\n \\n context: + Retrieved context from the knowledge base \\n \\n chunks: List of retrieved + text chunks with sources \\n \\n summary: Summary of the context or partial + answer \\n \\n \\n answer: The final answer text (Markdown formatted) \\n + \\n \\n generated_text: Intermediate generated text \\n \\n \\n possible_answer: + Alternative answer being considered \\n \\n \\n exception: Error details if + something went wrong \\n \\n \\n Processing Responses \\n ```python \\n from + nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction + import AnswerOperation \\n agent = NucliaAgent() \\n for response in agent.interact(question= + Tell me about AI ): \\n if response.operation == AnswerOperation.START: \\n + print( Starting... ) \\n elif response.step: \\n print(f Step: {response.step.module} + ({response.step.timeit:.2f}s) ) \\n \\n elif response.context: \\n print(f + Retrieved {len(response.context.chunks)} chunks ) \\n for chunk in response.context.chunks: + \\n print(f - {chunk.title}: {chunk.text[:100]}... ) \\n \\n elif response.answer: + \\n print(f \\\\nFinal Answer:\\\\n{response.answer} ) \\n \\n elif response.operation + == AnswerOperation.DONE: \\n print( Complete! ) \\n \\n elif response.operation + == AnswerOperation.ERROR: \\n print(f Error: {response.exception.detail if + response.exception else 'Unknown'} ) \\n \\n ``` \\n Standard CLI for Raw + Messages \\n For debugging or advanced use cases, you can access raw websocket + messages programmatically: \\n ```python \\n from nuclia.sdk.agent import + NucliaAgent \\n agent = NucliaAgent() \\n Iterate over all messages \\n for + message in agent.interact( \\n question= What is RAO? \\n ): \\n # message + is an AragAnswer object with all raw data \\n print(f Operation: {message.operation} + ) \\n print(f Raw message: {message.model_dump_json(indent=2)} ) \\n ``` \\n + This gives you direct access to all websocket message data for debugging or + custom processing. \\n Advanced Features \\n Agent Feedback Requests \\n Agents + can request additional input from users during processing: \\n ```python \\n + from nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction + import AnswerOperation \\n agent = NucliaAgent() \\n generator = agent.interact(question= + Help me with X ) \\n for response in generator: \\n if response.operation + == AnswerOperation.AGENT_REQUEST: \\n # Agent is requesting user input \\n + user_input = input(f Agent asks: {response.feedback.question}\\\\n> ) \\n + # Send response back \\n generator.send(user_input) \\n elif response.answer: + \\n print(response.answer) \\n ``` \\n Error Handling \\n ```python \\n from + nuclia.sdk.agent import NucliaAgent \\n from nuclia.exceptions import RaoAPIException + \\n agent = NucliaAgent() \\n try: \\n for response in agent.interact(question= + Hello? ): \\n if response.exception: \\n print(f Agent error: {response.exception.detail} + ) \\n elif response.answer: \\n print(response.answer) \\n except RaoAPIException + as e: \\n print(f API error: {e.detail} ) \\n except Exception as e: \\n print(f + Unexpected error: {e} ) \\n ``` \\n Passing Custom Headers to MCP \\n If your + Retrieval Agents Orchestrator requires custom headers for MCP Agents, you + can pass them as follows: \\n CLI: \\n bash \\n nuclia agent interact What + is AI? --headers '{ X-Custom-Header : value }' \\n SDK: \\n ```python \\n + from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n for + response in agent.interact( \\n question= What is AI? , \\n headers={ X-Custom-Header + : value } \\n ): \\n if response.answer: \\n print(response.answer) \\n ``` + \\n Please ensure that the 'Allowed Headers' configuration in your MCP agent + includes any custom headers you wish to use. \\n Best Practices \\n \\n Use + Sessions for Context: Create sessions when you need multi-turn conversations + with context retention \\n Use Ephemeral Sessions for One-offs: Don't supply + a session UUID for using agents in a stateless manner. \\n Stream for UX: + Process responses as they arrive for better user experience \\n Handle All + Operations: Check for different operation types (START, ANSWER, DONE, ERROR) + when processing responses \\n Clean Up Sessions: Delete sessions when done + to avoid clutter \\n Use Interactive CLI: For manual testing and exploration, + the interactive CLI provides the best experience \\n 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Properties\\n\\n### attachments\\\\_images\\n\\n> + **attachments\\\\_images**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:385](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L385)\\n\\n***\\n\\n### + attachments\\\\_text\\n\\n> **attachments\\\\_text**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:384](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L384)\\n\\n***\\n\\n### + full\\n\\n> **full**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:386](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L386)\\n\\n***\\n\\n### + max\\\\_messages?\\n\\n> `optional` **max\\\\_messages**: `number`\\n\\n#### + Defined 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libs/sdk-core/src/lib/db/kb/kb.models.ts:384 \\n \\n full \\n \\n full: boolean + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:386 \\n \\n + max_messages? \\n \\n optional max_messages: number \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/kb/kb.models.ts:387 \\n \\n name \\n \\n name: CONVERSATION + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:383\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":351,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":351,\"key\":\"\"}]},{\"start\":351,\"end\":554,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":352,\"end\":450,\"key\":\"\"},{\"start\":450,\"end\":554,\"key\":\"\"}]},{\"start\":554,\"end\":636,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":555,\"end\":636,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:46.119337Z\",\"last_understanding\":\"2026-07-14T12:51:45.741783Z\",\"last_extract\":\"2026-07-14T12:51:45.425207Z\",\"last_processing_start\":\"2026-07-14T12:51:45.404045Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > ConversationalStrategy\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > ConversationalStrategy\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"c27a1e5f5ddb4b118921345d713401b8/t/page/351-554\":{\"score\":0.5960951447486877,\"score_type\":\"VECTOR\",\"order\":19,\"text\":\" + full: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:386 + \\n \\n max_messages? \\n \\n optional max_messages: number \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:387 \\n \\n name \\n \\n\",\"id\":\"c27a1e5f5ddb4b118921345d713401b8/t/page/351-554\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":1,\"start\":351,\"end\":554,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0d01e250360a4d6c91f3baf2de5e7d38\":{\"id\":\"0d01e250360a4d6c91f3baf2de5e7d38\",\"slug\":\"docs-develop-js-sdk-interfaces-ReasoningConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ReasoningConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-24T11:15:01.495997\",\"modified\":\"2026-07-14T12:49:30.245034\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ReasoningConfig\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ReasoningConfig\\n\\n# + Interface: ReasoningConfig\\n\\n## Properties\\n\\n### budget\\\\_tokens?\\n\\n> + `optional` **budget\\\\_tokens**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:647](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L647)\\n\\n***\\n\\n### + effort?\\n\\n> `optional` **effort**: [`NumericReasoningEffort`](../enumerations/NumericReasoningEffort.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:648](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L648)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"940c8be17c938dcc14e4abb000b0f8b5\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ReasoningConfig \\n Interface: ReasoningConfig + \\n Properties \\n budget_tokens? \\n \\n optional budget_tokens: number \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 \\n \\n effort? + \\n \\n optional effort: NumericReasoningEffort \\n \\n Defined in \\n 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> develop > js sdk > interfaces > ReasoningConfig\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > ReasoningConfig\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224\":{\"score\":0.6099268198013306,\"score_type\":\"VECTOR\",\"order\":10,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ReasoningConfig \\n Interface: ReasoningConfig + \\n Properties \\n budget_tokens? \\n \\n optional budget_tokens: number \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 \\n \\n effort? + \\n\",\"id\":\"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":224,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"66b6f0dbd883413e98fbbf5b59f049b9\":{\"id\":\"66b6f0dbd883413e98fbbf5b59f049b9\",\"slug\":\"docs-develop-js-sdk-enumerations-UsageType-md\",\"title\":\"docs + > develop > js sdk > enumerations > UsageType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"tl\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T09:59:02.349911\",\"modified\":\"2026-07-14T12:54:11.386825\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/enumerations/UsageType\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / UsageType\\n\\n# + Enumeration: UsageType\\n\\n## Enumeration Members\\n\\n### AI\\\\_TOKENS\\\\_USED\\n\\n> + **AI\\\\_TOKENS\\\\_USED**: `\\\"ai_tokens_used\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:206](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L206)\\n\\n***\\n\\n### + BYTES\\\\_PROCESSED\\n\\n> **BYTES\\\\_PROCESSED**: `\\\"bytes_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:197](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L197)\\n\\n***\\n\\n### + CHARS\\\\_PROCESSED\\n\\n> **CHARS\\\\_PROCESSED**: `\\\"chars_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:198](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L198)\\n\\n***\\n\\n### + MEDIA\\\\_FILES\\\\_PROCESSED\\n\\n> **MEDIA\\\\_FILES\\\\_PROCESSED**: `\\\"media_files_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:200](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L200)\\n\\n***\\n\\n### + MEDIA\\\\_SECONDS\\\\_PROCESSED\\n\\n> **MEDIA\\\\_SECONDS\\\\_PROCESSED**: + `\\\"media_seconds_processed\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:199](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L199)\\n\\n***\\n\\n### + NUCLIA\\\\_TOKENS\\n\\n> **NUCLIA\\\\_TOKENS**: `\\\"nuclia_tokens_billed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:207](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L207)\\n\\n***\\n\\n### + PAGES\\\\_PROCESSED\\n\\n> **PAGES\\\\_PROCESSED**: `\\\"pages_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:201](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L201)\\n\\n***\\n\\n### + PARAGRAPHS\\\\_PROCESSED\\n\\n> **PARAGRAPHS\\\\_PROCESSED**: `\\\"paragraphs_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:202](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L202)\\n\\n***\\n\\n### + PRE\\\\_PROCESSING\\\\_TIME\\n\\n> **PRE\\\\_PROCESSING\\\\_TIME**: `\\\"pre_processing_time\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:194](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L194)\\n\\n***\\n\\n### + RESOURCES\\\\_PROCESSED\\n\\n> **RESOURCES\\\\_PROCESSED**: `\\\"resources_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:196](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L196)\\n\\n***\\n\\n### + SEARCHES\\\\_PERFORMED\\n\\n> **SEARCHES\\\\_PERFORMED**: `\\\"searches_performed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:204](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L204)\\n\\n***\\n\\n### + SLOW\\\\_PROCESSING\\\\_TIME\\n\\n> **SLOW\\\\_PROCESSING\\\\_TIME**: `\\\"slow_processing_time\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:195](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L195)\\n\\n***\\n\\n### + SUGGESTIONS\\\\_PERFORMED\\n\\n> **SUGGESTIONS\\\\_PERFORMED**: `\\\"suggestions_performed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:205](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L205)\\n\\n***\\n\\n### + TRAIN\\\\_SECONDS\\n\\n> **TRAIN\\\\_SECONDS**: `\\\"train_seconds\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:203](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L203)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"a6825b7bf9d5960444b0981f205811a3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / UsageType \\n Enumeration: UsageType \\n + Enumeration Members \\n AI_TOKENS_USED \\n \\n AI_TOKENS_USED: ai_tokens_used + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:206 \\n \\n BYTES_PROCESSED + \\n \\n BYTES_PROCESSED: bytes_processed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:197 + \\n \\n CHARS_PROCESSED \\n \\n CHARS_PROCESSED: chars_processed \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:198 \\n \\n MEDIA_FILES_PROCESSED + \\n \\n MEDIA_FILES_PROCESSED: media_files_processed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:200 \\n \\n MEDIA_SECONDS_PROCESSED + \\n \\n MEDIA_SECONDS_PROCESSED: media_seconds_processed \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n + NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 + \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED + \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n + \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 + \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED + \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 + \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED + \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: + train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":1833,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:54:13.123173Z\",\"last_understanding\":\"2026-07-14T12:54:12.864112Z\",\"last_extract\":\"2026-07-14T12:54:12.463871Z\",\"last_processing_start\":\"2026-07-14T12:54:12.433665Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > enumerations > UsageType\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > enumerations > UsageType\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833\":{\"score\":0.6017837524414062,\"score_type\":\"VECTOR\",\"order\":15,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / UsageType \\n Enumeration: UsageType \\n + Enumeration Members \\n AI_TOKENS_USED \\n \\n AI_TOKENS_USED: ai_tokens_used + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:206 \\n \\n BYTES_PROCESSED + \\n \\n BYTES_PROCESSED: bytes_processed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:197 + \\n \\n CHARS_PROCESSED \\n \\n CHARS_PROCESSED: chars_processed \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:198 \\n \\n MEDIA_FILES_PROCESSED + \\n \\n MEDIA_FILES_PROCESSED: media_files_processed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:200 \\n \\n MEDIA_SECONDS_PROCESSED + \\n \\n MEDIA_SECONDS_PROCESSED: media_seconds_processed \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n + NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 + \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED + \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n + \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 + \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED + \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 + \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED + \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: + train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"id\":\"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0a003c3f724e45e392a9c8d1ce8800c1\":{\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1\",\"slug\":\"docs-develop-js-sdk-interfaces-Consumption-md\",\"title\":\"docs + > develop > js sdk > interfaces > Consumption\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:51:46.788864\",\"modified\":\"2026-07-14T12:51:15.300757\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / Consumption\\n\\n# + Interface: Consumption\\n\\n## Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> + **customer\\\\_key\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:230](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L230)\\n\\n***\\n\\n### + normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:229](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L229)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"654b0dfe17ab08959c78891dd24c3424\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption + \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n + \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":349,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:16.563837Z\",\"last_understanding\":\"2026-07-14T12:51:16.208384Z\",\"last_extract\":\"2026-07-14T12:51:15.984803Z\",\"last_processing_start\":\"2026-07-14T12:51:15.966495Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > Consumption\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > Consumption\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\":{\"score\":0.6027967929840088,\"score_type\":\"VECTOR\",\"order\":14,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption + \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n + \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs + > rag > advanced > consumption.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-10-03T08:32:26.341394\",\"modified\":\"2026-06-09T08:18:16.730959\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + consumption\\ntitle: Token consumption\\n---\\n\\nimport Tabs from \\\"@theme/Tabs\\\";\\nimport + TabItem from \\\"@theme/TabItem\\\";\\n\\n# Token consumption\\n\\nAgentic + RAG is a license and consumption-based service. This means that you pay for + the computational resources you consume. The consumption is measured in **Agentic + RAG tokens**.\\nAll public 3rd-party LLMs base their pricing on the number + of tokens consumed. In the LLM world, a token is around 4-5 characters on + average, which might fit an entire word or be split into parts. The number + of tokens is proportional to the amount of text, measured in chunks of 4-5 + characters. It closely relates to words but not entirely. The longer a sentence + is, the more tokens it will consume to read or to generate it.\\nSince all + these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize + the cost across all of them.\\n\\n## How Tokens Are Consumed in RAG\\n\\nWhen + a user asks a question to your Knowledge Box, the token consumption process + follows these steps:\\n\\n1. **Question Processing**: The system finds the + most relevant paragraphs to answer the question\\n2. **Context Assembly**: + These paragraphs are used as context when calling the LLM model\\n3. **Prompt + Creation**: Agentic RAG assembles the **prompt**, **context**, and **question** + into a single string\\n4. **LLM Processing**: This complete string is sent + to the LLM, corresponding to a certain number of **input tokens**\\n5. **Answer + Generation**: The LLM generates the answer, which corresponds to a certain + number of **output tokens**\\n\\n**Total consumption** = Input tokens + Output + tokens + Image tokens\\n\\n### Factors That Impact Token Consumption\\n\\nToken + consumption is directly affected by:\\n\\n- **Large context**: Results from + using RAG strategies like \\\"Full resource\\\" or \\\"Neighbouring paragraphs\\\", + or from using the `extra_context` parameter\\n- **Long questions**: More detailed + or complex questions require more input tokens\\n- **Long prompts**: Extensive + system prompts increase the input token count\\n- **Detailed answers**: Comprehensive + responses require more output tokens\\n- **Images in context**: When using + multimodal models, images included in the retrieved context significantly + increase token consumption\\n\\n## How to Limit and Control Token Consumption\\n\\n### + Strategy 1: Optimize Your Parameters\\n\\nThe first approach to reducing token + consumption is to fine-tune your request parameters:\\n\\n- **Optimize prompts**: + Ensure your prompts are concise and focused, avoiding unnecessary verbosity\\n- + **Control resource scope**: When using the \\\"Full resource\\\" strategy, + use the `count` attribute to limit the number of resources returned\\n- **Tune + neighboring context**: For the \\\"Neighbouring paragraphs\\\" strategy, optimize + the `before` and `after` attributes to balance context quality with token + efficiency\\n- **Manage summary length**: When using the \\\"Hierarchical\\\" + strategy, ensure that resource summaries are appropriately sized\\n- **Choose + efficient models**: Select LLMs that offer better token efficiency (typically, + ChatGPT 4o-mini is more cost-effective than ChatGPT 4o)\\n\\n### Strategy + 2: Set Hard Limits\\n\\nYou can implement safeguards against excessive token + consumption:\\n\\nUse the `max_tokens` parameter on the [`/ask` endpoint](/docs/api#tag/Search/operation/ask_knowledgebox_endpoint_kb__kbid__ask_post) + to set hard limits on:\\n- **Context size**: Limits the amount of retrieved + information sent to the LLM\\n- **Answer length**: Limits the length of the + generated response\\n\\n#### Important Considerations\\n\\n**Context Limitations**:\\n- + Restricting context size may result in less relevant answers since the LLM + has less information to work with\\n- Balance between cost control and answer + quality\\n\\n**Answer Length Limitations**:\\n- The LLM might not complete + its response if it hits the token limit, potentially cutting sentences mid-way\\n- + **Recommended approach**: Include length requirements in your prompt (e.g., + \\\"Please answer in less than 200 words\\\") rather than relying solely on + hard limits\\n- This allows the LLM to naturally conclude its response within + the desired length\\n\\n## How to Monitor Token Consumption\\n\\n### Understanding + Token Consumption Data\\n\\nYou can receive detailed token consumption information + from the following endpoints that utilize LLM models: `ask`, `chat`, `remi`, + `query`, `sentence`, `summarize`, `tokens`, and `rerank`.\\n\\n:::note\\nThe + `rephrase` endpoint currently does not support token consumption monitoring.\\n:::\\n\\nTo + receive token consumption data, you must include the following header in your + request:\\n```\\nX-SHOW-CONSUMPTION: true\\n```\\n\\nThe token consumption + data is provided in different formats depending on the response type:\\n- + **Streaming responses** (`application/x-ndjson`): Token consumption appears + as a separate JSON chunk with type \\\"consumption\\\"\\n- **Standard responses** + (`application/json`): Token consumption is included in a \\\"consumption\\\" + field within the main response\\n\\n### Token Consumption Response Format\\n\\n\\n \\n ```json\\n {\\n \\\"item\\\": + {\\n \\\"type\\\": \\\"consumption\\\",\\n \\\"normalized_tokens\\\": + {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": + 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": + 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n + \ }\\n }\\n ```\\n \\n \\n ```json\\n {\\n \\\"consumption\\\": {\\n \\\"normalized_tokens\\\": + {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": + 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": + 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n + \ }\\n }\\n ```\\n \\n\\n\\n### Understanding + Token Types\\n\\n**Normalized Tokens** (`normalized_tokens`):\\n- These represent + the number of Agentic RAG tokens consumed and that you will be billed for\\n- + Values are normalized across different LLM providers for consistent billing\\n- + Include separate counts for:\\n - `input`: Tokens used for the prompt, context, + and question\\n - `output`: Tokens used for the generated response\\n - + `image`: Tokens used for image processing (when applicable)\\n\\n**Customer + Key Tokens** (`customer_key_tokens`):\\n- These represent tokens consumed + when using your own LLM API keys\\n- These tokens are **not billed** by Agentic + RAG since you're using your own API keys\\n- Values are also normalized for + comparison purposes across different providers\\n\",\"format\":\"MARKDOWN\",\"md5\":\"204fe47dbd7eb38d465d05fa7538e51e\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: consumption \\n title: Token consumption \\n \\n import Tabs from + @theme/Tabs ; \\n import TabItem from @theme/TabItem ; \\n Token consumption + \\n Agentic RAG is a license and consumption-based service. This means that + you pay for the computational resources you consume. The consumption is measured + in Agentic RAG tokens. \\n All public 3rd-party LLMs base their pricing on + the number of tokens consumed. In the LLM world, a token is around 4-5 characters + on average, which might fit an entire word or be split into parts. The number + of tokens is proportional to the amount of text, measured in chunks of 4-5 + characters. It closely relates to words but not entirely. The longer a sentence + is, the more tokens it will consume to read or to generate it. \\n Since all + these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize + the cost across all of them. \\n How Tokens Are Consumed in RAG \\n When a + user asks a question to your Knowledge Box, the token consumption process + follows these steps: \\n \\n Question Processing: The system finds the most + relevant paragraphs to answer the question \\n Context Assembly: These paragraphs + are used as context when calling the LLM model \\n Prompt Creation: Agentic + RAG assembles the prompt, context, and question into a single string \\n LLM + Processing: This complete string is sent to the LLM, corresponding to a certain + number of input tokens \\n Answer Generation: The LLM generates the answer, + which corresponds to a certain number of output tokens \\n \\n Total consumption + = Input tokens + Output tokens + Image tokens \\n Factors That Impact Token + Consumption \\n Token consumption is directly affected by: \\n \\n Large context: + Results from using RAG strategies like Full resource or Neighbouring paragraphs + , or from using the extra_context parameter \\n Long questions: More detailed + or complex questions require more input tokens \\n Long prompts: Extensive + system prompts increase the input token count \\n Detailed answers: Comprehensive + responses require more output tokens \\n Images in context: When using multimodal + models, images included in the retrieved context significantly increase token + consumption \\n \\n How to Limit and Control Token Consumption \\n Strategy + 1: Optimize Your Parameters \\n The first approach to reducing token consumption + is to fine-tune your request parameters: \\n \\n Optimize prompts: Ensure + your prompts are concise and focused, avoiding unnecessary verbosity \\n Control + resource scope: When using the Full resource strategy, use the count attribute + to limit the number of resources returned \\n Tune neighboring context: For + the Neighbouring paragraphs strategy, optimize the before and after attributes + to balance context quality with token efficiency \\n Manage summary length: + When using the Hierarchical strategy, ensure that resource summaries are appropriately + sized \\n Choose efficient models: Select LLMs that offer better token efficiency + (typically, ChatGPT 4o-mini is more cost-effective than ChatGPT 4o) \\n \\n + Strategy 2: Set Hard Limits \\n You can implement safeguards against excessive + token consumption: \\n Use the max_tokens parameter on the /ask endpoint to + set hard limits on: \\n - Context size: Limits the amount of retrieved information + sent to the LLM \\n - Answer length: Limits the length of the generated response + \\n Important Considerations \\n Context Limitations: \\n - Restricting context + size may result in less relevant answers since the LLM has less information + to work with \\n - Balance between cost control and answer quality \\n Answer + Length Limitations: \\n - The LLM might not complete its response if it hits + the token limit, potentially cutting sentences mid-way \\n - Recommended approach: + Include length requirements in your prompt (e.g., Please answer in less than + 200 words ) rather than relying solely on hard limits \\n - This allows the + LLM to naturally conclude its response within the desired length \\n How to + Monitor Token Consumption \\n Understanding Token Consumption Data \\n You + can receive detailed token consumption information from the following endpoints + that utilize LLM models: ask, chat, remi, query, sentence, summarize, tokens, + and rerank. \\n :::note \\n The rephrase endpoint currently does not support + token consumption monitoring. \\n ::: \\n To receive token consumption data, + you must include the following header in your request: \\n X-SHOW-CONSUMPTION: + true \\n The token consumption data is provided in different formats depending + on the response type: \\n - Streaming responses (application/x-ndjson): Token + consumption appears as a separate JSON chunk with type consumption \\n - Standard + responses (application/json): Token consumption is included in a consumption + field within the main response \\n Token Consumption Response Format \\n \\n + \\n json \\n { \\n item : { \\n type : consumption , \\n normalized_tokens + : { \\n input : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens + : { \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n + \\n \\n json \\n { \\n consumption : { \\n normalized_tokens : { \\n input + : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens : { + \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n \\n + \\n Understanding Token Types \\n Normalized Tokens (normalized_tokens): \\n + - These represent the number of Agentic RAG tokens consumed and that you will + be billed for \\n - Values are normalized across different LLM providers for + consistent billing \\n - Include separate counts for: \\n - input: Tokens + used for the prompt, context, and question \\n - output: Tokens used for the + generated response \\n - image: Tokens used for image processing (when applicable) + \\n Customer Key Tokens (customer_key_tokens): \\n - These represent tokens + consumed when using your own LLM API keys \\n - These tokens are not billed + by Agentic RAG since you're using your own API keys \\n - Values are also + normalized for comparison purposes across different 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Context size: Limits the amount of retrieved information sent to the LLM + \\n - Answer length: Limits the length of the generated response \\n Important + Considerations \\n Context Limitations: \\n\",\"id\":\"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":6,\"start\":3075,\"end\":3340,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326\":{\"score\":0.6072185635566711,\"score_type\":\"VECTOR\",\"order\":12,\"text\":\" + \\n Large context: Results from using RAG strategies like Full resource or + Neighbouring paragraphs , or from using the extra_context parameter \\n Long + questions: More detailed or complex questions require more input tokens \\n + Long prompts: Extensive system prompts increase the input token count \\n + Detailed answers: Comprehensive responses require more output tokens \\n Images + in context: When using multimodal models, images included in the retrieved + context significantly increase token consumption \\n \\n How to Limit and + Control Token Consumption \\n Strategy 1: Optimize Your Parameters \\n The + first approach to reducing token consumption is to fine-tune your request + parameters: \\n\",\"id\":\"4039d76b0fff4962900836ab3fdec9f7/t/page/1650-2326\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":4,\"start\":1650,\"end\":2326,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"89cc367c149e4f6eab0e06a743d1edba\":{\"id\":\"89cc367c149e4f6eab0e06a743d1edba\",\"slug\":\"docs-rag-advanced-openai-api-compatible-models-md\",\"title\":\"docs + > rag > advanced > openai api compatible models\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-05-23T07:21:32.894218\",\"modified\":\"2026-06-09T08:07:43.359058\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + openai-api-compatible-models\\ntitle: Connect to any OpenAI API compatible + LLM\\n---\\n\\n# Connect to any OpenAI API compatible LLM\\n\\nAgentic RAG + allows you to connect to any OpenAI API compatible LLM. This means that you + can use any LLM that has an API compatible with the OpenAI API which has become + a standard in the industry.\\n\\nMany of the options for self-hosted LLMs, + open-source LLMs hosted by cloud providers or commercial LLMs are compatible + with the OpenAI API. This means that you can use them with Agentic RAG without + any modifications.\\n\\n## Configuration\\n\\nTo modify your knowledge box + configuration you can do so in three manners, through the API, the Nuclia + CLI / SDK or the Agentic RAG dashboard.\\n\\nThe Agentic RAG dashboard offers + the most user-friendly way to modify the configuration of your knowledge box + and we will use it in this example.\\n\\nWe will be setting up a connection + to the **Phi 4 Reasoning Plus** model, hosted by **OpenRouter** which offers + a wide range of open-source and commercial models compatible with the OpenAI + API. We can see more information about this specific model [here](https://openrouter.ai/microsoft/phi-4-reasoning-plus:free), + the API parameters are located under the **API** tab.\\n\\n1. **Open the AI + Models page** \\n In the left sidebar under **Advanced**, click **AI Models**.\\n2. + **Select \u201COpenAI API Compatible Model\u201D** \\n From the models + list, choose **OpenAI API Compatible Model**.\\n3. **Enable custom Key** \\n + \ Toggle the option for using you own `OpenAI API Compatible Key` if it is + not already enabled.\\n4. **Fill in the configuration parameters**\\n\\n - + **API Key**:\\n - Description: The API key for your LLM. This is the key + that you would use as an authorization header in the API. You may leave this + blank if the endpoint you are connecting to does not require an API key.\\n + \ - Example: We will set this to our OpenRouter API key.\\n - **API URL**:\\n + \ - Description: The URL of the API endpoint for your LLM. This may be + shared between multiple models.\\n - Example: For OpenRouter, it is the + same for all models: `https://openrouter.ai/api/v1`\\n - **Model**:\\n - + Description: The name of the model you want to use, it needs to exactly match + the name of the model in the API.\\n - Example: For Phi 4 Reasoning Plus + in the OpenRouter API, it is `microsoft/phi-4-reasoning-plus:free`.\\n - + **Maximum supported input tokens**:\\n - Description: The maximum number + of tokens that the model can accept as input. Be mindful that this takes into + account the tokens used in the prompt, query and context. Also take note that + some models may provide their context window as the total between input and + output tokens, while others may provide it as the input tokens only.\\n - + Example: For Phi 4 Reasoning Plus, the total context size is `32768` tokens, + as we want to leave room for the output, we will set the maximum supported + input tokens as `32768 - 1024 = 31744`.\\n - **Maximum supported output + tokens**:\\n - Description: The maximum number of tokens that the model + can generate as output. Again, we should keep in mind that this value summed + to the **Maximum supported input tokens** should not exceed the total context + size supported by the model.\\n - Example: For Phi 4 Reasoning Plus, the + maximum output tokens is specified at `32768`, but we already reserved `31744` + for the input tokens, so we will set this to `32768 - 31744 = 1024`.\\n - + **Model Features**:\\n - Description: Under this section you will find + multiple toggles related to features supported by the model, these vary from + model to model, but most often the default values are well suited to most + use cases. The most relevant toggle is for `Image Support` which allows you + to use images as input for the model.\\n - Example: Image input is not + supported by Phi 4 Reasoning Plus, so we will leave it disabled.\\n\\n5. **Save** + \ \\n Click **Save changes**.\\n\\n6. **Test your model** \\n Run a sample + query in Agentic RAG or via API/CLI. Adjust your prompt templates and token + settings as needed.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"37cd8aff748addd04a363fa50828d1fe\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: openai-api-compatible-models \\n title: Connect to any OpenAI API + compatible LLM \\n \\n Connect to any OpenAI API compatible LLM \\n Agentic + RAG allows you to connect to any OpenAI API compatible LLM. This means that + you can use any LLM that has an API compatible with the OpenAI API which has + become a standard in the industry. \\n Many of the options for self-hosted + LLMs, open-source LLMs hosted by cloud providers or commercial LLMs are compatible + with the OpenAI API. This means that you can use them with Agentic RAG without + any modifications. \\n Configuration \\n To modify your knowledge box configuration + you can do so in three manners, through the API, the Nuclia CLI / SDK or the + Agentic RAG dashboard. \\n The Agentic RAG dashboard offers the most user-friendly + way to modify the configuration of your knowledge box and we will use it in + this example. \\n We will be setting up a connection to the Phi 4 Reasoning + Plus model, hosted by OpenRouter which offers a wide range of open-source + and commercial models compatible with the OpenAI API. We can see more information + about this specific model here, the API parameters are located under the API + tab. \\n \\n Open the AI Models page \\n In the left sidebar under Advanced, + click AI Models. \\n Select OpenAI API Compatible Model \\n From the models + list, choose OpenAI API Compatible Model. \\n Enable custom Key \\n Toggle + the option for using you own OpenAI API Compatible Key if it is not already + enabled. \\n \\n Fill in the configuration parameters \\n \\n \\n API Key: + \\n \\n Description: The API key for your LLM. This is the key that you would + use as an authorization header in the API. You may leave this blank if the + endpoint you are connecting to does not require an API key. \\n Example: We + will set this to our OpenRouter API key. \\n \\n \\n API URL: \\n Description: + The URL of the API endpoint for your LLM. This may be shared between multiple + models. \\n Example: For OpenRouter, it is the same for all models: https://openrouter.ai/api/v1 + \\n \\n \\n Model: \\n Description: The name of the model you want to use, + it needs to exactly match the name of the model in the API. \\n Example: For + Phi 4 Reasoning Plus in the OpenRouter API, it is microsoft/phi-4-reasoning-plus:free. + \\n \\n \\n Maximum supported input tokens: \\n Description: The maximum number + of tokens that the model can accept as input. Be mindful that this takes into + account the tokens used in the prompt, query and context. Also take note that + some models may provide their context window as the total between input and + output tokens, while others may provide it as the input tokens only. \\n Example: + For Phi 4 Reasoning Plus, the total context size is 32768 tokens, as we want + to leave room for the output, we will set the maximum supported input tokens + as 32768 - 1024 = 31744. \\n \\n \\n Maximum supported output tokens: \\n + Description: The maximum number of tokens that the model can generate as output. + Again, we should keep in mind that this value summed to the Maximum supported + input tokens should not exceed the total context size supported by the model. + \\n Example: For Phi 4 Reasoning Plus, the maximum output tokens is specified + at 32768, but we already reserved 31744 for the input tokens, so we will set + this to 32768 - 31744 = 1024. \\n \\n \\n \\n Model Features: \\n \\n Description: + Under this section you will find multiple toggles related to features supported + by the model, these vary from model to model, but most often the default values + are well suited to most use cases. The most relevant toggle is for Image Support + which allows you to use images as input for the model. \\n Example: Image + input is not supported by Phi 4 Reasoning Plus, so we will leave it disabled. + \\n \\n \\n \\n Save \\n Click Save changes. \\n \\n \\n Test your model \\n + Run a sample query in Agentic RAG or via API/CLI. Adjust your prompt templates + and token settings as needed. \\n \\n 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Be mindful that this takes into + account the tokens used in the prompt, query and context. Also take note that + some models may provide their context window as the total between input and + output tokens, while others may provide it as the input tokens only. \\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":8,\"start\":2202,\"end\":2575,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\":{\"score\":0.6517809629440308,\"score_type\":\"VECTOR\",\"order\":5,\"text\":\" + Description: The maximum number of tokens that the model can generate as output. + Again, we should keep in mind that this value summed to the Maximum supported + input tokens should not exceed the total context size supported by the model. + \\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":10,\"start\":2804,\"end\":3043,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-07-14T12:49:58.922592\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ModelConfig\\n\\n# + Interface: ModelConfig\\n\\n## Properties\\n\\n### assume\\\\_role?\\n\\n> + `optional` **assume\\\\_role**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:592](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L592)\\n\\n***\\n\\n### + driver?\\n\\n> `optional` **driver**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:590](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L590)\\n\\n***\\n\\n### + input\\\\_tokens\\n\\n> **input\\\\_tokens**: `object`\\n\\n#### max\\n\\n> + **max**: `number`\\n\\n#### min?\\n\\n> `optional` **min**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:587](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L587)\\n\\n***\\n\\n### + max\\\\_images?\\n\\n> `optional` **max\\\\_images**: `string`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:591](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L591)\\n\\n***\\n\\n### + output\\\\_tokens\\n\\n> **output\\\\_tokens**: `object`\\n\\n#### default\\\\_max?\\n\\n> + `optional` **default\\\\_max**: `number`\\n\\n#### max\\n\\n> **max**: `number`\\n\\n#### + min?\\n\\n> `optional` **min**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:588](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L588)\\n\\n***\\n\\n### + prompt\\\\_id?\\n\\n> `optional` **prompt\\\\_id**: `string`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:589](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L589)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"0ce41cb0494bcb99176527165e321fec\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ModelConfig \\n Interface: ModelConfig + \\n Properties \\n assume_role? \\n \\n optional assume_role: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:592 \\n \\n driver? + \\n \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 + \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: + number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \\n \\n max_images? \\n \\n optional max_images: string \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \\n \\n output_tokens \\n + \\n output_tokens: object \\n \\n default_max? \\n \\n optional default_max: + number \\n \\n max \\n \\n max: number \\n \\n min? \\n \\n optional min: + number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:588 + \\n \\n prompt_id? \\n \\n optional prompt_id: string \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/kb/kb.models.ts:589\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":212,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":108,\"key\":\"\"},{\"start\":108,\"end\":212,\"key\":\"\"}]},{\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":215,\"end\":380,\"key\":\"\"},{\"start\":380,\"end\":480,\"key\":\"\"}]},{\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":483,\"end\":638,\"key\":\"\"},{\"start\":638,\"end\":703,\"key\":\"\"}]},{\"start\":703,\"end\":895,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":704,\"end\":806,\"key\":\"\"},{\"start\":806,\"end\":895,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:01.191702Z\",\"last_understanding\":\"2026-07-14T12:50:00.962823Z\",\"last_extract\":\"2026-07-14T12:50:00.418522Z\",\"last_processing_start\":\"2026-07-14T12:50:00.364723Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > ModelConfig\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > ModelConfig\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\":{\"score\":0.6226930022239685,\"score_type\":\"VECTOR\",\"order\":6,\"text\":\" + \\n optional max_images: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 + \\n \\n output_tokens \\n \\n output_tokens: object \\n \\n default_max? \\n + \\n optional default_max: number \\n \\n max \\n \\n max: number \\n \\n min? + \\n \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":2,\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\":{\"score\":0.5966856479644775,\"score_type\":\"VECTOR\",\"order\":18,\"text\":\" + \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 + \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: + number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \\n \\n max_images? \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":1,\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"dd41482018924facb5dbb87a7d53f122\":{\"id\":\"dd41482018924facb5dbb87a7d53f122\",\"slug\":\"docs-ingestion-how-to-rate-limiting-md\",\"title\":\"docs + > ingestion > how to > rate limiting\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:05.339624\",\"modified\":\"2026-06-09T08:18:12.259849\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + rate-limiting\\ntitle: Manage rate limiting\\n---\\n\\n# Manage rate limiting\\n\\nRate + limits are an essential aspect of the Agentic RAG platform, ensuring fair + usage and optimal performance for all users interacting with Agentic RAG APIs. + This document outlines the rate limits enforced by Agentic RAG and provides + guidelines for handling rate-limited responses effectively.\\n\\n## Introduction\\n\\nAgentic + RAG can apply two types of limits to its APIs:\\n\\n- **Regular API rate limits**: + By default, the sum of all authenticated requests in a Agentic RAG account + cannot exceed 2400 requests per minute. Note that this limit can be customized + on a per-account basis. Please contact [Agentic RAG's support team](mailto:support@nuclia.com) + if you need an increase.\\n\\n- **Ingestion back pressure limits**: Agentic + RAG implements a back-pressure mechanism to manage ingestion pipeline overload. + This mainly affects endpoints for uploading data and creating or updating + resources.\\n\\n## Handling Rate-Limited Responses\\n\\nAgentic RAG adheres + to [the HTTP standard](https://datatracker.ietf.org/doc/html/rfc6585#section-4) + and will return a response with a `429` status codes when the limits are exceeded.\\n\\nThe + official Agentic RAG API clients already have built-in mechanisms for retrying + requests when rate limits are encountered:\\n\\n- [Nuclia Python client](/docs/develop/python-sdk/README)\\n- + [Nuclia JavaScript client](/docs/develop/js-sdk/)\\n\\nHowever, if you are + interacting directly with the API, we recommend using an [exponential backoff + retry strategy](https://en.wikipedia.org/wiki/Exponential_backoff) when limits + are reached.\\n\\nWhen ingestion back pressure rate limits are hit, the response + will include a `try_after` key with an estimated UTC time for retrying the + request. You can use this value for retry logic as an alternative to the exponential + backoff strategy.\\n\\n## Example 1: Regular API rate limits\\n\\nHere's an + example of how to implement an exponential backoff retry strategy in Python:\\n\\n```python\\nimport + time\\nimport requests\\n\\ndef make_request_with_exponential_backoff(url, + headers, max_retries=5):\\n retries = 0\\n while retries < max_retries:\\n + \ response = requests.get(url, headers=headers)\\n if response.status_code + == 200:\\n return response.json()\\n elif response.status_code + == 429:\\n wait_time = 2 ** retries # Exponential backoff: 2^retries\\n + \ print(f\\\"Rate limit exceeded. Retrying in {wait_time} seconds...\\\")\\n + \ time.sleep(wait_time)\\n retries += 1\\n else:\\n + \ response.raise_for_status()\\n raise Exception(\\\"Max retries + exceeded\\\")\\n\\n# Example usage\\nurl = \\\"https://your-endpoint\\\"\\nheaders + = {\\\"Authorization\\\": \\\"Bearer YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_exponential_backoff(url, + headers)\\nprint(data)\\n```\\n\\n## Example 2: Ingestion back pressure limits\\n\\nHere's + an example of how to use the try_after key from the response to manage rate + limits:\\n\\n```python\\nimport time\\nfrom datetime import datetime\\n\\nimport + requests\\n\\n\\ndef make_request_with_try_after_info(url, headers, max_retries=5):\\n + \ retries = 0\\n while retries < max_retries:\\n response = requests.get(url, + headers=headers)\\n response_body = response.json()\\n if response.status_code + == 200:\\n return response.json()\\n elif response.status_code + == 429 and \\\"try_after\\\" in response_body:\\n try_after = response_body[\\\"try_after\\\"]\\n + \ retry_time = datetime.strptime(try_after, \\\"%Y-%m-%dT%H:%M:%S.%fZ\\\")\\n + \ wait_time = (retry_time - datetime.utcnow()).total_seconds()\\n + \ print(\\n f\\\"Rate limit exceeded. Retrying at + {retry_time} (in {wait_time} seconds)...\\\"\\n )\\n time.sleep(wait_time)\\n + \ retries += 1\\n else:\\n response.raise_for_status()\\n + \ raise Exception(\\\"Max retries exceeded\\\")\\n\\n\\n# Example usage\\nurl + = \\\"https://your-endpoint\\\"\\nheaders = {\\\"Authorization\\\": \\\"Bearer + YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_try_after_info(url, headers)\\nprint(data)\\n```\\n\\nThese + examples demonstrate how to handle rate limits effectively, ensuring that + your application respects the limits and retries appropriately.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"ed11945857f4618eec7ed0d1b16ffa44\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: rate-limiting \\n title: Manage rate limiting \\n \\n Manage rate + limiting \\n Rate limits are an essential aspect of the Agentic RAG platform, + ensuring fair usage and optimal performance for all users interacting with + Agentic RAG APIs. This document outlines the rate limits enforced by Agentic + RAG and provides guidelines for handling rate-limited responses effectively. + \\n Introduction \\n Agentic RAG can apply two types of limits to its APIs: + \\n \\n \\n Regular API rate limits: By default, the sum of all authenticated + requests in a Agentic RAG account cannot exceed 2400 requests per minute. + Note that this limit can be customized on a per-account basis. Please contact + Agentic RAG's support team if you need an increase. \\n \\n \\n Ingestion + back pressure limits: Agentic RAG implements a back-pressure mechanism to + manage ingestion pipeline overload. This mainly affects endpoints for uploading + data and creating or updating resources. \\n \\n \\n Handling Rate-Limited + Responses \\n Agentic RAG adheres to the HTTP standard and will return a response + with a 429 status codes when the limits are exceeded. \\n The official Agentic + RAG API clients already have built-in mechanisms for retrying requests when + rate limits are encountered: \\n \\n Nuclia Python client \\n Nuclia JavaScript + client \\n \\n However, if you are interacting directly with the API, we recommend + using an exponential backoff retry strategy when limits are reached. \\n When + ingestion back pressure rate limits are hit, the response will include a try_after + key with an estimated UTC time for retrying the request. You can use this + value for retry logic as an alternative to the exponential backoff strategy. + \\n Example 1: Regular API rate limits \\n Here's an example of how to implement + an exponential backoff retry strategy in Python: \\n ```python \\n import + time \\n import requests \\n def make_request_with_exponential_backoff(url, + headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: + \\n response = requests.get(url, headers=headers) \\n if response.status_code + == 200: \\n return response.json() \\n elif response.status_code == 429: \\n + wait_time = 2 retries # Exponential backoff: 2^retries \\n print(f Rate limit + exceeded. Retrying in {wait_time} seconds... ) \\n time.sleep(wait_time) \\n + retries += 1 \\n else: \\n response.raise_for_status() \\n raise Exception( + Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint \\n + headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_exponential_backoff(url, + headers) \\n print(data) \\n ``` \\n Example 2: Ingestion back pressure limits + \\n Here's an example of how to use the try_after key from the response to + manage rate limits: \\n ```python \\n import time \\n from datetime import + datetime \\n import requests \\n def make_request_with_try_after_info(url, + headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: + \\n response = requests.get(url, headers=headers) \\n response_body = response.json() + \\n if response.status_code == 200: \\n return response.json() \\n elif response.status_code + == 429 and try_after in response_body: \\n try_after = response_body[ try_after + ] \\n retry_time = datetime.strptime(try_after, %Y-%m-%dT%H:%M:%S.%fZ ) \\n + wait_time = (retry_time - datetime.utcnow()).total_seconds() \\n print( \\n + f Rate limit exceeded. Retrying at {retry_time} (in {wait_time} seconds)... + \\n ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() + \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint + \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, + headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle + rate limits effectively, ensuring that your application respects the limits + and retries 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API\"},\"TIME/UTC\":{\"position\":[{\"start\":1526,\"end\":1529}],\"entity\":\"UTC\"},\"PRODUCT/Python\":{\"position\":[{\"start\":1232,\"end\":1238},{\"start\":1773,\"end\":1779}],\"entity\":\"Python\"},\"TIME/seconds\":{\"position\":[{\"start\":2199,\"end\":2206}],\"entity\":\"seconds\"}},\"relations\":[{\"relation\":\"OTHER\",\"label\":\"operating + system\",\"metadata\":{\"paragraph_id\":\"dd41482018924facb5dbb87a7d53f122/t/page/1222-1656\",\"source_start\":1248,\"source_end\":1254,\"to_start\":1232,\"to_end\":1238},\"from\":{\"value\":\"Nuclia\",\"type\":\"entity\",\"group\":\"ORG\"},\"to\":{\"value\":\"Python\",\"type\":\"entity\",\"group\":\"PRODUCT\"}}],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > ingestion > how to > rate limiting\",\"extracted\":{\"text\":{\"text\":\"docs + > ingestion > how to > rate limiting\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\":{\"score\":0.6079242825508118,\"score_type\":\"VECTOR\",\"order\":11,\"text\":\" + ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() + \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint + \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, + headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle + rate limits effectively, ensuring that your application respects the limits + and retries appropriately.\",\"id\":\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":9,\"start\":3310,\"end\":3757,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"50aac6f34b6d47de8e3b01f8b2de6e9c\":{\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c\",\"slug\":\"docs-develop-js-sdk-interfaces-PredictAnswerOptions-md\",\"title\":\"docs + > develop > js sdk > interfaces > PredictAnswerOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:11.443619\",\"modified\":\"2026-07-14T12:50:46.385594\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / PredictAnswerOptions\\n\\n# + Interface: PredictAnswerOptions\\n\\n## Properties\\n\\n### chat\\\\_history?\\n\\n> + `optional` **chat\\\\_history**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:242](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L242)\\n\\n***\\n\\n### + citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L249)\\n\\n***\\n\\n### + citations?\\n\\n> `optional` **citations**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L248)\\n\\n***\\n\\n### + context?\\n\\n> `optional` **context**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:243](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L243)\\n\\n***\\n\\n### + format\\\\_prompt?\\n\\n> `optional` **format\\\\_prompt**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:258](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L258)\\n\\n***\\n\\n### + generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L250)\\n\\n***\\n\\n### + json\\\\_schema?\\n\\n> `optional` **json\\\\_schema**: `object`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:257](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L257)\\n\\n***\\n\\n### + max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L251)\\n\\n***\\n\\n### + prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:256](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L256)\\n\\n***\\n\\n### + query\\\\_context?\\n\\n> `optional` **query\\\\_context**: `string`[] \\\\| + `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:244](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L244)\\n\\n***\\n\\n### + query\\\\_context\\\\_images?\\n\\n> `optional` **query\\\\_context\\\\_images**: + `object`\\n\\n#### b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> + **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:252](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L252)\\n\\n***\\n\\n### + query\\\\_context\\\\_order?\\n\\n> `optional` **query\\\\_context\\\\_order**: + `object`\\n\\n#### Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:245](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L245)\\n\\n***\\n\\n### + reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:260](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L260)\\n\\n***\\n\\n### + rerank\\\\_context?\\n\\n> `optional` **rerank\\\\_context**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:259](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L259)\\n\\n***\\n\\n### + retrieval?\\n\\n> `optional` **retrieval**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:240](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L240)\\n\\n***\\n\\n### + system?\\n\\n> `optional` **system**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:241](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L241)\\n\\n***\\n\\n### + truncate?\\n\\n> `optional` **truncate**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L246)\\n\\n***\\n\\n### + user\\\\_prompt?\\n\\n> `optional` **user\\\\_prompt**: `object`\\n\\n#### + prompt\\n\\n> **prompt**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"470be50f3c6aeeff5ae3310ed007b9b3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / PredictAnswerOptions \\n Interface: PredictAnswerOptions + \\n Properties \\n chat_history? \\n \\n optional chat_history: ContextEntry[] + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:242 \\n + \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:249 \\n \\n citations? + \\n \\n optional citations: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:248 + \\n \\n context? \\n \\n optional context: ContextEntry[] \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:243 \\n \\n format_prompt? + \\n \\n optional format_prompt: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:258 + \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 \\n \\n json_schema? + \\n \\n optional json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 + \\n \\n max_tokens? \\n \\n optional max_tokens: number \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 \\n \\n prefer_markdown? + \\n \\n optional prefer_markdown: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 + \\n \\n query_context? \\n \\n optional query_context: string[] \\\\| object + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:244 \\n + \\n query_context_images? \\n \\n optional query_context_images: object \\n + \\n b64encoded \\n \\n b64encoded: string \\n \\n content_type \\n \\n content_type: + string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:252 + \\n \\n query_context_order? \\n \\n optional query_context_order: object + \\n \\n Index Signature \\n [key: string]: number \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:245 + \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:260 \\n \\n rerank_context? + \\n \\n optional rerank_context: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:259 + \\n \\n retrieval? \\n \\n optional retrieval: boolean \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/ask.models.ts:240 \\n \\n system? \\n + \\n optional system: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:241 + \\n \\n truncate? \\n \\n optional truncate: boolean \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/search/ask.models.ts:246 \\n \\n user_prompt? \\n + \\n optional user_prompt: object \\n \\n prompt \\n \\n prompt: string \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:247\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":257,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":127,\"key\":\"\"},{\"start\":127,\"end\":257,\"key\":\"\"}]},{\"start\":257,\"end\":491,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":260,\"end\":382,\"key\":\"\"},{\"start\":382,\"end\":491,\"key\":\"\"}]},{\"start\":491,\"end\":739,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":494,\"end\":617,\"key\":\"\"},{\"start\":617,\"end\":739,\"key\":\"\"}]},{\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":742,\"end\":864,\"key\":\"\"},{\"start\":864,\"end\":977,\"key\":\"\"}]},{\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":980,\"end\":1100,\"key\":\"\"},{\"start\":1100,\"end\":1221,\"key\":\"\"}]},{\"start\":1221,\"end\":1575,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1224,\"end\":1364,\"key\":\"\"},{\"start\":1364,\"end\":1575,\"key\":\"\"}]},{\"start\":1575,\"end\":1866,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1578,\"end\":1743,\"key\":\"\"},{\"start\":1743,\"end\":1866,\"key\":\"\"}]},{\"start\":1866,\"end\":2096,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1869,\"end\":1988,\"key\":\"\"},{\"start\":1988,\"end\":2096,\"key\":\"\"}]},{\"start\":2096,\"end\":2320,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2099,\"end\":2208,\"key\":\"\"},{\"start\":2208,\"end\":2320,\"key\":\"\"}]},{\"start\":2320,\"end\":2449,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2323,\"end\":2449,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:49.024021Z\",\"last_understanding\":\"2026-07-14T12:50:48.461687Z\",\"last_extract\":\"2026-07-14T12:50:47.086918Z\",\"last_processing_start\":\"2026-07-14T12:50:47.048628Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > PredictAnswerOptions\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > PredictAnswerOptions\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\":{\"score\":0.6562845706939697,\"score_type\":\"VECTOR\",\"order\":4,\"text\":\" + \\n optional max_tokens: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \\n \\n query_context? + \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":4,\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\":{\"score\":0.6046878099441528,\"score_type\":\"VECTOR\",\"order\":13,\"text\":\" + \\n optional generative_model: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 + \\n \\n json_schema? \\n \\n optional json_schema: object \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 \\n \\n max_tokens? + \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":3,\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs + > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-07-14T12:51:04.368823\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ChatOptions\\n\\n# + Interface: ChatOptions\\n\\n## Extends\\n\\n- [`BaseSearchOptions`](BaseSearchOptions.md)\\n\\n## + Properties\\n\\n### answer\\\\_json\\\\_schema?\\n\\n> `optional` **answer\\\\_json\\\\_schema**: + `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:114](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L114)\\n\\n***\\n\\n### + audit\\\\_metadata?\\n\\n> `optional` **audit\\\\_metadata**: `object`\\n\\n#### + Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `string`\\n\\n#### Inherited + from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`audit_metadata`](BaseSearchOptions.md#audit_metadata)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:81](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L81)\\n\\n***\\n\\n### + citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:116](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L116)\\n\\n***\\n\\n### + citations?\\n\\n> `optional` **citations**: `boolean` \\\\| `\\\"none\\\"` + \\\\| `\\\"default\\\"` \\\\| `\\\"llm_footnotes\\\"`\\n\\nIt will return + the text blocks that have been effectively used to build each section of the + answer.\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:105](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L105)\\n\\n***\\n\\n### + debug?\\n\\n> `optional` **debug**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`debug`](BaseSearchOptions.md#debug)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:79](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L79)\\n\\n***\\n\\n### + extra\\\\_context?\\n\\n> `optional` **extra\\\\_context**: `string`[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:115](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L115)\\n\\n***\\n\\n### + extra\\\\_context\\\\_images?\\n\\n> `optional` **extra\\\\_context\\\\_images**: + `object`[]\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:118](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L118)\\n\\n***\\n\\n### + ~~extracted?~~\\n\\n> `optional` **extracted**: [`ExtractedDataTypes`](../enumerations/ExtractedDataTypes.md)[]\\n\\n#### + Deprecated\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`extracted`](BaseSearchOptions.md#extracted)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:73](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L73)\\n\\n***\\n\\n### + features?\\n\\n> `optional` **features**: [`Features`](../namespaces/Ask/enumerations/Features.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:117](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L117)\\n\\n***\\n\\n### + field\\\\_type\\\\_filter?\\n\\n> `optional` **field\\\\_type\\\\_filter**: + [`FIELD_TYPE`](../enumerations/FIELD_TYPE.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`field_type_filter`](BaseSearchOptions.md#field_type_filter)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:74](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L74)\\n\\n***\\n\\n### + fields?\\n\\n> `optional` **fields**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`fields`](BaseSearchOptions.md#fields)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:62](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L62)\\n\\n***\\n\\n### + filter\\\\_expression?\\n\\n> `optional` **filter\\\\_expression**: [`FilterExpression`](FilterExpression.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filter_expression`](BaseSearchOptions.md#filter_expression)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:64](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L64)\\n\\n***\\n\\n### + filters?\\n\\n> `optional` **filters**: `string`[] \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filters`](BaseSearchOptions.md#filters)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:63](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L63)\\n\\n***\\n\\n### + generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:108](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L108)\\n\\n***\\n\\n### + highlight?\\n\\n> `optional` **highlight**: `boolean`\\n\\n#### Inherited + from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`highlight`](BaseSearchOptions.md#highlight)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:76](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L76)\\n\\n***\\n\\n### + keyword\\\\_filters?\\n\\n> `optional` **keyword\\\\_filters**: `string`[] + \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`keyword_filters`](BaseSearchOptions.md#keyword_filters)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:65](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L65)\\n\\n***\\n\\n### + max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number` \\\\| `object`\\n\\nDefines + the maximum number of tokens that the model will take as context.\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:112](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L112)\\n\\n***\\n\\n### + min\\\\_score?\\n\\n> `optional` **min\\\\_score**: `number` \\\\| [`MinScore`](MinScore.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`min_score`](BaseSearchOptions.md#min_score)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:66](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L66)\\n\\n***\\n\\n### + prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:113](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L113)\\n\\n***\\n\\n### + prompt?\\n\\n> `optional` **prompt**: `string` \\\\| [`Prompts`](Prompts.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:101](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L101)\\n\\n***\\n\\n### + query\\\\_image?\\n\\n> `optional` **query\\\\_image**: `object`\\n\\n#### + b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> + **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:122](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L122)\\n\\n***\\n\\n### + rag\\\\_images\\\\_strategies?\\n\\n> `optional` **rag\\\\_images\\\\_strategies**: + [`RAGImageStrategy`](../type-aliases/RAGImageStrategy.md)[]\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:107](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L107)\\n\\n***\\n\\n### + rag\\\\_strategies?\\n\\n> `optional` **rag\\\\_strategies**: [`RAGStrategy`](../type-aliases/RAGStrategy.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:106](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L106)\\n\\n***\\n\\n### + range\\\\_creation\\\\_end?\\n\\n> `optional` **range\\\\_creation\\\\_end**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_end`](BaseSearchOptions.md#range_creation_end)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:68](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L68)\\n\\n***\\n\\n### + range\\\\_creation\\\\_start?\\n\\n> `optional` **range\\\\_creation\\\\_start**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_start`](BaseSearchOptions.md#range_creation_start)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:67](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L67)\\n\\n***\\n\\n### + range\\\\_modification\\\\_end?\\n\\n> `optional` **range\\\\_modification\\\\_end**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_end`](BaseSearchOptions.md#range_modification_end)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:70](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L70)\\n\\n***\\n\\n### + range\\\\_modification\\\\_start?\\n\\n> `optional` **range\\\\_modification\\\\_start**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_start`](BaseSearchOptions.md#range_modification_start)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:69](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L69)\\n\\n***\\n\\n### + rank\\\\_fusion?\\n\\n> `optional` **rank\\\\_fusion**: [`RankFusion`](RankFusion.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rank_fusion`](BaseSearchOptions.md#rank_fusion)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:84](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L84)\\n\\n***\\n\\n### + reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L126)\\n\\n***\\n\\n### + rephrase?\\n\\n> `optional` **rephrase**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rephrase`](BaseSearchOptions.md#rephrase)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:77](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L77)\\n\\n***\\n\\n### + reranker?\\n\\n> `optional` **reranker**: [`Reranker`](../enumerations/Reranker.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`reranker`](BaseSearchOptions.md#reranker)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:83](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L83)\\n\\n***\\n\\n### + resource\\\\_filters?\\n\\n> `optional` **resource\\\\_filters**: `string`[]\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`resource_filters`](BaseSearchOptions.md#resource_filters)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:75](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L75)\\n\\n***\\n\\n### + search\\\\_configuration?\\n\\n> `optional` **search\\\\_configuration**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`search_configuration`](BaseSearchOptions.md#search_configuration)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:86](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L86)\\n\\n***\\n\\n### + security?\\n\\n> `optional` **security**: `object`\\n\\n#### groups\\n\\n> + **groups**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`security`](BaseSearchOptions.md#security)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:85](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L85)\\n\\n***\\n\\n### + show?\\n\\n> `optional` **show**: [`ResourceProperties`](../enumerations/ResourceProperties.md)[]\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show`](BaseSearchOptions.md#show)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:71](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L71)\\n\\n***\\n\\n### + show\\\\_consumption?\\n\\n> `optional` **show\\\\_consumption**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L127)\\n\\n***\\n\\n### + show\\\\_hidden?\\n\\n> `optional` **show\\\\_hidden**: `boolean`\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show_hidden`](BaseSearchOptions.md#show_hidden)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:80](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L80)\\n\\n***\\n\\n### + synchronous?\\n\\n> `optional` **synchronous**: `boolean`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:100](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L100)\\n\\n***\\n\\n### + top\\\\_k?\\n\\n> `optional` **top\\\\_k**: `number`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`top_k`](BaseSearchOptions.md#top_k)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:82](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L82)\\n\\n***\\n\\n### + vectorset?\\n\\n> `optional` **vectorset**: `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`vectorset`](BaseSearchOptions.md#vectorset)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:78](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L78)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"d6b2f3f31ba0af4fa58490cdf6abeb52\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ChatOptions \\n Interface: ChatOptions + \\n Extends \\n \\n BaseSearchOptions \\n \\n Properties \\n answer_json_schema? + \\n \\n optional answer_json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:114 + \\n \\n audit_metadata? \\n \\n optional audit_metadata: object \\n \\n Index + Signature \\n [key: string]: string \\n Inherited from \\n BaseSearchOptions.audit_metadata + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:81 \\n + \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:116 \\n \\n + citations? \\n \\n optional citations: boolean \\\\| none \\\\| default \\\\| + llm_footnotes \\n \\n It will return the text blocks that have been effectively + used to build each section of the answer. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:105 + \\n \\n debug? \\n \\n optional debug: boolean \\n \\n Inherited from \\n + BaseSearchOptions.debug \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:79 + \\n \\n extra_context? \\n \\n optional extra_context: string[] \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:115 \\n \\n extra_context_images? + \\n \\n optional extra_context_images: object[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:118 + \\n \\n ~~extracted?~~ \\n \\n optional extracted: ExtractedDataTypes[] \\n + \\n Deprecated \\n Inherited from \\n BaseSearchOptions.extracted \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:73 \\n \\n features? + \\n \\n optional features: Features[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:117 + \\n \\n field_type_filter? \\n \\n optional field_type_filter: FIELD_TYPE[] + \\n \\n Inherited from \\n BaseSearchOptions.field_type_filter \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:74 \\n \\n fields? + \\n \\n optional fields: string[] \\n \\n Inherited from \\n BaseSearchOptions.fields + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:62 \\n + \\n filter_expression? \\n \\n optional filter_expression: FilterExpression + \\n \\n Inherited from \\n BaseSearchOptions.filter_expression \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:64 \\n \\n filters? + \\n \\n optional filters: string[] \\\\| Filter[] \\n \\n Inherited from \\n + BaseSearchOptions.filters \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:63 + \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:108 \\n \\n + highlight? \\n \\n optional highlight: boolean \\n \\n Inherited from \\n + BaseSearchOptions.highlight \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:76 + \\n \\n keyword_filters? \\n \\n optional keyword_filters: string[] \\\\| + Filter[] \\n \\n Inherited from \\n BaseSearchOptions.keyword_filters \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:65 \\n \\n + max_tokens? \\n \\n optional max_tokens: number \\\\| object \\n \\n Defines + the maximum number of tokens that the model will take as context. \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 \\n \\n min_score? + \\n \\n optional min_score: number \\\\| MinScore \\n \\n Inherited from \\n + BaseSearchOptions.min_score \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:66 + \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:113 \\n \\n + prompt? \\n \\n optional prompt: string \\\\| Prompts \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/search/search.models.ts:101 \\n \\n query_image? + \\n \\n optional query_image: object \\n \\n b64encoded \\n \\n b64encoded: + string \\n \\n content_type \\n \\n content_type: string \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/search.models.ts:122 \\n \\n rag_images_strategies? + \\n \\n optional rag_images_strategies: RAGImageStrategy[] \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:107 \\n \\n rag_strategies? + \\n \\n optional rag_strategies: RAGStrategy[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:106 + \\n \\n range_creation_end? \\n \\n optional range_creation_end: string \\n + \\n Inherited from \\n BaseSearchOptions.range_creation_end \\n Defined in + \\n libs/sdk-core/src/lib/db/search/search.models.ts:68 \\n \\n range_creation_start? + \\n \\n optional range_creation_start: string \\n \\n Inherited from \\n BaseSearchOptions.range_creation_start + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:67 \\n + \\n range_modification_end? \\n \\n optional range_modification_end: string + \\n \\n Inherited from \\n BaseSearchOptions.range_modification_end \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:70 \\n \\n range_modification_start? + \\n \\n optional range_modification_start: string \\n \\n Inherited from \\n + BaseSearchOptions.range_modification_start \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:69 + \\n \\n rank_fusion? \\n \\n optional rank_fusion: RankFusion \\n \\n Inherited + from \\n BaseSearchOptions.rank_fusion \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:84 + \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:126 \\n \\n rephrase? + \\n \\n optional rephrase: boolean \\n \\n Inherited from \\n BaseSearchOptions.rephrase + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:77 \\n + \\n reranker? \\n \\n optional reranker: Reranker \\n \\n Inherited from \\n + BaseSearchOptions.reranker \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:83 + \\n \\n resource_filters? \\n \\n optional resource_filters: string[] \\n + \\n Inherited from \\n BaseSearchOptions.resource_filters \\n Defined in \\n + libs/sdk-core/src/lib/db/search/search.models.ts:75 \\n \\n search_configuration? + \\n \\n optional search_configuration: string \\n \\n Inherited from \\n BaseSearchOptions.search_configuration + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:86 \\n + \\n security? \\n \\n optional security: object \\n \\n groups \\n \\n groups: + string[] \\n \\n Inherited from \\n BaseSearchOptions.security \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:85 \\n \\n show? \\n + \\n optional show: ResourceProperties[] \\n \\n Inherited from \\n BaseSearchOptions.show + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:71 \\n + \\n show_consumption? \\n \\n optional show_consumption: boolean \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:127 \\n \\n show_hidden? + \\n \\n optional show_hidden: boolean \\n \\n Inherited from \\n BaseSearchOptions.show_hidden + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:80 \\n + \\n synchronous? \\n \\n optional synchronous: boolean \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/search.models.ts:100 \\n \\n top_k? \\n + \\n optional top_k: number \\n \\n Inherited from \\n BaseSearchOptions.top_k + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:82 \\n + \\n vectorset? \\n \\n optional vectorset: string \\n \\n Inherited from \\n + BaseSearchOptions.vectorset \\n Defined in \\n 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Your role is to provide accurate, clear, and well-structured - answers based strictly on the information provided to you.\nKey principles:\n- - Answer only using the information in the provided context\n- Do not use external - knowledge, assumptions, or prior experience\n- Maintain a professional and informative - tone\n- Be concise yet thorough\n- If information is insufficient, acknowledge - this clearly\n\nAlways follow any additional instructions provided about format, - style, or domain-specific behavior.", "chat_history": [], "context": [], "query_context": - {}, "query_context_order": {}, "truncate": true, "user_prompt": {"prompt": "\n## - Question\nExplica c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol, - incluyendo un enlace a la documentaci\u00f3n oficial.\n\n## Provided Context\n[START - OF CONTEXT]\n## Retrieval on nuclia-docs Knowledge Box\n\n# Explica c\u00f3mo - usar el par\u00e1metro `max_tokens` en espa\u00f1ol, incluyendo un enlace a - la documentaci\u00f3n oficial.\n\n El par\u00e1metro `max_tokens` define el - n\u00famero m\u00e1ximo de tokens que el modelo tomar\u00e1 como contexto. 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a/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple_disable_ai_parameter_search.yaml +++ b/agents/nucliadb/tests/cassettes/test_nucliadb/test_nucliadb_agent_simple_disable_ai_parameter_search.yaml @@ -1,6 +1,6 @@ interactions: - request: - body: '' + body: '{"prefixes": [{"prefix": "/n/i"}]}' headers: Accept: - '*/*' @@ -8,123 +8,128 @@ interactions: - gzip, deflate Connection: - keep-alive + Content-Length: + - '32' Host: - - europe-1.dp.progress.cloud + - europe-1.nuclia.cloud User-Agent: - - nuclia.py/4.11.5 - x-nuclia-nuakey: + - nucliadb-sdk/6.13.1.post6414 + content-type: + - application/json + x-stf-serviceaccount: - DUMMY - method: GET - uri: https://europe-1.dp.progress.cloud/api/authorizer/info + method: POST + uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/catalog/facets response: body: - string: 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If you do not find an answer + in the context, please say \"Right now I don''t have enough context to answer + your question. Please contact us at support@nuclia.com\". ","prompt":""},"palm":null,"anthropic":null,"claude3":null,"anthropic_vertex":null,"anthropic_bedrock":null,"text_generation":null,"mistral":null,"azure_mistral":null,"hf_llm":null,"openai_url":null,"vertex_llama":null,"deepseek":null,"openai_compat":null,"nova":null},"summary":"simple","summary_model":"claude-4-5-sonnet","summary_prompt":null,"prefer_markdown_generative_response":false,"allow_all_default_models":true,"semantic_model_configs":{"multilingual-2024-05-06":{"similarity":0,"size":1024,"threshold":0.4,"max_tokens":2048,"matryoshka_dims":[],"external":false}},"semantic_graph_node_model_configs":{},"semantic_graph_edge_model_configs":{}}' headers: Alt-Svc: - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Content-Length: - - '115' + - '1814' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 05 Aug 2026 08:09:40 GMT - nuclia-learning-model: - - multilingual + - Wed, 15 Jul 2026 08:11:05 GMT,Wed, 15 Jul 2026 08:11:05 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '17' + - '40' x-nuclia-trace-id: - - a453460ebff452852b5a65cb128ff5b0 + - a7f55c613552d67c7b7048b2b40fb725 status: code: 200 message: OK - request: - body: '{"question": "", "retrieval": true, "user_id": "arag-ask", "system": null, - "chat_history": [], "context": [], "query_context": {}, "query_context_order": - {}, "truncate": true, "user_prompt": {"prompt": "\n\nInformation about the KB:\n\n# - nuclia-docs\n\ndescription: Documentation of the Nuclia API, recipies, reference - \n\nAnd given the question: Explica c\u00f3mo usar el par\u00e1metro `max_tokens` - en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n oficial.\n\n## - labels: {''pmm'': [''Videos'', ''Partner Content'', ''Softcat'', ''Sales Enablement - Assets'', ''KO 26'', ''Data Sheets'', ''Progress Agentic RAG Training Materials - 2026'']}\n\n## Facets:\n\n## Content Types\nThe following content types are - available in the KB:\n\n- /n/i: 994\n- application/json: 1\n- text/markdown: - 993\nThe following languages are available in the KB:\n\n- ca: 4\n- cy: 1\n- - da: 1\n- en: 974\n- eo: 4\n- la: 7\n- nb: 1\n- tl: 1\n- yo: 1\n\n\n# Important - rules to follow\n\n\nprompt=''Be polite''\n"}, "citations": false, "citation_threshold": - null, "generative_model": "gemini-2.5-flash", "max_tokens": 8192, "query_context_images": - {}, "prefer_markdown": null, "json_schema": {"title": "ask_configuration", "description": - "Configuration extracted from reasoning engine", "parameters": {"type": "object", - "properties": {"link": {"type": "boolean", "description": "The user wants link - reference to the answer?"}, "knowledge_scan": {"type": "string", "description": - "If the query requires a knowledge aggregation or scan search to answer define - the entities, labels and relations to query in the KB. 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DO NOT ADD ANY EXTRA NOTES AT THE END, JUST ONE SENTENCE"}, "visual": - {"type": "boolean", "description": "Is required an analysis of an image to answer - this question, answer with false or true"}, "keywords_filter": {"type": "array", - "items": {"type": "string"}, "description": "Extract if any the keywords that - should appear on the retrieved results and its a must match, make sure that - are keywords that are not common words, and that are not the same as the question - or answer. Please define ONLY the keywords without any explanation. Only one - or two words maximum. JUST A LIST OF KEYWORDS. DO NOT ADD ANY EXTRA NOTES AT - THE END, JUST A LIST OF KEYWORDS"}, "reason": {"type": "string"}, "entities": - {"type": "array", "description": "Entities related to the user question to query - in the KB", "items": {"type": "string"}}, "relations": {"type": "array", "description": - "Relations related to the user question to query in the KB", "items": {"type": - "string"}}, "pre_queries": {"type": "array", "items": {"type": "string"}, "description": - "Pre queries to run before the main query to gather more information"}}, "required": - ["semantic_query", "lexical_query", "visual", "keywords_filter", "reason", "pre_queries"]}}, - "format_prompt": false, "rerank_context": false, "tools": [], "tool_choice": - {"type": "required"}, "reasoning": false, "seed": null}' + body: '{"features": ["keyword"], "faceted": ["/classification.labels"]}' headers: Accept: - - application/x-ndjson + - '*/*' Accept-Encoding: - gzip, deflate Connection: - keep-alive Content-Length: - - '3375' - Content-Type: + - '61' + Host: + - europe-1.nuclia.cloud + User-Agent: + - nucliadb-sdk/6.13.1.post6414 + content-type: + - application/json + x-stf-serviceaccount: + - DUMMY + method: POST + uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/search + response: + body: + string: "{\"resources\":{\"2a0d73029ad24c599d6dc1e117a41897\":{\"id\":\"2a0d73029ad24c599d6dc1e117a41897\",\"slug\":\"docs-agentic-deploy-md\",\"title\":\"docs + > agentic > deploy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-29T13:39:02.557258\",\"modified\":\"2026-06-29T13:39:02.557276\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"007b445866574d7ca69891d388663cc6\":{\"id\":\"007b445866574d7ca69891d388663cc6\",\"slug\":\"docs-management-security-5-public-ips-md\",\"title\":\"docs + > management > security > 5 public ips\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-07-03T09:28:57.937064\",\"modified\":\"2026-07-03T09:28:57.937076\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false},\"b28e388104644fc5bba68c0cd44e01d4\":{\"id\":\"b28e388104644fc5bba68c0cd44e01d4\",\"slug\":\"docs-agentic-how-to-agentic-retrieval-md\",\"title\":\"docs + > agentic > how to > agentic retrieval\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-06-29T13:39:03.379512\",\"modified\":\"2026-06-29T13:39:03.379525\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false}},\"paragraphs\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Outbound \u2014 the source IP addresses that Progress Agentic RAG uses when + making connections to your systems (e.g., webhooks, sync agents, or other + integrations). Allowlist these if you restrict inbound traffic to your infrastructure. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n :::note \\n The current list of IP addresses is also available in machine-readable + format: JSON | YAML. These lists may change over time, so we recommend periodically + fetching and applying updates to your firewall rules to ensure uninterrupted + service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall + restricts network traffic, you may need to allowlist the following IP addresses. + They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | + --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 + | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 + | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- + | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n + | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 + | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | + 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 + | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 + | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United + States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- + | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 + | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS + PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately + through an AWS endpoint service (AWS PrivateLink) instead of over the public + internet, allowing connections to be established from your VPC without traversing + public IP addresses. This option is not available through self-service configuration. + Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests + on. Allowlist these if you restrict outbound traffic from your infrastructure + and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent + \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful + tool that enhances the capabilities of traditional retrieval-augmented generation + (RAG) systems. Regular RAG's fixed search-then-generate process is limiting + for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Different models can be chosen for different tasks: \\n \\n Context validation + happens when the Prune context option is enabled (recommended), we recommend + using a fast model - planning or the execution model (depending on the planning + mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Note: the rephrasing model is only used in more complex workflow, it can + be ignored in the present case. \\n Finally, add a Summarize agent in the + Generation step to generate a final answer from the retrieved information. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The Smart Agent plans the answer: picks the most appropriate sources, splits + the question into sub-questions, evaluates relevancy, and iterates autonomously + until the information is sufficient. \\n Basic usage \\n To set up a Smart + Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, + etc.) in the Sources section of the left menu. Then, create a new workflow + in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Chat mode \\n If you want to use the Smart Agent in a chat interface, you + need the following: \\n \\n Enable the Session history option in the Smart + Agent configuration. This will allow the Smart Agent to take into account + the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Then connect your sources as Registered Agents to the Smart Agent. It is very + important that you provide an extensive description of each registered agent, + so that the Smart Agent can understand what each source is about and when + to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n reactive: The Smart Agent will decide what to do first, and will plan + the next steps based on the information it retrieves. It is expected to be + faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, + and will execute them. It will be slower but more accurate when processing + complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also select the proper function for each registered agent, depending on the + type of source (MCP agents will not need one, the functions are provided dynamically + by the MCP server). \\n In the Smart Agent configuration, you can select the + planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In the Summarize Agent, enable the Conversational mode. This will allow the + Summarize Agent to generate a final answer that will not repeat the information + already provided in the previous conversation, and will be more natural for + a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Custom frontend \\n You can also create a custom frontend for your Retrieval + Agent. This allows you to have full control over the user interface and user + experience. \\n You can directly implement the API calls to your Retrieval + Agent in your frontend code (see the Websocket API section for more details), + or you can use the JavaScript SDK provided by Agentic to simplify the integration. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based + system (for example Claude Cowork or Copilot), it is reachable throught MCP. + \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval + Agent can be deployed in different ways, depending on your needs and the environment + you are working in. \\n Ready-to-use widget \\n The easiest way to deploy + your Retrieval Agent is to use the ready-to-use widget. 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Allowlist these if you restrict inbound traffic to your infrastructure. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":418,\"end\":652},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n :::note \\n The current list of IP addresses is also available in machine-readable + format: JSON | YAML. These lists may change over time, so we recommend periodically + fetching and applying updates to your firewall rules to ensure uninterrupted + service. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":652,\"end\":907},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: public-ips \\n title: Public IP Addresses \\n \\n If your firewall + restricts network traffic, you may need to allowlist the following IP addresses. + They are grouped by region and split into two categories: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":208},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + ::: \\n Europe (GCP) \\n | Inbound | Outbound | \\n | ------------------ | + --------------------- | \\n | 34.111.1.187/32 | 35.204.65.155/32 | \\n | 136.68.112.29/32 + | 34.91.38.151/32 | \\n | | 35.204.139.129/32 | \\n | | 35.204.108.221/32 + | \\n Australia (AWS) \\n | Inbound | Outbound | \\n | ------------------- + | --------------------- | \\n | 54.253.224.44/32 | 15.135.151.213/32 | \\n + | 3.25.20.9/32 | 3.24.144.83/32 | \\n | 52.64.202.159/32 | 3.24.81.206/32 + | \\n Europe (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 63.182.151.234/32 | 63.179.23.139/32 | \\n | + 35.159.36.135/32 | 3.78.13.149/32 | \\n | 52.57.40.91/32 | 3.66.123.24/32 + | \\n Israel (AWS) \\n | Inbound | Outbound | \\n | ------------------- | + --------------------- | \\n | 51.84.176.167/32 | 51.17.150.97/32 | \\n | 16.164.50.185/32 + | 51.84.112.203/32 | \\n | 16.164.85.69/32 | 51.17.212.226/32 | \\n United + States (AWS) \\n | Inbound | Outbound | \\n | -------------------- | -------------------- + | \\n | 18.225.228.199/32 | 3.137.28.168/32 | \\n | 18.119.145.185/32 | 18.225.104.91/32 + | \\n | 3.21.239.244/32 | 16.59.115.61/32 | \\n Private connectivity (AWS + PrivateLink) \\n For AWS-hosted regions, it is possible to expose access privately + through an AWS endpoint service (AWS PrivateLink) instead of over the public + internet, allowing connections to be established from your VPC without traversing + public IP addresses. This option is not available through self-service configuration. + Please reach out to your account manager for details.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":907,\"end\":2402},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Inbound \u2014 the IP addresses that Progress Agentic RAG receives requests + on. Allowlist these if you restrict outbound traffic from your infrastructure + and need to reach our services (e.g., calling our APIs). \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":208,\"end\":418},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > management > security > 5 public ips\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"text\":\"docs + > agentic > how to > agentic retrieval\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":43},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: agentic-retrieval \\n title: Agentic retrieval with the Smart agent + \\n \\n Agentic retrieval with the Smart agent \\n The Smart agent is a powerful + tool that enhances the capabilities of traditional retrieval-augmented generation + (RAG) systems. Regular RAG's fixed search-then-generate process is limiting + for complex questions that need intermediary steps and reasoning. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":373},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Different models can be chosen for different tasks: \\n \\n Context validation + happens when the Prune context option is enabled (recommended), we recommend + using a fast model - planning or the execution model (depending on the planning + mode you have selected): we recommend using a more powerful model. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":5,\"start\":1640,\"end\":1943},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n Note: the rephrasing model is only used in more complex workflow, it can + be ignored in the present case. \\n Finally, add a Summarize agent in the + Generation step to generate a final answer from the retrieved information. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":6,\"start\":1943,\"end\":2167},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + The Smart Agent plans the answer: picks the most appropriate sources, splits + the question into sub-questions, evaluates relevancy, and iterates autonomously + until the information is sufficient. \\n Basic usage \\n To set up a Smart + Agent, declare all the sources you want to use (Knowledge Boxes, Perplexity, + etc.) in the Sources section of the left menu. Then, create a new workflow + in the Workflows section and add a Smart Agent in the Retrieval step. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":373,\"end\":825},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Chat mode \\n If you want to use the Smart Agent in a chat interface, you + need the following: \\n \\n Enable the Session history option in the Smart + Agent configuration. This will allow the Smart Agent to take into account + the previous conversation when planning its next steps. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":7,\"start\":2167,\"end\":2442},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Then connect your sources as Registered Agents to the Smart Agent. It is very + important that you provide an extensive description of each registered agent, + so that the Smart Agent can understand what each source is about and when + to use it. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":825,\"end\":1068},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n reactive: The Smart Agent will decide what to do first, and will plan + the next steps based on the information it retrieves. It is expected to be + faster. \\n plan_execute: The Smart Agent will plan all the steps in advance, + and will execute them. It will be slower but more accurate when processing + complex questions. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":4,\"start\":1321,\"end\":1640},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Also select the proper function for each registered agent, depending on the + type of source (MCP agents will not need one, the functions are provided dynamically + by the MCP server). \\n In the Smart Agent configuration, you can select the + planning mode: \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1068,\"end\":1321},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + In the Summarize Agent, enable the Conversational mode. This will allow the + Summarize Agent to generate a final answer that will not repeat the information + already provided in the previous conversation, and will be more natural for + a chat interface. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":8,\"start\":2442,\"end\":2694},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Custom frontend \\n You can also create a custom frontend for your Retrieval + Agent. This allows you to have full control over the user interface and user + experience. \\n You can directly implement the API calls to your Retrieval + Agent in your frontend code (see the Websocket API section for more details), + or you can use the JavaScript SDK provided by Agentic to simplify the integration. + \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":2,\"start\":617,\"end\":1005},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + MCP \\n If you want to integrate your Retrieval Agent with a broader AI-based + system (for example Claude Cowork or Copilot), it is reachable throught MCP. + \\n The MCP endpoint is visible on the agent home page on the dashboard.\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":3,\"start\":1005,\"end\":1230},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + \\n id: deploy \\n title: Deploy \\n \\n Deploy \\n Your Agentic Retrieval + Agent can be deployed in different ways, depending on your needs and the environment + you are working in. \\n Ready-to-use widget \\n The easiest way to deploy + your Retrieval Agent is to use the ready-to-use widget. You can embed it in + your website or application, and it will provide a chat user interface for + interacting with the agent. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":401},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"text\":\" + Go to the Widgets section in the left menu, and click on Create widget to + create a new widget. You can customize its appearance, and then copy the generated + code snippet to embed it in your website or application. \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":401,\"end\":617},\"fuzzy_result\":false}],\"facets\":{\"/k\":{\"/k/text\":5294}},\"query\":\"\",\"total\":5294,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"fulltext\":{\"results\":[{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"007b445866574d7ca69891d388663cc6\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"b28e388104644fc5bba68c0cd44e01d4\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"2a0d73029ad24c599d6dc1e117a41897\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"f13642b2862f4a1ea2144c9eb2abb2a3\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"t\",\"field\":\"page\",\"labels\":[]},{\"score\":0.0,\"rid\":\"ed6fda7434aa43a3bd5138b95e7fe081\",\"field_type\":\"a\",\"field\":\"title\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-resources\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-search\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-rag-lab\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"account-arag\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-kv-schemas\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"user-profile\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-users\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-widgets\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"kb-remi-analytics\",\"labels\":[]},{\"score\":0.0,\"rid\":\"a572ce0c7eb949e4a17babae21a03a4a\",\"field_type\":\"t\",\"field\":\"agent-users\",\"labels\":[]}],\"facets\":{},\"query\":\"\",\"total\":2013,\"page_number\":0,\"page_size\":20,\"next_page\":true,\"min_score\":0.0},\"shards\":[\"306cbabb-72a5-417c-827f-7874e205c858\"]}" headers: Alt-Svc: - h3=":443"; ma=2592000 - Transfer-Encoding: - - chunked + Content-Length: + - '16898' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - - application/x-ndjson + - application/json date: - - Wed, 05 Aug 2026 08:09:40 GMT - nuclia-learning-id: - - 0a090a761a1f43e3802839819646990f - nuclia-learning-model: - - gemini-2.5-flash + - Wed, 15 Jul 2026 08:11:05 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '1993' + - '71' x-nuclia-trace-id: - - 86509b3f428f5321d6ae0b3152ba4b26 + - 903025bdfd59ddc87309b5ce82eff861 status: code: 200 message: OK - request: - body: '{"question": "Explica c\u00f3mo usar el par\u00e1metro `max_tokens` en - espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n oficial.", "user_id": - "arag-ask-rerank", "context": {"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412": - " max_tokens: the maximum number of input tokens to put in the final context - (including the prompt, the retrieved results and the user question). \n max_output_tokens: - the maximum number of tokens to generate. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n", - "0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349": "@nuclia/core \u2022 Docs \n - \n @nuclia/core / Consumption \n Interface: Consumption \n Properties \n customer_key_tokens - \n \n customer_key_tokens: TokenConsumption \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:230 - \n \n normalized_tokens \n \n normalized_tokens: TokenConsumption \n \n Defined - in \n libs/sdk-core/src/lib/db/search/ask.models.ts:229\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Consumption\n", - "43004f553e534ffe9c9e735856bd9b23/t/page/480-703": " \n optional max_images: - string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \n \n - output_tokens \n \n output_tokens: object \n \n default_max? \n \n optional - default_max: number \n \n max \n \n max: number \n \n min? \n \n\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n", - "43004f553e534ffe9c9e735856bd9b23/t/page/212-480": " \n optional driver: string - \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 \n \n input_tokens - \n \n input_tokens: object \n \n max \n \n max: number \n \n min? \n \n optional - min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \n \n max_images? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n", - "dd41482018924facb5dbb87a7d53f122/t/page/3310-3757": " ) \n time.sleep(wait_time) - \n retries += 1 \n else: \n response.raise_for_status() \n raise Exception( - Max retries exceeded ) \n Example usage \n url = https://your-endpoint \n headers - = { Authorization : Bearer YOUR_ACCESS_TOKEN } \n data = make_request_with_try_after_info(url, - headers) \n print(data) \n ``` \n These examples demonstrate how to handle rate - limits effectively, ensuring that your application respects the limits and retries - appropriately.\n\n\nLink: https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\n", - "e8525e64c5b44982b958d32cf6090613/t/page/2808-3011": " \n optional max_tokens: - number \\| object \n \n Defines the maximum number of tokens that the model - will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 - \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n", - "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221": " \n optional max_tokens: - number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined - in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", - "50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977": " \n optional generative_model: - string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 - \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 - \n \n max_tokens? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n", - "f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299": "@nuclia/core \u2022 Docs \n - \n @nuclia/core / PageToken \n Interface: PageToken \n Properties \n height - \n \n height: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 - \n \n line \n \n line: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 - \n \n text \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageToken\n", - "0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224": "@nuclia/core \u2022 Docs \n - \n @nuclia/core / ReasoningConfig \n Interface: ReasoningConfig \n Properties - \n budget_tokens? \n \n optional budget_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 - \n \n effort? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ReasoningConfig\n", - "24ad6997e1fe4a109d67d7802a083678/a/title/0-55": "docs > develop > js sdk > - interfaces > TokenConsumption\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/TokenConsumption\n", - "6e8250e6b5264156988657a221fd5e94/t/page/0-397": "@nuclia/core \u2022 Docs \n - \n @nuclia/core / Ask / ConsumptionAskResponseItem \n Interface: ConsumptionAskResponseItem - \n Properties \n customer_key_tokens \n \n customer_key_tokens: TokenConsumption - \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:127 \n \n - normalized_tokens \n \n normalized_tokens: TokenConsumption \n \n Defined in - \n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \n \n type \n \n\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/namespaces/Ask/interfaces/ConsumptionAskResponseItem\n", - "44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668": " \n step: Information - about the current processing step \n module: The module being executed (e.g., - rephrase , basic_ask , remi ) \n title: Display title for the step \n value: - Result of the step \n reason: Explanation for the step \n timeit: Time taken - in seconds \n \n input_nuclia_tokens/output_nuclia_tokens: Token usage \n \n - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/python-sdk/rao\n", - "4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340": " Use the max_tokens parameter - on the /ask endpoint to set hard limits on: \n - Context size: Limits the amount - of retrieved information sent to the LLM \n - Answer length: Limits the length - of the generated response \n Important Considerations \n Context Limitations: - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n", - "8b3e0ef630a346d1b591143309db87ec/t/page/0-281": "@nuclia/core \u2022 Docs \n - \n @nuclia/core / NucliaTokensMetric \n Interface: NucliaTokensMetric \n Extends - \n \n UsageMetric \n \n Properties \n details \n \n details: NucliaTokensDetails[] - \n \n Overrides \n UsageMetric.details \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:187 - \n \n name \n \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/NucliaTokensMetric\n", - "66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833": "@nuclia/core \u2022 Docs - \n \n @nuclia/core / UsageType \n Enumeration: UsageType \n Enumeration Members - \n AI_TOKENS_USED \n \n AI_TOKENS_USED: ai_tokens_used \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:208 - \n \n BYTES_PROCESSED \n \n BYTES_PROCESSED: bytes_processed \n \n Defined in - \n libs/sdk-core/src/lib/db/db.models.ts:199 \n \n CHARS_PROCESSED \n \n CHARS_PROCESSED: - chars_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:200 - \n \n MEDIA_FILES_PROCESSED \n \n MEDIA_FILES_PROCESSED: media_files_processed - \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:202 \n \n MEDIA_SECONDS_PROCESSED - \n \n MEDIA_SECONDS_PROCESSED: media_seconds_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:201 - \n \n NUCLIA_TOKENS \n \n NUCLIA_TOKENS: nuclia_tokens_billed \n \n Defined - in \n libs/sdk-core/src/lib/db/db.models.ts:209 \n \n PAGES_PROCESSED \n \n - PAGES_PROCESSED: pages_processed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:203 - \n \n PARAGRAPHS_PROCESSED \n \n PARAGRAPHS_PROCESSED: paragraphs_processed - \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:204 \n \n PRE_PROCESSING_TIME - \n \n PRE_PROCESSING_TIME: pre_processing_time \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:196 - \n \n RESOURCES_PROCESSED \n \n RESOURCES_PROCESSED: resources_processed \n - \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:198 \n \n SEARCHES_PERFORMED - \n \n SEARCHES_PERFORMED: searches_performed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:206 - \n \n SLOW_PROCESSING_TIME \n \n SLOW_PROCESSING_TIME: slow_processing_time - \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:197 \n \n SUGGESTIONS_PERFORMED - \n \n SUGGESTIONS_PERFORMED: suggestions_performed \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:207 - \n \n TRAIN_SECONDS \n \n TRAIN_SECONDS: train_seconds \n \n Defined in \n libs/sdk-core/src/lib/db/db.models.ts:205\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/enumerations/UsageType\n", - "89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043": " Description: The maximum - number of tokens that the model can generate as output. Again, we should keep - in mind that this value summed to the Maximum supported input tokens should - not exceed the total context size supported by the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", - "89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575": " \n \n Maximum supported - input tokens: \n Description: The maximum number of tokens that the model can - accept as input. Be mindful that this takes into account the tokens used in - the prompt, query and context. Also take note that some models may provide their - context window as the total between input and output tokens, while others may - provide it as the input tokens only. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n", - "4194605cdfbd414f8fa762630d555bc1/t/page/0-358": "@nuclia/core \u2022 Docs \n - \n @nuclia/core / PageStructure \n Interface: PageStructure \n Properties \n - page \n \n page: object \n \n height \n \n height: number \n \n width \n \n - width: number \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:238 - \n \n tokens \n \n tokens: PageToken[] \n \n Defined in \n libs/sdk-core/src/lib/db/resource/resource.models.ts:242\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageStructure\n", - "42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696": " \n optional max_paragraph: - number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 \n \n - name? \n \n optional name: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\n\n\nLink: - https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/SplitStrategy\n"}}' + body: '{"user_id": "arag-ask", "texts": ["Explica c\u00f3mo usar el par\u00e1metro + `max_tokens` en espa\u00f1ol y proporciona un enlace a la documentaci\u00f3n + oficial."]}' headers: Accept: - '*/*' @@ -404,312 +563,3700 @@ interactions: Connection: - keep-alive Content-Length: - - '10388' - Content-Type: + - '145' + Host: + - europe-1.nuclia.cloud + User-Agent: + - nucliadb-sdk/6.13.1.post6414 + content-type: - application/json + x-stf-serviceaccount: + - DUMMY + method: POST + uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/predict/run-agents-text + response: + body: + string: '{"results":[{"input_nuclia_tokens":0.0,"output_nuclia_tokens":0.0,"time":0.00010657310485839844,"payloads":[]}]}' + headers: + Alt-Svc: + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 + Content-Length: + - '112' + access-control-expose-headers: + - X-NUCLIA-TRACE-ID + content-type: + - application/json + date: + - Wed, 15 Jul 2026 08:11:05 GMT + via: + - 1.1 google + x-envoy-upstream-service-time: + - '77' + x-nuclia-trace-id: + - b6014ac30500dc75acb7511c85029cca + status: + code: 200 + message: OK +- request: + body: '{"query": "Esboniwch sut i ddefnyddio''r paramedr `max_tokens` a darparwch + ddolen i''r ddogfennaeth swyddogol.", "filters": [], "show": ["basic", "origin", + "extra", "extracted", "values", "relations"], "extracted": ["text", "metadata", + "file", "link"], "security": {"groups": []}, "features": ["keyword"], "reranker": + "noop", "keyword_filters": ["max_tokens", "par\u00e1metro"]}' + headers: + Accept: + - '*/*' + Accept-Encoding: + - gzip, deflate + Connection: + - keep-alive + Content-Length: + - '347' Host: - - europe-1.dp.progress.cloud + - europe-1.nuclia.cloud User-Agent: - - nuclia.py/4.11.5 - x-stf-nuakey: + - nucliadb-sdk/6.13.1.post6414 + content-type: + - application/json + x-stf-serviceaccount: - DUMMY method: POST - uri: https://europe-1.dp.progress.cloud/api/v1/predict/rerank + uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find response: body: - string: '{"context_scores":{"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340":0.5153226852416992,"9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412":0.5087576508522034,"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011":0.16411417722702026,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221":0.14128142595291138,"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977":0.09859886020421982,"43004f553e534ffe9c9e735856bd9b23/t/page/212-480":0.08787643909454346,"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043":0.08108211308717728,"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575":0.07463503628969193,"43004f553e534ffe9c9e735856bd9b23/t/page/480-703":0.04084571450948715,"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757":0.020844316110014915,"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833":0.017442485317587852,"24ad6997e1fe4a109d67d7802a083678/a/title/0-55":0.0034970103297382593,"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349":0.0031480707693845034,"4194605cdfbd414f8fa762630d555bc1/t/page/0-358":0.002822832902893424,"6e8250e6b5264156988657a221fd5e94/t/page/0-397":0.0026316740550100803,"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696":0.0023688741493970156,"44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668":0.0017821963410824537,"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224":0.0016356753185391426,"8b3e0ef630a346d1b591143309db87ec/t/page/0-281":0.001560889184474945,"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299":0.0010608151787891984}}' + string: '{"resources":{},"relations":{"entities":{}},"query":"Esboniwch sut + i ddefnyddio''r paramedr `max_tokens` a darparwch ddolen i''r ddogfennaeth + swyddogol.","rephrased_query":null,"total":0,"page_number":0,"page_size":20,"next_page":false,"shards":["306cbabb-72a5-417c-827f-7874e205c858"],"min_score":{"semantic":0.0,"bm25":0.0},"best_matches":[]}' headers: Alt-Svc: - h3=":443"; ma=2592000 Content-Length: - - '1436' + - '342' access-control-expose-headers: - X-NUCLIA-TRACE-ID content-type: - application/json date: - - Wed, 05 Aug 2026 08:09:44 GMT - nuclia-learning-model: - - bge-reranker-v2-m3 + - Wed, 15 Jul 2026 08:11:07 GMT via: - 1.1 google x-envoy-upstream-service-time: - - '155' + - '18' x-nuclia-trace-id: - - 490d79e7ba3417a95ff3cf0b74409013 + - c9e82256f6716efce37aba8dca5f700f status: code: 200 message: OK - request: - body: '{"question": "", "retrieval": true, "user_id": "rao_answer_summary-ask", - "system": null, "chat_history": [], "context": [], "query_context": {}, "query_context_order": - {}, "truncate": true, "user_prompt": {"prompt": "\nBased on the provided context - and user question, perform the following tasks:\n\n1. Select only information - directly relevant to the question.\n2. Break down compound sentences into simple, - single-idea statements. Preserve original phrasing when possible.\n3. For any - named entity with descriptive details, separate those details into distinct - propositions.\n4. Ensure clarity by replacing pronouns (e.g., \"it\", \"he\", - \"she\", \"they\", \"this\", \"that\") with the full names of the entities they - reference, and add necessary modifiers to clarify meaning.\n5. The context may - be delimited by tags such as and . Treat - everything between these tags as context.\n6. Assess whether the context sufficiently - answers the question. If it answers it partially, provide the answer; if it - does not answer it fully, specify what information is missing to answer the - question.\n7. If the context does not answer the question at all, just return - the original question as the missing information.\n8. The `citations` field - consists ONLY in a list of block IDs that are relevant to the answer, following - these rules:\n - Use the format: block-AB\n - Just mention the block IDs, - do NOT include any other text.\n - Just mention the blocks actually relevant - and that contain information used in the answer, do NOT include blocks that - are not relevant.\n - No duplicates.\n9. Do NOT hallucinate block IDs. Only - use those provided in the context.\n10. Your output must be a JSON object with - the following fields:\n - \"reason\": Explain your reasoning for the answer - or validation.\n - \"answer\": Provide a partial or complete answer to the - user query strictly from the information in the context. If there isn''t enough - information to even provide a partial answer, leave ''answer'' empty.\n - - \"missing_info_query\": If the context is insufficient, specify what information - is missing in a query shape; otherwise, leave it empty. Just return the query - needed to retrieve the missing information.\n - \"useful\": Indicate if the - context is useful to answer the question (\"yes\" or \"no\").\n - \"citations\": - List the IDs of the blocks relevant to the answer, if any (e.g., [\"block-AB\", - \"block-CD\"]).\n11. **IMPORTANT** If any extra instructions are provided, you - MUST follow them carefully when generating the answer field. These instructions - may specify the format, style, tools to use, or other requirements for the answer.\n\n\nExplica - c\u00f3mo usar el par\u00e1metro `max_tokens` en espa\u00f1ol y proporciona - un enlace a la documentaci\u00f3n oficial.\n\n\n\nContext:\n\n**block-AA**\n\n#### - Chunk: 4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\nTags: /k/text\n``` Use - the max_tokens parameter on the /ask endpoint to set hard limits on: \n - Context - size: Limits the amount of retrieved information sent to the LLM \n - Answer - length: Limits the length of the generated response \n Important Considerations - \n Context Limitations: \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/consumption\n - ```\n\n\n---\"\n\n\n**block-AB**\n\n#### Chunk: 9f7036a7a6694700b72d52eb58a8326c/t/page/5203-5412\nTags: - /k/text\n``` max_tokens: the maximum number of input tokens to put in the final - context (including the prompt, the retrieved results and the user question). - \n max_output_tokens: the maximum number of tokens to generate. \n\n\n\nLink: - https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\n ```\n\n\n---\"\n\n\n**block-AC**\n\n#### - Chunk: e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\nTags: /k/text\n``` \n - optional max_tokens: number \\| object \n \n Defines the maximum number of tokens - that the model will take as context. \n Defined in \n libs/sdk-core/src/lib/db/search/search.models.ts:112 - \n \n min_score? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\n - ```\n\n\n---\"\n\n\n**block-AD**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\nTags: - /k/text\n``` \n optional max_tokens: number \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:251 - \n \n prefer_markdown? \n \n optional prefer_markdown: boolean \n \n Defined - in \n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \n \n query_context? - \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n - ```\n\n\n---\"\n\n\n**block-AE**\n\n#### Chunk: 50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\nTags: - /k/text\n``` \n optional generative_model: string \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:250 - \n \n json_schema? \n \n optional json_schema: object \n \n Defined in \n libs/sdk-core/src/lib/db/search/ask.models.ts:257 - \n \n max_tokens? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\n - ```\n\n\n---\"\n\n\n**block-AF**\n\n#### Chunk: 43004f553e534ffe9c9e735856bd9b23/t/page/212-480\nTags: - /k/text\n``` \n optional driver: string \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 - \n \n input_tokens \n \n input_tokens: object \n \n max \n \n max: number \n - \n min? \n \n optional min: number \n \n Defined in \n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 - \n \n max_images? \n\n\n\nLink: https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\n - ```\n\n\n---\"\n\n\n**block-AG**\n\n#### Chunk: 89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\nTags: - /k/text\n``` Description: The maximum number of tokens that the model can generate - as output. Again, we should keep in mind that this value summed to the Maximum - supported input tokens should not exceed the total context size supported by - the model. \n\n\n\nLink: https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n - ```\n\n\n---\"\n\n\n**block-AH**\n\n#### Chunk: 89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\nTags: - /k/text\n``` \n \n Maximum supported input tokens: \n Description: The maximum - number of tokens that the model can accept as input. Be mindful that this takes - into account the tokens used in the prompt, query and context. Also take note - that some models may provide their context window as the total between input - and output tokens, while others may provide it as the input tokens only. \n\n\n\nLink: - https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\n - ```\n\n\n---\"\n\n\n\n\n\n\n"}, "citations": false, "citation_threshold": - null, "generative_model": "chatgpt-azure-4o-mini", "max_tokens": 8192, "query_context_images": - {}, "prefer_markdown": null, "json_schema": {"title": "validate_or_answer", - "description": "Validate or answer", "parameters": {"type": "object", "properties": - {"reason": {"type": "string", "description": "Reasoning for the answer or validation"}, - "answer": {"type": "string", "description": "Partial or complete answer to the - user query from the information in the context."}, "missing_info_query": {"type": - "string", "description": "Query needed to retrieve the missing information in - case the context is not enough to answer the question. If the context does not - answer the question at all, just return the original question."}, "useful": - {"type": "string", "description": "Is the context useful to answer the question?", - "enum": ["yes", "no"]}, "citations": {"type": "array", "items": {"type": "string", - "description": "Block ID cited in the answer, e.g. block-AB"}, "description": - "List of block IDs cited in the answer, if any"}}, "required": ["reason", "answer", - "missing_info_query", "useful", "citations"]}}, "format_prompt": false, "rerank_context": - false, "tools": [], "tool_choice": {"type": "required"}, "reasoning": false, - "seed": null}' + body: '{"query": "Explica el uso del par\u00e1metro `max_tokens` y enlaza a la + documentaci\u00f3n oficial.", "filters": [], "min_score": {"semantic": 0.4}, + "show": ["basic", "origin", "extra", "extracted", "values", "relations"], "extracted": + ["text", "metadata", "file", "link"], "vectorset": "multilingual-2024-05-06", + "security": {"groups": []}, "features": ["semantic"], "reranker": "noop"}' headers: Accept: - - application/x-ndjson + - '*/*' Accept-Encoding: - gzip, deflate Connection: - keep-alive Content-Length: - - '7839' - Content-Type: + - '352' + Host: + - europe-1.nuclia.cloud + User-Agent: + - nucliadb-sdk/6.13.1.post6414 + content-type: + - application/json + x-stf-serviceaccount: + - DUMMY + method: POST + uri: https://europe-1.nuclia.cloud/api/v1/kb/df8b4c24-2807-4888-ad6c-ae97357a638b/find + response: + body: + string: "{\"resources\":{\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs + > rag > advanced > consumption.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-10-03T08:32:26.341394\",\"modified\":\"2026-06-09T08:18:16.730959\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + consumption\\ntitle: Token consumption\\n---\\n\\nimport Tabs from \\\"@theme/Tabs\\\";\\nimport + TabItem from \\\"@theme/TabItem\\\";\\n\\n# Token consumption\\n\\nAgentic + RAG is a license and consumption-based service. This means that you pay for + the computational resources you consume. The consumption is measured in **Agentic + RAG tokens**.\\nAll public 3rd-party LLMs base their pricing on the number + of tokens consumed. In the LLM world, a token is around 4-5 characters on + average, which might fit an entire word or be split into parts. The number + of tokens is proportional to the amount of text, measured in chunks of 4-5 + characters. It closely relates to words but not entirely. The longer a sentence + is, the more tokens it will consume to read or to generate it.\\nSince all + these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize + the cost across all of them.\\n\\n## How Tokens Are Consumed in RAG\\n\\nWhen + a user asks a question to your Knowledge Box, the token consumption process + follows these steps:\\n\\n1. **Question Processing**: The system finds the + most relevant paragraphs to answer the question\\n2. **Context Assembly**: + These paragraphs are used as context when calling the LLM model\\n3. **Prompt + Creation**: Agentic RAG assembles the **prompt**, **context**, and **question** + into a single string\\n4. **LLM Processing**: This complete string is sent + to the LLM, corresponding to a certain number of **input tokens**\\n5. **Answer + Generation**: The LLM generates the answer, which corresponds to a certain + number of **output tokens**\\n\\n**Total consumption** = Input tokens + Output + tokens + Image tokens\\n\\n### Factors That Impact Token Consumption\\n\\nToken + consumption is directly affected by:\\n\\n- **Large context**: Results from + using RAG strategies like \\\"Full resource\\\" or \\\"Neighbouring paragraphs\\\", + or from using the `extra_context` parameter\\n- **Long questions**: More detailed + or complex questions require more input tokens\\n- **Long prompts**: Extensive + system prompts increase the input token count\\n- **Detailed answers**: Comprehensive + responses require more output tokens\\n- **Images in context**: When using + multimodal models, images included in the retrieved context significantly + increase token consumption\\n\\n## How to Limit and Control Token Consumption\\n\\n### + Strategy 1: Optimize Your Parameters\\n\\nThe first approach to reducing token + consumption is to fine-tune your request parameters:\\n\\n- **Optimize prompts**: + Ensure your prompts are concise and focused, avoiding unnecessary verbosity\\n- + **Control resource scope**: When using the \\\"Full resource\\\" strategy, + use the `count` attribute to limit the number of resources returned\\n- **Tune + neighboring context**: For the \\\"Neighbouring paragraphs\\\" strategy, optimize + the `before` and `after` attributes to balance context quality with token + efficiency\\n- **Manage summary length**: When using the \\\"Hierarchical\\\" + strategy, ensure that resource summaries are appropriately sized\\n- **Choose + efficient models**: Select LLMs that offer better token efficiency (typically, + ChatGPT 4o-mini is more cost-effective than ChatGPT 4o)\\n\\n### Strategy + 2: Set Hard Limits\\n\\nYou can implement safeguards against excessive token + consumption:\\n\\nUse the `max_tokens` parameter on the [`/ask` endpoint](/docs/api#tag/Search/operation/ask_knowledgebox_endpoint_kb__kbid__ask_post) + to set hard limits on:\\n- **Context size**: Limits the amount of retrieved + information sent to the LLM\\n- **Answer length**: Limits the length of the + generated response\\n\\n#### Important Considerations\\n\\n**Context Limitations**:\\n- + Restricting context size may result in less relevant answers since the LLM + has less information to work with\\n- Balance between cost control and answer + quality\\n\\n**Answer Length Limitations**:\\n- The LLM might not complete + its response if it hits the token limit, potentially cutting sentences mid-way\\n- + **Recommended approach**: Include length requirements in your prompt (e.g., + \\\"Please answer in less than 200 words\\\") rather than relying solely on + hard limits\\n- This allows the LLM to naturally conclude its response within + the desired length\\n\\n## How to Monitor Token Consumption\\n\\n### Understanding + Token Consumption Data\\n\\nYou can receive detailed token consumption information + from the following endpoints that utilize LLM models: `ask`, `chat`, `remi`, + `query`, `sentence`, `summarize`, `tokens`, and `rerank`.\\n\\n:::note\\nThe + `rephrase` endpoint currently does not support token consumption monitoring.\\n:::\\n\\nTo + receive token consumption data, you must include the following header in your + request:\\n```\\nX-SHOW-CONSUMPTION: true\\n```\\n\\nThe token consumption + data is provided in different formats depending on the response type:\\n- + **Streaming responses** (`application/x-ndjson`): Token consumption appears + as a separate JSON chunk with type \\\"consumption\\\"\\n- **Standard responses** + (`application/json`): Token consumption is included in a \\\"consumption\\\" + field within the main response\\n\\n### Token Consumption Response Format\\n\\n\\n \\n ```json\\n {\\n \\\"item\\\": + {\\n \\\"type\\\": \\\"consumption\\\",\\n \\\"normalized_tokens\\\": + {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": + 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": + 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n + \ }\\n }\\n ```\\n \\n \\n ```json\\n {\\n \\\"consumption\\\": {\\n \\\"normalized_tokens\\\": + {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": + 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": + 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n + \ }\\n }\\n ```\\n \\n\\n\\n### Understanding + Token Types\\n\\n**Normalized Tokens** (`normalized_tokens`):\\n- These represent + the number of Agentic RAG tokens consumed and that you will be billed for\\n- + Values are normalized across different LLM providers for consistent billing\\n- + Include separate counts for:\\n - `input`: Tokens used for the prompt, context, + and question\\n - `output`: Tokens used for the generated response\\n - + `image`: Tokens used for image processing (when applicable)\\n\\n**Customer + Key Tokens** (`customer_key_tokens`):\\n- These represent tokens consumed + when using your own LLM API keys\\n- These tokens are **not billed** by Agentic + RAG since you're using your own API keys\\n- Values are also normalized for + comparison purposes across different providers\\n\",\"format\":\"MARKDOWN\",\"md5\":\"204fe47dbd7eb38d465d05fa7538e51e\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: consumption \\n title: Token consumption \\n \\n import Tabs from + @theme/Tabs ; \\n import TabItem from @theme/TabItem ; \\n Token consumption + \\n Agentic RAG is a license and consumption-based service. This means that + you pay for the computational resources you consume. The consumption is measured + in Agentic RAG tokens. \\n All public 3rd-party LLMs base their pricing on + the number of tokens consumed. In the LLM world, a token is around 4-5 characters + on average, which might fit an entire word or be split into parts. The number + of tokens is proportional to the amount of text, measured in chunks of 4-5 + characters. It closely relates to words but not entirely. The longer a sentence + is, the more tokens it will consume to read or to generate it. \\n Since all + these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize + the cost across all of them. \\n How Tokens Are Consumed in RAG \\n When a + user asks a question to your Knowledge Box, the token consumption process + follows these steps: \\n \\n Question Processing: The system finds the most + relevant paragraphs to answer the question \\n Context Assembly: These paragraphs + are used as context when calling the LLM model \\n Prompt Creation: Agentic + RAG assembles the prompt, context, and question into a single string \\n LLM + Processing: This complete string is sent to the LLM, corresponding to a certain + number of input tokens \\n Answer Generation: The LLM generates the answer, + which corresponds to a certain number of output tokens \\n \\n Total consumption + = Input tokens + Output tokens + Image tokens \\n Factors That Impact Token + Consumption \\n Token consumption is directly affected by: \\n \\n Large context: + Results from using RAG strategies like Full resource or Neighbouring paragraphs + , or from using the extra_context parameter \\n Long questions: More detailed + or complex questions require more input tokens \\n Long prompts: Extensive + system prompts increase the input token count \\n Detailed answers: Comprehensive + responses require more output tokens \\n Images in context: When using multimodal + models, images included in the retrieved context significantly increase token + consumption \\n \\n How to Limit and Control Token Consumption \\n Strategy + 1: Optimize Your Parameters \\n The first approach to reducing token consumption + is to fine-tune your request parameters: \\n \\n Optimize prompts: Ensure + your prompts are concise and focused, avoiding unnecessary verbosity \\n Control + resource scope: When using the Full resource strategy, use the count attribute + to limit the number of resources returned \\n Tune neighboring context: For + the Neighbouring paragraphs strategy, optimize the before and after attributes + to balance context quality with token efficiency \\n Manage summary length: + When using the Hierarchical strategy, ensure that resource summaries are appropriately + sized \\n Choose efficient models: Select LLMs that offer better token efficiency + (typically, ChatGPT 4o-mini is more cost-effective than ChatGPT 4o) \\n \\n + Strategy 2: Set Hard Limits \\n You can implement safeguards against excessive + token consumption: \\n Use the max_tokens parameter on the /ask endpoint to + set hard limits on: \\n - Context size: Limits the amount of retrieved information + sent to the LLM \\n - Answer length: Limits the length of the generated response + \\n Important Considerations \\n Context Limitations: \\n - Restricting context + size may result in less relevant answers since the LLM has less information + to work with \\n - Balance between cost control and answer quality \\n Answer + Length Limitations: \\n - The LLM might not complete its response if it hits + the token limit, potentially cutting sentences mid-way \\n - Recommended approach: + Include length requirements in your prompt (e.g., Please answer in less than + 200 words ) rather than relying solely on hard limits \\n - This allows the + LLM to naturally conclude its response within the desired length \\n How to + Monitor Token Consumption \\n Understanding Token Consumption Data \\n You + can receive detailed token consumption information from the following endpoints + that utilize LLM models: ask, chat, remi, query, sentence, summarize, tokens, + and rerank. \\n :::note \\n The rephrase endpoint currently does not support + token consumption monitoring. \\n ::: \\n To receive token consumption data, + you must include the following header in your request: \\n X-SHOW-CONSUMPTION: + true \\n The token consumption data is provided in different formats depending + on the response type: \\n - Streaming responses (application/x-ndjson): Token + consumption appears as a separate JSON chunk with type consumption \\n - Standard + responses (application/json): Token consumption is included in a consumption + field within the main response \\n Token Consumption Response Format \\n \\n + \\n json \\n { \\n item : { \\n type : consumption , \\n normalized_tokens + : { \\n input : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens + : { \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n + \\n \\n json \\n { \\n consumption : { \\n normalized_tokens : { \\n input + : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens : { + \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n \\n + \\n Understanding Token Types \\n Normalized Tokens (normalized_tokens): \\n + - These represent the number of Agentic RAG tokens consumed and that you will + be billed for \\n - Values are normalized across different LLM providers for + consistent billing \\n - Include separate counts for: \\n - input: Tokens + used for the prompt, context, and question \\n - output: Tokens used for the + generated response \\n - image: Tokens used for image processing (when applicable) + \\n Customer Key Tokens (customer_key_tokens): \\n - These represent tokens + consumed when using your own LLM API keys \\n - These tokens are not billed + by Agentic RAG since you're using your own API keys \\n - Values are also + normalized for comparison purposes across different providers\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":319,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":3,\"end\":198,\"key\":\"\"},{\"start\":198,\"end\":267,\"key\":\"\"},{\"start\":267,\"end\":319,\"key\":\"\"}]},{\"start\":319,\"end\":747,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":320,\"end\":399,\"key\":\"\"},{\"start\":399,\"end\":517,\"key\":\"\"},{\"start\":517,\"end\":615,\"key\":\"\"},{\"start\":615,\"end\":661,\"key\":\"\"},{\"start\":661,\"end\":747,\"key\":\"\"}]},{\"start\":747,\"end\":1008,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":748,\"end\":872,\"key\":\"\"},{\"start\":872,\"end\":1008,\"key\":\"\"}]},{\"start\":1008,\"end\":1650,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1011,\"end\":1650,\"key\":\"\"}]},{\"start\":1650,\"end\":2326,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1653,\"end\":2326,\"key\":\"\"}]},{\"start\":2326,\"end\":3075,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2329,\"end\":3075,\"key\":\"\"}]},{\"start\":3075,\"end\":3340,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":3076,\"end\":3340,\"key\":\"\"}]},{\"start\":3340,\"end\":4136,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":3341,\"end\":4136,\"key\":\"\"}]},{\"start\":4136,\"end\":4446,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":4137,\"end\":4228,\"key\":\"\"},{\"start\":4228,\"end\":4446,\"key\":\"\"}]},{\"start\":4446,\"end\":4728,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":4447,\"end\":4728,\"key\":\"\"}]},{\"start\":4728,\"end\":4932,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":4729,\"end\":4932,\"key\":\"\"}]},{\"start\":4932,\"end\":5189,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":4933,\"end\":5189,\"key\":\"\"}]},{\"start\":5189,\"end\":5396,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":5190,\"end\":5396,\"key\":\"\"}]},{\"start\":5396,\"end\":5615,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":5397,\"end\":5615,\"key\":\"\"}]},{\"start\":5615,\"end\":5849,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":5616,\"end\":5849,\"key\":\"\"}]}],\"ner\":{\"LLM\":\"ORG\",\"json\":\"PERSON\",\"Knowledge + Box\":\"PRODUCT\",\"Agentic RAG\":\"PRODUCT\"},\"entities\":{\"processor\":{\"entities\":[{\"text\":\"Agentic + RAG\",\"label\":\"PRODUCT\",\"positions\":[{\"start\":298,\"end\":309},{\"start\":5222,\"end\":5233},{\"start\":5718,\"end\":5729}]},{\"text\":\"LLM\",\"label\":\"ORG\",\"positions\":[{\"start\":406,\"end\":409},{\"start\":4058,\"end\":4061},{\"start\":5325,\"end\":5328}]},{\"text\":\"Knowledge + Box\",\"label\":\"PRODUCT\",\"positions\":[{\"start\":941,\"end\":954}]},{\"text\":\"json\",\"label\":\"PERSON\",\"positions\":[{\"start\":4729,\"end\":4733}]}]}},\"classifications\":[],\"last_index\":\"2026-06-09T08:18:26.967788Z\",\"last_understanding\":\"2026-06-09T08:18:26.517989Z\",\"last_extract\":\"2026-06-09T08:18:20.828386Z\",\"last_processing_start\":\"2026-06-09T08:18:20.761441Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{\"PRODUCT/Knowledge + Box\":{\"position\":[{\"start\":941,\"end\":954}],\"entity\":\"Knowledge Box\"},\"PRODUCT/Agentic + RAG\":{\"position\":[{\"start\":298,\"end\":309},{\"start\":5222,\"end\":5233},{\"start\":5718,\"end\":5729}],\"entity\":\"Agentic + RAG\"},\"PERSON/json\":{\"position\":[{\"start\":4729,\"end\":4733}],\"entity\":\"json\"},\"ORG/LLM\":{\"position\":[{\"start\":406,\"end\":409},{\"start\":4058,\"end\":4061},{\"start\":5325,\"end\":5328}],\"entity\":\"LLM\"}},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > rag > advanced > consumption.\",\"extracted\":{\"text\":{\"text\":\"docs + > rag > advanced > consumption.\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\":{\"score\":0.6558797359466553,\"score_type\":\"VECTOR\",\"order\":2,\"text\":\" + Use the max_tokens parameter on the /ask endpoint to set hard limits on: \\n + - Context size: Limits the amount of retrieved information sent to the LLM + \\n - Answer length: Limits the length of the generated response \\n Important + Considerations \\n Context Limitations: \\n\",\"id\":\"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":6,\"start\":3075,\"end\":3340,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"50aac6f34b6d47de8e3b01f8b2de6e9c\":{\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c\",\"slug\":\"docs-develop-js-sdk-interfaces-PredictAnswerOptions-md\",\"title\":\"docs + > develop > js sdk > interfaces > PredictAnswerOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:11.443619\",\"modified\":\"2026-07-14T12:50:46.385594\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / PredictAnswerOptions\\n\\n# + Interface: PredictAnswerOptions\\n\\n## Properties\\n\\n### chat\\\\_history?\\n\\n> + `optional` **chat\\\\_history**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:242](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L242)\\n\\n***\\n\\n### + citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L249)\\n\\n***\\n\\n### + citations?\\n\\n> `optional` **citations**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L248)\\n\\n***\\n\\n### + context?\\n\\n> `optional` **context**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:243](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L243)\\n\\n***\\n\\n### + format\\\\_prompt?\\n\\n> `optional` **format\\\\_prompt**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:258](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L258)\\n\\n***\\n\\n### + generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L250)\\n\\n***\\n\\n### + json\\\\_schema?\\n\\n> `optional` **json\\\\_schema**: `object`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:257](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L257)\\n\\n***\\n\\n### + max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L251)\\n\\n***\\n\\n### + prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:256](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L256)\\n\\n***\\n\\n### + query\\\\_context?\\n\\n> `optional` **query\\\\_context**: `string`[] \\\\| + `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:244](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L244)\\n\\n***\\n\\n### + query\\\\_context\\\\_images?\\n\\n> `optional` **query\\\\_context\\\\_images**: + `object`\\n\\n#### b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> + **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:252](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L252)\\n\\n***\\n\\n### + query\\\\_context\\\\_order?\\n\\n> `optional` **query\\\\_context\\\\_order**: + `object`\\n\\n#### Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:245](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L245)\\n\\n***\\n\\n### + reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:260](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L260)\\n\\n***\\n\\n### + rerank\\\\_context?\\n\\n> `optional` **rerank\\\\_context**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:259](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L259)\\n\\n***\\n\\n### + retrieval?\\n\\n> `optional` **retrieval**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:240](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L240)\\n\\n***\\n\\n### + system?\\n\\n> `optional` **system**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:241](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L241)\\n\\n***\\n\\n### + truncate?\\n\\n> `optional` **truncate**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L246)\\n\\n***\\n\\n### + user\\\\_prompt?\\n\\n> `optional` **user\\\\_prompt**: `object`\\n\\n#### + prompt\\n\\n> **prompt**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"470be50f3c6aeeff5ae3310ed007b9b3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / PredictAnswerOptions \\n Interface: PredictAnswerOptions + \\n Properties \\n chat_history? \\n \\n optional chat_history: ContextEntry[] + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:242 \\n + \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:249 \\n \\n citations? + \\n \\n optional citations: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:248 + \\n \\n context? \\n \\n optional context: ContextEntry[] \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:243 \\n \\n format_prompt? + \\n \\n optional format_prompt: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:258 + \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 \\n \\n json_schema? + \\n \\n optional json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 + \\n \\n max_tokens? \\n \\n optional max_tokens: number \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 \\n \\n prefer_markdown? + \\n \\n optional prefer_markdown: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 + \\n \\n query_context? \\n \\n optional query_context: string[] \\\\| object + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:244 \\n + \\n query_context_images? \\n \\n optional query_context_images: object \\n + \\n b64encoded \\n \\n b64encoded: string \\n \\n content_type \\n \\n content_type: + string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:252 + \\n \\n query_context_order? \\n \\n optional query_context_order: object + \\n \\n Index Signature \\n [key: string]: number \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:245 + \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:260 \\n \\n rerank_context? + \\n \\n optional rerank_context: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:259 + \\n \\n retrieval? \\n \\n optional retrieval: boolean \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/ask.models.ts:240 \\n \\n system? \\n + \\n optional system: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:241 + \\n \\n truncate? \\n \\n optional truncate: boolean \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/search/ask.models.ts:246 \\n \\n user_prompt? \\n + \\n optional user_prompt: object \\n \\n prompt \\n \\n prompt: string \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:247\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":257,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":127,\"key\":\"\"},{\"start\":127,\"end\":257,\"key\":\"\"}]},{\"start\":257,\"end\":491,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":260,\"end\":382,\"key\":\"\"},{\"start\":382,\"end\":491,\"key\":\"\"}]},{\"start\":491,\"end\":739,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":494,\"end\":617,\"key\":\"\"},{\"start\":617,\"end\":739,\"key\":\"\"}]},{\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":742,\"end\":864,\"key\":\"\"},{\"start\":864,\"end\":977,\"key\":\"\"}]},{\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":980,\"end\":1100,\"key\":\"\"},{\"start\":1100,\"end\":1221,\"key\":\"\"}]},{\"start\":1221,\"end\":1575,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1224,\"end\":1364,\"key\":\"\"},{\"start\":1364,\"end\":1575,\"key\":\"\"}]},{\"start\":1575,\"end\":1866,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1578,\"end\":1743,\"key\":\"\"},{\"start\":1743,\"end\":1866,\"key\":\"\"}]},{\"start\":1866,\"end\":2096,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1869,\"end\":1988,\"key\":\"\"},{\"start\":1988,\"end\":2096,\"key\":\"\"}]},{\"start\":2096,\"end\":2320,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2099,\"end\":2208,\"key\":\"\"},{\"start\":2208,\"end\":2320,\"key\":\"\"}]},{\"start\":2320,\"end\":2449,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2323,\"end\":2449,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:49.024021Z\",\"last_understanding\":\"2026-07-14T12:50:48.461687Z\",\"last_extract\":\"2026-07-14T12:50:47.086918Z\",\"last_processing_start\":\"2026-07-14T12:50:47.048628Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > PredictAnswerOptions\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > PredictAnswerOptions\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\":{\"score\":0.6482165455818176,\"score_type\":\"VECTOR\",\"order\":3,\"text\":\" + \\n optional max_tokens: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \\n \\n query_context? + \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":4,\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\":{\"score\":0.5993967652320862,\"score_type\":\"VECTOR\",\"order\":12,\"text\":\" + \\n optional generative_model: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 + \\n \\n json_schema? \\n \\n optional json_schema: object \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 \\n \\n max_tokens? + \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":3,\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"8b3e0ef630a346d1b591143309db87ec\":{\"id\":\"8b3e0ef630a346d1b591143309db87ec\",\"slug\":\"docs-develop-js-sdk-interfaces-NucliaTokensMetric-md\",\"title\":\"docs + > develop > js sdk > interfaces > NucliaTokensMetric\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"la\",\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:48:48.423622\",\"modified\":\"2026-07-14T12:51:37.835367\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/NucliaTokensMetric\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / NucliaTokensMetric\\n\\n# + Interface: NucliaTokensMetric\\n\\n## Extends\\n\\n- [`UsageMetric`](UsageMetric.md)\\n\\n## + Properties\\n\\n### details\\n\\n> **details**: [`NucliaTokensDetails`](NucliaTokensDetails.md)[]\\n\\n#### + Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`details`](UsageMetric.md#details)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:185](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L185)\\n\\n***\\n\\n### + name\\n\\n> **name**: `\\\"nuclia_tokens\\\"`\\n\\n#### Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`name`](UsageMetric.md#name)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:183](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L183)\\n\\n***\\n\\n### + value\\n\\n> **value**: `number`\\n\\n#### Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`value`](UsageMetric.md#value)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:184](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L184)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"af7b6aa34935b09fa5ddc2badd6da04f\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / NucliaTokensMetric \\n Interface: NucliaTokensMetric + \\n Extends \\n \\n UsageMetric \\n \\n Properties \\n details \\n \\n details: + NucliaTokensDetails[] \\n \\n Overrides \\n UsageMetric.details \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n name \\n \\n name: + nuclia_tokens \\n \\n Overrides \\n UsageMetric.name \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:183 + \\n \\n value \\n \\n value: number \\n \\n Overrides \\n UsageMetric.value + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[\"UsageMetric.name\"],\"paragraphs\":[{\"start\":0,\"end\":281,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":281,\"key\":\"\"}]},{\"start\":281,\"end\":511,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":282,\"end\":511,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:39.809701Z\",\"last_understanding\":\"2026-07-14T12:51:39.578340Z\",\"last_extract\":\"2026-07-14T12:51:39.320533Z\",\"last_processing_start\":\"2026-07-14T12:51:39.300652Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > NucliaTokensMetric\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > NucliaTokensMetric\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"8b3e0ef630a346d1b591143309db87ec/t/page/0-281\":{\"score\":0.5960935354232788,\"score_type\":\"VECTOR\",\"order\":13,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / NucliaTokensMetric \\n Interface: NucliaTokensMetric + \\n Extends \\n \\n UsageMetric \\n \\n Properties \\n details \\n \\n details: + NucliaTokensDetails[] \\n \\n Overrides \\n UsageMetric.details \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n name \\n \\n\",\"id\":\"8b3e0ef630a346d1b591143309db87ec/t/page/0-281\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":281,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"42a4cd5a30314e94aa079ed0cfe81381\":{\"id\":\"42a4cd5a30314e94aa079ed0cfe81381\",\"slug\":\"docs-develop-js-sdk-interfaces-SplitStrategy-md\",\"title\":\"docs + > develop > js sdk > interfaces > SplitStrategy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:02:38.468609\",\"modified\":\"2026-07-14T12:51:02.450318\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/SplitStrategy\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / SplitStrategy\\n\\n# + Interface: SplitStrategy\\n\\n## Properties\\n\\n### custom\\\\_split?\\n\\n> + `optional` **custom\\\\_split**: [`CustomSplitStrategy`](../enumerations/CustomSplitStrategy.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:537](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L537)\\n\\n***\\n\\n### + llm\\\\_split?\\n\\n> `optional` **llm\\\\_split**: [`SplitLLMConfig`](SplitLLMConfig.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:538](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L538)\\n\\n***\\n\\n### + manual\\\\_split?\\n\\n> `optional` **manual\\\\_split**: `object`\\n\\n#### + splitter\\n\\n> **splitter**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:539](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L539)\\n\\n***\\n\\n### + max\\\\_paragraph?\\n\\n> `optional` **max\\\\_paragraph**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:536](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L536)\\n\\n***\\n\\n### + name?\\n\\n> `optional` **name**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:535](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L535)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"d24d884112df2f67b327ac6d6302ddf1\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / SplitStrategy \\n Interface: SplitStrategy + \\n Properties \\n custom_split? \\n \\n optional custom_split: CustomSplitStrategy + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:537 \\n \\n + llm_split? \\n \\n optional llm_split: SplitLLMConfig \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/kb/kb.models.ts:538 \\n \\n manual_split? \\n \\n + optional manual_split: object \\n \\n splitter \\n \\n splitter: string \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:539 \\n \\n max_paragraph? + \\n \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 + \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":234,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":113,\"key\":\"\"},{\"start\":113,\"end\":234,\"key\":\"\"}]},{\"start\":234,\"end\":502,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":237,\"end\":356,\"key\":\"\"},{\"start\":356,\"end\":502,\"key\":\"\"}]},{\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":505,\"end\":612,\"key\":\"\"},{\"start\":612,\"end\":696,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:04.701538Z\",\"last_understanding\":\"2026-07-14T12:51:04.225754Z\",\"last_extract\":\"2026-07-14T12:51:03.819024Z\",\"last_processing_start\":\"2026-07-14T12:51:03.798124Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > SplitStrategy\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > SplitStrategy\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\":{\"score\":0.5957005620002747,\"score_type\":\"VECTOR\",\"order\":15,\"text\":\" + \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 + \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"id\":\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":2,\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"6e8250e6b5264156988657a221fd5e94\":{\"id\":\"6e8250e6b5264156988657a221fd5e94\",\"slug\":\"docs-develop-js-sdk-namespaces-Ask-interfaces-ConsumptionAskResponseItem-md\",\"title\":\"docs + > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:47:37.548412\",\"modified\":\"2026-07-14T12:48:09.327828\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/namespaces/Ask/interfaces/ConsumptionAskResponseItem\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../../../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../../../globals.md) / [Ask](../README.md) + / ConsumptionAskResponseItem\\n\\n# Interface: ConsumptionAskResponseItem\\n\\n## + Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> **customer\\\\_key\\\\_tokens**: + [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L127)\\n\\n***\\n\\n### + normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L126)\\n\\n***\\n\\n### + type\\n\\n> **type**: `\\\"consumption\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:125](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L125)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"3d72cf5a8634c4719acbe4304e79b48d\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: + ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n + customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 + \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n + type \\n \\n type: consumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:125\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":397,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":397,\"key\":\"\"}]},{\"start\":397,\"end\":483,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":398,\"end\":483,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:48:23.234967Z\",\"last_understanding\":\"2026-07-14T12:48:22.068785Z\",\"last_extract\":\"2026-07-14T12:48:21.777104Z\",\"last_processing_start\":\"2026-07-14T12:48:21.755089Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > namespaces > Ask > interfaces > ConsumptionAskResponseItem\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\":{\"score\":0.599697470664978,\"score_type\":\"VECTOR\",\"order\":11,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Ask / ConsumptionAskResponseItem \\n Interface: + ConsumptionAskResponseItem \\n Properties \\n customer_key_tokens \\n \\n + customer_key_tokens: TokenConsumption \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:127 + \\n \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:126 \\n \\n + type \\n \\n\",\"id\":\"6e8250e6b5264156988657a221fd5e94/t/page/0-397\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":397,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-07-14T12:49:58.922592\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ModelConfig\\n\\n# + Interface: ModelConfig\\n\\n## Properties\\n\\n### assume\\\\_role?\\n\\n> + `optional` **assume\\\\_role**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:592](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L592)\\n\\n***\\n\\n### + driver?\\n\\n> `optional` **driver**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:590](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L590)\\n\\n***\\n\\n### + input\\\\_tokens\\n\\n> **input\\\\_tokens**: `object`\\n\\n#### max\\n\\n> + **max**: `number`\\n\\n#### min?\\n\\n> `optional` **min**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:587](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L587)\\n\\n***\\n\\n### + max\\\\_images?\\n\\n> `optional` **max\\\\_images**: `string`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:591](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L591)\\n\\n***\\n\\n### + output\\\\_tokens\\n\\n> **output\\\\_tokens**: `object`\\n\\n#### default\\\\_max?\\n\\n> + `optional` **default\\\\_max**: `number`\\n\\n#### max\\n\\n> **max**: `number`\\n\\n#### + min?\\n\\n> `optional` **min**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:588](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L588)\\n\\n***\\n\\n### + prompt\\\\_id?\\n\\n> `optional` **prompt\\\\_id**: `string`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:589](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L589)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"0ce41cb0494bcb99176527165e321fec\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ModelConfig \\n Interface: ModelConfig + \\n Properties \\n assume_role? \\n \\n optional assume_role: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:592 \\n \\n driver? + \\n \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 + \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: + number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \\n \\n max_images? \\n \\n optional max_images: string \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \\n \\n output_tokens \\n + \\n output_tokens: object \\n \\n default_max? \\n \\n optional default_max: + number \\n \\n max \\n \\n max: number \\n \\n min? \\n \\n optional min: + number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:588 + \\n \\n prompt_id? \\n \\n optional prompt_id: string \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/kb/kb.models.ts:589\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":212,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":108,\"key\":\"\"},{\"start\":108,\"end\":212,\"key\":\"\"}]},{\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":215,\"end\":380,\"key\":\"\"},{\"start\":380,\"end\":480,\"key\":\"\"}]},{\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":483,\"end\":638,\"key\":\"\"},{\"start\":638,\"end\":703,\"key\":\"\"}]},{\"start\":703,\"end\":895,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":704,\"end\":806,\"key\":\"\"},{\"start\":806,\"end\":895,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:01.191702Z\",\"last_understanding\":\"2026-07-14T12:50:00.962823Z\",\"last_extract\":\"2026-07-14T12:50:00.418522Z\",\"last_processing_start\":\"2026-07-14T12:50:00.364723Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > ModelConfig\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > ModelConfig\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\":{\"score\":0.6202770471572876,\"score_type\":\"VECTOR\",\"order\":6,\"text\":\" + \\n optional max_images: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 + \\n \\n output_tokens \\n \\n output_tokens: object \\n \\n default_max? \\n + \\n optional default_max: number \\n \\n max \\n \\n max: number \\n \\n min? + \\n \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":2,\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\":{\"score\":0.594592273235321,\"score_type\":\"VECTOR\",\"order\":16,\"text\":\" + \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 + \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: + number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \\n \\n max_images? \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":1,\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0d01e250360a4d6c91f3baf2de5e7d38\":{\"id\":\"0d01e250360a4d6c91f3baf2de5e7d38\",\"slug\":\"docs-develop-js-sdk-interfaces-ReasoningConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ReasoningConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-24T11:15:01.495997\",\"modified\":\"2026-07-14T12:49:30.245034\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ReasoningConfig\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ReasoningConfig\\n\\n# + Interface: ReasoningConfig\\n\\n## Properties\\n\\n### budget\\\\_tokens?\\n\\n> + `optional` **budget\\\\_tokens**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:647](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L647)\\n\\n***\\n\\n### + effort?\\n\\n> `optional` **effort**: [`NumericReasoningEffort`](../enumerations/NumericReasoningEffort.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:648](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L648)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"940c8be17c938dcc14e4abb000b0f8b5\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ReasoningConfig \\n Interface: ReasoningConfig + \\n Properties \\n budget_tokens? \\n \\n optional budget_tokens: number \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 \\n \\n effort? + \\n \\n optional effort: NumericReasoningEffort \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:648\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":224,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":118,\"key\":\"\"},{\"start\":118,\"end\":224,\"key\":\"\"}]},{\"start\":224,\"end\":329,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":227,\"end\":329,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:49:31.596307Z\",\"last_understanding\":\"2026-07-14T12:49:31.194629Z\",\"last_extract\":\"2026-07-14T12:49:31.030734Z\",\"last_processing_start\":\"2026-07-14T12:49:30.980505Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > ReasoningConfig\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > ReasoningConfig\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224\":{\"score\":0.6052000522613525,\"score_type\":\"VECTOR\",\"order\":9,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ReasoningConfig \\n Interface: ReasoningConfig + \\n Properties \\n budget_tokens? \\n \\n optional budget_tokens: number \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 \\n \\n effort? + \\n\",\"id\":\"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":224,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"44d05174f1954331b62f5e4026f2b01a\":{\"id\":\"44d05174f1954331b62f5e4026f2b01a\",\"slug\":\"docs-develop-python-sdk-14-rao-md\",\"title\":\"docs + > develop > python sdk > 14 rao\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-22T13:38:09.919472\",\"modified\":\"2026-06-09T08:08:04.176136\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/python-sdk/rao\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"# + Retrieval Agents Orchestrator\\n\\nInteract with Nuclia's Retrieval Agents + Orchestrator to have intelligent conversations over several knowledge sources + with persistent session management and real-time streaming responses.\\n\\n## + Prerequisites\\n\\nInstall the Nuclia SDK:\\n\\n```sh\\npip install nuclia\\n```\\n\\nEnsure + you have:\\n- A valid Nuclia authentication token (see [Authentication](02-auth.md))\\n- + Access to a configured Retrieval Agent\\n\\n## Overview\\n\\nThe nuclia.py + library provides several ways to interact with your Retrieval Agents Orchestrators:\\n\\n- + **Interactive CLI**: A rich, user-friendly terminal interface (recommended)\\n- + **Standard CLI**: Direct access to raw websocket messages for debugging\\n- + **Session Management**: Create and manage persistent conversation sessions\\n- + **Programmatic API**: Python SDK for building custom applications\\n\\n\\n## + Listing Available Agents\\n\\nDiscover what Retrieval Agents Orchestrators + you have access to.\\n\\n- CLI:\\n\\n ```sh\\n nuclia agents list\\n ```\\n\\n- + SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n + \ agents = NucliaAgents()\\n all_agents = agents.list()\\n\\n for agent + in all_agents:\\n print(f\\\"Agent: {agent.title} ({agent.id})\\\")\\n + \ print(f\\\" Slug: {agent.slug}\\\")\\n print(f\\\" Zone: {agent.zone}\\\")\\n + \ ```\\n\\n### Getting a Specific Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia + agents get --account=\\\"my-account\\\" --id=\\\"agent-uuid\\\" --zone=\\\"europe-1\\\"\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n + \ agents = NucliaAgents()\\n agent_details = agents.get(\\n account=\\\"my-account\\\",\\n + \ id=\\\"agent-uuid\\\",\\n zone=\\\"europe-1\\\"\\n )\\n print(agent_details)\\n + \ ```\\n\\n### Setting a Default Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia + agents default [AGENT_SLUG or AGENT_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n + \ from nuclia.sdk.agents import NucliaAgents\\n\\n agents = NucliaAgents()\\n + \ agents.default(\\\"my-agent\\\")\\n ```\\n\\nThis sets the default agent + for all subsequent operations.\\n\\n## Interactive CLI (Recommended)\\n\\nThe + interactive CLI provides a beautiful, real-time interface for conversing with + your Retrieval Agents Orchestrator.\\n\\n### Starting the Interactive CLI\\n\\n- + CLI:\\n\\n ```sh\\n nuclia agent cli interact\\n ```\\n\\n- SDK:\\n\\n + \ ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n + \ agent.cli.interact()\\n ```\\n\\nThis launches an interactive terminal + session where you can:\\n- Ask questions and see streaming responses\\n- View + processing steps in real-time\\n- Manage conversation sessions\\n- See retrieved + context and citations\\n\\n### Interactive CLI Commands\\n\\nThe CLI supports + several commands (prefix with `/`):\\n\\n| Command | Description |\\n|---------|-------------|\\n| + `/help` | Show available commands |\\n| `/new_session` | Create a new persistent + session |\\n| `/list_sessions` | List all your sessions |\\n| `/change_session` + | Switch to a different session, use 'ephemeral' for a temporary session |\\n| + `/clear` | Clear the screen |\\n| `/exit` | Exit the CLI |\\n\\nPlease note + that all commands related to sessions require a Retrieval Agent Orchestrator + with the option **Agent with memory** enabled during creation.\\n\\n## Session + Management\\n\\nSessions allow you to maintain conversation context across + multiple interactions.\\n\\n> This feature will only be available if you checked + **Agent with memory** during the creation of your Retrieval Agents Orchestrator.\\n\\n### + Creating a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent session new --name=\\\"My + Research Session\\\"\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent + import NucliaAgent\\n\\n agent = NucliaAgent()\\n session_uuid = agent.session.new(\\\"My + Research Session\\\")\\n print(f\\\"Created session: {session_uuid}\\\")\\n + \ ```\\n\\n### Listing Sessions\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent + session list\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent + import NucliaAgent\\n\\n agent = NucliaAgent()\\n sessions = agent.session.list()\\n + \ for session in sessions.resources:\\n print(f\\\"{session.title}: {session.id}\\\")\\n + \ ```\\n\\n### Getting a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent + session get --session_uuid=[SESSION_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n + \ from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n + \ session = agent.session.get(session_uuid)\\n print(f\\\"Session: {session.title}\\\")\\n + \ print(f\\\"Created: {session.created}\\\")\\n ```\\n\\n### Deleting a Session\\n\\n- + CLI:\\n\\n ```sh\\n nuclia agent session delete --session_uuid=[SESSION_UUID]\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n + \ agent = NucliaAgent()\\n agent.session.delete(session_uuid)\\n ```\\n\\n## + Interaction\\n\\nAside from the interactive CLI, you can interact with your + Retrieval Agents Orchestrator with the simple CLI or programmatically using + the SDK.\\n\\n### Basic Interaction\\n\\n\\n**CLI:**\\n```bash\\nnuclia agent + interact \\\"What is Eric known for?\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate + over streaming responses\\nfor response in agent.interact(\\n question=\\\"What + is Eric known for?\\\"\\n):\\n if response.operation == \\\"ANSWER\\\" + and response.answer:\\n print(response.answer)\\n elif response.step:\\n + \ print(f\\\"Processing: {response.step.module}\\\")\\n```\\n\\nNot + supplying a `session_uuid` when calling `interact` will use an ephemeral session + by default. To maintain context, provide a persistent session UUID.\\n\\n### + Using Persistent Sessions\\n\\n**CLI:**\\n```bash\\nnuclia agent sessions + new \\\"Customer Support Chat\\\"\\n# Note the session UUID returned\\nnuclia + agent interact \\\"What are your business hours?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\nnuclia + agent interact \\\"Are you open on weekends?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Create + a session\\nsession_uuid = agent.session.new(\\\"Customer Support Chat\\\")\\n\\n# + Have a conversation with context\\nfor response in agent.interact(\\n session_uuid=session_uuid,\\n + \ question=\\\"What are your business hours?\\\"\\n):\\n if response.answer:\\n + \ print(response.answer)\\n\\n# Follow-up question maintains context\\nfor + response in agent.interact(\\n session_uuid=session_uuid,\\n question=\\\"Are + you open on weekends?\\\"\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\n## + Understanding Response Types\\n\\nWhen interacting with an agent, you receive + a stream of `AragAnswer` objects with different operations:\\n\\n| Operation + | Description |\\n|-----------|-------------|\\n| `START` | Interaction has + begun |\\n| `ANSWER` | Processing step or partial answer |\\n| `DONE` | Interaction + complete |\\n| `ERROR` | An error occurred |\\n| `AGENT_REQUEST` | Agent needs + user feedback |\\n\\n### Response Attributes\\n\\nEach response may contain:\\n\\n- + **`step`**: Information about the current processing step\\n - `module`: + The module being executed (e.g., \\\"rephrase\\\", \\\"basic_ask\\\", \\\"remi\\\")\\n + \ - `title`: Display title for the step\\n - `value`: Result of the step\\n + \ - `reason`: Explanation for the step\\n - `timeit`: Time taken in seconds\\n + \ - `input_nuclia_tokens`/`output_nuclia_tokens`: Token usage\\n\\n- **`context`**: + Retrieved context from the knowledge base\\n - `chunks`: List of retrieved + text chunks with sources\\n - `summary`: Summary of the context or partial + answer\\n\\n- **`answer`**: The final answer text (Markdown formatted)\\n\\n- + **`generated_text`**: Intermediate generated text\\n\\n- **`possible_answer`**: + Alternative answer being considered\\n\\n- **`exception`**: Error details + if something went wrong\\n\\n### Processing Responses\\n\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\nfrom nuclia_models.agent.interaction + import AnswerOperation\\n\\nagent = NucliaAgent()\\n\\nfor response in agent.interact(question=\\\"Tell + me about AI\\\"):\\n if response.operation == AnswerOperation.START:\\n + \ print(\\\"Starting...\\\")\\n \\n elif response.step:\\n print(f\\\"Step: + {response.step.module} ({response.step.timeit:.2f}s)\\\")\\n \\n elif + response.context:\\n print(f\\\"Retrieved {len(response.context.chunks)} + chunks\\\")\\n for chunk in response.context.chunks:\\n print(f\\\" + \ - {chunk.title}: {chunk.text[:100]}...\\\")\\n \\n elif response.answer:\\n + \ print(f\\\"\\\\nFinal Answer:\\\\n{response.answer}\\\")\\n \\n + \ elif response.operation == AnswerOperation.DONE:\\n print(\\\"Complete!\\\")\\n + \ \\n elif response.operation == AnswerOperation.ERROR:\\n print(f\\\"Error: + {response.exception.detail if response.exception else 'Unknown'}\\\")\\n```\\n\\n## + Standard CLI for Raw Messages\\n\\nFor debugging or advanced use cases, you + can access raw websocket messages programmatically:\\n\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate + over all messages\\nfor message in agent.interact(\\n question=\\\"What + is RAO?\\\"\\n):\\n # message is an AragAnswer object with all raw data\\n + \ print(f\\\"Operation: {message.operation}\\\")\\n print(f\\\"Raw message: + {message.model_dump_json(indent=2)}\\\")\\n```\\n\\nThis gives you direct + access to all websocket message data for debugging or custom processing.\\n\\n## + Advanced Features\\n\\n### Agent Feedback Requests\\n\\nAgents can request + additional input from users during processing:\\n\\n```python\\nfrom nuclia.sdk.agent + import NucliaAgent\\nfrom nuclia_models.agent.interaction import AnswerOperation\\n\\nagent + = NucliaAgent()\\ngenerator = agent.interact(question=\\\"Help me with X\\\")\\n\\nfor + response in generator:\\n if response.operation == AnswerOperation.AGENT_REQUEST:\\n + \ # Agent is requesting user input\\n user_input = input(f\\\"Agent + asks: {response.feedback.question}\\\\n> \\\")\\n # Send response back\\n + \ generator.send(user_input)\\n elif response.answer:\\n print(response.answer)\\n```\\n\\n### + Error Handling\\n\\n```python\\nfrom nuclia.sdk.agent import NucliaAgent\\nfrom + nuclia.exceptions import RaoAPIException\\n\\nagent = NucliaAgent()\\n\\ntry:\\n + \ for response in agent.interact(question=\\\"Hello?\\\"):\\n if + response.exception:\\n print(f\\\"Agent error: {response.exception.detail}\\\")\\n + \ elif response.answer:\\n print(response.answer)\\nexcept + RaoAPIException as e:\\n print(f\\\"API error: {e.detail}\\\")\\nexcept + Exception as e:\\n print(f\\\"Unexpected error: {e}\\\")\\n```\\n\\n### + Passing Custom Headers to MCP\\n\\nIf your Retrieval Agents Orchestrator requires + custom headers for MCP Agents, you can pass them as follows:\\n\\n**CLI:**\\n```bash\\nnuclia + agent interact \\\"What is AI?\\\" --headers '{\\\"X-Custom-Header\\\": \\\"value\\\"}'\\n```\\n\\n**SDK:**\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\nfor response + in agent.interact(\\n question=\\\"What is AI?\\\",\\n headers={\\\"X-Custom-Header\\\": + \\\"value\\\"}\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\nPlease + ensure that the 'Allowed Headers' configuration in your MCP agent includes + any custom headers you wish to use.\\n\\n## Best Practices\\n\\n1. **Use Sessions + for Context**: Create sessions when you need multi-turn conversations with + context retention\\n2. **Use Ephemeral Sessions for One-offs**: Don't supply + a session UUID for using agents in a stateless manner.\\n3. **Stream for UX**: + Process responses as they arrive for better user experience\\n4. **Handle + All Operations**: Check for different operation types (START, ANSWER, DONE, + ERROR) when processing responses\\n5. **Clean Up Sessions**: Delete sessions + when done to avoid clutter\\n6. **Use Interactive CLI**: For manual testing + and exploration, the interactive CLI provides the best experience\\n\",\"format\":\"MARKDOWN\",\"md5\":\"bbaaf8cccd2b664ba4f7daf47d1f2bf4\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"Retrieval + Agents Orchestrator \\n Interact with Nuclia's Retrieval Agents Orchestrator + to have intelligent conversations over several knowledge sources with persistent + session management and real-time streaming responses. \\n Prerequisites \\n + Install the Nuclia SDK: \\n sh \\n pip install nuclia \\n Ensure you have: + \\n - A valid Nuclia authentication token (see Authentication) \\n - Access + to a configured Retrieval Agent \\n Overview \\n The nuclia.py library provides + several ways to interact with your Retrieval Agents Orchestrators: \\n \\n + Interactive CLI: A rich, user-friendly terminal interface (recommended) \\n + Standard CLI: Direct access to raw websocket messages for debugging \\n Session + Management: Create and manage persistent conversation sessions \\n Programmatic + API: Python SDK for building custom applications \\n \\n Listing Available + Agents \\n Discover what Retrieval Agents Orchestrators you have access to. + \\n \\n CLI: \\n \\n sh \\n nuclia agents list \\n \\n SDK: \\n \\n ```python + \\n from nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() + \\n all_agents = agents.list() \\n for agent in all_agents: \\n print(f Agent: + {agent.title} ({agent.id}) ) \\n print(f Slug: {agent.slug} ) \\n print(f + Zone: {agent.zone} ) \\n ``` \\n Getting a Specific Agent \\n \\n CLI: \\n + \\n sh \\n nuclia agents get --account= my-account --id= agent-uuid --zone= + europe-1 \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agents import + NucliaAgents \\n agents = NucliaAgents() \\n agent_details = agents.get( \\n + account= my-account , \\n id= agent-uuid , \\n zone= europe-1 \\n ) \\n print(agent_details) + \\n ``` \\n Setting a Default Agent \\n \\n CLI: \\n \\n sh \\n nuclia agents + default [AGENT_SLUG or AGENT_UUID] \\n \\n SDK: \\n \\n ```python \\n from + nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() \\n agents.default( + my-agent ) \\n ``` \\n This sets the default agent for all subsequent operations. + \\n Interactive CLI (Recommended) \\n The interactive CLI provides a beautiful, + real-time interface for conversing with your Retrieval Agents Orchestrator. + \\n Starting the Interactive CLI \\n \\n CLI: \\n \\n sh \\n nuclia agent + cli interact \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import + NucliaAgent \\n agent = NucliaAgent() \\n agent.cli.interact() \\n ``` \\n + This launches an interactive terminal session where you can: \\n - Ask questions + and see streaming responses \\n - View processing steps in real-time \\n - + Manage conversation sessions \\n - See retrieved context and citations \\n + Interactive CLI Commands \\n The CLI supports several commands (prefix with + /): \\n | Command | Description | \\n |---------|-------------| \\n | /help + | Show available commands | \\n | /new_session | Create a new persistent session + | \\n | /list_sessions | List all your sessions | \\n | /change_session | + Switch to a different session, use 'ephemeral' for a temporary session | \\n + | /clear | Clear the screen | \\n | /exit | Exit the CLI | \\n Please note + that all commands related to sessions require a Retrieval Agent Orchestrator + with the option Agent with memory enabled during creation. \\n Session Management + \\n Sessions allow you to maintain conversation context across multiple interactions. + \\n \\n This feature will only be available if you checked Agent with memory + during the creation of your Retrieval Agents Orchestrator. \\n \\n Creating + a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session new --name= My + Research Session \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent + import NucliaAgent \\n agent = NucliaAgent() \\n session_uuid = agent.session.new( + My Research Session ) \\n print(f Created session: {session_uuid} ) \\n ``` + \\n Listing Sessions \\n \\n CLI: \\n \\n sh \\n nuclia agent session list + \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import NucliaAgent + \\n agent = NucliaAgent() \\n sessions = agent.session.list() \\n for session + in sessions.resources: \\n print(f {session.title}: {session.id} ) \\n ``` + \\n Getting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session get + --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent + import NucliaAgent \\n agent = NucliaAgent() \\n session = agent.session.get(session_uuid) + \\n print(f Session: {session.title} ) \\n print(f Created: {session.created} + ) \\n ``` \\n Deleting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent + session delete --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python + \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n + agent.session.delete(session_uuid) \\n ``` \\n Interaction \\n Aside from + the interactive CLI, you can interact with your Retrieval Agents Orchestrator + with the simple CLI or programmatically using the SDK. \\n Basic Interaction + \\n CLI: \\n bash \\n nuclia agent interact What is Eric known for? \\n SDK: + \\n ```python \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() + \\n Iterate over streaming responses \\n for response in agent.interact( \\n + question= What is Eric known for? \\n ): \\n if response.operation == ANSWER + and response.answer: \\n print(response.answer) \\n elif response.step: \\n + print(f Processing: {response.step.module} ) \\n ``` \\n Not supplying a session_uuid + when calling interact will use an ephemeral session by default. To maintain + context, provide a persistent session UUID. \\n Using Persistent Sessions + \\n CLI: \\n ```bash \\n nuclia agent sessions new Customer Support Chat \\n + Note the session UUID returned \\n nuclia agent interact What are your business + hours? --session_uuid= SESSION_UUID \\n nuclia agent interact Are you open + on weekends? --session_uuid= SESSION_UUID \\n ``` \\n SDK: \\n ```python \\n + from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n Create + a session \\n session_uuid = agent.session.new( Customer Support Chat ) \\n + Have a conversation with context \\n for response in agent.interact( \\n session_uuid=session_uuid, + \\n question= What are your business hours? \\n ): \\n if response.answer: + \\n print(response.answer) \\n Follow-up question maintains context \\n for + response in agent.interact( \\n session_uuid=session_uuid, \\n question= Are + you open on weekends? \\n ): \\n if response.answer: \\n print(response.answer) + \\n ``` \\n Understanding Response Types \\n When interacting with an agent, + you receive a stream of AragAnswer objects with different operations: \\n + | Operation | Description | \\n |-----------|-------------| \\n | START | + Interaction has begun | \\n | ANSWER | Processing step or partial answer | + \\n | DONE | Interaction complete | \\n | ERROR | An error occurred | \\n + | AGENT_REQUEST | Agent needs user feedback | \\n Response Attributes \\n + Each response may contain: \\n \\n step: Information about the current processing + step \\n module: The module being executed (e.g., rephrase , basic_ask , remi + ) \\n title: Display title for the step \\n value: Result of the step \\n + reason: Explanation for the step \\n timeit: Time taken in seconds \\n \\n + input_nuclia_tokens/output_nuclia_tokens: Token usage \\n \\n \\n context: + Retrieved context from the knowledge base \\n \\n chunks: List of retrieved + text chunks with sources \\n \\n summary: Summary of the context or partial + answer \\n \\n \\n answer: The final answer text (Markdown formatted) \\n + \\n \\n generated_text: Intermediate generated text \\n \\n \\n possible_answer: + Alternative answer being considered \\n \\n \\n exception: Error details if + something went wrong \\n \\n \\n Processing Responses \\n ```python \\n from + nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction + import AnswerOperation \\n agent = NucliaAgent() \\n for response in agent.interact(question= + Tell me about AI ): \\n if response.operation == AnswerOperation.START: \\n + print( Starting... ) \\n elif response.step: \\n print(f Step: {response.step.module} + ({response.step.timeit:.2f}s) ) \\n \\n elif response.context: \\n print(f + Retrieved {len(response.context.chunks)} chunks ) \\n for chunk in response.context.chunks: + \\n print(f - {chunk.title}: {chunk.text[:100]}... ) \\n \\n elif response.answer: + \\n print(f \\\\nFinal Answer:\\\\n{response.answer} ) \\n \\n elif response.operation + == AnswerOperation.DONE: \\n print( Complete! ) \\n \\n elif response.operation + == AnswerOperation.ERROR: \\n print(f Error: {response.exception.detail if + response.exception else 'Unknown'} ) \\n \\n ``` \\n Standard CLI for Raw + Messages \\n For debugging or advanced use cases, you can access raw websocket + messages programmatically: \\n ```python \\n from nuclia.sdk.agent import + NucliaAgent \\n agent = NucliaAgent() \\n Iterate over all messages \\n for + message in agent.interact( \\n question= What is RAO? \\n ): \\n # message + is an AragAnswer object with all raw data \\n print(f Operation: {message.operation} + ) \\n print(f Raw message: {message.model_dump_json(indent=2)} ) \\n ``` \\n + This gives you direct access to all websocket message data for debugging or + custom processing. \\n Advanced Features \\n Agent Feedback Requests \\n Agents + can request additional input from users during processing: \\n ```python \\n + from nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction + import AnswerOperation \\n agent = NucliaAgent() \\n generator = agent.interact(question= + Help me with X ) \\n for response in generator: \\n if response.operation + == AnswerOperation.AGENT_REQUEST: \\n # Agent is requesting user input \\n + user_input = input(f Agent asks: {response.feedback.question}\\\\n> ) \\n + # Send response back \\n generator.send(user_input) \\n elif response.answer: + \\n print(response.answer) \\n ``` \\n Error Handling \\n ```python \\n from + nuclia.sdk.agent import NucliaAgent \\n from nuclia.exceptions import RaoAPIException + \\n agent = NucliaAgent() \\n try: \\n for response in agent.interact(question= + Hello? ): \\n if response.exception: \\n print(f Agent error: {response.exception.detail} + ) \\n elif response.answer: \\n print(response.answer) \\n except RaoAPIException + as e: \\n print(f API error: {e.detail} ) \\n except Exception as e: \\n print(f + Unexpected error: {e} ) \\n ``` \\n Passing Custom Headers to MCP \\n If your + Retrieval Agents Orchestrator requires custom headers for MCP Agents, you + can pass them as follows: \\n CLI: \\n bash \\n nuclia agent interact What + is AI? --headers '{ X-Custom-Header : value }' \\n SDK: \\n ```python \\n + from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n for + response in agent.interact( \\n question= What is AI? , \\n headers={ X-Custom-Header + : value } \\n ): \\n if response.answer: \\n print(response.answer) \\n ``` + \\n Please ensure that the 'Allowed Headers' configuration in your MCP agent + includes any custom headers you wish to use. \\n Best Practices \\n \\n Use + Sessions for Context: Create sessions when you need multi-turn conversations + with context retention \\n Use Ephemeral Sessions for One-offs: Don't supply + a session UUID for using agents in a stateless manner. \\n Stream for UX: + Process responses as they arrive for better user experience \\n Handle All + Operations: Check for different operation types (START, ANSWER, DONE, ERROR) + when processing responses \\n Clean Up Sessions: Delete sessions when done + to avoid clutter \\n Use Interactive CLI: For manual testing and exploration, + the interactive CLI provides the best experience \\n 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\\n timeit: Time taken in seconds \\n \\n input_nuclia_tokens/output_nuclia_tokens: + Token usage \\n \\n \\n\",\"id\":\"44d05174f1954331b62f5e4026f2b01a/t/page/6346-6668\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":19,\"start\":6346,\"end\":6668,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0a003c3f724e45e392a9c8d1ce8800c1\":{\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1\",\"slug\":\"docs-develop-js-sdk-interfaces-Consumption-md\",\"title\":\"docs + > develop > js sdk > interfaces > Consumption\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:51:46.788864\",\"modified\":\"2026-07-14T12:51:15.300757\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / Consumption\\n\\n# + Interface: Consumption\\n\\n## Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> + **customer\\\\_key\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:230](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L230)\\n\\n***\\n\\n### + normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:229](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L229)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"654b0dfe17ab08959c78891dd24c3424\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption + \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n + \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":349,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:16.563837Z\",\"last_understanding\":\"2026-07-14T12:51:16.208384Z\",\"last_extract\":\"2026-07-14T12:51:15.984803Z\",\"last_processing_start\":\"2026-07-14T12:51:15.966495Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > Consumption\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > Consumption\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\":{\"score\":0.6083368062973022,\"score_type\":\"VECTOR\",\"order\":7,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption + \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n + \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"b14cf452a3434839a04c111f2ea4dc51\":{\"id\":\"b14cf452a3434839a04c111f2ea4dc51\",\"slug\":\"docs-develop-js-sdk-enums-UsageType-md\",\"title\":\"docs + > develop > js sdk > enums > UsageType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"tn\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:41.582110\",\"modified\":\"2026-06-09T08:13:34.112208\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/enums/UsageType\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[@nuclia/core](../README.md) + / [Exports](../modules.md) / UsageType\\n\\n# Enumeration: UsageType\\n\\n## + Table of contents\\n\\n### Enumeration Members\\n\\n- [AI\\\\_TOKENS\\\\_USED](UsageType.md#ai_tokens_used)\\n- + [BYTES\\\\_PROCESSED](UsageType.md#bytes_processed)\\n- [CHARS\\\\_PROCESSED](UsageType.md#chars_processed)\\n- + [MEDIA\\\\_FILES\\\\_PROCESSED](UsageType.md#media_files_processed)\\n- [MEDIA\\\\_SECONDS\\\\_PROCESSED](UsageType.md#media_seconds_processed)\\n- + [NUCLIA\\\\_TOKENS](UsageType.md#nuclia_tokens)\\n- [PAGES\\\\_PROCESSED](UsageType.md#pages_processed)\\n- + [PARAGRAPHS\\\\_PROCESSED](UsageType.md#paragraphs_processed)\\n- [PRE\\\\_PROCESSING\\\\_TIME](UsageType.md#pre_processing_time)\\n- + [RESOURCES\\\\_PROCESSED](UsageType.md#resources_processed)\\n- [SEARCHES\\\\_PERFORMED](UsageType.md#searches_performed)\\n- + [SLOW\\\\_PROCESSING\\\\_TIME](UsageType.md#slow_processing_time)\\n- [SUGGESTIONS\\\\_PERFORMED](UsageType.md#suggestions_performed)\\n- + [TRAIN\\\\_SECONDS](UsageType.md#train_seconds)\\n\\n## Enumeration Members\\n\\n### + AI\\\\_TOKENS\\\\_USED\\n\\n\u2022 **AI\\\\_TOKENS\\\\_USED** = ``\\\"ai_tokens_used\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:190](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L190)\\n\\n___\\n\\n### + BYTES\\\\_PROCESSED\\n\\n\u2022 **BYTES\\\\_PROCESSED** = ``\\\"bytes_processed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:181](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L181)\\n\\n___\\n\\n### + CHARS\\\\_PROCESSED\\n\\n\u2022 **CHARS\\\\_PROCESSED** = ``\\\"chars_processed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:182](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L182)\\n\\n___\\n\\n### + MEDIA\\\\_FILES\\\\_PROCESSED\\n\\n\u2022 **MEDIA\\\\_FILES\\\\_PROCESSED** + = ``\\\"media_files_processed\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:184](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L184)\\n\\n___\\n\\n### + MEDIA\\\\_SECONDS\\\\_PROCESSED\\n\\n\u2022 **MEDIA\\\\_SECONDS\\\\_PROCESSED** + = ``\\\"media_seconds_processed\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:183](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L183)\\n\\n___\\n\\n### + NUCLIA\\\\_TOKENS\\n\\n\u2022 **NUCLIA\\\\_TOKENS** = ``\\\"nuclia_tokens_billed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:191](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L191)\\n\\n___\\n\\n### + PAGES\\\\_PROCESSED\\n\\n\u2022 **PAGES\\\\_PROCESSED** = ``\\\"pages_processed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:185](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L185)\\n\\n___\\n\\n### + PARAGRAPHS\\\\_PROCESSED\\n\\n\u2022 **PARAGRAPHS\\\\_PROCESSED** = ``\\\"paragraphs_processed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:186](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L186)\\n\\n___\\n\\n### + PRE\\\\_PROCESSING\\\\_TIME\\n\\n\u2022 **PRE\\\\_PROCESSING\\\\_TIME** = + ``\\\"pre_processing_time\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:178](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L178)\\n\\n___\\n\\n### + RESOURCES\\\\_PROCESSED\\n\\n\u2022 **RESOURCES\\\\_PROCESSED** = ``\\\"resources_processed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:180](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L180)\\n\\n___\\n\\n### + SEARCHES\\\\_PERFORMED\\n\\n\u2022 **SEARCHES\\\\_PERFORMED** = ``\\\"searches_performed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:188](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L188)\\n\\n___\\n\\n### + SLOW\\\\_PROCESSING\\\\_TIME\\n\\n\u2022 **SLOW\\\\_PROCESSING\\\\_TIME** + = ``\\\"slow_processing_time\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:179](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L179)\\n\\n___\\n\\n### + SUGGESTIONS\\\\_PERFORMED\\n\\n\u2022 **SUGGESTIONS\\\\_PERFORMED** = ``\\\"suggestions_performed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:189](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L189)\\n\\n___\\n\\n### + TRAIN\\\\_SECONDS\\n\\n\u2022 **TRAIN\\\\_SECONDS** = ``\\\"train_seconds\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:187](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L187)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"232462bafe6a7eb30c1df7131403005e\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + / Exports / UsageType \\n Enumeration: UsageType \\n Table of contents \\n + Enumeration Members \\n \\n AI_TOKENS_USED \\n BYTES_PROCESSED \\n CHARS_PROCESSED + \\n MEDIA_FILES_PROCESSED \\n MEDIA_SECONDS_PROCESSED \\n NUCLIA_TOKENS \\n + PAGES_PROCESSED \\n PARAGRAPHS_PROCESSED \\n PRE_PROCESSING_TIME \\n RESOURCES_PROCESSED + \\n SEARCHES_PERFORMED \\n SLOW_PROCESSING_TIME \\n SUGGESTIONS_PERFORMED + \\n TRAIN_SECONDS \\n \\n Enumeration Members \\n AI_TOKENS_USED \\n \u2022 + AI_TOKENS_USED = ai_tokens_used \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:190 + \\n \\n BYTES_PROCESSED \\n \u2022 BYTES_PROCESSED = bytes_processed \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:181 \\n \\n CHARS_PROCESSED \\n + \u2022 CHARS_PROCESSED = chars_processed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:182 + \\n \\n MEDIA_FILES_PROCESSED \\n \u2022 MEDIA_FILES_PROCESSED = media_files_processed + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184 \\n \\n MEDIA_SECONDS_PROCESSED + \\n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \\n Defined in + \\n libs/sdk-core/src/lib/db/db.models.ts:183 \\n \\n NUCLIA_TOKENS \\n \u2022 + NUCLIA_TOKENS = nuclia_tokens_billed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:191 + \\n \\n PAGES_PROCESSED \\n \u2022 PAGES_PROCESSED = pages_processed \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n PARAGRAPHS_PROCESSED + \\n \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:186 \\n \\n PRE_PROCESSING_TIME \\n + \u2022 PRE_PROCESSING_TIME = pre_processing_time \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:178 + \\n \\n RESOURCES_PROCESSED \\n \u2022 RESOURCES_PROCESSED = resources_processed + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:180 \\n \\n SEARCHES_PERFORMED + \\n \u2022 SEARCHES_PERFORMED = searches_performed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:188 + \\n \\n SLOW_PROCESSING_TIME \\n \u2022 SLOW_PROCESSING_TIME = slow_processing_time + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:179 \\n \\n SUGGESTIONS_PERFORMED + \\n \u2022 SUGGESTIONS_PERFORMED = suggestions_performed \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:189 \\n \\n TRAIN_SECONDS \\n \u2022 + TRAIN_SECONDS = train_seconds \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:187\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":2139,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":2139,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-06-09T08:13:38.314222Z\",\"last_understanding\":\"2026-06-09T08:13:35.850668Z\",\"last_extract\":\"2026-06-09T08:13:35.182287Z\",\"last_processing_start\":\"2026-06-09T08:13:35.144379Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > enums > UsageType\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > enums > UsageType\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139\":{\"score\":0.5916038155555725,\"score_type\":\"VECTOR\",\"order\":17,\"text\":\"@nuclia/core + / Exports / UsageType \\n Enumeration: UsageType \\n Table of contents \\n + Enumeration Members \\n \\n AI_TOKENS_USED \\n BYTES_PROCESSED \\n CHARS_PROCESSED + \\n MEDIA_FILES_PROCESSED \\n MEDIA_SECONDS_PROCESSED \\n NUCLIA_TOKENS \\n + PAGES_PROCESSED \\n PARAGRAPHS_PROCESSED \\n PRE_PROCESSING_TIME \\n RESOURCES_PROCESSED + \\n SEARCHES_PERFORMED \\n SLOW_PROCESSING_TIME \\n SUGGESTIONS_PERFORMED + \\n TRAIN_SECONDS \\n \\n Enumeration Members \\n AI_TOKENS_USED \\n \u2022 + AI_TOKENS_USED = ai_tokens_used \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:190 + \\n \\n BYTES_PROCESSED \\n \u2022 BYTES_PROCESSED = bytes_processed \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:181 \\n \\n CHARS_PROCESSED \\n + \u2022 CHARS_PROCESSED = chars_processed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:182 + \\n \\n MEDIA_FILES_PROCESSED \\n \u2022 MEDIA_FILES_PROCESSED = media_files_processed + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184 \\n \\n MEDIA_SECONDS_PROCESSED + \\n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \\n Defined in + \\n libs/sdk-core/src/lib/db/db.models.ts:183 \\n \\n NUCLIA_TOKENS \\n \u2022 + NUCLIA_TOKENS = nuclia_tokens_billed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:191 + \\n \\n PAGES_PROCESSED \\n \u2022 PAGES_PROCESSED = pages_processed \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n PARAGRAPHS_PROCESSED + \\n \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:186 \\n \\n PRE_PROCESSING_TIME \\n + \u2022 PRE_PROCESSING_TIME = pre_processing_time \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:178 + \\n \\n RESOURCES_PROCESSED \\n \u2022 RESOURCES_PROCESSED = resources_processed + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:180 \\n \\n SEARCHES_PERFORMED + \\n \u2022 SEARCHES_PERFORMED = searches_performed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:188 + \\n \\n SLOW_PROCESSING_TIME \\n \u2022 SLOW_PROCESSING_TIME = slow_processing_time + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:179 \\n \\n SUGGESTIONS_PERFORMED + \\n \u2022 SUGGESTIONS_PERFORMED = suggestions_performed \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:189 \\n \\n TRAIN_SECONDS \\n \u2022 + TRAIN_SECONDS = train_seconds \\n Defined in \\n 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PageToken\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:49:28.645864\",\"modified\":\"2026-07-14T12:51:05.803476\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PageToken\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / PageToken\\n\\n# + Interface: PageToken\\n\\n## Properties\\n\\n### height\\n\\n> **height**: + `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L249)\\n\\n***\\n\\n### + line\\n\\n> **line**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L251)\\n\\n***\\n\\n### + text\\n\\n> **text**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L250)\\n\\n***\\n\\n### + width\\n\\n> **width**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L248)\\n\\n***\\n\\n### + x\\n\\n> **x**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L246)\\n\\n***\\n\\n### + y\\n\\n> **y**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"e72ffebe78398e6654aceec2addfd240\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n + Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 + \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 + \\n \\n text \\n \\n text: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:250 + \\n \\n width \\n \\n width: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:248 + \\n \\n x \\n \\n x: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:246 + \\n \\n y \\n \\n y: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:247\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":299,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":299,\"key\":\"\"}]},{\"start\":299,\"end\":592,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":300,\"end\":592,\"key\":\"\"}]},{\"start\":592,\"end\":677,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":593,\"end\":677,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:07.412857Z\",\"last_understanding\":\"2026-07-14T12:51:07.180359Z\",\"last_extract\":\"2026-07-14T12:51:06.857039Z\",\"last_processing_start\":\"2026-07-14T12:51:06.837097Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > PageToken\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > PageToken\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\":{\"score\":0.5957225561141968,\"score_type\":\"VECTOR\",\"order\":14,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n + Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 + \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 + \\n \\n text \\n \\n\",\"id\":\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":299,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"9f7036a7a6694700b72d52eb58a8326c\":{\"id\":\"9f7036a7a6694700b72d52eb58a8326c\",\"slug\":\"docs-rag-advanced-widget-features-md\",\"title\":\"docs + > rag > advanced > widget > features\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2024-07-18T14:32:26.204740\",\"modified\":\"2026-06-09T08:07:51.648767\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/widget/features\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + features\\ntitle: Features\\n---\\n\\n# Widgets features\\n\\nThe Agentic + RAG widgets allows you to embed the Agentic RAG search experience directly + into your website or web application through a simple HTML snippet:\\n\\n```html\\n\\n\\n\\n```\\n\\nThe + easiest way to explore the different features of the widgets is to use the + [Agentic RAG Dashboard](https://rag.progress.cloud/) in the Widgets section + and to play with the different options.\\n\\nThe _Embed widget_ button will + generate the HTML snippet for you.\\n\\n## Widget types\\n\\nThere are 3 different + types of widgets:\\n\\n- **Embedded in page**: the search input is embedded + in a page and the results are displayed under the input. Once the initial + answer is displayed, the user can click on _Ask more_ to access the full chat + interface. Note: For the correct reading of the results, the width of the + widget container should not be less than 384px.\\n\\n Web components:\\n\\n + \ ```html\\n \\n \\n + \ ```\\n\\n- **Chat mode**: displays directly the full chat interface.\\n\\n + \ Web component:\\n\\n ```html\\n \\n ```\\n\\n- + **Popup modal**: the search inout and the results are displayed in a popup + modal.\\n\\n Web component:\\n\\n ```html\\n \\n + \ ```\\n\\n## The `features` parameter\\n\\nThe `features` parameter allows + you to customize the behavior of the widget. It is a comma-separated list + of features among the following:\\n\\n- `filter`: display a filter dropdown + in the search bar.\\n- `navigateToFile`: open the file in the browser when + clicking on the result (by default, the file is displayed in the viewer).\\n- + `navigateToLink`: open the link in the browser when clicking on the result + (by default, the link is displayed in the viewer).\\n- `permalink`: add the + search query and criteria to the URL, allowing the widget to re-render the + same results upon loading.\\n- `relations`: display an info card on the right + side of the widget listing all the relations of the entity mentioned in the + user query.\\n- `suggestions`: display a list of suggested resource titles + matching the user input.\\n- `suggestLabels`: display a list of suggestions + based on the labels when the user starts typing in the search bar.\\n- `autocompleteFromNERs`: + display a list of suggestions based on the NERs extracted from the user query + when the user starts typing in the search bar.\\n- `displayMetadata`: display + the metadata associated with the resource in the result rows.\\n- `answers`: + trigger the answer generation process when the user makes a search.\\n- `hideResults`: + hide the search results, only the generative answer will be displayed.\\n- + `hideThumbnails`: hide the thumbnails associated with the resource in the + result rows.\\n- `displayFieldList`: display a section listing all the fields + of the resource in the right sidebar of the viewer. This section is only visible + for resources containing multiple fields.\\n- `citations`: include citations + in the generative answer.\\n- `rephrase`: rephrase the user question in order + to optimize the quality of the search results.\\n- `debug`: display extra + buttons to download the last request full log of the debug metadata returned + by the API. It must not be used in production.\\n- `preferMarkdown`: require + the generative answer to be formatted in Markdown.\\n- `openNewTab`: open + the link in a new tab when clicking on the result.\\n- `orFilterLogic`: use + the OR logic for filters instead of the default AND logic.\\n- `noChatHistory`: + the previous questions and answers in the chat mode will not be passed as + context when generating a new answer.\\n- `showHidden`: display hidden resources + in the search results.\\n- `showAttachedImages`: display images attached to + the matching paragraphs in the search results.\\n\\n### Other parameters\\n\\n- + `backend`: the URL of the backend to use. Useful if you use your own proxy + to access the Agentic RAG API.\\n- `zone`: the zone to use.\\n- `knowledgebox`: + the Knowledge Box id.\\n- `placeholder`: the text displayed in the search + bar when it is empty.\\n- `lang`: the language of the widget. Currently supported: + `ca`, `fr`, `en`, `es`. Default: `en`.\\n- `apikey`: the API key to use. It + is not recommended to use it in production (the API key is meant to be injected + by your proxy).\\n- `account`: the account id.\\n- `state`: the publication + state of the Knowledge Box.\\n- `standalone`: set to `true` when using a standalone + NucliaDB instance.\\n- `proxy`: set to `true` when using a proxy to access + the Agentic RAG API.\\n- `mode`: set to `dark` to display the widget in dark + mode.\\n- `filters`: define the filters offered to the user in the search + bar among `labels`, `entities`, `created` and `labelFamilies`.\\n- `preselected_filters`: + define filters that will be applied by default to any query.\\n- `csspath`: + the path to the CSS file to use to customize the widget style.\\n- `prompt`: + the prompt to use for the generative model. It must use `{context}` and `{question}` + variables.\\n- `system_prompt`: the system prompt to use for the generative + model.\\n- `rephrase_prompt`: the prompt to use when optimizing the user query + to get the best search results.\\n- `generativemodel`: the generative model + to use for the answer generation.\\n- `rag_strategies`: the RAG strategies + to apply to the retrieved paragraphs.\\n- `rag_images_strategies`: the RAG + strategies to apply to the retrieved images.\\n- `not_enough_data_message`: + the message to display when there is not enough data to generate an answer.\\n- + `ask_to_resource`: the resource ID to use as context for the generative model.\\n- + `max_tokens`: the maximum number of input tokens to put in the final context + (including the prompt, the retrieved results and the user question).\\n- `max_output_tokens`: + the maximum number of tokens to generate.\\n- `max_paragraphs`: the maximum + number of paragraphs to pass in the context to the generative model (default: + 20).\\n- `query_prepend`: the hard-coded text to prepend to the user query.\\n- + `json_schema`: the JSON schema to use to get a JSON answer from the generative + model.\\n- `vectorset`: the embedding model to use for the semantic search.\\n- + `chat_placeholder`: the placeholder to display in the chat input.\\n- `audit_metadata`: + custom metatada to add in API calls for auditing purposes.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"8f3044c65d6a551153cea36353a2cdac\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: features \\n title: Features \\n \\n Widgets features \\n The Agentic + RAG widgets allows you to embed the Agentic RAG search experience directly + into your website or web application through a simple HTML snippet: \\n ```html + \\n \\n \\n \\n ``` \\n The easiest way to explore the different features + of the widgets is to use the Agentic RAG Dashboard in the Widgets section + and to play with the different options. \\n The Embed widget button will generate + the HTML snippet for you. \\n Widget types \\n There are 3 different types + of widgets: \\n \\n Embedded in page: the search input is embedded in a page + and the results are displayed under the input. Once the initial answer is + displayed, the user can click on Ask more to access the full chat interface. + Note: For the correct reading of the results, the width of the widget container + should not be less than 384px. \\n \\n Web components: \\n html \\n \\n \\n + \\n Chat mode: displays directly the full chat interface. \\n \\n Web component: + \\n html \\n \\n \\n Popup modal: the search inout and the results are displayed + in a popup modal. \\n \\n Web component: \\n html \\n \\n The features parameter + \\n The features parameter allows you to customize the behavior of the widget. + It is a comma-separated list of features among the following: \\n \\n filter: + display a filter dropdown in the search bar. \\n navigateToFile: open the + file in the browser when clicking on the result (by default, the file is displayed + in the viewer). \\n navigateToLink: open the link in the browser when clicking + on the result (by default, the link is displayed in the viewer). \\n permalink: + add the search query and criteria to the URL, allowing the widget to re-render + the same results upon loading. \\n relations: display an info card on the + right side of the widget listing all the relations of the entity mentioned + in the user query. \\n suggestions: display a list of suggested resource titles + matching the user input. \\n suggestLabels: display a list of suggestions + based on the labels when the user starts typing in the search bar. \\n autocompleteFromNERs: + display a list of suggestions based on the NERs extracted from the user query + when the user starts typing in the search bar. \\n displayMetadata: display + the metadata associated with the resource in the result rows. \\n answers: + trigger the answer generation process when the user makes a search. \\n hideResults: + hide the search results, only the generative answer will be displayed. \\n + hideThumbnails: hide the thumbnails associated with the resource in the result + rows. \\n displayFieldList: display a section listing all the fields of the + resource in the right sidebar of the viewer. This section is only visible + for resources containing multiple fields. \\n citations: include citations + in the generative answer. \\n rephrase: rephrase the user question in order + to optimize the quality of the search results. \\n debug: display extra buttons + to download the last request full log of the debug metadata returned by the + API. It must not be used in production. \\n preferMarkdown: require the generative + answer to be formatted in Markdown. \\n openNewTab: open the link in a new + tab when clicking on the result. \\n orFilterLogic: use the OR logic for filters + instead of the default AND logic. \\n noChatHistory: the previous questions + and answers in the chat mode will not be passed as context when generating + a new answer. \\n showHidden: display hidden resources in the search results. + \\n showAttachedImages: display images attached to the matching paragraphs + in the search results. \\n \\n Other parameters \\n \\n backend: the URL of + the backend to use. Useful if you use your own proxy to access the Agentic + RAG API. \\n zone: the zone to use. \\n knowledgebox: the Knowledge Box id. + \\n placeholder: the text displayed in the search bar when it is empty. \\n + lang: the language of the widget. Currently supported: ca, fr, en, es. Default: + en. \\n apikey: the API key to use. It is not recommended to use it in production + (the API key is meant to be injected by your proxy). \\n account: the account + id. \\n state: the publication state of the Knowledge Box. \\n standalone: + set to true when using a standalone NucliaDB instance. \\n proxy: set to true + when using a proxy to access the Agentic RAG API. \\n mode: set to dark to + display the widget in dark mode. \\n filters: define the filters offered to + the user in the search bar among labels, entities, created and labelFamilies. + \\n preselected_filters: define filters that will be applied by default to + any query. \\n csspath: the path to the CSS file to use to customize the widget + style. \\n prompt: the prompt to use for the generative model. It must use + {context} and {question} variables. \\n system_prompt: the system prompt to + use for the generative model. \\n rephrase_prompt: the prompt to use when + optimizing the user query to get the best search results. \\n generativemodel: + the generative model to use for the answer generation. \\n rag_strategies: + the RAG strategies to apply to the retrieved paragraphs. \\n rag_images_strategies: + the RAG strategies to apply to the retrieved images. \\n not_enough_data_message: + the message to display when there is not enough data to generate an answer. + \\n ask_to_resource: the resource ID to use as context for the generative + model. \\n max_tokens: the maximum number of input tokens to put in the final + context (including the prompt, the retrieved results and the user question). + \\n max_output_tokens: the maximum number of tokens to generate. \\n max_paragraphs: + the maximum number of paragraphs to pass in the context to the generative + model (default: 20). \\n query_prepend: the hard-coded text to prepend to + the user query. \\n json_schema: the JSON schema to use to get a JSON answer + from the generative model. \\n vectorset: the embedding model to use for the + semantic search. \\n chat_placeholder: the placeholder to display in the chat + input. \\n audit_metadata: custom metatada to add in API calls for auditing + purposes. \\n 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limiting\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:05.339624\",\"modified\":\"2026-06-09T08:18:12.259849\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + rate-limiting\\ntitle: Manage rate limiting\\n---\\n\\n# Manage rate limiting\\n\\nRate + limits are an essential aspect of the Agentic RAG platform, ensuring fair + usage and optimal performance for all users interacting with Agentic RAG APIs. + This document outlines the rate limits enforced by Agentic RAG and provides + guidelines for handling rate-limited responses effectively.\\n\\n## Introduction\\n\\nAgentic + RAG can apply two types of limits to its APIs:\\n\\n- **Regular API rate limits**: + By default, the sum of all authenticated requests in a Agentic RAG account + cannot exceed 2400 requests per minute. Note that this limit can be customized + on a per-account basis. Please contact [Agentic RAG's support team](mailto:support@nuclia.com) + if you need an increase.\\n\\n- **Ingestion back pressure limits**: Agentic + RAG implements a back-pressure mechanism to manage ingestion pipeline overload. + This mainly affects endpoints for uploading data and creating or updating + resources.\\n\\n## Handling Rate-Limited Responses\\n\\nAgentic RAG adheres + to [the HTTP standard](https://datatracker.ietf.org/doc/html/rfc6585#section-4) + and will return a response with a `429` status codes when the limits are exceeded.\\n\\nThe + official Agentic RAG API clients already have built-in mechanisms for retrying + requests when rate limits are encountered:\\n\\n- [Nuclia Python client](/docs/develop/python-sdk/README)\\n- + [Nuclia JavaScript client](/docs/develop/js-sdk/)\\n\\nHowever, if you are + interacting directly with the API, we recommend using an [exponential backoff + retry strategy](https://en.wikipedia.org/wiki/Exponential_backoff) when limits + are reached.\\n\\nWhen ingestion back pressure rate limits are hit, the response + will include a `try_after` key with an estimated UTC time for retrying the + request. You can use this value for retry logic as an alternative to the exponential + backoff strategy.\\n\\n## Example 1: Regular API rate limits\\n\\nHere's an + example of how to implement an exponential backoff retry strategy in Python:\\n\\n```python\\nimport + time\\nimport requests\\n\\ndef make_request_with_exponential_backoff(url, + headers, max_retries=5):\\n retries = 0\\n while retries < max_retries:\\n + \ response = requests.get(url, headers=headers)\\n if response.status_code + == 200:\\n return response.json()\\n elif response.status_code + == 429:\\n wait_time = 2 ** retries # Exponential backoff: 2^retries\\n + \ print(f\\\"Rate limit exceeded. Retrying in {wait_time} seconds...\\\")\\n + \ time.sleep(wait_time)\\n retries += 1\\n else:\\n + \ response.raise_for_status()\\n raise Exception(\\\"Max retries + exceeded\\\")\\n\\n# Example usage\\nurl = \\\"https://your-endpoint\\\"\\nheaders + = {\\\"Authorization\\\": \\\"Bearer YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_exponential_backoff(url, + headers)\\nprint(data)\\n```\\n\\n## Example 2: Ingestion back pressure limits\\n\\nHere's + an example of how to use the try_after key from the response to manage rate + limits:\\n\\n```python\\nimport time\\nfrom datetime import datetime\\n\\nimport + requests\\n\\n\\ndef make_request_with_try_after_info(url, headers, max_retries=5):\\n + \ retries = 0\\n while retries < max_retries:\\n response = requests.get(url, + headers=headers)\\n response_body = response.json()\\n if response.status_code + == 200:\\n return response.json()\\n elif response.status_code + == 429 and \\\"try_after\\\" in response_body:\\n try_after = response_body[\\\"try_after\\\"]\\n + \ retry_time = datetime.strptime(try_after, \\\"%Y-%m-%dT%H:%M:%S.%fZ\\\")\\n + \ wait_time = (retry_time - datetime.utcnow()).total_seconds()\\n + \ print(\\n f\\\"Rate limit exceeded. Retrying at + {retry_time} (in {wait_time} seconds)...\\\"\\n )\\n time.sleep(wait_time)\\n + \ retries += 1\\n else:\\n response.raise_for_status()\\n + \ raise Exception(\\\"Max retries exceeded\\\")\\n\\n\\n# Example usage\\nurl + = \\\"https://your-endpoint\\\"\\nheaders = {\\\"Authorization\\\": \\\"Bearer + YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_try_after_info(url, headers)\\nprint(data)\\n```\\n\\nThese + examples demonstrate how to handle rate limits effectively, ensuring that + your application respects the limits and retries appropriately.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"ed11945857f4618eec7ed0d1b16ffa44\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: rate-limiting \\n title: Manage rate limiting \\n \\n Manage rate + limiting \\n Rate limits are an essential aspect of the Agentic RAG platform, + ensuring fair usage and optimal performance for all users interacting with + Agentic RAG APIs. This document outlines the rate limits enforced by Agentic + RAG and provides guidelines for handling rate-limited responses effectively. + \\n Introduction \\n Agentic RAG can apply two types of limits to its APIs: + \\n \\n \\n Regular API rate limits: By default, the sum of all authenticated + requests in a Agentic RAG account cannot exceed 2400 requests per minute. + Note that this limit can be customized on a per-account basis. Please contact + Agentic RAG's support team if you need an increase. \\n \\n \\n Ingestion + back pressure limits: Agentic RAG implements a back-pressure mechanism to + manage ingestion pipeline overload. This mainly affects endpoints for uploading + data and creating or updating resources. \\n \\n \\n Handling Rate-Limited + Responses \\n Agentic RAG adheres to the HTTP standard and will return a response + with a 429 status codes when the limits are exceeded. \\n The official Agentic + RAG API clients already have built-in mechanisms for retrying requests when + rate limits are encountered: \\n \\n Nuclia Python client \\n Nuclia JavaScript + client \\n \\n However, if you are interacting directly with the API, we recommend + using an exponential backoff retry strategy when limits are reached. \\n When + ingestion back pressure rate limits are hit, the response will include a try_after + key with an estimated UTC time for retrying the request. You can use this + value for retry logic as an alternative to the exponential backoff strategy. + \\n Example 1: Regular API rate limits \\n Here's an example of how to implement + an exponential backoff retry strategy in Python: \\n ```python \\n import + time \\n import requests \\n def make_request_with_exponential_backoff(url, + headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: + \\n response = requests.get(url, headers=headers) \\n if response.status_code + == 200: \\n return response.json() \\n elif response.status_code == 429: \\n + wait_time = 2 retries # Exponential backoff: 2^retries \\n print(f Rate limit + exceeded. Retrying in {wait_time} seconds... ) \\n time.sleep(wait_time) \\n + retries += 1 \\n else: \\n response.raise_for_status() \\n raise Exception( + Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint \\n + headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_exponential_backoff(url, + headers) \\n print(data) \\n ``` \\n Example 2: Ingestion back pressure limits + \\n Here's an example of how to use the try_after key from the response to + manage rate limits: \\n ```python \\n import time \\n from datetime import + datetime \\n import requests \\n def make_request_with_try_after_info(url, + headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: + \\n response = requests.get(url, headers=headers) \\n response_body = response.json() + \\n if response.status_code == 200: \\n return response.json() \\n elif response.status_code + == 429 and try_after in response_body: \\n try_after = response_body[ try_after + ] \\n retry_time = datetime.strptime(try_after, %Y-%m-%dT%H:%M:%S.%fZ ) \\n + wait_time = (retry_time - datetime.utcnow()).total_seconds() \\n print( \\n + f Rate limit exceeded. Retrying at {retry_time} (in {wait_time} seconds)... + \\n ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() + \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint + \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, + headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle + rate limits effectively, ensuring that your application respects the limits + and retries 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+ RAG\"},\"LAW/HTTP\":{\"position\":[{\"start\":998,\"end\":1002}],\"entity\":\"HTTP\"},\"PRODUCT/Max\":{\"position\":[{\"start\":3409,\"end\":3412}],\"entity\":\"Max\"},\"TIME/seconds\":{\"position\":[{\"start\":2199,\"end\":2206}],\"entity\":\"seconds\"},\"PRODUCT/Python\":{\"position\":[{\"start\":1232,\"end\":1238},{\"start\":1773,\"end\":1779}],\"entity\":\"Python\"},\"ORG/Agentic + RAG's\":{\"position\":[{\"start\":668,\"end\":681}],\"entity\":\"Agentic RAG's\"},\"LAW/Handling + Rate-Limited Responses Agentic RAG\":{\"position\":[{\"start\":937,\"end\":982}],\"entity\":\"Handling + Rate-Limited Responses Agentic RAG\"},\"TIME/UTC\":{\"position\":[{\"start\":1526,\"end\":1529}],\"entity\":\"UTC\"},\"PRODUCT/Agentic + RAG API\":{\"position\":[{\"start\":1108,\"end\":1123}],\"entity\":\"Agentic + RAG API\"},\"ORG/Nuclia\":{\"position\":[{\"start\":1225,\"end\":1231},{\"start\":1248,\"end\":1254}],\"entity\":\"Nuclia\"}},\"relations\":[{\"relation\":\"OTHER\",\"label\":\"operating + system\",\"metadata\":{\"paragraph_id\":\"dd41482018924facb5dbb87a7d53f122/t/page/1222-1656\",\"source_start\":1248,\"source_end\":1254,\"to_start\":1232,\"to_end\":1238},\"from\":{\"value\":\"Nuclia\",\"type\":\"entity\",\"group\":\"ORG\"},\"to\":{\"value\":\"Python\",\"type\":\"entity\",\"group\":\"PRODUCT\"}}],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > ingestion > how to > rate limiting\",\"extracted\":{\"text\":{\"text\":\"docs + > ingestion > how to > rate limiting\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\":{\"score\":0.590923011302948,\"score_type\":\"VECTOR\",\"order\":18,\"text\":\" + ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() + \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint + \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, + headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle + rate limits effectively, ensuring that your application respects the limits + and retries appropriately.\",\"id\":\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":9,\"start\":3310,\"end\":3757,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"1b2a9e67b9f14a0cb81efaa05b8793b8\":{\"id\":\"1b2a9e67b9f14a0cb81efaa05b8793b8\",\"slug\":\"docs-develop-js-sdk-interfaces-AugmentedField-md\",\"title\":\"docs + > develop > js sdk > interfaces > AugmentedField\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:00:05.937520\",\"modified\":\"2026-07-14T12:49:32.163110\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/AugmentedField\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / AugmentedField\\n\\n# + Interface: AugmentedField\\n\\n## Properties\\n\\n### applied\\\\_data\\\\_augmentation\\n\\n> + **applied\\\\_data\\\\_augmentation**: [`AppliedDataAugmentation`](AppliedDataAugmentation.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:571](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L571)\\n\\n***\\n\\n### + input\\\\_nuclia\\\\_tokens\\n\\n> **input\\\\_nuclia\\\\_tokens**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:572](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L572)\\n\\n***\\n\\n### + metadata\\n\\n> **metadata**: [`FieldMetadata`](FieldMetadata.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:570](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L570)\\n\\n***\\n\\n### + output\\\\_nuclia\\\\_tokens\\n\\n> **output\\\\_nuclia\\\\_tokens**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:573](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L573)\\n\\n***\\n\\n### + time\\n\\n> **time**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:574](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L574)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"1e8e95b886439059ae4ec717c9bcf283\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / AugmentedField \\n Interface: AugmentedField + \\n Properties \\n applied_data_augmentation \\n \\n applied_data_augmentation: + AppliedDataAugmentation \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:571 + \\n \\n input_nuclia_tokens \\n \\n input_nuclia_tokens: number \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:572 \\n \\n metadata + \\n \\n metadata: FieldMetadata \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:570 + \\n \\n output_nuclia_tokens \\n \\n output_nuclia_tokens: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:573 \\n + \\n time \\n \\n time: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:574\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":641,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":641,\"key\":\"\"}]},{\"start\":641,\"end\":729,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":642,\"end\":729,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:49:33.585675Z\",\"last_understanding\":\"2026-07-14T12:49:33.340252Z\",\"last_extract\":\"2026-07-14T12:49:32.941746Z\",\"last_processing_start\":\"2026-07-14T12:49:32.917812Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > AugmentedField\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > AugmentedField\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"1b2a9e67b9f14a0cb81efaa05b8793b8/t/page/0-641\":{\"score\":0.5881041884422302,\"score_type\":\"VECTOR\",\"order\":19,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / AugmentedField \\n Interface: AugmentedField + \\n Properties \\n applied_data_augmentation \\n \\n applied_data_augmentation: + AppliedDataAugmentation \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:571 + \\n \\n input_nuclia_tokens \\n \\n input_nuclia_tokens: number \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:572 \\n \\n metadata + \\n \\n metadata: FieldMetadata \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:570 + \\n \\n output_nuclia_tokens \\n \\n output_nuclia_tokens: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:573 \\n + \\n time \\n \\n\",\"id\":\"1b2a9e67b9f14a0cb81efaa05b8793b8/t/page/0-641\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":641,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs + > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-07-14T12:51:04.368823\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ChatOptions\\n\\n# + Interface: ChatOptions\\n\\n## Extends\\n\\n- [`BaseSearchOptions`](BaseSearchOptions.md)\\n\\n## + Properties\\n\\n### answer\\\\_json\\\\_schema?\\n\\n> `optional` **answer\\\\_json\\\\_schema**: + `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:114](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L114)\\n\\n***\\n\\n### + audit\\\\_metadata?\\n\\n> `optional` **audit\\\\_metadata**: `object`\\n\\n#### + Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `string`\\n\\n#### Inherited + from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`audit_metadata`](BaseSearchOptions.md#audit_metadata)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:81](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L81)\\n\\n***\\n\\n### + citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:116](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L116)\\n\\n***\\n\\n### + citations?\\n\\n> `optional` **citations**: `boolean` \\\\| `\\\"none\\\"` + \\\\| `\\\"default\\\"` \\\\| `\\\"llm_footnotes\\\"`\\n\\nIt will return + the text blocks that have been effectively used to build each section of the + answer.\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:105](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L105)\\n\\n***\\n\\n### + debug?\\n\\n> `optional` **debug**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`debug`](BaseSearchOptions.md#debug)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:79](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L79)\\n\\n***\\n\\n### + extra\\\\_context?\\n\\n> `optional` **extra\\\\_context**: `string`[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:115](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L115)\\n\\n***\\n\\n### + extra\\\\_context\\\\_images?\\n\\n> `optional` **extra\\\\_context\\\\_images**: + `object`[]\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:118](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L118)\\n\\n***\\n\\n### + ~~extracted?~~\\n\\n> `optional` **extracted**: [`ExtractedDataTypes`](../enumerations/ExtractedDataTypes.md)[]\\n\\n#### + Deprecated\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`extracted`](BaseSearchOptions.md#extracted)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:73](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L73)\\n\\n***\\n\\n### + features?\\n\\n> `optional` **features**: [`Features`](../namespaces/Ask/enumerations/Features.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:117](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L117)\\n\\n***\\n\\n### + field\\\\_type\\\\_filter?\\n\\n> `optional` **field\\\\_type\\\\_filter**: + [`FIELD_TYPE`](../enumerations/FIELD_TYPE.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`field_type_filter`](BaseSearchOptions.md#field_type_filter)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:74](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L74)\\n\\n***\\n\\n### + fields?\\n\\n> `optional` **fields**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`fields`](BaseSearchOptions.md#fields)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:62](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L62)\\n\\n***\\n\\n### + filter\\\\_expression?\\n\\n> `optional` **filter\\\\_expression**: [`FilterExpression`](FilterExpression.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filter_expression`](BaseSearchOptions.md#filter_expression)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:64](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L64)\\n\\n***\\n\\n### + filters?\\n\\n> `optional` **filters**: `string`[] \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filters`](BaseSearchOptions.md#filters)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:63](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L63)\\n\\n***\\n\\n### + generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:108](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L108)\\n\\n***\\n\\n### + highlight?\\n\\n> `optional` **highlight**: `boolean`\\n\\n#### Inherited + from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`highlight`](BaseSearchOptions.md#highlight)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:76](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L76)\\n\\n***\\n\\n### + keyword\\\\_filters?\\n\\n> `optional` **keyword\\\\_filters**: `string`[] + \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`keyword_filters`](BaseSearchOptions.md#keyword_filters)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:65](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L65)\\n\\n***\\n\\n### + max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number` \\\\| `object`\\n\\nDefines + the maximum number of tokens that the model will take as context.\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:112](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L112)\\n\\n***\\n\\n### + min\\\\_score?\\n\\n> `optional` **min\\\\_score**: `number` \\\\| [`MinScore`](MinScore.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`min_score`](BaseSearchOptions.md#min_score)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:66](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L66)\\n\\n***\\n\\n### + prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:113](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L113)\\n\\n***\\n\\n### + prompt?\\n\\n> `optional` **prompt**: `string` \\\\| [`Prompts`](Prompts.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:101](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L101)\\n\\n***\\n\\n### + query\\\\_image?\\n\\n> `optional` **query\\\\_image**: `object`\\n\\n#### + b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> + **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:122](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L122)\\n\\n***\\n\\n### + rag\\\\_images\\\\_strategies?\\n\\n> `optional` **rag\\\\_images\\\\_strategies**: + [`RAGImageStrategy`](../type-aliases/RAGImageStrategy.md)[]\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:107](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L107)\\n\\n***\\n\\n### + rag\\\\_strategies?\\n\\n> `optional` **rag\\\\_strategies**: [`RAGStrategy`](../type-aliases/RAGStrategy.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:106](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L106)\\n\\n***\\n\\n### + range\\\\_creation\\\\_end?\\n\\n> `optional` **range\\\\_creation\\\\_end**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_end`](BaseSearchOptions.md#range_creation_end)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:68](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L68)\\n\\n***\\n\\n### + range\\\\_creation\\\\_start?\\n\\n> `optional` **range\\\\_creation\\\\_start**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_start`](BaseSearchOptions.md#range_creation_start)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:67](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L67)\\n\\n***\\n\\n### + range\\\\_modification\\\\_end?\\n\\n> `optional` **range\\\\_modification\\\\_end**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_end`](BaseSearchOptions.md#range_modification_end)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:70](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L70)\\n\\n***\\n\\n### + range\\\\_modification\\\\_start?\\n\\n> `optional` **range\\\\_modification\\\\_start**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_start`](BaseSearchOptions.md#range_modification_start)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:69](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L69)\\n\\n***\\n\\n### + rank\\\\_fusion?\\n\\n> `optional` **rank\\\\_fusion**: [`RankFusion`](RankFusion.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rank_fusion`](BaseSearchOptions.md#rank_fusion)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:84](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L84)\\n\\n***\\n\\n### + reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L126)\\n\\n***\\n\\n### + rephrase?\\n\\n> `optional` **rephrase**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rephrase`](BaseSearchOptions.md#rephrase)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:77](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L77)\\n\\n***\\n\\n### + reranker?\\n\\n> `optional` **reranker**: [`Reranker`](../enumerations/Reranker.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`reranker`](BaseSearchOptions.md#reranker)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:83](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L83)\\n\\n***\\n\\n### + resource\\\\_filters?\\n\\n> `optional` **resource\\\\_filters**: `string`[]\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`resource_filters`](BaseSearchOptions.md#resource_filters)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:75](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L75)\\n\\n***\\n\\n### + search\\\\_configuration?\\n\\n> `optional` **search\\\\_configuration**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`search_configuration`](BaseSearchOptions.md#search_configuration)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:86](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L86)\\n\\n***\\n\\n### + security?\\n\\n> `optional` **security**: `object`\\n\\n#### groups\\n\\n> + **groups**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`security`](BaseSearchOptions.md#security)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:85](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L85)\\n\\n***\\n\\n### + show?\\n\\n> `optional` **show**: [`ResourceProperties`](../enumerations/ResourceProperties.md)[]\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show`](BaseSearchOptions.md#show)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:71](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L71)\\n\\n***\\n\\n### + show\\\\_consumption?\\n\\n> `optional` **show\\\\_consumption**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L127)\\n\\n***\\n\\n### + show\\\\_hidden?\\n\\n> `optional` **show\\\\_hidden**: `boolean`\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show_hidden`](BaseSearchOptions.md#show_hidden)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:80](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L80)\\n\\n***\\n\\n### + synchronous?\\n\\n> `optional` **synchronous**: `boolean`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:100](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L100)\\n\\n***\\n\\n### + top\\\\_k?\\n\\n> `optional` **top\\\\_k**: `number`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`top_k`](BaseSearchOptions.md#top_k)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:82](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L82)\\n\\n***\\n\\n### + vectorset?\\n\\n> `optional` **vectorset**: `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`vectorset`](BaseSearchOptions.md#vectorset)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:78](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L78)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"d6b2f3f31ba0af4fa58490cdf6abeb52\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ChatOptions \\n Interface: ChatOptions + \\n Extends \\n \\n BaseSearchOptions \\n \\n Properties \\n answer_json_schema? + \\n \\n optional answer_json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:114 + \\n \\n audit_metadata? \\n \\n optional audit_metadata: object \\n \\n Index + Signature \\n [key: string]: string \\n Inherited from \\n BaseSearchOptions.audit_metadata + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:81 \\n + \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:116 \\n \\n + citations? \\n \\n optional citations: boolean \\\\| none \\\\| default \\\\| + llm_footnotes \\n \\n It will return the text blocks that have been effectively + used to build each section of the answer. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:105 + \\n \\n debug? \\n \\n optional debug: boolean \\n \\n Inherited from \\n + BaseSearchOptions.debug \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:79 + \\n \\n extra_context? \\n \\n optional extra_context: string[] \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:115 \\n \\n extra_context_images? + \\n \\n optional extra_context_images: object[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:118 + \\n \\n ~~extracted?~~ \\n \\n optional extracted: ExtractedDataTypes[] \\n + \\n Deprecated \\n Inherited from \\n BaseSearchOptions.extracted \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:73 \\n \\n features? + \\n \\n optional features: Features[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:117 + \\n \\n field_type_filter? \\n \\n optional field_type_filter: FIELD_TYPE[] + \\n \\n Inherited from \\n BaseSearchOptions.field_type_filter \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:74 \\n \\n fields? + \\n \\n optional fields: string[] \\n \\n Inherited from \\n BaseSearchOptions.fields + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:62 \\n + \\n filter_expression? \\n \\n optional filter_expression: FilterExpression + \\n \\n Inherited from \\n BaseSearchOptions.filter_expression \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:64 \\n \\n filters? + \\n \\n optional filters: string[] \\\\| Filter[] \\n \\n Inherited from \\n + BaseSearchOptions.filters \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:63 + \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:108 \\n \\n + highlight? \\n \\n optional highlight: boolean \\n \\n Inherited from \\n + BaseSearchOptions.highlight \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:76 + \\n \\n keyword_filters? \\n \\n optional keyword_filters: string[] \\\\| + Filter[] \\n \\n Inherited from \\n BaseSearchOptions.keyword_filters \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:65 \\n \\n + max_tokens? \\n \\n optional max_tokens: number \\\\| object \\n \\n Defines + the maximum number of tokens that the model will take as context. \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 \\n \\n min_score? + \\n \\n optional min_score: number \\\\| MinScore \\n \\n Inherited from \\n + BaseSearchOptions.min_score \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:66 + \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:113 \\n \\n + prompt? \\n \\n optional prompt: string \\\\| Prompts \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/search/search.models.ts:101 \\n \\n query_image? + \\n \\n optional query_image: object \\n \\n b64encoded \\n \\n b64encoded: + string \\n \\n content_type \\n \\n content_type: string \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/search.models.ts:122 \\n \\n rag_images_strategies? + \\n \\n optional rag_images_strategies: RAGImageStrategy[] \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:107 \\n \\n rag_strategies? + \\n \\n optional rag_strategies: RAGStrategy[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:106 + \\n \\n range_creation_end? \\n \\n optional range_creation_end: string \\n + \\n Inherited from \\n BaseSearchOptions.range_creation_end \\n Defined in + \\n libs/sdk-core/src/lib/db/search/search.models.ts:68 \\n \\n range_creation_start? + \\n \\n optional range_creation_start: string \\n \\n Inherited from \\n BaseSearchOptions.range_creation_start + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:67 \\n + \\n range_modification_end? \\n \\n optional range_modification_end: string + \\n \\n Inherited from \\n BaseSearchOptions.range_modification_end \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:70 \\n \\n range_modification_start? + \\n \\n optional range_modification_start: string \\n \\n Inherited from \\n + BaseSearchOptions.range_modification_start \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:69 + \\n \\n rank_fusion? \\n \\n optional rank_fusion: RankFusion \\n \\n Inherited + from \\n BaseSearchOptions.rank_fusion \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:84 + \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:126 \\n \\n rephrase? + \\n \\n optional rephrase: boolean \\n \\n Inherited from \\n BaseSearchOptions.rephrase + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:77 \\n + \\n reranker? \\n \\n optional reranker: Reranker \\n \\n Inherited from \\n + BaseSearchOptions.reranker \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:83 + \\n \\n resource_filters? \\n \\n optional resource_filters: string[] \\n + \\n Inherited from \\n BaseSearchOptions.resource_filters \\n Defined in \\n + libs/sdk-core/src/lib/db/search/search.models.ts:75 \\n \\n search_configuration? + \\n \\n optional search_configuration: string \\n \\n Inherited from \\n BaseSearchOptions.search_configuration + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:86 \\n + \\n security? \\n \\n optional security: object \\n \\n groups \\n \\n groups: + string[] \\n \\n Inherited from \\n BaseSearchOptions.security \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:85 \\n \\n show? \\n + \\n optional show: ResourceProperties[] \\n \\n Inherited from \\n BaseSearchOptions.show + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:71 \\n + \\n show_consumption? \\n \\n optional show_consumption: boolean \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:127 \\n \\n show_hidden? + \\n \\n optional show_hidden: boolean \\n \\n Inherited from \\n BaseSearchOptions.show_hidden + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:80 \\n + \\n synchronous? \\n \\n optional synchronous: boolean \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/search.models.ts:100 \\n \\n top_k? \\n + \\n optional top_k: number \\n \\n Inherited from \\n BaseSearchOptions.top_k + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:82 \\n + \\n vectorset? \\n \\n optional vectorset: string \\n \\n Inherited from \\n + BaseSearchOptions.vectorset \\n Defined in \\n 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+ min\":\"TIME\"},\"entities\":{\"processor\":{\"entities\":[{\"text\":\"boolean\",\"label\":\"PERSON\",\"positions\":[{\"start\":647,\"end\":654}]},{\"text\":\"112 + min\",\"label\":\"TIME\",\"positions\":[{\"start\":2991,\"end\":3002}]}]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:09.547197Z\",\"last_understanding\":\"2026-07-14T12:51:09.110083Z\",\"last_extract\":\"2026-07-14T12:51:05.901654Z\",\"last_processing_start\":\"2026-07-14T12:51:05.827255Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{\"TIME/112 + min\":{\"position\":[{\"start\":2991,\"end\":3002}],\"entity\":\"112 min\"},\"PERSON/boolean\":{\"position\":[{\"start\":647,\"end\":654}],\"entity\":\"boolean\"}},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > ChatOptions\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > ChatOptions\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\":{\"score\":0.6769328117370605,\"score_type\":\"VECTOR\",\"order\":1,\"text\":\" + \\n optional max_tokens: number \\\\| object \\n \\n Defines the maximum number + of tokens that the model will take as context. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 + \\n \\n min_score? \\n\",\"id\":\"e8525e64c5b44982b958d32cf6090613/t/page/2808-3011\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":9,\"start\":2808,\"end\":3011,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"89cc367c149e4f6eab0e06a743d1edba\":{\"id\":\"89cc367c149e4f6eab0e06a743d1edba\",\"slug\":\"docs-rag-advanced-openai-api-compatible-models-md\",\"title\":\"docs + > rag > advanced > openai api compatible models\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-05-23T07:21:32.894218\",\"modified\":\"2026-06-09T08:07:43.359058\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + openai-api-compatible-models\\ntitle: Connect to any OpenAI API compatible + LLM\\n---\\n\\n# Connect to any OpenAI API compatible LLM\\n\\nAgentic RAG + allows you to connect to any OpenAI API compatible LLM. This means that you + can use any LLM that has an API compatible with the OpenAI API which has become + a standard in the industry.\\n\\nMany of the options for self-hosted LLMs, + open-source LLMs hosted by cloud providers or commercial LLMs are compatible + with the OpenAI API. This means that you can use them with Agentic RAG without + any modifications.\\n\\n## Configuration\\n\\nTo modify your knowledge box + configuration you can do so in three manners, through the API, the Nuclia + CLI / SDK or the Agentic RAG dashboard.\\n\\nThe Agentic RAG dashboard offers + the most user-friendly way to modify the configuration of your knowledge box + and we will use it in this example.\\n\\nWe will be setting up a connection + to the **Phi 4 Reasoning Plus** model, hosted by **OpenRouter** which offers + a wide range of open-source and commercial models compatible with the OpenAI + API. We can see more information about this specific model [here](https://openrouter.ai/microsoft/phi-4-reasoning-plus:free), + the API parameters are located under the **API** tab.\\n\\n1. **Open the AI + Models page** \\n In the left sidebar under **Advanced**, click **AI Models**.\\n2. + **Select \u201COpenAI API Compatible Model\u201D** \\n From the models + list, choose **OpenAI API Compatible Model**.\\n3. **Enable custom Key** \\n + \ Toggle the option for using you own `OpenAI API Compatible Key` if it is + not already enabled.\\n4. **Fill in the configuration parameters**\\n\\n - + **API Key**:\\n - Description: The API key for your LLM. This is the key + that you would use as an authorization header in the API. You may leave this + blank if the endpoint you are connecting to does not require an API key.\\n + \ - Example: We will set this to our OpenRouter API key.\\n - **API URL**:\\n + \ - Description: The URL of the API endpoint for your LLM. This may be + shared between multiple models.\\n - Example: For OpenRouter, it is the + same for all models: `https://openrouter.ai/api/v1`\\n - **Model**:\\n - + Description: The name of the model you want to use, it needs to exactly match + the name of the model in the API.\\n - Example: For Phi 4 Reasoning Plus + in the OpenRouter API, it is `microsoft/phi-4-reasoning-plus:free`.\\n - + **Maximum supported input tokens**:\\n - Description: The maximum number + of tokens that the model can accept as input. Be mindful that this takes into + account the tokens used in the prompt, query and context. Also take note that + some models may provide their context window as the total between input and + output tokens, while others may provide it as the input tokens only.\\n - + Example: For Phi 4 Reasoning Plus, the total context size is `32768` tokens, + as we want to leave room for the output, we will set the maximum supported + input tokens as `32768 - 1024 = 31744`.\\n - **Maximum supported output + tokens**:\\n - Description: The maximum number of tokens that the model + can generate as output. Again, we should keep in mind that this value summed + to the **Maximum supported input tokens** should not exceed the total context + size supported by the model.\\n - Example: For Phi 4 Reasoning Plus, the + maximum output tokens is specified at `32768`, but we already reserved `31744` + for the input tokens, so we will set this to `32768 - 31744 = 1024`.\\n - + **Model Features**:\\n - Description: Under this section you will find + multiple toggles related to features supported by the model, these vary from + model to model, but most often the default values are well suited to most + use cases. The most relevant toggle is for `Image Support` which allows you + to use images as input for the model.\\n - Example: Image input is not + supported by Phi 4 Reasoning Plus, so we will leave it disabled.\\n\\n5. **Save** + \ \\n Click **Save changes**.\\n\\n6. **Test your model** \\n Run a sample + query in Agentic RAG or via API/CLI. Adjust your prompt templates and token + settings as needed.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"37cd8aff748addd04a363fa50828d1fe\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: openai-api-compatible-models \\n title: Connect to any OpenAI API + compatible LLM \\n \\n Connect to any OpenAI API compatible LLM \\n Agentic + RAG allows you to connect to any OpenAI API compatible LLM. This means that + you can use any LLM that has an API compatible with the OpenAI API which has + become a standard in the industry. \\n Many of the options for self-hosted + LLMs, open-source LLMs hosted by cloud providers or commercial LLMs are compatible + with the OpenAI API. This means that you can use them with Agentic RAG without + any modifications. \\n Configuration \\n To modify your knowledge box configuration + you can do so in three manners, through the API, the Nuclia CLI / SDK or the + Agentic RAG dashboard. \\n The Agentic RAG dashboard offers the most user-friendly + way to modify the configuration of your knowledge box and we will use it in + this example. \\n We will be setting up a connection to the Phi 4 Reasoning + Plus model, hosted by OpenRouter which offers a wide range of open-source + and commercial models compatible with the OpenAI API. We can see more information + about this specific model here, the API parameters are located under the API + tab. \\n \\n Open the AI Models page \\n In the left sidebar under Advanced, + click AI Models. \\n Select OpenAI API Compatible Model \\n From the models + list, choose OpenAI API Compatible Model. \\n Enable custom Key \\n Toggle + the option for using you own OpenAI API Compatible Key if it is not already + enabled. \\n \\n Fill in the configuration parameters \\n \\n \\n API Key: + \\n \\n Description: The API key for your LLM. This is the key that you would + use as an authorization header in the API. You may leave this blank if the + endpoint you are connecting to does not require an API key. \\n Example: We + will set this to our OpenRouter API key. \\n \\n \\n API URL: \\n Description: + The URL of the API endpoint for your LLM. This may be shared between multiple + models. \\n Example: For OpenRouter, it is the same for all models: https://openrouter.ai/api/v1 + \\n \\n \\n Model: \\n Description: The name of the model you want to use, + it needs to exactly match the name of the model in the API. \\n Example: For + Phi 4 Reasoning Plus in the OpenRouter API, it is microsoft/phi-4-reasoning-plus:free. + \\n \\n \\n Maximum supported input tokens: \\n Description: The maximum number + of tokens that the model can accept as input. Be mindful that this takes into + account the tokens used in the prompt, query and context. Also take note that + some models may provide their context window as the total between input and + output tokens, while others may provide it as the input tokens only. \\n Example: + For Phi 4 Reasoning Plus, the total context size is 32768 tokens, as we want + to leave room for the output, we will set the maximum supported input tokens + as 32768 - 1024 = 31744. \\n \\n \\n Maximum supported output tokens: \\n + Description: The maximum number of tokens that the model can generate as output. + Again, we should keep in mind that this value summed to the Maximum supported + input tokens should not exceed the total context size supported by the model. + \\n Example: For Phi 4 Reasoning Plus, the maximum output tokens is specified + at 32768, but we already reserved 31744 for the input tokens, so we will set + this to 32768 - 31744 = 1024. \\n \\n \\n \\n Model Features: \\n \\n Description: + Under this section you will find multiple toggles related to features supported + by the model, these vary from model to model, but most often the default values + are well suited to most use cases. The most relevant toggle is for Image Support + which allows you to use images as input for the model. \\n Example: Image + input is not supported by Phi 4 Reasoning Plus, so we will leave it disabled. + \\n \\n \\n \\n Save \\n Click Save changes. \\n \\n \\n Test your model \\n + Run a sample query in Agentic RAG or via API/CLI. Adjust your prompt templates + and token settings as needed. \\n \\n 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\\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":10,\"start\":2804,\"end\":3043,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\":{\"score\":0.63338303565979,\"score_type\":\"VECTOR\",\"order\":5,\"text\":\" + \\n \\n Maximum supported input tokens: \\n Description: The maximum number + of tokens that the model can accept as input. 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ConsumptionAskResponseItem\\n\\n# Interface: ConsumptionAskResponseItem\\n\\n## + Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> **customer\\\\_key\\\\_tokens**: + [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L127)\\n\\n***\\n\\n### + normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](../../../interfaces/TokenConsumption.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L126)\\n\\n***\\n\\n### + type\\n\\n> **type**: `\\\"consumption\\\"`\\n\\n#### Defined 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simple HTML snippet:\\n\\n```html\\n\\n\\n\\n```\\n\\nThe + easiest way to explore the different features of the widgets is to use the + [Agentic RAG Dashboard](https://rag.progress.cloud/) in the Widgets section + and to play with the different options.\\n\\nThe _Embed widget_ button will + generate the HTML snippet for you.\\n\\n## Widget types\\n\\nThere are 3 different + types of widgets:\\n\\n- **Embedded in page**: the search input is embedded + in a page and the results are displayed under the input. Once the initial + answer is displayed, the user can click on _Ask more_ to access the full chat + interface. Note: For the correct reading of the results, the width of the + widget container should not be less than 384px.\\n\\n Web components:\\n\\n + \ ```html\\n \\n \\n + \ ```\\n\\n- **Chat mode**: displays directly the full chat interface.\\n\\n + \ Web component:\\n\\n ```html\\n \\n ```\\n\\n- + **Popup modal**: the search inout and the results are displayed in a popup + modal.\\n\\n Web component:\\n\\n ```html\\n \\n + \ ```\\n\\n## The `features` parameter\\n\\nThe `features` parameter allows + you to customize the behavior of the widget. It is a comma-separated list + of features among the following:\\n\\n- `filter`: display a filter dropdown + in the search bar.\\n- `navigateToFile`: open the file in the browser when + clicking on the result (by default, the file is displayed in the viewer).\\n- + `navigateToLink`: open the link in the browser when clicking on the result + (by default, the link is displayed in the viewer).\\n- `permalink`: add the + search query and criteria to the URL, allowing the widget to re-render the + same results upon loading.\\n- `relations`: display an info card on the right + side of the widget listing all the relations of the entity mentioned in the + user query.\\n- `suggestions`: display a list of suggested resource titles + matching the user input.\\n- `suggestLabels`: display a list of suggestions + based on the labels when the user starts typing in the search bar.\\n- `autocompleteFromNERs`: + display a list of suggestions based on the NERs extracted from the user query + when the user starts typing in the search bar.\\n- `displayMetadata`: display + the metadata associated with the resource in the result rows.\\n- `answers`: + trigger the answer generation process when the user makes a search.\\n- `hideResults`: + hide the search results, only the generative answer will be displayed.\\n- + `hideThumbnails`: hide the thumbnails associated with the resource in the + result rows.\\n- `displayFieldList`: display a section listing all the fields + of the resource in the right sidebar of the viewer. This section is only visible + for resources containing multiple fields.\\n- `citations`: include citations + in the generative answer.\\n- `rephrase`: rephrase the user question in order + to optimize the quality of the search results.\\n- `debug`: display extra + buttons to download the last request full log of the debug metadata returned + by the API. It must not be used in production.\\n- `preferMarkdown`: require + the generative answer to be formatted in Markdown.\\n- `openNewTab`: open + the link in a new tab when clicking on the result.\\n- `orFilterLogic`: use + the OR logic for filters instead of the default AND logic.\\n- `noChatHistory`: + the previous questions and answers in the chat mode will not be passed as + context when generating a new answer.\\n- `showHidden`: display hidden resources + in the search results.\\n- `showAttachedImages`: display images attached to + the matching paragraphs in the search results.\\n\\n### Other parameters\\n\\n- + `backend`: the URL of the backend to use. Useful if you use your own proxy + to access the Agentic RAG API.\\n- `zone`: the zone to use.\\n- `knowledgebox`: + the Knowledge Box id.\\n- `placeholder`: the text displayed in the search + bar when it is empty.\\n- `lang`: the language of the widget. Currently supported: + `ca`, `fr`, `en`, `es`. Default: `en`.\\n- `apikey`: the API key to use. It + is not recommended to use it in production (the API key is meant to be injected + by your proxy).\\n- `account`: the account id.\\n- `state`: the publication + state of the Knowledge Box.\\n- `standalone`: set to `true` when using a standalone + NucliaDB instance.\\n- `proxy`: set to `true` when using a proxy to access + the Agentic RAG API.\\n- `mode`: set to `dark` to display the widget in dark + mode.\\n- `filters`: define the filters offered to the user in the search + bar among `labels`, `entities`, `created` and `labelFamilies`.\\n- `preselected_filters`: + define filters that will be applied by default to any query.\\n- `csspath`: + the path to the CSS file to use to customize the widget style.\\n- `prompt`: + the prompt to use for the generative model. It must use `{context}` and `{question}` + variables.\\n- `system_prompt`: the system prompt to use for the generative + model.\\n- `rephrase_prompt`: the prompt to use when optimizing the user query + to get the best search results.\\n- `generativemodel`: the generative model + to use for the answer generation.\\n- `rag_strategies`: the RAG strategies + to apply to the retrieved paragraphs.\\n- `rag_images_strategies`: the RAG + strategies to apply to the retrieved images.\\n- `not_enough_data_message`: + the message to display when there is not enough data to generate an answer.\\n- + `ask_to_resource`: the resource ID to use as context for the generative model.\\n- + `max_tokens`: the maximum number of input tokens to put in the final context + (including the prompt, the retrieved results and the user question).\\n- `max_output_tokens`: + the maximum number of tokens to generate.\\n- `max_paragraphs`: the maximum + number of paragraphs to pass in the context to the generative model (default: + 20).\\n- `query_prepend`: the hard-coded text to prepend to the user query.\\n- + `json_schema`: the JSON schema to use to get a JSON answer from the generative + model.\\n- `vectorset`: the embedding model to use for the semantic search.\\n- + `chat_placeholder`: the placeholder to display in the chat input.\\n- `audit_metadata`: + custom metatada to add in API calls for auditing purposes.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"8f3044c65d6a551153cea36353a2cdac\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: features \\n title: Features \\n \\n Widgets features \\n The Agentic + RAG widgets allows you to embed the Agentic RAG search experience directly + into your website or web application through a simple HTML snippet: \\n ```html + \\n \\n \\n \\n ``` \\n The easiest way to explore the different features + of the widgets is to use the Agentic RAG Dashboard in the Widgets section + and to play with the different options. \\n The Embed widget button will generate + the HTML snippet for you. \\n Widget types \\n There are 3 different types + of widgets: \\n \\n Embedded in page: the search input is embedded in a page + and the results are displayed under the input. Once the initial answer is + displayed, the user can click on Ask more to access the full chat interface. + Note: For the correct reading of the results, the width of the widget container + should not be less than 384px. \\n \\n Web components: \\n html \\n \\n \\n + \\n Chat mode: displays directly the full chat interface. \\n \\n Web component: + \\n html \\n \\n \\n Popup modal: the search inout and the results are displayed + in a popup modal. \\n \\n Web component: \\n html \\n \\n The features parameter + \\n The features parameter allows you to customize the behavior of the widget. + It is a comma-separated list of features among the following: \\n \\n filter: + display a filter dropdown in the search bar. \\n navigateToFile: open the + file in the browser when clicking on the result (by default, the file is displayed + in the viewer). \\n navigateToLink: open the link in the browser when clicking + on the result (by default, the link is displayed in the viewer). \\n permalink: + add the search query and criteria to the URL, allowing the widget to re-render + the same results upon loading. \\n relations: display an info card on the + right side of the widget listing all the relations of the entity mentioned + in the user query. \\n suggestions: display a list of suggested resource titles + matching the user input. \\n suggestLabels: display a list of suggestions + based on the labels when the user starts typing in the search bar. \\n autocompleteFromNERs: + display a list of suggestions based on the NERs extracted from the user query + when the user starts typing in the search bar. \\n displayMetadata: display + the metadata associated with the resource in the result rows. \\n answers: + trigger the answer generation process when the user makes a search. \\n hideResults: + hide the search results, only the generative answer will be displayed. \\n + hideThumbnails: hide the thumbnails associated with the resource in the result + rows. \\n displayFieldList: display a section listing all the fields of the + resource in the right sidebar of the viewer. This section is only visible + for resources containing multiple fields. \\n citations: include citations + in the generative answer. \\n rephrase: rephrase the user question in order + to optimize the quality of the search results. \\n debug: display extra buttons + to download the last request full log of the debug metadata returned by the + API. It must not be used in production. \\n preferMarkdown: require the generative + answer to be formatted in Markdown. \\n openNewTab: open the link in a new + tab when clicking on the result. \\n orFilterLogic: use the OR logic for filters + instead of the default AND logic. \\n noChatHistory: the previous questions + and answers in the chat mode will not be passed as context when generating + a new answer. \\n showHidden: display hidden resources in the search results. + \\n showAttachedImages: display images attached to the matching paragraphs + in the search results. \\n \\n Other parameters \\n \\n backend: the URL of + the backend to use. Useful if you use your own proxy to access the Agentic + RAG API. \\n zone: the zone to use. \\n knowledgebox: the Knowledge Box id. + \\n placeholder: the text displayed in the search bar when it is empty. \\n + lang: the language of the widget. Currently supported: ca, fr, en, es. Default: + en. \\n apikey: the API key to use. It is not recommended to use it in production + (the API key is meant to be injected by your proxy). \\n account: the account + id. \\n state: the publication state of the Knowledge Box. \\n standalone: + set to true when using a standalone NucliaDB instance. \\n proxy: set to true + when using a proxy to access the Agentic RAG API. \\n mode: set to dark to + display the widget in dark mode. \\n filters: define the filters offered to + the user in the search bar among labels, entities, created and labelFamilies. + \\n preselected_filters: define filters that will be applied by default to + any query. \\n csspath: the path to the CSS file to use to customize the widget + style. \\n prompt: the prompt to use for the generative model. It must use + {context} and {question} variables. \\n system_prompt: the system prompt to + use for the generative model. \\n rephrase_prompt: the prompt to use when + optimizing the user query to get the best search results. \\n generativemodel: + the generative model to use for the answer generation. \\n rag_strategies: + the RAG strategies to apply to the retrieved paragraphs. \\n rag_images_strategies: + the RAG strategies to apply to the retrieved images. \\n not_enough_data_message: + the message to display when there is not enough data to generate an answer. + \\n ask_to_resource: the resource ID to use as context for the generative + model. \\n max_tokens: the maximum number of input tokens to put in the final + context (including the prompt, the retrieved results and the user question). + \\n max_output_tokens: the maximum number of tokens to generate. \\n max_paragraphs: + the maximum number of paragraphs to pass in the context to the generative + model (default: 20). \\n query_prepend: the hard-coded text to prepend to + the user query. \\n json_schema: the JSON schema to use to get a JSON answer + from the generative model. \\n vectorset: the embedding model to use for the + semantic search. \\n chat_placeholder: the placeholder to display in the chat + input. \\n audit_metadata: custom metatada to add in API calls for auditing + purposes. \\n 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`number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L249)\\n\\n***\\n\\n### + line\\n\\n> **line**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L251)\\n\\n***\\n\\n### + text\\n\\n> **text**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L250)\\n\\n***\\n\\n### + width\\n\\n> **width**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L248)\\n\\n***\\n\\n### + x\\n\\n> **x**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L246)\\n\\n***\\n\\n### + y\\n\\n> **y**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"e72ffebe78398e6654aceec2addfd240\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n + Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 + \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 + \\n \\n text \\n \\n text: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:250 + \\n \\n width \\n \\n width: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:248 + \\n \\n x \\n \\n x: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:246 + \\n \\n y \\n \\n y: number \\n \\n Defined in \\n 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+ > develop > js sdk > interfaces > PageToken\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > PageToken\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\":{\"score\":0.5957225561141968,\"score_type\":\"VECTOR\",\"order\":14,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / PageToken \\n Interface: PageToken \\n + Properties \\n height \\n \\n height: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:249 + \\n \\n line \\n \\n line: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:251 + \\n \\n text \\n \\n\",\"id\":\"f02da6c4bdf34596a89a8106f4b0ea9f/t/page/0-299\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":299,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"1b2a9e67b9f14a0cb81efaa05b8793b8\":{\"id\":\"1b2a9e67b9f14a0cb81efaa05b8793b8\",\"slug\":\"docs-develop-js-sdk-interfaces-AugmentedField-md\",\"title\":\"docs + > develop > js sdk > interfaces > AugmentedField\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:00:05.937520\",\"modified\":\"2026-07-14T12:49:32.163110\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/AugmentedField\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / AugmentedField\\n\\n# + Interface: AugmentedField\\n\\n## Properties\\n\\n### applied\\\\_data\\\\_augmentation\\n\\n> + **applied\\\\_data\\\\_augmentation**: [`AppliedDataAugmentation`](AppliedDataAugmentation.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:571](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L571)\\n\\n***\\n\\n### + input\\\\_nuclia\\\\_tokens\\n\\n> **input\\\\_nuclia\\\\_tokens**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:572](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L572)\\n\\n***\\n\\n### + metadata\\n\\n> **metadata**: [`FieldMetadata`](FieldMetadata.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:570](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L570)\\n\\n***\\n\\n### + output\\\\_nuclia\\\\_tokens\\n\\n> **output\\\\_nuclia\\\\_tokens**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:573](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L573)\\n\\n***\\n\\n### + time\\n\\n> **time**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/resource/resource.models.ts:574](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/resource/resource.models.ts#L574)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"1e8e95b886439059ae4ec717c9bcf283\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / AugmentedField \\n Interface: AugmentedField + \\n Properties \\n applied_data_augmentation \\n \\n applied_data_augmentation: + AppliedDataAugmentation \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:571 + \\n \\n input_nuclia_tokens \\n \\n input_nuclia_tokens: number \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:572 \\n \\n metadata + \\n \\n metadata: FieldMetadata \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:570 + \\n \\n output_nuclia_tokens \\n \\n output_nuclia_tokens: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:573 \\n + \\n time \\n \\n time: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:574\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":641,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":641,\"key\":\"\"}]},{\"start\":641,\"end\":729,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":642,\"end\":729,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:49:33.585675Z\",\"last_understanding\":\"2026-07-14T12:49:33.340252Z\",\"last_extract\":\"2026-07-14T12:49:32.941746Z\",\"last_processing_start\":\"2026-07-14T12:49:32.917812Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > AugmentedField\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > AugmentedField\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"1b2a9e67b9f14a0cb81efaa05b8793b8/t/page/0-641\":{\"score\":0.5881041884422302,\"score_type\":\"VECTOR\",\"order\":19,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / AugmentedField \\n Interface: AugmentedField + \\n Properties \\n applied_data_augmentation \\n \\n applied_data_augmentation: + AppliedDataAugmentation \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:571 + \\n \\n input_nuclia_tokens \\n \\n input_nuclia_tokens: number \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:572 \\n \\n metadata + \\n \\n metadata: FieldMetadata \\n \\n Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:570 + \\n \\n output_nuclia_tokens \\n \\n output_nuclia_tokens: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/resource/resource.models.ts:573 \\n + \\n time \\n \\n\",\"id\":\"1b2a9e67b9f14a0cb81efaa05b8793b8/t/page/0-641\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":641,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"44d05174f1954331b62f5e4026f2b01a\":{\"id\":\"44d05174f1954331b62f5e4026f2b01a\",\"slug\":\"docs-develop-python-sdk-14-rao-md\",\"title\":\"docs + > develop > python sdk > 14 rao\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-22T13:38:09.919472\",\"modified\":\"2026-06-09T08:08:04.176136\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/python-sdk/rao\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"# + Retrieval Agents Orchestrator\\n\\nInteract with Nuclia's Retrieval Agents + Orchestrator to have intelligent conversations over several knowledge sources + with persistent session management and real-time streaming responses.\\n\\n## + Prerequisites\\n\\nInstall the Nuclia SDK:\\n\\n```sh\\npip install nuclia\\n```\\n\\nEnsure + you have:\\n- A valid Nuclia authentication token (see [Authentication](02-auth.md))\\n- + Access to a configured Retrieval Agent\\n\\n## Overview\\n\\nThe nuclia.py + library provides several ways to interact with your Retrieval Agents Orchestrators:\\n\\n- + **Interactive CLI**: A rich, user-friendly terminal interface (recommended)\\n- + **Standard CLI**: Direct access to raw websocket messages for debugging\\n- + **Session Management**: Create and manage persistent conversation sessions\\n- + **Programmatic API**: Python SDK for building custom applications\\n\\n\\n## + Listing Available Agents\\n\\nDiscover what Retrieval Agents Orchestrators + you have access to.\\n\\n- CLI:\\n\\n ```sh\\n nuclia agents list\\n ```\\n\\n- + SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n + \ agents = NucliaAgents()\\n all_agents = agents.list()\\n\\n for agent + in all_agents:\\n print(f\\\"Agent: {agent.title} ({agent.id})\\\")\\n + \ print(f\\\" Slug: {agent.slug}\\\")\\n print(f\\\" Zone: {agent.zone}\\\")\\n + \ ```\\n\\n### Getting a Specific Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia + agents get --account=\\\"my-account\\\" --id=\\\"agent-uuid\\\" --zone=\\\"europe-1\\\"\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agents import NucliaAgents\\n\\n + \ agents = NucliaAgents()\\n agent_details = agents.get(\\n account=\\\"my-account\\\",\\n + \ id=\\\"agent-uuid\\\",\\n zone=\\\"europe-1\\\"\\n )\\n print(agent_details)\\n + \ ```\\n\\n### Setting a Default Agent\\n\\n- CLI:\\n\\n ```sh\\n nuclia + agents default [AGENT_SLUG or AGENT_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n + \ from nuclia.sdk.agents import NucliaAgents\\n\\n agents = NucliaAgents()\\n + \ agents.default(\\\"my-agent\\\")\\n ```\\n\\nThis sets the default agent + for all subsequent operations.\\n\\n## Interactive CLI (Recommended)\\n\\nThe + interactive CLI provides a beautiful, real-time interface for conversing with + your Retrieval Agents Orchestrator.\\n\\n### Starting the Interactive CLI\\n\\n- + CLI:\\n\\n ```sh\\n nuclia agent cli interact\\n ```\\n\\n- SDK:\\n\\n + \ ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n + \ agent.cli.interact()\\n ```\\n\\nThis launches an interactive terminal + session where you can:\\n- Ask questions and see streaming responses\\n- View + processing steps in real-time\\n- Manage conversation sessions\\n- See retrieved + context and citations\\n\\n### Interactive CLI Commands\\n\\nThe CLI supports + several commands (prefix with `/`):\\n\\n| Command | Description |\\n|---------|-------------|\\n| + `/help` | Show available commands |\\n| `/new_session` | Create a new persistent + session |\\n| `/list_sessions` | List all your sessions |\\n| `/change_session` + | Switch to a different session, use 'ephemeral' for a temporary session |\\n| + `/clear` | Clear the screen |\\n| `/exit` | Exit the CLI |\\n\\nPlease note + that all commands related to sessions require a Retrieval Agent Orchestrator + with the option **Agent with memory** enabled during creation.\\n\\n## Session + Management\\n\\nSessions allow you to maintain conversation context across + multiple interactions.\\n\\n> This feature will only be available if you checked + **Agent with memory** during the creation of your Retrieval Agents Orchestrator.\\n\\n### + Creating a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent session new --name=\\\"My + Research Session\\\"\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent + import NucliaAgent\\n\\n agent = NucliaAgent()\\n session_uuid = agent.session.new(\\\"My + Research Session\\\")\\n print(f\\\"Created session: {session_uuid}\\\")\\n + \ ```\\n\\n### Listing Sessions\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent + session list\\n ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent + import NucliaAgent\\n\\n agent = NucliaAgent()\\n sessions = agent.session.list()\\n + \ for session in sessions.resources:\\n print(f\\\"{session.title}: {session.id}\\\")\\n + \ ```\\n\\n### Getting a Session\\n\\n- CLI:\\n\\n ```sh\\n nuclia agent + session get --session_uuid=[SESSION_UUID]\\n ```\\n\\n- SDK:\\n\\n ```python\\n + \ from nuclia.sdk.agent import NucliaAgent\\n\\n agent = NucliaAgent()\\n + \ session = agent.session.get(session_uuid)\\n print(f\\\"Session: {session.title}\\\")\\n + \ print(f\\\"Created: {session.created}\\\")\\n ```\\n\\n### Deleting a Session\\n\\n- + CLI:\\n\\n ```sh\\n nuclia agent session delete --session_uuid=[SESSION_UUID]\\n + \ ```\\n\\n- SDK:\\n\\n ```python\\n from nuclia.sdk.agent import NucliaAgent\\n\\n + \ agent = NucliaAgent()\\n agent.session.delete(session_uuid)\\n ```\\n\\n## + Interaction\\n\\nAside from the interactive CLI, you can interact with your + Retrieval Agents Orchestrator with the simple CLI or programmatically using + the SDK.\\n\\n### Basic Interaction\\n\\n\\n**CLI:**\\n```bash\\nnuclia agent + interact \\\"What is Eric known for?\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate + over streaming responses\\nfor response in agent.interact(\\n question=\\\"What + is Eric known for?\\\"\\n):\\n if response.operation == \\\"ANSWER\\\" + and response.answer:\\n print(response.answer)\\n elif response.step:\\n + \ print(f\\\"Processing: {response.step.module}\\\")\\n```\\n\\nNot + supplying a `session_uuid` when calling `interact` will use an ephemeral session + by default. To maintain context, provide a persistent session UUID.\\n\\n### + Using Persistent Sessions\\n\\n**CLI:**\\n```bash\\nnuclia agent sessions + new \\\"Customer Support Chat\\\"\\n# Note the session UUID returned\\nnuclia + agent interact \\\"What are your business hours?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\nnuclia + agent interact \\\"Are you open on weekends?\\\" --session_uuid=\\\"SESSION_UUID\\\"\\n```\\n\\n**SDK:**\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Create + a session\\nsession_uuid = agent.session.new(\\\"Customer Support Chat\\\")\\n\\n# + Have a conversation with context\\nfor response in agent.interact(\\n session_uuid=session_uuid,\\n + \ question=\\\"What are your business hours?\\\"\\n):\\n if response.answer:\\n + \ print(response.answer)\\n\\n# Follow-up question maintains context\\nfor + response in agent.interact(\\n session_uuid=session_uuid,\\n question=\\\"Are + you open on weekends?\\\"\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\n## + Understanding Response Types\\n\\nWhen interacting with an agent, you receive + a stream of `AragAnswer` objects with different operations:\\n\\n| Operation + | Description |\\n|-----------|-------------|\\n| `START` | Interaction has + begun |\\n| `ANSWER` | Processing step or partial answer |\\n| `DONE` | Interaction + complete |\\n| `ERROR` | An error occurred |\\n| `AGENT_REQUEST` | Agent needs + user feedback |\\n\\n### Response Attributes\\n\\nEach response may contain:\\n\\n- + **`step`**: Information about the current processing step\\n - `module`: + The module being executed (e.g., \\\"rephrase\\\", \\\"basic_ask\\\", \\\"remi\\\")\\n + \ - `title`: Display title for the step\\n - `value`: Result of the step\\n + \ - `reason`: Explanation for the step\\n - `timeit`: Time taken in seconds\\n + \ - `input_nuclia_tokens`/`output_nuclia_tokens`: Token usage\\n\\n- **`context`**: + Retrieved context from the knowledge base\\n - `chunks`: List of retrieved + text chunks with sources\\n - `summary`: Summary of the context or partial + answer\\n\\n- **`answer`**: The final answer text (Markdown formatted)\\n\\n- + **`generated_text`**: Intermediate generated text\\n\\n- **`possible_answer`**: + Alternative answer being considered\\n\\n- **`exception`**: Error details + if something went wrong\\n\\n### Processing Responses\\n\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\nfrom nuclia_models.agent.interaction + import AnswerOperation\\n\\nagent = NucliaAgent()\\n\\nfor response in agent.interact(question=\\\"Tell + me about AI\\\"):\\n if response.operation == AnswerOperation.START:\\n + \ print(\\\"Starting...\\\")\\n \\n elif response.step:\\n print(f\\\"Step: + {response.step.module} ({response.step.timeit:.2f}s)\\\")\\n \\n elif + response.context:\\n print(f\\\"Retrieved {len(response.context.chunks)} + chunks\\\")\\n for chunk in response.context.chunks:\\n print(f\\\" + \ - {chunk.title}: {chunk.text[:100]}...\\\")\\n \\n elif response.answer:\\n + \ print(f\\\"\\\\nFinal Answer:\\\\n{response.answer}\\\")\\n \\n + \ elif response.operation == AnswerOperation.DONE:\\n print(\\\"Complete!\\\")\\n + \ \\n elif response.operation == AnswerOperation.ERROR:\\n print(f\\\"Error: + {response.exception.detail if response.exception else 'Unknown'}\\\")\\n```\\n\\n## + Standard CLI for Raw Messages\\n\\nFor debugging or advanced use cases, you + can access raw websocket messages programmatically:\\n\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\n\\n# Iterate + over all messages\\nfor message in agent.interact(\\n question=\\\"What + is RAO?\\\"\\n):\\n # message is an AragAnswer object with all raw data\\n + \ print(f\\\"Operation: {message.operation}\\\")\\n print(f\\\"Raw message: + {message.model_dump_json(indent=2)}\\\")\\n```\\n\\nThis gives you direct + access to all websocket message data for debugging or custom processing.\\n\\n## + Advanced Features\\n\\n### Agent Feedback Requests\\n\\nAgents can request + additional input from users during processing:\\n\\n```python\\nfrom nuclia.sdk.agent + import NucliaAgent\\nfrom nuclia_models.agent.interaction import AnswerOperation\\n\\nagent + = NucliaAgent()\\ngenerator = agent.interact(question=\\\"Help me with X\\\")\\n\\nfor + response in generator:\\n if response.operation == AnswerOperation.AGENT_REQUEST:\\n + \ # Agent is requesting user input\\n user_input = input(f\\\"Agent + asks: {response.feedback.question}\\\\n> \\\")\\n # Send response back\\n + \ generator.send(user_input)\\n elif response.answer:\\n print(response.answer)\\n```\\n\\n### + Error Handling\\n\\n```python\\nfrom nuclia.sdk.agent import NucliaAgent\\nfrom + nuclia.exceptions import RaoAPIException\\n\\nagent = NucliaAgent()\\n\\ntry:\\n + \ for response in agent.interact(question=\\\"Hello?\\\"):\\n if + response.exception:\\n print(f\\\"Agent error: {response.exception.detail}\\\")\\n + \ elif response.answer:\\n print(response.answer)\\nexcept + RaoAPIException as e:\\n print(f\\\"API error: {e.detail}\\\")\\nexcept + Exception as e:\\n print(f\\\"Unexpected error: {e}\\\")\\n```\\n\\n### + Passing Custom Headers to MCP\\n\\nIf your Retrieval Agents Orchestrator requires + custom headers for MCP Agents, you can pass them as follows:\\n\\n**CLI:**\\n```bash\\nnuclia + agent interact \\\"What is AI?\\\" --headers '{\\\"X-Custom-Header\\\": \\\"value\\\"}'\\n```\\n\\n**SDK:**\\n```python\\nfrom + nuclia.sdk.agent import NucliaAgent\\n\\nagent = NucliaAgent()\\nfor response + in agent.interact(\\n question=\\\"What is AI?\\\",\\n headers={\\\"X-Custom-Header\\\": + \\\"value\\\"}\\n):\\n if response.answer:\\n print(response.answer)\\n```\\n\\nPlease + ensure that the 'Allowed Headers' configuration in your MCP agent includes + any custom headers you wish to use.\\n\\n## Best Practices\\n\\n1. **Use Sessions + for Context**: Create sessions when you need multi-turn conversations with + context retention\\n2. **Use Ephemeral Sessions for One-offs**: Don't supply + a session UUID for using agents in a stateless manner.\\n3. **Stream for UX**: + Process responses as they arrive for better user experience\\n4. **Handle + All Operations**: Check for different operation types (START, ANSWER, DONE, + ERROR) when processing responses\\n5. **Clean Up Sessions**: Delete sessions + when done to avoid clutter\\n6. **Use Interactive CLI**: For manual testing + and exploration, the interactive CLI provides the best experience\\n\",\"format\":\"MARKDOWN\",\"md5\":\"bbaaf8cccd2b664ba4f7daf47d1f2bf4\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"Retrieval + Agents Orchestrator \\n Interact with Nuclia's Retrieval Agents Orchestrator + to have intelligent conversations over several knowledge sources with persistent + session management and real-time streaming responses. \\n Prerequisites \\n + Install the Nuclia SDK: \\n sh \\n pip install nuclia \\n Ensure you have: + \\n - A valid Nuclia authentication token (see Authentication) \\n - Access + to a configured Retrieval Agent \\n Overview \\n The nuclia.py library provides + several ways to interact with your Retrieval Agents Orchestrators: \\n \\n + Interactive CLI: A rich, user-friendly terminal interface (recommended) \\n + Standard CLI: Direct access to raw websocket messages for debugging \\n Session + Management: Create and manage persistent conversation sessions \\n Programmatic + API: Python SDK for building custom applications \\n \\n Listing Available + Agents \\n Discover what Retrieval Agents Orchestrators you have access to. + \\n \\n CLI: \\n \\n sh \\n nuclia agents list \\n \\n SDK: \\n \\n ```python + \\n from nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() + \\n all_agents = agents.list() \\n for agent in all_agents: \\n print(f Agent: + {agent.title} ({agent.id}) ) \\n print(f Slug: {agent.slug} ) \\n print(f + Zone: {agent.zone} ) \\n ``` \\n Getting a Specific Agent \\n \\n CLI: \\n + \\n sh \\n nuclia agents get --account= my-account --id= agent-uuid --zone= + europe-1 \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agents import + NucliaAgents \\n agents = NucliaAgents() \\n agent_details = agents.get( \\n + account= my-account , \\n id= agent-uuid , \\n zone= europe-1 \\n ) \\n print(agent_details) + \\n ``` \\n Setting a Default Agent \\n \\n CLI: \\n \\n sh \\n nuclia agents + default [AGENT_SLUG or AGENT_UUID] \\n \\n SDK: \\n \\n ```python \\n from + nuclia.sdk.agents import NucliaAgents \\n agents = NucliaAgents() \\n agents.default( + my-agent ) \\n ``` \\n This sets the default agent for all subsequent operations. + \\n Interactive CLI (Recommended) \\n The interactive CLI provides a beautiful, + real-time interface for conversing with your Retrieval Agents Orchestrator. + \\n Starting the Interactive CLI \\n \\n CLI: \\n \\n sh \\n nuclia agent + cli interact \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import + NucliaAgent \\n agent = NucliaAgent() \\n agent.cli.interact() \\n ``` \\n + This launches an interactive terminal session where you can: \\n - Ask questions + and see streaming responses \\n - View processing steps in real-time \\n - + Manage conversation sessions \\n - See retrieved context and citations \\n + Interactive CLI Commands \\n The CLI supports several commands (prefix with + /): \\n | Command | Description | \\n |---------|-------------| \\n | /help + | Show available commands | \\n | /new_session | Create a new persistent session + | \\n | /list_sessions | List all your sessions | \\n | /change_session | + Switch to a different session, use 'ephemeral' for a temporary session | \\n + | /clear | Clear the screen | \\n | /exit | Exit the CLI | \\n Please note + that all commands related to sessions require a Retrieval Agent Orchestrator + with the option Agent with memory enabled during creation. \\n Session Management + \\n Sessions allow you to maintain conversation context across multiple interactions. + \\n \\n This feature will only be available if you checked Agent with memory + during the creation of your Retrieval Agents Orchestrator. \\n \\n Creating + a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session new --name= My + Research Session \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent + import NucliaAgent \\n agent = NucliaAgent() \\n session_uuid = agent.session.new( + My Research Session ) \\n print(f Created session: {session_uuid} ) \\n ``` + \\n Listing Sessions \\n \\n CLI: \\n \\n sh \\n nuclia agent session list + \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent import NucliaAgent + \\n agent = NucliaAgent() \\n sessions = agent.session.list() \\n for session + in sessions.resources: \\n print(f {session.title}: {session.id} ) \\n ``` + \\n Getting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent session get + --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python \\n from nuclia.sdk.agent + import NucliaAgent \\n agent = NucliaAgent() \\n session = agent.session.get(session_uuid) + \\n print(f Session: {session.title} ) \\n print(f Created: {session.created} + ) \\n ``` \\n Deleting a Session \\n \\n CLI: \\n \\n sh \\n nuclia agent + session delete --session_uuid=[SESSION_UUID] \\n \\n SDK: \\n \\n ```python + \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n + agent.session.delete(session_uuid) \\n ``` \\n Interaction \\n Aside from + the interactive CLI, you can interact with your Retrieval Agents Orchestrator + with the simple CLI or programmatically using the SDK. \\n Basic Interaction + \\n CLI: \\n bash \\n nuclia agent interact What is Eric known for? \\n SDK: + \\n ```python \\n from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() + \\n Iterate over streaming responses \\n for response in agent.interact( \\n + question= What is Eric known for? \\n ): \\n if response.operation == ANSWER + and response.answer: \\n print(response.answer) \\n elif response.step: \\n + print(f Processing: {response.step.module} ) \\n ``` \\n Not supplying a session_uuid + when calling interact will use an ephemeral session by default. To maintain + context, provide a persistent session UUID. \\n Using Persistent Sessions + \\n CLI: \\n ```bash \\n nuclia agent sessions new Customer Support Chat \\n + Note the session UUID returned \\n nuclia agent interact What are your business + hours? --session_uuid= SESSION_UUID \\n nuclia agent interact Are you open + on weekends? --session_uuid= SESSION_UUID \\n ``` \\n SDK: \\n ```python \\n + from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n Create + a session \\n session_uuid = agent.session.new( Customer Support Chat ) \\n + Have a conversation with context \\n for response in agent.interact( \\n session_uuid=session_uuid, + \\n question= What are your business hours? \\n ): \\n if response.answer: + \\n print(response.answer) \\n Follow-up question maintains context \\n for + response in agent.interact( \\n session_uuid=session_uuid, \\n question= Are + you open on weekends? \\n ): \\n if response.answer: \\n print(response.answer) + \\n ``` \\n Understanding Response Types \\n When interacting with an agent, + you receive a stream of AragAnswer objects with different operations: \\n + | Operation | Description | \\n |-----------|-------------| \\n | START | + Interaction has begun | \\n | ANSWER | Processing step or partial answer | + \\n | DONE | Interaction complete | \\n | ERROR | An error occurred | \\n + | AGENT_REQUEST | Agent needs user feedback | \\n Response Attributes \\n + Each response may contain: \\n \\n step: Information about the current processing + step \\n module: The module being executed (e.g., rephrase , basic_ask , remi + ) \\n title: Display title for the step \\n value: Result of the step \\n + reason: Explanation for the step \\n timeit: Time taken in seconds \\n \\n + input_nuclia_tokens/output_nuclia_tokens: Token usage \\n \\n \\n context: + Retrieved context from the knowledge base \\n \\n chunks: List of retrieved + text chunks with sources \\n \\n summary: Summary of the context or partial + answer \\n \\n \\n answer: The final answer text (Markdown formatted) \\n + \\n \\n generated_text: Intermediate generated text \\n \\n \\n possible_answer: + Alternative answer being considered \\n \\n \\n exception: Error details if + something went wrong \\n \\n \\n Processing Responses \\n ```python \\n from + nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction + import AnswerOperation \\n agent = NucliaAgent() \\n for response in agent.interact(question= + Tell me about AI ): \\n if response.operation == AnswerOperation.START: \\n + print( Starting... ) \\n elif response.step: \\n print(f Step: {response.step.module} + ({response.step.timeit:.2f}s) ) \\n \\n elif response.context: \\n print(f + Retrieved {len(response.context.chunks)} chunks ) \\n for chunk in response.context.chunks: + \\n print(f - {chunk.title}: {chunk.text[:100]}... ) \\n \\n elif response.answer: + \\n print(f \\\\nFinal Answer:\\\\n{response.answer} ) \\n \\n elif response.operation + == AnswerOperation.DONE: \\n print( Complete! ) \\n \\n elif response.operation + == AnswerOperation.ERROR: \\n print(f Error: {response.exception.detail if + response.exception else 'Unknown'} ) \\n \\n ``` \\n Standard CLI for Raw + Messages \\n For debugging or advanced use cases, you can access raw websocket + messages programmatically: \\n ```python \\n from nuclia.sdk.agent import + NucliaAgent \\n agent = NucliaAgent() \\n Iterate over all messages \\n for + message in agent.interact( \\n question= What is RAO? \\n ): \\n # message + is an AragAnswer object with all raw data \\n print(f Operation: {message.operation} + ) \\n print(f Raw message: {message.model_dump_json(indent=2)} ) \\n ``` \\n + This gives you direct access to all websocket message data for debugging or + custom processing. \\n Advanced Features \\n Agent Feedback Requests \\n Agents + can request additional input from users during processing: \\n ```python \\n + from nuclia.sdk.agent import NucliaAgent \\n from nuclia_models.agent.interaction + import AnswerOperation \\n agent = NucliaAgent() \\n generator = agent.interact(question= + Help me with X ) \\n for response in generator: \\n if response.operation + == AnswerOperation.AGENT_REQUEST: \\n # Agent is requesting user input \\n + user_input = input(f Agent asks: {response.feedback.question}\\\\n> ) \\n + # Send response back \\n generator.send(user_input) \\n elif response.answer: + \\n print(response.answer) \\n ``` \\n Error Handling \\n ```python \\n from + nuclia.sdk.agent import NucliaAgent \\n from nuclia.exceptions import RaoAPIException + \\n agent = NucliaAgent() \\n try: \\n for response in agent.interact(question= + Hello? ): \\n if response.exception: \\n print(f Agent error: {response.exception.detail} + ) \\n elif response.answer: \\n print(response.answer) \\n except RaoAPIException + as e: \\n print(f API error: {e.detail} ) \\n except Exception as e: \\n print(f + Unexpected error: {e} ) \\n ``` \\n Passing Custom Headers to MCP \\n If your + Retrieval Agents Orchestrator requires custom headers for MCP Agents, you + can pass them as follows: \\n CLI: \\n bash \\n nuclia agent interact What + is AI? --headers '{ X-Custom-Header : value }' \\n SDK: \\n ```python \\n + from nuclia.sdk.agent import NucliaAgent \\n agent = NucliaAgent() \\n for + response in agent.interact( \\n question= What is AI? , \\n headers={ X-Custom-Header + : value } \\n ): \\n if response.answer: \\n print(response.answer) \\n ``` + \\n Please ensure that the 'Allowed Headers' configuration in your MCP agent + includes any custom headers you wish to use. \\n Best Practices \\n \\n Use + Sessions for Context: Create sessions when you need multi-turn conversations + with context retention \\n Use Ephemeral Sessions for One-offs: Don't supply + a session UUID for using agents in a stateless manner. \\n Stream for UX: + Process responses as they arrive for better user experience \\n Handle All + Operations: Check for different operation types (START, ANSWER, DONE, ERROR) + when processing responses \\n Clean Up Sessions: Delete sessions when done + to avoid clutter \\n Use Interactive CLI: For manual testing and exploration, + the interactive CLI provides the best experience \\n 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[`UsageMetric`](UsageMetric.md)\\n\\n## + Properties\\n\\n### details\\n\\n> **details**: [`NucliaTokensDetails`](NucliaTokensDetails.md)[]\\n\\n#### + Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`details`](UsageMetric.md#details)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:185](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L185)\\n\\n***\\n\\n### + name\\n\\n> **name**: `\\\"nuclia_tokens\\\"`\\n\\n#### Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`name`](UsageMetric.md#name)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:183](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L183)\\n\\n***\\n\\n### + value\\n\\n> **value**: `number`\\n\\n#### Overrides\\n\\n[`UsageMetric`](UsageMetric.md).[`value`](UsageMetric.md#value)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:184](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L184)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"af7b6aa34935b09fa5ddc2badd6da04f\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / NucliaTokensMetric \\n Interface: NucliaTokensMetric + \\n Extends \\n \\n UsageMetric \\n \\n Properties \\n details \\n \\n details: + NucliaTokensDetails[] \\n \\n Overrides \\n UsageMetric.details \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n name \\n \\n name: + nuclia_tokens \\n \\n Overrides \\n UsageMetric.name \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:183 + \\n \\n value \\n \\n value: number \\n \\n Overrides \\n UsageMetric.value + \\n Defined in \\n 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\\n\",\"id\":\"8b3e0ef630a346d1b591143309db87ec/t/page/0-281\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":281,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0d01e250360a4d6c91f3baf2de5e7d38\":{\"id\":\"0d01e250360a4d6c91f3baf2de5e7d38\",\"slug\":\"docs-develop-js-sdk-interfaces-ReasoningConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ReasoningConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-02-24T11:15:01.495997\",\"modified\":\"2026-07-14T12:49:30.245034\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ReasoningConfig\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ReasoningConfig\\n\\n# + Interface: ReasoningConfig\\n\\n## Properties\\n\\n### budget\\\\_tokens?\\n\\n> + `optional` **budget\\\\_tokens**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:647](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L647)\\n\\n***\\n\\n### + effort?\\n\\n> `optional` **effort**: [`NumericReasoningEffort`](../enumerations/NumericReasoningEffort.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:648](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L648)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"940c8be17c938dcc14e4abb000b0f8b5\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ReasoningConfig \\n Interface: ReasoningConfig + \\n Properties \\n budget_tokens? \\n \\n optional budget_tokens: number \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 \\n \\n effort? + \\n \\n optional effort: NumericReasoningEffort \\n \\n Defined in \\n 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> develop > js sdk > interfaces > ReasoningConfig\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > ReasoningConfig\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224\":{\"score\":0.6052000522613525,\"score_type\":\"VECTOR\",\"order\":9,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ReasoningConfig \\n Interface: ReasoningConfig + \\n Properties \\n budget_tokens? \\n \\n optional budget_tokens: number \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:647 \\n \\n effort? + \\n\",\"id\":\"0d01e250360a4d6c91f3baf2de5e7d38/t/page/0-224\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":224,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"66b6f0dbd883413e98fbbf5b59f049b9\":{\"id\":\"66b6f0dbd883413e98fbbf5b59f049b9\",\"slug\":\"docs-develop-js-sdk-enumerations-UsageType-md\",\"title\":\"docs + > develop > js sdk > enumerations > UsageType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"tl\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T09:59:02.349911\",\"modified\":\"2026-07-14T12:54:11.386825\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/enumerations/UsageType\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / UsageType\\n\\n# + Enumeration: UsageType\\n\\n## Enumeration Members\\n\\n### AI\\\\_TOKENS\\\\_USED\\n\\n> + **AI\\\\_TOKENS\\\\_USED**: `\\\"ai_tokens_used\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:206](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L206)\\n\\n***\\n\\n### + BYTES\\\\_PROCESSED\\n\\n> **BYTES\\\\_PROCESSED**: `\\\"bytes_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:197](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L197)\\n\\n***\\n\\n### + CHARS\\\\_PROCESSED\\n\\n> **CHARS\\\\_PROCESSED**: `\\\"chars_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:198](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L198)\\n\\n***\\n\\n### + MEDIA\\\\_FILES\\\\_PROCESSED\\n\\n> **MEDIA\\\\_FILES\\\\_PROCESSED**: `\\\"media_files_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:200](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L200)\\n\\n***\\n\\n### + MEDIA\\\\_SECONDS\\\\_PROCESSED\\n\\n> **MEDIA\\\\_SECONDS\\\\_PROCESSED**: + `\\\"media_seconds_processed\\\"`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:199](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L199)\\n\\n***\\n\\n### + NUCLIA\\\\_TOKENS\\n\\n> **NUCLIA\\\\_TOKENS**: `\\\"nuclia_tokens_billed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:207](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L207)\\n\\n***\\n\\n### + PAGES\\\\_PROCESSED\\n\\n> **PAGES\\\\_PROCESSED**: `\\\"pages_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:201](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L201)\\n\\n***\\n\\n### + PARAGRAPHS\\\\_PROCESSED\\n\\n> **PARAGRAPHS\\\\_PROCESSED**: `\\\"paragraphs_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:202](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L202)\\n\\n***\\n\\n### + PRE\\\\_PROCESSING\\\\_TIME\\n\\n> **PRE\\\\_PROCESSING\\\\_TIME**: `\\\"pre_processing_time\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:194](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L194)\\n\\n***\\n\\n### + RESOURCES\\\\_PROCESSED\\n\\n> **RESOURCES\\\\_PROCESSED**: `\\\"resources_processed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:196](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L196)\\n\\n***\\n\\n### + SEARCHES\\\\_PERFORMED\\n\\n> **SEARCHES\\\\_PERFORMED**: `\\\"searches_performed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:204](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L204)\\n\\n***\\n\\n### + SLOW\\\\_PROCESSING\\\\_TIME\\n\\n> **SLOW\\\\_PROCESSING\\\\_TIME**: `\\\"slow_processing_time\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:195](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L195)\\n\\n***\\n\\n### + SUGGESTIONS\\\\_PERFORMED\\n\\n> **SUGGESTIONS\\\\_PERFORMED**: `\\\"suggestions_performed\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:205](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L205)\\n\\n***\\n\\n### + TRAIN\\\\_SECONDS\\n\\n> **TRAIN\\\\_SECONDS**: `\\\"train_seconds\\\"`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:203](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/db.models.ts#L203)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"a6825b7bf9d5960444b0981f205811a3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / UsageType \\n Enumeration: UsageType \\n + Enumeration Members \\n AI_TOKENS_USED \\n \\n AI_TOKENS_USED: ai_tokens_used + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:206 \\n \\n BYTES_PROCESSED + \\n \\n BYTES_PROCESSED: bytes_processed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:197 + \\n \\n CHARS_PROCESSED \\n \\n CHARS_PROCESSED: chars_processed \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:198 \\n \\n MEDIA_FILES_PROCESSED + \\n \\n MEDIA_FILES_PROCESSED: media_files_processed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:200 \\n \\n MEDIA_SECONDS_PROCESSED + \\n \\n MEDIA_SECONDS_PROCESSED: media_seconds_processed \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n + NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 + \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED + \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n + \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 + \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED + \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 + \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED + \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: + train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":1833,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:54:13.123173Z\",\"last_understanding\":\"2026-07-14T12:54:12.864112Z\",\"last_extract\":\"2026-07-14T12:54:12.463871Z\",\"last_processing_start\":\"2026-07-14T12:54:12.433665Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > enumerations > UsageType\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > enumerations > UsageType\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833\":{\"score\":0.6058452725410461,\"score_type\":\"VECTOR\",\"order\":8,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / UsageType \\n Enumeration: UsageType \\n + Enumeration Members \\n AI_TOKENS_USED \\n \\n AI_TOKENS_USED: ai_tokens_used + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:206 \\n \\n BYTES_PROCESSED + \\n \\n BYTES_PROCESSED: bytes_processed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:197 + \\n \\n CHARS_PROCESSED \\n \\n CHARS_PROCESSED: chars_processed \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:198 \\n \\n MEDIA_FILES_PROCESSED + \\n \\n MEDIA_FILES_PROCESSED: media_files_processed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:200 \\n \\n MEDIA_SECONDS_PROCESSED + \\n \\n MEDIA_SECONDS_PROCESSED: media_seconds_processed \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/db.models.ts:199 \\n \\n NUCLIA_TOKENS \\n \\n + NUCLIA_TOKENS: nuclia_tokens_billed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:207 + \\n \\n PAGES_PROCESSED \\n \\n PAGES_PROCESSED: pages_processed \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:201 \\n \\n PARAGRAPHS_PROCESSED + \\n \\n PARAGRAPHS_PROCESSED: paragraphs_processed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:202 \\n \\n PRE_PROCESSING_TIME \\n + \\n PRE_PROCESSING_TIME: pre_processing_time \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:194 + \\n \\n RESOURCES_PROCESSED \\n \\n RESOURCES_PROCESSED: resources_processed + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:196 \\n \\n SEARCHES_PERFORMED + \\n \\n SEARCHES_PERFORMED: searches_performed \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:204 + \\n \\n SLOW_PROCESSING_TIME \\n \\n SLOW_PROCESSING_TIME: slow_processing_time + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:195 \\n \\n SUGGESTIONS_PERFORMED + \\n \\n SUGGESTIONS_PERFORMED: suggestions_performed \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:205 \\n \\n TRAIN_SECONDS \\n \\n TRAIN_SECONDS: + train_seconds \\n \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:203\",\"id\":\"66b6f0dbd883413e98fbbf5b59f049b9/t/page/0-1833\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":1833,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"0a003c3f724e45e392a9c8d1ce8800c1\":{\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1\",\"slug\":\"docs-develop-js-sdk-interfaces-Consumption-md\",\"title\":\"docs + > develop > js sdk > interfaces > Consumption\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-12-09T11:51:46.788864\",\"modified\":\"2026-07-14T12:51:15.300757\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/Consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / Consumption\\n\\n# + Interface: Consumption\\n\\n## Properties\\n\\n### customer\\\\_key\\\\_tokens\\n\\n> + **customer\\\\_key\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:230](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L230)\\n\\n***\\n\\n### + normalized\\\\_tokens\\n\\n> **normalized\\\\_tokens**: [`TokenConsumption`](TokenConsumption.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:229](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L229)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"654b0dfe17ab08959c78891dd24c3424\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption + \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n + \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":349,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:16.563837Z\",\"last_understanding\":\"2026-07-14T12:51:16.208384Z\",\"last_extract\":\"2026-07-14T12:51:15.984803Z\",\"last_processing_start\":\"2026-07-14T12:51:15.966495Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > Consumption\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > Consumption\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\":{\"score\":0.6083368062973022,\"score_type\":\"VECTOR\",\"order\":7,\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / Consumption \\n Interface: Consumption + \\n Properties \\n customer_key_tokens \\n \\n customer_key_tokens: TokenConsumption + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:230 \\n + \\n normalized_tokens \\n \\n normalized_tokens: TokenConsumption \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:229\",\"id\":\"0a003c3f724e45e392a9c8d1ce8800c1/t/page/0-349\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":349,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"4039d76b0fff4962900836ab3fdec9f7\":{\"id\":\"4039d76b0fff4962900836ab3fdec9f7\",\"slug\":\"docs-rag-advanced-consumption-mdx\",\"title\":\"docs + > rag > advanced > consumption.\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-10-03T08:32:26.341394\",\"modified\":\"2026-06-09T08:18:16.730959\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/consumption\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + consumption\\ntitle: Token consumption\\n---\\n\\nimport Tabs from \\\"@theme/Tabs\\\";\\nimport + TabItem from \\\"@theme/TabItem\\\";\\n\\n# Token consumption\\n\\nAgentic + RAG is a license and consumption-based service. This means that you pay for + the computational resources you consume. The consumption is measured in **Agentic + RAG tokens**.\\nAll public 3rd-party LLMs base their pricing on the number + of tokens consumed. In the LLM world, a token is around 4-5 characters on + average, which might fit an entire word or be split into parts. The number + of tokens is proportional to the amount of text, measured in chunks of 4-5 + characters. It closely relates to words but not entirely. The longer a sentence + is, the more tokens it will consume to read or to generate it.\\nSince all + these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize + the cost across all of them.\\n\\n## How Tokens Are Consumed in RAG\\n\\nWhen + a user asks a question to your Knowledge Box, the token consumption process + follows these steps:\\n\\n1. **Question Processing**: The system finds the + most relevant paragraphs to answer the question\\n2. **Context Assembly**: + These paragraphs are used as context when calling the LLM model\\n3. **Prompt + Creation**: Agentic RAG assembles the **prompt**, **context**, and **question** + into a single string\\n4. **LLM Processing**: This complete string is sent + to the LLM, corresponding to a certain number of **input tokens**\\n5. **Answer + Generation**: The LLM generates the answer, which corresponds to a certain + number of **output tokens**\\n\\n**Total consumption** = Input tokens + Output + tokens + Image tokens\\n\\n### Factors That Impact Token Consumption\\n\\nToken + consumption is directly affected by:\\n\\n- **Large context**: Results from + using RAG strategies like \\\"Full resource\\\" or \\\"Neighbouring paragraphs\\\", + or from using the `extra_context` parameter\\n- **Long questions**: More detailed + or complex questions require more input tokens\\n- **Long prompts**: Extensive + system prompts increase the input token count\\n- **Detailed answers**: Comprehensive + responses require more output tokens\\n- **Images in context**: When using + multimodal models, images included in the retrieved context significantly + increase token consumption\\n\\n## How to Limit and Control Token Consumption\\n\\n### + Strategy 1: Optimize Your Parameters\\n\\nThe first approach to reducing token + consumption is to fine-tune your request parameters:\\n\\n- **Optimize prompts**: + Ensure your prompts are concise and focused, avoiding unnecessary verbosity\\n- + **Control resource scope**: When using the \\\"Full resource\\\" strategy, + use the `count` attribute to limit the number of resources returned\\n- **Tune + neighboring context**: For the \\\"Neighbouring paragraphs\\\" strategy, optimize + the `before` and `after` attributes to balance context quality with token + efficiency\\n- **Manage summary length**: When using the \\\"Hierarchical\\\" + strategy, ensure that resource summaries are appropriately sized\\n- **Choose + efficient models**: Select LLMs that offer better token efficiency (typically, + ChatGPT 4o-mini is more cost-effective than ChatGPT 4o)\\n\\n### Strategy + 2: Set Hard Limits\\n\\nYou can implement safeguards against excessive token + consumption:\\n\\nUse the `max_tokens` parameter on the [`/ask` endpoint](/docs/api#tag/Search/operation/ask_knowledgebox_endpoint_kb__kbid__ask_post) + to set hard limits on:\\n- **Context size**: Limits the amount of retrieved + information sent to the LLM\\n- **Answer length**: Limits the length of the + generated response\\n\\n#### Important Considerations\\n\\n**Context Limitations**:\\n- + Restricting context size may result in less relevant answers since the LLM + has less information to work with\\n- Balance between cost control and answer + quality\\n\\n**Answer Length Limitations**:\\n- The LLM might not complete + its response if it hits the token limit, potentially cutting sentences mid-way\\n- + **Recommended approach**: Include length requirements in your prompt (e.g., + \\\"Please answer in less than 200 words\\\") rather than relying solely on + hard limits\\n- This allows the LLM to naturally conclude its response within + the desired length\\n\\n## How to Monitor Token Consumption\\n\\n### Understanding + Token Consumption Data\\n\\nYou can receive detailed token consumption information + from the following endpoints that utilize LLM models: `ask`, `chat`, `remi`, + `query`, `sentence`, `summarize`, `tokens`, and `rerank`.\\n\\n:::note\\nThe + `rephrase` endpoint currently does not support token consumption monitoring.\\n:::\\n\\nTo + receive token consumption data, you must include the following header in your + request:\\n```\\nX-SHOW-CONSUMPTION: true\\n```\\n\\nThe token consumption + data is provided in different formats depending on the response type:\\n- + **Streaming responses** (`application/x-ndjson`): Token consumption appears + as a separate JSON chunk with type \\\"consumption\\\"\\n- **Standard responses** + (`application/json`): Token consumption is included in a \\\"consumption\\\" + field within the main response\\n\\n### Token Consumption Response Format\\n\\n\\n \\n ```json\\n {\\n \\\"item\\\": + {\\n \\\"type\\\": \\\"consumption\\\",\\n \\\"normalized_tokens\\\": + {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": + 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": + 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n + \ }\\n }\\n ```\\n \\n \\n ```json\\n {\\n \\\"consumption\\\": {\\n \\\"normalized_tokens\\\": + {\\n \\\"input\\\": 13,\\n \\\"output\\\": 34,\\n \\\"image\\\": + 0.0\\n },\\n \\\"customer_key_tokens\\\": {\\n \\\"input\\\": + 0.0,\\n \\\"output\\\": 0.0,\\n \\\"image\\\": 0.0\\n }\\n + \ }\\n }\\n ```\\n \\n\\n\\n### Understanding + Token Types\\n\\n**Normalized Tokens** (`normalized_tokens`):\\n- These represent + the number of Agentic RAG tokens consumed and that you will be billed for\\n- + Values are normalized across different LLM providers for consistent billing\\n- + Include separate counts for:\\n - `input`: Tokens used for the prompt, context, + and question\\n - `output`: Tokens used for the generated response\\n - + `image`: Tokens used for image processing (when applicable)\\n\\n**Customer + Key Tokens** (`customer_key_tokens`):\\n- These represent tokens consumed + when using your own LLM API keys\\n- These tokens are **not billed** by Agentic + RAG since you're using your own API keys\\n- Values are also normalized for + comparison purposes across different providers\\n\",\"format\":\"MARKDOWN\",\"md5\":\"204fe47dbd7eb38d465d05fa7538e51e\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: consumption \\n title: Token consumption \\n \\n import Tabs from + @theme/Tabs ; \\n import TabItem from @theme/TabItem ; \\n Token consumption + \\n Agentic RAG is a license and consumption-based service. This means that + you pay for the computational resources you consume. The consumption is measured + in Agentic RAG tokens. \\n All public 3rd-party LLMs base their pricing on + the number of tokens consumed. In the LLM world, a token is around 4-5 characters + on average, which might fit an entire word or be split into parts. The number + of tokens is proportional to the amount of text, measured in chunks of 4-5 + characters. It closely relates to words but not entirely. The longer a sentence + is, the more tokens it will consume to read or to generate it. \\n Since all + these 3rd-party LLMs have different pricing, Agentic RAG tokens serve to normalize + the cost across all of them. \\n How Tokens Are Consumed in RAG \\n When a + user asks a question to your Knowledge Box, the token consumption process + follows these steps: \\n \\n Question Processing: The system finds the most + relevant paragraphs to answer the question \\n Context Assembly: These paragraphs + are used as context when calling the LLM model \\n Prompt Creation: Agentic + RAG assembles the prompt, context, and question into a single string \\n LLM + Processing: This complete string is sent to the LLM, corresponding to a certain + number of input tokens \\n Answer Generation: The LLM generates the answer, + which corresponds to a certain number of output tokens \\n \\n Total consumption + = Input tokens + Output tokens + Image tokens \\n Factors That Impact Token + Consumption \\n Token consumption is directly affected by: \\n \\n Large context: + Results from using RAG strategies like Full resource or Neighbouring paragraphs + , or from using the extra_context parameter \\n Long questions: More detailed + or complex questions require more input tokens \\n Long prompts: Extensive + system prompts increase the input token count \\n Detailed answers: Comprehensive + responses require more output tokens \\n Images in context: When using multimodal + models, images included in the retrieved context significantly increase token + consumption \\n \\n How to Limit and Control Token Consumption \\n Strategy + 1: Optimize Your Parameters \\n The first approach to reducing token consumption + is to fine-tune your request parameters: \\n \\n Optimize prompts: Ensure + your prompts are concise and focused, avoiding unnecessary verbosity \\n Control + resource scope: When using the Full resource strategy, use the count attribute + to limit the number of resources returned \\n Tune neighboring context: For + the Neighbouring paragraphs strategy, optimize the before and after attributes + to balance context quality with token efficiency \\n Manage summary length: + When using the Hierarchical strategy, ensure that resource summaries are appropriately + sized \\n Choose efficient models: Select LLMs that offer better token efficiency + (typically, ChatGPT 4o-mini is more cost-effective than ChatGPT 4o) \\n \\n + Strategy 2: Set Hard Limits \\n You can implement safeguards against excessive + token consumption: \\n Use the max_tokens parameter on the /ask endpoint to + set hard limits on: \\n - Context size: Limits the amount of retrieved information + sent to the LLM \\n - Answer length: Limits the length of the generated response + \\n Important Considerations \\n Context Limitations: \\n - Restricting context + size may result in less relevant answers since the LLM has less information + to work with \\n - Balance between cost control and answer quality \\n Answer + Length Limitations: \\n - The LLM might not complete its response if it hits + the token limit, potentially cutting sentences mid-way \\n - Recommended approach: + Include length requirements in your prompt (e.g., Please answer in less than + 200 words ) rather than relying solely on hard limits \\n - This allows the + LLM to naturally conclude its response within the desired length \\n How to + Monitor Token Consumption \\n Understanding Token Consumption Data \\n You + can receive detailed token consumption information from the following endpoints + that utilize LLM models: ask, chat, remi, query, sentence, summarize, tokens, + and rerank. \\n :::note \\n The rephrase endpoint currently does not support + token consumption monitoring. \\n ::: \\n To receive token consumption data, + you must include the following header in your request: \\n X-SHOW-CONSUMPTION: + true \\n The token consumption data is provided in different formats depending + on the response type: \\n - Streaming responses (application/x-ndjson): Token + consumption appears as a separate JSON chunk with type consumption \\n - Standard + responses (application/json): Token consumption is included in a consumption + field within the main response \\n Token Consumption Response Format \\n \\n + \\n json \\n { \\n item : { \\n type : consumption , \\n normalized_tokens + : { \\n input : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens + : { \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n + \\n \\n json \\n { \\n consumption : { \\n normalized_tokens : { \\n input + : 13, \\n output : 34, \\n image : 0.0 \\n }, \\n customer_key_tokens : { + \\n input : 0.0, \\n output : 0.0, \\n image : 0.0 \\n } \\n } \\n } \\n \\n + \\n Understanding Token Types \\n Normalized Tokens (normalized_tokens): \\n + - These represent the number of Agentic RAG tokens consumed and that you will + be billed for \\n - Values are normalized across different LLM providers for + consistent billing \\n - Include separate counts for: \\n - input: Tokens + used for the prompt, context, and question \\n - output: Tokens used for the + generated response \\n - image: Tokens used for image processing (when applicable) + \\n Customer Key Tokens (customer_key_tokens): \\n - These represent tokens + consumed when using your own LLM API keys \\n - These tokens are not billed + by Agentic RAG since you're using your own API keys \\n - Values are also + normalized for comparison purposes across different 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Context size: Limits the amount of retrieved information sent to the LLM + \\n - Answer length: Limits the length of the generated response \\n Important + Considerations \\n Context Limitations: \\n\",\"id\":\"4039d76b0fff4962900836ab3fdec9f7/t/page/3075-3340\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":6,\"start\":3075,\"end\":3340,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"89cc367c149e4f6eab0e06a743d1edba\":{\"id\":\"89cc367c149e4f6eab0e06a743d1edba\",\"slug\":\"docs-rag-advanced-openai-api-compatible-models-md\",\"title\":\"docs + > rag > advanced > openai api compatible models\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-05-23T07:21:32.894218\",\"modified\":\"2026-06-09T08:07:43.359058\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/rag/advanced/openai-api-compatible-models\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + openai-api-compatible-models\\ntitle: Connect to any OpenAI API compatible + LLM\\n---\\n\\n# Connect to any OpenAI API compatible LLM\\n\\nAgentic RAG + allows you to connect to any OpenAI API compatible LLM. This means that you + can use any LLM that has an API compatible with the OpenAI API which has become + a standard in the industry.\\n\\nMany of the options for self-hosted LLMs, + open-source LLMs hosted by cloud providers or commercial LLMs are compatible + with the OpenAI API. This means that you can use them with Agentic RAG without + any modifications.\\n\\n## Configuration\\n\\nTo modify your knowledge box + configuration you can do so in three manners, through the API, the Nuclia + CLI / SDK or the Agentic RAG dashboard.\\n\\nThe Agentic RAG dashboard offers + the most user-friendly way to modify the configuration of your knowledge box + and we will use it in this example.\\n\\nWe will be setting up a connection + to the **Phi 4 Reasoning Plus** model, hosted by **OpenRouter** which offers + a wide range of open-source and commercial models compatible with the OpenAI + API. We can see more information about this specific model [here](https://openrouter.ai/microsoft/phi-4-reasoning-plus:free), + the API parameters are located under the **API** tab.\\n\\n1. **Open the AI + Models page** \\n In the left sidebar under **Advanced**, click **AI Models**.\\n2. + **Select \u201COpenAI API Compatible Model\u201D** \\n From the models + list, choose **OpenAI API Compatible Model**.\\n3. **Enable custom Key** \\n + \ Toggle the option for using you own `OpenAI API Compatible Key` if it is + not already enabled.\\n4. **Fill in the configuration parameters**\\n\\n - + **API Key**:\\n - Description: The API key for your LLM. This is the key + that you would use as an authorization header in the API. You may leave this + blank if the endpoint you are connecting to does not require an API key.\\n + \ - Example: We will set this to our OpenRouter API key.\\n - **API URL**:\\n + \ - Description: The URL of the API endpoint for your LLM. This may be + shared between multiple models.\\n - Example: For OpenRouter, it is the + same for all models: `https://openrouter.ai/api/v1`\\n - **Model**:\\n - + Description: The name of the model you want to use, it needs to exactly match + the name of the model in the API.\\n - Example: For Phi 4 Reasoning Plus + in the OpenRouter API, it is `microsoft/phi-4-reasoning-plus:free`.\\n - + **Maximum supported input tokens**:\\n - Description: The maximum number + of tokens that the model can accept as input. Be mindful that this takes into + account the tokens used in the prompt, query and context. Also take note that + some models may provide their context window as the total between input and + output tokens, while others may provide it as the input tokens only.\\n - + Example: For Phi 4 Reasoning Plus, the total context size is `32768` tokens, + as we want to leave room for the output, we will set the maximum supported + input tokens as `32768 - 1024 = 31744`.\\n - **Maximum supported output + tokens**:\\n - Description: The maximum number of tokens that the model + can generate as output. Again, we should keep in mind that this value summed + to the **Maximum supported input tokens** should not exceed the total context + size supported by the model.\\n - Example: For Phi 4 Reasoning Plus, the + maximum output tokens is specified at `32768`, but we already reserved `31744` + for the input tokens, so we will set this to `32768 - 31744 = 1024`.\\n - + **Model Features**:\\n - Description: Under this section you will find + multiple toggles related to features supported by the model, these vary from + model to model, but most often the default values are well suited to most + use cases. The most relevant toggle is for `Image Support` which allows you + to use images as input for the model.\\n - Example: Image input is not + supported by Phi 4 Reasoning Plus, so we will leave it disabled.\\n\\n5. **Save** + \ \\n Click **Save changes**.\\n\\n6. **Test your model** \\n Run a sample + query in Agentic RAG or via API/CLI. Adjust your prompt templates and token + settings as needed.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"37cd8aff748addd04a363fa50828d1fe\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: openai-api-compatible-models \\n title: Connect to any OpenAI API + compatible LLM \\n \\n Connect to any OpenAI API compatible LLM \\n Agentic + RAG allows you to connect to any OpenAI API compatible LLM. This means that + you can use any LLM that has an API compatible with the OpenAI API which has + become a standard in the industry. \\n Many of the options for self-hosted + LLMs, open-source LLMs hosted by cloud providers or commercial LLMs are compatible + with the OpenAI API. This means that you can use them with Agentic RAG without + any modifications. \\n Configuration \\n To modify your knowledge box configuration + you can do so in three manners, through the API, the Nuclia CLI / SDK or the + Agentic RAG dashboard. \\n The Agentic RAG dashboard offers the most user-friendly + way to modify the configuration of your knowledge box and we will use it in + this example. \\n We will be setting up a connection to the Phi 4 Reasoning + Plus model, hosted by OpenRouter which offers a wide range of open-source + and commercial models compatible with the OpenAI API. We can see more information + about this specific model here, the API parameters are located under the API + tab. \\n \\n Open the AI Models page \\n In the left sidebar under Advanced, + click AI Models. \\n Select OpenAI API Compatible Model \\n From the models + list, choose OpenAI API Compatible Model. \\n Enable custom Key \\n Toggle + the option for using you own OpenAI API Compatible Key if it is not already + enabled. \\n \\n Fill in the configuration parameters \\n \\n \\n API Key: + \\n \\n Description: The API key for your LLM. This is the key that you would + use as an authorization header in the API. You may leave this blank if the + endpoint you are connecting to does not require an API key. \\n Example: We + will set this to our OpenRouter API key. \\n \\n \\n API URL: \\n Description: + The URL of the API endpoint for your LLM. This may be shared between multiple + models. \\n Example: For OpenRouter, it is the same for all models: https://openrouter.ai/api/v1 + \\n \\n \\n Model: \\n Description: The name of the model you want to use, + it needs to exactly match the name of the model in the API. \\n Example: For + Phi 4 Reasoning Plus in the OpenRouter API, it is microsoft/phi-4-reasoning-plus:free. + \\n \\n \\n Maximum supported input tokens: \\n Description: The maximum number + of tokens that the model can accept as input. Be mindful that this takes into + account the tokens used in the prompt, query and context. Also take note that + some models may provide their context window as the total between input and + output tokens, while others may provide it as the input tokens only. \\n Example: + For Phi 4 Reasoning Plus, the total context size is 32768 tokens, as we want + to leave room for the output, we will set the maximum supported input tokens + as 32768 - 1024 = 31744. \\n \\n \\n Maximum supported output tokens: \\n + Description: The maximum number of tokens that the model can generate as output. + Again, we should keep in mind that this value summed to the Maximum supported + input tokens should not exceed the total context size supported by the model. + \\n Example: For Phi 4 Reasoning Plus, the maximum output tokens is specified + at 32768, but we already reserved 31744 for the input tokens, so we will set + this to 32768 - 31744 = 1024. \\n \\n \\n \\n Model Features: \\n \\n Description: + Under this section you will find multiple toggles related to features supported + by the model, these vary from model to model, but most often the default values + are well suited to most use cases. The most relevant toggle is for Image Support + which allows you to use images as input for the model. \\n Example: Image + input is not supported by Phi 4 Reasoning Plus, so we will leave it disabled. + \\n \\n \\n \\n Save \\n Click Save changes. \\n \\n \\n Test your model \\n + Run a sample query in Agentic RAG or via API/CLI. Adjust your prompt templates + and token settings as needed. \\n \\n 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\\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2804-3043\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":10,\"start\":2804,\"end\":3043,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\":{\"score\":0.63338303565979,\"score_type\":\"VECTOR\",\"order\":5,\"text\":\" + \\n \\n Maximum supported input tokens: \\n Description: The maximum number + of tokens that the model can accept as input. Be mindful that this takes into + account the tokens used in the prompt, query and context. Also take note that + some models may provide their context window as the total between input and + output tokens, while others may provide it as the input tokens only. \\n\",\"id\":\"89cc367c149e4f6eab0e06a743d1edba/t/page/2202-2575\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":8,\"start\":2202,\"end\":2575,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"43004f553e534ffe9c9e735856bd9b23\":{\"id\":\"43004f553e534ffe9c9e735856bd9b23\",\"slug\":\"docs-develop-js-sdk-interfaces-ModelConfig-md\",\"title\":\"docs + > develop > js sdk > interfaces > ModelConfig\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2026-01-08T16:32:44.621593\",\"modified\":\"2026-07-14T12:49:58.922592\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ModelConfig\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ModelConfig\\n\\n# + Interface: ModelConfig\\n\\n## Properties\\n\\n### assume\\\\_role?\\n\\n> + `optional` **assume\\\\_role**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:592](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L592)\\n\\n***\\n\\n### + driver?\\n\\n> `optional` **driver**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:590](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L590)\\n\\n***\\n\\n### + input\\\\_tokens\\n\\n> **input\\\\_tokens**: `object`\\n\\n#### max\\n\\n> + **max**: `number`\\n\\n#### min?\\n\\n> `optional` **min**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:587](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L587)\\n\\n***\\n\\n### + max\\\\_images?\\n\\n> `optional` **max\\\\_images**: `string`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:591](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L591)\\n\\n***\\n\\n### + output\\\\_tokens\\n\\n> **output\\\\_tokens**: `object`\\n\\n#### default\\\\_max?\\n\\n> + `optional` **default\\\\_max**: `number`\\n\\n#### max\\n\\n> **max**: `number`\\n\\n#### + min?\\n\\n> `optional` **min**: `number`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:588](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L588)\\n\\n***\\n\\n### + prompt\\\\_id?\\n\\n> `optional` **prompt\\\\_id**: `string`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:589](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L589)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"0ce41cb0494bcb99176527165e321fec\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ModelConfig \\n Interface: ModelConfig + \\n Properties \\n assume_role? \\n \\n optional assume_role: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:592 \\n \\n driver? + \\n \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 + \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: + number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \\n \\n max_images? \\n \\n optional max_images: string \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 \\n \\n output_tokens \\n + \\n output_tokens: object \\n \\n default_max? \\n \\n optional default_max: + number \\n \\n max \\n \\n max: number \\n \\n min? \\n \\n optional min: + number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:588 + \\n \\n prompt_id? \\n \\n optional prompt_id: string \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/kb/kb.models.ts:589\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":212,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":108,\"key\":\"\"},{\"start\":108,\"end\":212,\"key\":\"\"}]},{\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":215,\"end\":380,\"key\":\"\"},{\"start\":380,\"end\":480,\"key\":\"\"}]},{\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":483,\"end\":638,\"key\":\"\"},{\"start\":638,\"end\":703,\"key\":\"\"}]},{\"start\":703,\"end\":895,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":704,\"end\":806,\"key\":\"\"},{\"start\":806,\"end\":895,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:01.191702Z\",\"last_understanding\":\"2026-07-14T12:50:00.962823Z\",\"last_extract\":\"2026-07-14T12:50:00.418522Z\",\"last_processing_start\":\"2026-07-14T12:50:00.364723Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > ModelConfig\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > ModelConfig\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\":{\"score\":0.6202770471572876,\"score_type\":\"VECTOR\",\"order\":6,\"text\":\" + \\n optional max_images: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:591 + \\n \\n output_tokens \\n \\n output_tokens: object \\n \\n default_max? \\n + \\n optional default_max: number \\n \\n max \\n \\n max: number \\n \\n min? + \\n \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/480-703\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":2,\"start\":480,\"end\":703,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\":{\"score\":0.594592273235321,\"score_type\":\"VECTOR\",\"order\":16,\"text\":\" + \\n optional driver: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:590 + \\n \\n input_tokens \\n \\n input_tokens: object \\n \\n max \\n \\n max: + number \\n \\n min? \\n \\n optional min: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:587 + \\n \\n max_images? \\n\",\"id\":\"43004f553e534ffe9c9e735856bd9b23/t/page/212-480\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":1,\"start\":212,\"end\":480,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"42a4cd5a30314e94aa079ed0cfe81381\":{\"id\":\"42a4cd5a30314e94aa079ed0cfe81381\",\"slug\":\"docs-develop-js-sdk-interfaces-SplitStrategy-md\",\"title\":\"docs + > develop > js sdk > interfaces > SplitStrategy\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:02:38.468609\",\"modified\":\"2026-07-14T12:51:02.450318\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/SplitStrategy\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / SplitStrategy\\n\\n# + Interface: SplitStrategy\\n\\n## Properties\\n\\n### custom\\\\_split?\\n\\n> + `optional` **custom\\\\_split**: [`CustomSplitStrategy`](../enumerations/CustomSplitStrategy.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:537](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L537)\\n\\n***\\n\\n### + llm\\\\_split?\\n\\n> `optional` **llm\\\\_split**: [`SplitLLMConfig`](SplitLLMConfig.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:538](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L538)\\n\\n***\\n\\n### + manual\\\\_split?\\n\\n> `optional` **manual\\\\_split**: `object`\\n\\n#### + splitter\\n\\n> **splitter**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:539](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L539)\\n\\n***\\n\\n### + max\\\\_paragraph?\\n\\n> `optional` **max\\\\_paragraph**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:536](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L536)\\n\\n***\\n\\n### + name?\\n\\n> `optional` **name**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/kb/kb.models.ts:535](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/kb/kb.models.ts#L535)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"d24d884112df2f67b327ac6d6302ddf1\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / SplitStrategy \\n Interface: SplitStrategy + \\n Properties \\n custom_split? \\n \\n optional custom_split: CustomSplitStrategy + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:537 \\n \\n + llm_split? \\n \\n optional llm_split: SplitLLMConfig \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/kb/kb.models.ts:538 \\n \\n manual_split? \\n \\n + optional manual_split: object \\n \\n splitter \\n \\n splitter: string \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:539 \\n \\n max_paragraph? + \\n \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 + \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":234,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":113,\"key\":\"\"},{\"start\":113,\"end\":234,\"key\":\"\"}]},{\"start\":234,\"end\":502,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":237,\"end\":356,\"key\":\"\"},{\"start\":356,\"end\":502,\"key\":\"\"}]},{\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":505,\"end\":612,\"key\":\"\"},{\"start\":612,\"end\":696,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:51:04.701538Z\",\"last_understanding\":\"2026-07-14T12:51:04.225754Z\",\"last_extract\":\"2026-07-14T12:51:03.819024Z\",\"last_processing_start\":\"2026-07-14T12:51:03.798124Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > SplitStrategy\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > SplitStrategy\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\":{\"score\":0.5957005620002747,\"score_type\":\"VECTOR\",\"order\":15,\"text\":\" + \\n optional max_paragraph: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:536 + \\n \\n name? \\n \\n optional name: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/kb/kb.models.ts:535\",\"id\":\"42a4cd5a30314e94aa079ed0cfe81381/t/page/502-696\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":2,\"start\":502,\"end\":696,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"b14cf452a3434839a04c111f2ea4dc51\":{\"id\":\"b14cf452a3434839a04c111f2ea4dc51\",\"slug\":\"docs-develop-js-sdk-enums-UsageType-md\",\"title\":\"docs + > develop > js sdk > enums > UsageType\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\",\"tn\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:51:41.582110\",\"modified\":\"2026-06-09T08:13:34.112208\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/enums/UsageType\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[@nuclia/core](../README.md) + / [Exports](../modules.md) / UsageType\\n\\n# Enumeration: UsageType\\n\\n## + Table of contents\\n\\n### Enumeration Members\\n\\n- [AI\\\\_TOKENS\\\\_USED](UsageType.md#ai_tokens_used)\\n- + [BYTES\\\\_PROCESSED](UsageType.md#bytes_processed)\\n- [CHARS\\\\_PROCESSED](UsageType.md#chars_processed)\\n- + [MEDIA\\\\_FILES\\\\_PROCESSED](UsageType.md#media_files_processed)\\n- [MEDIA\\\\_SECONDS\\\\_PROCESSED](UsageType.md#media_seconds_processed)\\n- + [NUCLIA\\\\_TOKENS](UsageType.md#nuclia_tokens)\\n- [PAGES\\\\_PROCESSED](UsageType.md#pages_processed)\\n- + [PARAGRAPHS\\\\_PROCESSED](UsageType.md#paragraphs_processed)\\n- [PRE\\\\_PROCESSING\\\\_TIME](UsageType.md#pre_processing_time)\\n- + [RESOURCES\\\\_PROCESSED](UsageType.md#resources_processed)\\n- [SEARCHES\\\\_PERFORMED](UsageType.md#searches_performed)\\n- + [SLOW\\\\_PROCESSING\\\\_TIME](UsageType.md#slow_processing_time)\\n- [SUGGESTIONS\\\\_PERFORMED](UsageType.md#suggestions_performed)\\n- + [TRAIN\\\\_SECONDS](UsageType.md#train_seconds)\\n\\n## Enumeration Members\\n\\n### + AI\\\\_TOKENS\\\\_USED\\n\\n\u2022 **AI\\\\_TOKENS\\\\_USED** = ``\\\"ai_tokens_used\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:190](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L190)\\n\\n___\\n\\n### + BYTES\\\\_PROCESSED\\n\\n\u2022 **BYTES\\\\_PROCESSED** = ``\\\"bytes_processed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:181](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L181)\\n\\n___\\n\\n### + CHARS\\\\_PROCESSED\\n\\n\u2022 **CHARS\\\\_PROCESSED** = ``\\\"chars_processed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:182](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L182)\\n\\n___\\n\\n### + MEDIA\\\\_FILES\\\\_PROCESSED\\n\\n\u2022 **MEDIA\\\\_FILES\\\\_PROCESSED** + = ``\\\"media_files_processed\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:184](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L184)\\n\\n___\\n\\n### + MEDIA\\\\_SECONDS\\\\_PROCESSED\\n\\n\u2022 **MEDIA\\\\_SECONDS\\\\_PROCESSED** + = ``\\\"media_seconds_processed\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:183](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L183)\\n\\n___\\n\\n### + NUCLIA\\\\_TOKENS\\n\\n\u2022 **NUCLIA\\\\_TOKENS** = ``\\\"nuclia_tokens_billed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:191](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L191)\\n\\n___\\n\\n### + PAGES\\\\_PROCESSED\\n\\n\u2022 **PAGES\\\\_PROCESSED** = ``\\\"pages_processed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:185](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L185)\\n\\n___\\n\\n### + PARAGRAPHS\\\\_PROCESSED\\n\\n\u2022 **PARAGRAPHS\\\\_PROCESSED** = ``\\\"paragraphs_processed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:186](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L186)\\n\\n___\\n\\n### + PRE\\\\_PROCESSING\\\\_TIME\\n\\n\u2022 **PRE\\\\_PROCESSING\\\\_TIME** = + ``\\\"pre_processing_time\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:178](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L178)\\n\\n___\\n\\n### + RESOURCES\\\\_PROCESSED\\n\\n\u2022 **RESOURCES\\\\_PROCESSED** = ``\\\"resources_processed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:180](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L180)\\n\\n___\\n\\n### + SEARCHES\\\\_PERFORMED\\n\\n\u2022 **SEARCHES\\\\_PERFORMED** = ``\\\"searches_performed\\\"``\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:188](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L188)\\n\\n___\\n\\n### + SLOW\\\\_PROCESSING\\\\_TIME\\n\\n\u2022 **SLOW\\\\_PROCESSING\\\\_TIME** + = ``\\\"slow_processing_time\\\"``\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/db.models.ts:179](https://github.com/nuclia/frontend/blob/55a20097/libs/sdk-core/src/lib/db/db.models.ts#L179)\\n\\n___\\n\\n### + SUGGESTIONS\\\\_PERFORMED\\n\\n\u2022 **SUGGESTIONS\\\\_PERFORMED** = ``\\\"suggestions_performed\\\"``\\n\\n#### + Defined 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TRAIN_SECONDS \\n \\n Enumeration Members \\n AI_TOKENS_USED \\n \u2022 + AI_TOKENS_USED = ai_tokens_used \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:190 + \\n \\n BYTES_PROCESSED \\n \u2022 BYTES_PROCESSED = bytes_processed \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:181 \\n \\n CHARS_PROCESSED \\n + \u2022 CHARS_PROCESSED = chars_processed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:182 + \\n \\n MEDIA_FILES_PROCESSED \\n \u2022 MEDIA_FILES_PROCESSED = media_files_processed + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184 \\n \\n MEDIA_SECONDS_PROCESSED + \\n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \\n Defined in + \\n libs/sdk-core/src/lib/db/db.models.ts:183 \\n \\n NUCLIA_TOKENS \\n \u2022 + NUCLIA_TOKENS = nuclia_tokens_billed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:191 + \\n \\n PAGES_PROCESSED \\n \u2022 PAGES_PROCESSED = pages_processed \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n PARAGRAPHS_PROCESSED + \\n \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:186 \\n \\n PRE_PROCESSING_TIME \\n + \u2022 PRE_PROCESSING_TIME = pre_processing_time \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:178 + \\n \\n RESOURCES_PROCESSED \\n \u2022 RESOURCES_PROCESSED = resources_processed + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:180 \\n \\n SEARCHES_PERFORMED + \\n \u2022 SEARCHES_PERFORMED = searches_performed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:188 + \\n \\n SLOW_PROCESSING_TIME \\n \u2022 SLOW_PROCESSING_TIME = slow_processing_time + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:179 \\n \\n SUGGESTIONS_PERFORMED + \\n \u2022 SUGGESTIONS_PERFORMED = suggestions_performed \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:189 \\n \\n TRAIN_SECONDS \\n \u2022 + TRAIN_SECONDS = train_seconds \\n Defined 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UsageType\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139\":{\"score\":0.5916038155555725,\"score_type\":\"VECTOR\",\"order\":17,\"text\":\"@nuclia/core + / Exports / UsageType \\n Enumeration: UsageType \\n Table of contents \\n + Enumeration Members \\n \\n AI_TOKENS_USED \\n BYTES_PROCESSED \\n CHARS_PROCESSED + \\n MEDIA_FILES_PROCESSED \\n MEDIA_SECONDS_PROCESSED \\n NUCLIA_TOKENS \\n + PAGES_PROCESSED \\n PARAGRAPHS_PROCESSED \\n PRE_PROCESSING_TIME \\n RESOURCES_PROCESSED + \\n SEARCHES_PERFORMED \\n SLOW_PROCESSING_TIME \\n SUGGESTIONS_PERFORMED + \\n TRAIN_SECONDS \\n \\n Enumeration Members \\n AI_TOKENS_USED \\n \u2022 + AI_TOKENS_USED = ai_tokens_used \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:190 + \\n \\n BYTES_PROCESSED \\n \u2022 BYTES_PROCESSED = bytes_processed \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:181 \\n \\n CHARS_PROCESSED \\n + \u2022 CHARS_PROCESSED = chars_processed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:182 + \\n \\n MEDIA_FILES_PROCESSED \\n \u2022 MEDIA_FILES_PROCESSED = media_files_processed + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:184 \\n \\n MEDIA_SECONDS_PROCESSED + \\n \u2022 MEDIA_SECONDS_PROCESSED = media_seconds_processed \\n Defined in + \\n libs/sdk-core/src/lib/db/db.models.ts:183 \\n \\n NUCLIA_TOKENS \\n \u2022 + NUCLIA_TOKENS = nuclia_tokens_billed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:191 + \\n \\n PAGES_PROCESSED \\n \u2022 PAGES_PROCESSED = pages_processed \\n Defined + in \\n libs/sdk-core/src/lib/db/db.models.ts:185 \\n \\n PARAGRAPHS_PROCESSED + \\n \u2022 PARAGRAPHS_PROCESSED = paragraphs_processed \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:186 \\n \\n PRE_PROCESSING_TIME \\n + \u2022 PRE_PROCESSING_TIME = pre_processing_time \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:178 + \\n \\n RESOURCES_PROCESSED \\n \u2022 RESOURCES_PROCESSED = resources_processed + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:180 \\n \\n SEARCHES_PERFORMED + \\n \u2022 SEARCHES_PERFORMED = searches_performed \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:188 + \\n \\n SLOW_PROCESSING_TIME \\n \u2022 SLOW_PROCESSING_TIME = slow_processing_time + \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:179 \\n \\n SUGGESTIONS_PERFORMED + \\n \u2022 SUGGESTIONS_PERFORMED = suggestions_performed \\n Defined in \\n + libs/sdk-core/src/lib/db/db.models.ts:189 \\n \\n TRAIN_SECONDS \\n \u2022 + TRAIN_SECONDS = train_seconds \\n Defined in \\n libs/sdk-core/src/lib/db/db.models.ts:187\",\"id\":\"b14cf452a3434839a04c111f2ea4dc51/t/page/0-2139\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":0,\"start\":0,\"end\":2139,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"dd41482018924facb5dbb87a7d53f122\":{\"id\":\"dd41482018924facb5dbb87a7d53f122\",\"slug\":\"docs-ingestion-how-to-rate-limiting-md\",\"title\":\"docs + > ingestion > how to > rate limiting\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:52:05.339624\",\"modified\":\"2026-06-09T08:18:12.259849\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/ingestion/how-to/rate-limiting\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"---\\nid: + rate-limiting\\ntitle: Manage rate limiting\\n---\\n\\n# Manage rate limiting\\n\\nRate + limits are an essential aspect of the Agentic RAG platform, ensuring fair + usage and optimal performance for all users interacting with Agentic RAG APIs. + This document outlines the rate limits enforced by Agentic RAG and provides + guidelines for handling rate-limited responses effectively.\\n\\n## Introduction\\n\\nAgentic + RAG can apply two types of limits to its APIs:\\n\\n- **Regular API rate limits**: + By default, the sum of all authenticated requests in a Agentic RAG account + cannot exceed 2400 requests per minute. Note that this limit can be customized + on a per-account basis. Please contact [Agentic RAG's support team](mailto:support@nuclia.com) + if you need an increase.\\n\\n- **Ingestion back pressure limits**: Agentic + RAG implements a back-pressure mechanism to manage ingestion pipeline overload. + This mainly affects endpoints for uploading data and creating or updating + resources.\\n\\n## Handling Rate-Limited Responses\\n\\nAgentic RAG adheres + to [the HTTP standard](https://datatracker.ietf.org/doc/html/rfc6585#section-4) + and will return a response with a `429` status codes when the limits are exceeded.\\n\\nThe + official Agentic RAG API clients already have built-in mechanisms for retrying + requests when rate limits are encountered:\\n\\n- [Nuclia Python client](/docs/develop/python-sdk/README)\\n- + [Nuclia JavaScript client](/docs/develop/js-sdk/)\\n\\nHowever, if you are + interacting directly with the API, we recommend using an [exponential backoff + retry strategy](https://en.wikipedia.org/wiki/Exponential_backoff) when limits + are reached.\\n\\nWhen ingestion back pressure rate limits are hit, the response + will include a `try_after` key with an estimated UTC time for retrying the + request. You can use this value for retry logic as an alternative to the exponential + backoff strategy.\\n\\n## Example 1: Regular API rate limits\\n\\nHere's an + example of how to implement an exponential backoff retry strategy in Python:\\n\\n```python\\nimport + time\\nimport requests\\n\\ndef make_request_with_exponential_backoff(url, + headers, max_retries=5):\\n retries = 0\\n while retries < max_retries:\\n + \ response = requests.get(url, headers=headers)\\n if response.status_code + == 200:\\n return response.json()\\n elif response.status_code + == 429:\\n wait_time = 2 ** retries # Exponential backoff: 2^retries\\n + \ print(f\\\"Rate limit exceeded. Retrying in {wait_time} seconds...\\\")\\n + \ time.sleep(wait_time)\\n retries += 1\\n else:\\n + \ response.raise_for_status()\\n raise Exception(\\\"Max retries + exceeded\\\")\\n\\n# Example usage\\nurl = \\\"https://your-endpoint\\\"\\nheaders + = {\\\"Authorization\\\": \\\"Bearer YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_exponential_backoff(url, + headers)\\nprint(data)\\n```\\n\\n## Example 2: Ingestion back pressure limits\\n\\nHere's + an example of how to use the try_after key from the response to manage rate + limits:\\n\\n```python\\nimport time\\nfrom datetime import datetime\\n\\nimport + requests\\n\\n\\ndef make_request_with_try_after_info(url, headers, max_retries=5):\\n + \ retries = 0\\n while retries < max_retries:\\n response = requests.get(url, + headers=headers)\\n response_body = response.json()\\n if response.status_code + == 200:\\n return response.json()\\n elif response.status_code + == 429 and \\\"try_after\\\" in response_body:\\n try_after = response_body[\\\"try_after\\\"]\\n + \ retry_time = datetime.strptime(try_after, \\\"%Y-%m-%dT%H:%M:%S.%fZ\\\")\\n + \ wait_time = (retry_time - datetime.utcnow()).total_seconds()\\n + \ print(\\n f\\\"Rate limit exceeded. Retrying at + {retry_time} (in {wait_time} seconds)...\\\"\\n )\\n time.sleep(wait_time)\\n + \ retries += 1\\n else:\\n response.raise_for_status()\\n + \ raise Exception(\\\"Max retries exceeded\\\")\\n\\n\\n# Example usage\\nurl + = \\\"https://your-endpoint\\\"\\nheaders = {\\\"Authorization\\\": \\\"Bearer + YOUR_ACCESS_TOKEN\\\"}\\ndata = make_request_with_try_after_info(url, headers)\\nprint(data)\\n```\\n\\nThese + examples demonstrate how to handle rate limits effectively, ensuring that + your application respects the limits and retries appropriately.\\n\",\"format\":\"MARKDOWN\",\"md5\":\"ed11945857f4618eec7ed0d1b16ffa44\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\" + \\n id: rate-limiting \\n title: Manage rate limiting \\n \\n Manage rate + limiting \\n Rate limits are an essential aspect of the Agentic RAG platform, + ensuring fair usage and optimal performance for all users interacting with + Agentic RAG APIs. This document outlines the rate limits enforced by Agentic + RAG and provides guidelines for handling rate-limited responses effectively. + \\n Introduction \\n Agentic RAG can apply two types of limits to its APIs: + \\n \\n \\n Regular API rate limits: By default, the sum of all authenticated + requests in a Agentic RAG account cannot exceed 2400 requests per minute. + Note that this limit can be customized on a per-account basis. Please contact + Agentic RAG's support team if you need an increase. \\n \\n \\n Ingestion + back pressure limits: Agentic RAG implements a back-pressure mechanism to + manage ingestion pipeline overload. This mainly affects endpoints for uploading + data and creating or updating resources. \\n \\n \\n Handling Rate-Limited + Responses \\n Agentic RAG adheres to the HTTP standard and will return a response + with a 429 status codes when the limits are exceeded. \\n The official Agentic + RAG API clients already have built-in mechanisms for retrying requests when + rate limits are encountered: \\n \\n Nuclia Python client \\n Nuclia JavaScript + client \\n \\n However, if you are interacting directly with the API, we recommend + using an exponential backoff retry strategy when limits are reached. \\n When + ingestion back pressure rate limits are hit, the response will include a try_after + key with an estimated UTC time for retrying the request. You can use this + value for retry logic as an alternative to the exponential backoff strategy. + \\n Example 1: Regular API rate limits \\n Here's an example of how to implement + an exponential backoff retry strategy in Python: \\n ```python \\n import + time \\n import requests \\n def make_request_with_exponential_backoff(url, + headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: + \\n response = requests.get(url, headers=headers) \\n if response.status_code + == 200: \\n return response.json() \\n elif response.status_code == 429: \\n + wait_time = 2 retries # Exponential backoff: 2^retries \\n print(f Rate limit + exceeded. Retrying in {wait_time} seconds... ) \\n time.sleep(wait_time) \\n + retries += 1 \\n else: \\n response.raise_for_status() \\n raise Exception( + Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint \\n + headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_exponential_backoff(url, + headers) \\n print(data) \\n ``` \\n Example 2: Ingestion back pressure limits + \\n Here's an example of how to use the try_after key from the response to + manage rate limits: \\n ```python \\n import time \\n from datetime import + datetime \\n import requests \\n def make_request_with_try_after_info(url, + headers, max_retries=5): \\n retries = 0 \\n while retries < max_retries: + \\n response = requests.get(url, headers=headers) \\n response_body = response.json() + \\n if response.status_code == 200: \\n return response.json() \\n elif response.status_code + == 429 and try_after in response_body: \\n try_after = response_body[ try_after + ] \\n retry_time = datetime.strptime(try_after, %Y-%m-%dT%H:%M:%S.%fZ ) \\n + wait_time = (retry_time - datetime.utcnow()).total_seconds() \\n print( \\n + f Rate limit exceeded. Retrying at {retry_time} (in {wait_time} seconds)... + \\n ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() + \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint + \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, + headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle + rate limits effectively, ensuring that your application respects the limits + and retries 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API\"},\"TIME/UTC\":{\"position\":[{\"start\":1526,\"end\":1529}],\"entity\":\"UTC\"},\"PRODUCT/Python\":{\"position\":[{\"start\":1232,\"end\":1238},{\"start\":1773,\"end\":1779}],\"entity\":\"Python\"},\"TIME/seconds\":{\"position\":[{\"start\":2199,\"end\":2206}],\"entity\":\"seconds\"}},\"relations\":[{\"relation\":\"OTHER\",\"label\":\"operating + system\",\"metadata\":{\"paragraph_id\":\"dd41482018924facb5dbb87a7d53f122/t/page/1222-1656\",\"source_start\":1248,\"source_end\":1254,\"to_start\":1232,\"to_end\":1238},\"from\":{\"value\":\"Nuclia\",\"type\":\"entity\",\"group\":\"ORG\"},\"to\":{\"value\":\"Python\",\"type\":\"entity\",\"group\":\"PRODUCT\"}}],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > ingestion > how to > rate limiting\",\"extracted\":{\"text\":{\"text\":\"docs + > ingestion > how to > rate limiting\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\":{\"score\":0.590923011302948,\"score_type\":\"VECTOR\",\"order\":18,\"text\":\" + ) \\n time.sleep(wait_time) \\n retries += 1 \\n else: \\n response.raise_for_status() + \\n raise Exception( Max retries exceeded ) \\n Example usage \\n url = https://your-endpoint + \\n headers = { Authorization : Bearer YOUR_ACCESS_TOKEN } \\n data = make_request_with_try_after_info(url, + headers) \\n print(data) \\n ``` \\n These examples demonstrate how to handle + rate limits effectively, ensuring that your application respects the limits + and retries appropriately.\",\"id\":\"dd41482018924facb5dbb87a7d53f122/t/page/3310-3757\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":9,\"start\":3310,\"end\":3757,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"50aac6f34b6d47de8e3b01f8b2de6e9c\":{\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c\",\"slug\":\"docs-develop-js-sdk-interfaces-PredictAnswerOptions-md\",\"title\":\"docs + > develop > js sdk > interfaces > PredictAnswerOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-08-26T10:03:11.443619\",\"modified\":\"2026-07-14T12:50:46.385594\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/PredictAnswerOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / PredictAnswerOptions\\n\\n# + Interface: PredictAnswerOptions\\n\\n## Properties\\n\\n### chat\\\\_history?\\n\\n> + `optional` **chat\\\\_history**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:242](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L242)\\n\\n***\\n\\n### + citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:249](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L249)\\n\\n***\\n\\n### + citations?\\n\\n> `optional` **citations**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:248](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L248)\\n\\n***\\n\\n### + context?\\n\\n> `optional` **context**: [`ContextEntry`](../namespaces/Ask/interfaces/ContextEntry.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:243](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L243)\\n\\n***\\n\\n### + format\\\\_prompt?\\n\\n> `optional` **format\\\\_prompt**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:258](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L258)\\n\\n***\\n\\n### + generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:250](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L250)\\n\\n***\\n\\n### + json\\\\_schema?\\n\\n> `optional` **json\\\\_schema**: `object`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:257](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L257)\\n\\n***\\n\\n### + max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:251](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L251)\\n\\n***\\n\\n### + prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:256](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L256)\\n\\n***\\n\\n### + query\\\\_context?\\n\\n> `optional` **query\\\\_context**: `string`[] \\\\| + `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:244](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L244)\\n\\n***\\n\\n### + query\\\\_context\\\\_images?\\n\\n> `optional` **query\\\\_context\\\\_images**: + `object`\\n\\n#### b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> + **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:252](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L252)\\n\\n***\\n\\n### + query\\\\_context\\\\_order?\\n\\n> `optional` **query\\\\_context\\\\_order**: + `object`\\n\\n#### Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:245](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L245)\\n\\n***\\n\\n### + reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:260](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L260)\\n\\n***\\n\\n### + rerank\\\\_context?\\n\\n> `optional` **rerank\\\\_context**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:259](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L259)\\n\\n***\\n\\n### + retrieval?\\n\\n> `optional` **retrieval**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:240](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L240)\\n\\n***\\n\\n### + system?\\n\\n> `optional` **system**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:241](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L241)\\n\\n***\\n\\n### + truncate?\\n\\n> `optional` **truncate**: `boolean`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:246](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L246)\\n\\n***\\n\\n### + user\\\\_prompt?\\n\\n> `optional` **user\\\\_prompt**: `object`\\n\\n#### + prompt\\n\\n> **prompt**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/ask.models.ts:247](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/ask.models.ts#L247)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"470be50f3c6aeeff5ae3310ed007b9b3\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / PredictAnswerOptions \\n Interface: PredictAnswerOptions + \\n Properties \\n chat_history? \\n \\n optional chat_history: ContextEntry[] + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:242 \\n + \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:249 \\n \\n citations? + \\n \\n optional citations: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:248 + \\n \\n context? \\n \\n optional context: ContextEntry[] \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:243 \\n \\n format_prompt? + \\n \\n optional format_prompt: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:258 + \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 \\n \\n json_schema? + \\n \\n optional json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 + \\n \\n max_tokens? \\n \\n optional max_tokens: number \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 \\n \\n prefer_markdown? + \\n \\n optional prefer_markdown: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 + \\n \\n query_context? \\n \\n optional query_context: string[] \\\\| object + \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:244 \\n + \\n query_context_images? \\n \\n optional query_context_images: object \\n + \\n b64encoded \\n \\n b64encoded: string \\n \\n content_type \\n \\n content_type: + string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:252 + \\n \\n query_context_order? \\n \\n optional query_context_order: object + \\n \\n Index Signature \\n [key: string]: number \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:245 + \\n \\n reasoning? \\n \\n optional reasoning: ReasoningParam \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:260 \\n \\n rerank_context? + \\n \\n optional rerank_context: boolean \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:259 + \\n \\n retrieval? \\n \\n optional retrieval: boolean \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/ask.models.ts:240 \\n \\n system? \\n + \\n optional system: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:241 + \\n \\n truncate? \\n \\n optional truncate: boolean \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/search/ask.models.ts:246 \\n \\n user_prompt? \\n + \\n optional user_prompt: object \\n \\n prompt \\n \\n prompt: string \\n + \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:247\",\"split_text\":{},\"deleted_splits\":[]},\"metadata\":{\"metadata\":{\"links\":[],\"paragraphs\":[{\"start\":0,\"end\":257,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":0,\"end\":127,\"key\":\"\"},{\"start\":127,\"end\":257,\"key\":\"\"}]},{\"start\":257,\"end\":491,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":260,\"end\":382,\"key\":\"\"},{\"start\":382,\"end\":491,\"key\":\"\"}]},{\"start\":491,\"end\":739,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":494,\"end\":617,\"key\":\"\"},{\"start\":617,\"end\":739,\"key\":\"\"}]},{\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":742,\"end\":864,\"key\":\"\"},{\"start\":864,\"end\":977,\"key\":\"\"}]},{\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":980,\"end\":1100,\"key\":\"\"},{\"start\":1100,\"end\":1221,\"key\":\"\"}]},{\"start\":1221,\"end\":1575,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1224,\"end\":1364,\"key\":\"\"},{\"start\":1364,\"end\":1575,\"key\":\"\"}]},{\"start\":1575,\"end\":1866,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1578,\"end\":1743,\"key\":\"\"},{\"start\":1743,\"end\":1866,\"key\":\"\"}]},{\"start\":1866,\"end\":2096,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":1869,\"end\":1988,\"key\":\"\"},{\"start\":1988,\"end\":2096,\"key\":\"\"}]},{\"start\":2096,\"end\":2320,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2099,\"end\":2208,\"key\":\"\"},{\"start\":2208,\"end\":2320,\"key\":\"\"}]},{\"start\":2320,\"end\":2449,\"start_seconds\":[],\"end_seconds\":[],\"kind\":\"TEXT\",\"classifications\":[],\"sentences\":[{\"start\":2323,\"end\":2449,\"key\":\"\"}]}],\"ner\":{},\"entities\":{\"processor\":{\"entities\":[]}},\"classifications\":[],\"last_index\":\"2026-07-14T12:50:49.024021Z\",\"last_understanding\":\"2026-07-14T12:50:48.461687Z\",\"last_extract\":\"2026-07-14T12:50:47.086918Z\",\"last_processing_start\":\"2026-07-14T12:50:47.048628Z\",\"language\":\"en\",\"summary\":\"\",\"positions\":{},\"relations\":[],\"mime_type\":\"text/markdown\"},\"split_metadata\":{},\"deleted_splits\":[]}}}},\"generics\":{\"title\":{\"value\":\"docs + > develop > js sdk > interfaces > PredictAnswerOptions\",\"extracted\":{\"text\":{\"text\":\"docs + > develop > js sdk > interfaces > PredictAnswerOptions\"}}}}},\"security\":null,\"fields\":{\"/t/page\":{\"paragraphs\":{\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\":{\"score\":0.6482165455818176,\"score_type\":\"VECTOR\",\"order\":3,\"text\":\" + \\n optional max_tokens: number \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:251 + \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:256 \\n \\n query_context? + \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/977-1221\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":4,\"start\":977,\"end\":1221,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\":{\"score\":0.5993967652320862,\"score_type\":\"VECTOR\",\"order\":12,\"text\":\" + \\n optional generative_model: string \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:250 + \\n \\n json_schema? \\n \\n optional json_schema: object \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/ask.models.ts:257 \\n \\n max_tokens? + \\n\",\"id\":\"50aac6f34b6d47de8e3b01f8b2de6e9c/t/page/739-977\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":0,\"index\":3,\"start\":739,\"end\":977,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":false,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null}}}}},\"e8525e64c5b44982b958d32cf6090613\":{\"id\":\"e8525e64c5b44982b958d32cf6090613\",\"slug\":\"docs-develop-js-sdk-interfaces-ChatOptions-md\",\"title\":\"docs + > develop > js sdk > interfaces > ChatOptions\",\"summary\":\"\",\"icon\":\"text/markdown\",\"thumbnail\":\"\",\"metadata\":{\"metadata\":{},\"language\":\"en\",\"languages\":[\"en\"],\"status\":\"PROCESSED\"},\"usermetadata\":{\"classifications\":[],\"relations\":[]},\"fieldmetadata\":[],\"computedmetadata\":{\"field_classifications\":[]},\"created\":\"2025-04-15T14:50:37.546010\",\"modified\":\"2026-07-14T12:51:04.368823\",\"last_seqid\":0,\"last_account_seq\":null,\"queue\":\"private\",\"hidden\":false,\"origin\":{\"source_id\":\"\",\"url\":\"https://docs.rag.progress.cloud/docs/develop/js-sdk/interfaces/ChatOptions\",\"metadata\":{},\"tags\":[],\"collaborators\":[],\"filename\":\"\",\"related\":[],\"path\":\"\",\"source\":\"API\"},\"extra\":null,\"relations\":null,\"data\":{\"texts\":{\"page\":{\"value\":{\"body\":\"[**@nuclia/core**](../README.md) + \u2022 **Docs**\\n\\n***\\n\\n[@nuclia/core](../globals.md) / ChatOptions\\n\\n# + Interface: ChatOptions\\n\\n## Extends\\n\\n- [`BaseSearchOptions`](BaseSearchOptions.md)\\n\\n## + Properties\\n\\n### answer\\\\_json\\\\_schema?\\n\\n> `optional` **answer\\\\_json\\\\_schema**: + `object`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:114](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L114)\\n\\n***\\n\\n### + audit\\\\_metadata?\\n\\n> `optional` **audit\\\\_metadata**: `object`\\n\\n#### + Index Signature\\n\\n \\\\[`key`: `string`\\\\]: `string`\\n\\n#### Inherited + from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`audit_metadata`](BaseSearchOptions.md#audit_metadata)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:81](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L81)\\n\\n***\\n\\n### + citation\\\\_threshold?\\n\\n> `optional` **citation\\\\_threshold**: `number`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:116](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L116)\\n\\n***\\n\\n### + citations?\\n\\n> `optional` **citations**: `boolean` \\\\| `\\\"none\\\"` + \\\\| `\\\"default\\\"` \\\\| `\\\"llm_footnotes\\\"`\\n\\nIt will return + the text blocks that have been effectively used to build each section of the + answer.\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:105](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L105)\\n\\n***\\n\\n### + debug?\\n\\n> `optional` **debug**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`debug`](BaseSearchOptions.md#debug)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:79](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L79)\\n\\n***\\n\\n### + extra\\\\_context?\\n\\n> `optional` **extra\\\\_context**: `string`[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:115](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L115)\\n\\n***\\n\\n### + extra\\\\_context\\\\_images?\\n\\n> `optional` **extra\\\\_context\\\\_images**: + `object`[]\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:118](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L118)\\n\\n***\\n\\n### + ~~extracted?~~\\n\\n> `optional` **extracted**: [`ExtractedDataTypes`](../enumerations/ExtractedDataTypes.md)[]\\n\\n#### + Deprecated\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`extracted`](BaseSearchOptions.md#extracted)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:73](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L73)\\n\\n***\\n\\n### + features?\\n\\n> `optional` **features**: [`Features`](../namespaces/Ask/enumerations/Features.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:117](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L117)\\n\\n***\\n\\n### + field\\\\_type\\\\_filter?\\n\\n> `optional` **field\\\\_type\\\\_filter**: + [`FIELD_TYPE`](../enumerations/FIELD_TYPE.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`field_type_filter`](BaseSearchOptions.md#field_type_filter)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:74](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L74)\\n\\n***\\n\\n### + fields?\\n\\n> `optional` **fields**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`fields`](BaseSearchOptions.md#fields)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:62](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L62)\\n\\n***\\n\\n### + filter\\\\_expression?\\n\\n> `optional` **filter\\\\_expression**: [`FilterExpression`](FilterExpression.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filter_expression`](BaseSearchOptions.md#filter_expression)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:64](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L64)\\n\\n***\\n\\n### + filters?\\n\\n> `optional` **filters**: `string`[] \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`filters`](BaseSearchOptions.md#filters)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:63](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L63)\\n\\n***\\n\\n### + generative\\\\_model?\\n\\n> `optional` **generative\\\\_model**: `string`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:108](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L108)\\n\\n***\\n\\n### + highlight?\\n\\n> `optional` **highlight**: `boolean`\\n\\n#### Inherited + from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`highlight`](BaseSearchOptions.md#highlight)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:76](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L76)\\n\\n***\\n\\n### + keyword\\\\_filters?\\n\\n> `optional` **keyword\\\\_filters**: `string`[] + \\\\| [`Filter`](../type-aliases/Filter.md)[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`keyword_filters`](BaseSearchOptions.md#keyword_filters)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:65](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L65)\\n\\n***\\n\\n### + max\\\\_tokens?\\n\\n> `optional` **max\\\\_tokens**: `number` \\\\| `object`\\n\\nDefines + the maximum number of tokens that the model will take as context.\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:112](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L112)\\n\\n***\\n\\n### + min\\\\_score?\\n\\n> `optional` **min\\\\_score**: `number` \\\\| [`MinScore`](MinScore.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`min_score`](BaseSearchOptions.md#min_score)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:66](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L66)\\n\\n***\\n\\n### + prefer\\\\_markdown?\\n\\n> `optional` **prefer\\\\_markdown**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:113](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L113)\\n\\n***\\n\\n### + prompt?\\n\\n> `optional` **prompt**: `string` \\\\| [`Prompts`](Prompts.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:101](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L101)\\n\\n***\\n\\n### + query\\\\_image?\\n\\n> `optional` **query\\\\_image**: `object`\\n\\n#### + b64encoded\\n\\n> **b64encoded**: `string`\\n\\n#### content\\\\_type\\n\\n> + **content\\\\_type**: `string`\\n\\n#### Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:122](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L122)\\n\\n***\\n\\n### + rag\\\\_images\\\\_strategies?\\n\\n> `optional` **rag\\\\_images\\\\_strategies**: + [`RAGImageStrategy`](../type-aliases/RAGImageStrategy.md)[]\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:107](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L107)\\n\\n***\\n\\n### + rag\\\\_strategies?\\n\\n> `optional` **rag\\\\_strategies**: [`RAGStrategy`](../type-aliases/RAGStrategy.md)[]\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:106](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L106)\\n\\n***\\n\\n### + range\\\\_creation\\\\_end?\\n\\n> `optional` **range\\\\_creation\\\\_end**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_end`](BaseSearchOptions.md#range_creation_end)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:68](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L68)\\n\\n***\\n\\n### + range\\\\_creation\\\\_start?\\n\\n> `optional` **range\\\\_creation\\\\_start**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_creation_start`](BaseSearchOptions.md#range_creation_start)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:67](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L67)\\n\\n***\\n\\n### + range\\\\_modification\\\\_end?\\n\\n> `optional` **range\\\\_modification\\\\_end**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_end`](BaseSearchOptions.md#range_modification_end)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:70](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L70)\\n\\n***\\n\\n### + range\\\\_modification\\\\_start?\\n\\n> `optional` **range\\\\_modification\\\\_start**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`range_modification_start`](BaseSearchOptions.md#range_modification_start)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:69](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L69)\\n\\n***\\n\\n### + rank\\\\_fusion?\\n\\n> `optional` **rank\\\\_fusion**: [`RankFusion`](RankFusion.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rank_fusion`](BaseSearchOptions.md#rank_fusion)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:84](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L84)\\n\\n***\\n\\n### + reasoning?\\n\\n> `optional` **reasoning**: [`ReasoningParam`](../type-aliases/ReasoningParam.md)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:126](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L126)\\n\\n***\\n\\n### + rephrase?\\n\\n> `optional` **rephrase**: `boolean`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`rephrase`](BaseSearchOptions.md#rephrase)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:77](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L77)\\n\\n***\\n\\n### + reranker?\\n\\n> `optional` **reranker**: [`Reranker`](../enumerations/Reranker.md)\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`reranker`](BaseSearchOptions.md#reranker)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:83](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L83)\\n\\n***\\n\\n### + resource\\\\_filters?\\n\\n> `optional` **resource\\\\_filters**: `string`[]\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`resource_filters`](BaseSearchOptions.md#resource_filters)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:75](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L75)\\n\\n***\\n\\n### + search\\\\_configuration?\\n\\n> `optional` **search\\\\_configuration**: + `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`search_configuration`](BaseSearchOptions.md#search_configuration)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:86](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L86)\\n\\n***\\n\\n### + security?\\n\\n> `optional` **security**: `object`\\n\\n#### groups\\n\\n> + **groups**: `string`[]\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`security`](BaseSearchOptions.md#security)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:85](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L85)\\n\\n***\\n\\n### + show?\\n\\n> `optional` **show**: [`ResourceProperties`](../enumerations/ResourceProperties.md)[]\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show`](BaseSearchOptions.md#show)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:71](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L71)\\n\\n***\\n\\n### + show\\\\_consumption?\\n\\n> `optional` **show\\\\_consumption**: `boolean`\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:127](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L127)\\n\\n***\\n\\n### + show\\\\_hidden?\\n\\n> `optional` **show\\\\_hidden**: `boolean`\\n\\n#### + Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`show_hidden`](BaseSearchOptions.md#show_hidden)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:80](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L80)\\n\\n***\\n\\n### + synchronous?\\n\\n> `optional` **synchronous**: `boolean`\\n\\n#### Defined + in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:100](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L100)\\n\\n***\\n\\n### + top\\\\_k?\\n\\n> `optional` **top\\\\_k**: `number`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`top_k`](BaseSearchOptions.md#top_k)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:82](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L82)\\n\\n***\\n\\n### + vectorset?\\n\\n> `optional` **vectorset**: `string`\\n\\n#### Inherited from\\n\\n[`BaseSearchOptions`](BaseSearchOptions.md).[`vectorset`](BaseSearchOptions.md#vectorset)\\n\\n#### + Defined in\\n\\n[libs/sdk-core/src/lib/db/search/search.models.ts:78](https://github.com/nuclia/frontend/blob/f1c1a5898c3d1fd8929aad7c184789dbbea1b896/libs/sdk-core/src/lib/db/search/search.models.ts#L78)\\n\",\"format\":\"MARKDOWN\",\"md5\":\"d6b2f3f31ba0af4fa58490cdf6abeb52\",\"extract_strategy\":\"\",\"split_strategy\":\"\"},\"extracted\":{\"text\":{\"text\":\"@nuclia/core + \u2022 Docs \\n \\n @nuclia/core / ChatOptions \\n Interface: ChatOptions + \\n Extends \\n \\n BaseSearchOptions \\n \\n Properties \\n answer_json_schema? + \\n \\n optional answer_json_schema: object \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:114 + \\n \\n audit_metadata? \\n \\n optional audit_metadata: object \\n \\n Index + Signature \\n [key: string]: string \\n Inherited from \\n BaseSearchOptions.audit_metadata + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:81 \\n + \\n citation_threshold? \\n \\n optional citation_threshold: number \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:116 \\n \\n + citations? \\n \\n optional citations: boolean \\\\| none \\\\| default \\\\| + llm_footnotes \\n \\n It will return the text blocks that have been effectively + used to build each section of the answer. \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:105 + \\n \\n debug? \\n \\n optional debug: boolean \\n \\n Inherited from \\n + BaseSearchOptions.debug \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:79 + \\n \\n extra_context? \\n \\n optional extra_context: string[] \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:115 \\n \\n extra_context_images? + \\n \\n optional extra_context_images: object[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:118 + \\n \\n ~~extracted?~~ \\n \\n optional extracted: ExtractedDataTypes[] \\n + \\n Deprecated \\n Inherited from \\n BaseSearchOptions.extracted \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:73 \\n \\n features? + \\n \\n optional features: Features[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:117 + \\n \\n field_type_filter? \\n \\n optional field_type_filter: FIELD_TYPE[] + \\n \\n Inherited from \\n BaseSearchOptions.field_type_filter \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:74 \\n \\n fields? + \\n \\n optional fields: string[] \\n \\n Inherited from \\n BaseSearchOptions.fields + \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:62 \\n + \\n filter_expression? \\n \\n optional filter_expression: FilterExpression + \\n \\n Inherited from \\n BaseSearchOptions.filter_expression \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:64 \\n \\n filters? + \\n \\n optional filters: string[] \\\\| Filter[] \\n \\n Inherited from \\n + BaseSearchOptions.filters \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:63 + \\n \\n generative_model? \\n \\n optional generative_model: string \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:108 \\n \\n + highlight? \\n \\n optional highlight: boolean \\n \\n Inherited from \\n + BaseSearchOptions.highlight \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:76 + \\n \\n keyword_filters? \\n \\n optional keyword_filters: string[] \\\\| + Filter[] \\n \\n Inherited from \\n BaseSearchOptions.keyword_filters \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:65 \\n \\n + max_tokens? \\n \\n optional max_tokens: number \\\\| object \\n \\n Defines + the maximum number of tokens that the model will take as context. \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:112 \\n \\n min_score? + \\n \\n optional min_score: number \\\\| MinScore \\n \\n Inherited from \\n + BaseSearchOptions.min_score \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:66 + \\n \\n prefer_markdown? \\n \\n optional prefer_markdown: boolean \\n \\n + Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:113 \\n \\n + prompt? \\n \\n optional prompt: string \\\\| Prompts \\n \\n Defined in \\n + libs/sdk-core/src/lib/db/search/search.models.ts:101 \\n \\n query_image? + \\n \\n optional query_image: object \\n \\n b64encoded \\n \\n b64encoded: + string \\n \\n content_type \\n \\n content_type: string \\n \\n Defined in + \\n libs/sdk-core/src/lib/db/search/search.models.ts:122 \\n \\n rag_images_strategies? + \\n \\n optional rag_images_strategies: RAGImageStrategy[] \\n \\n Defined + in \\n libs/sdk-core/src/lib/db/search/search.models.ts:107 \\n \\n rag_strategies? + \\n \\n optional rag_strategies: RAGStrategy[] \\n \\n Defined in \\n libs/sdk-core/src/lib/db/search/search.models.ts:106 + \\n \\n range_creation_end? \\n 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All - rights reserved. \n \n Welcome to the Team \n \n Vamshi Shanigala \n Coop/Intern - Technical 2 \n \n MarkLogic \n Hyderabad \n \n Nathan Van Gheem \n Enterprise - Architect \n \n PDP \n Raleigh \n \n Shivabalu Thouta \n Software Engineer, - Senior \n \n MarkLogic \n Hyderabad \n \n https://www.progress.com/ \n \n ```\n\n\n---\"\n\n\n**block-AB**\n\n#### - Chunk: Business Context and Product Vision 2026 1_self_signed.pdf\n``` \n 6\u00a9 - 2025 Progress Software Corporation and/or its subsidiaries or affiliates. 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All rights reserved. \\n \\n Progress Corticon \\n \\n \xC7\xC7 + \\n \\n Enhancements \\n \\n Cloud-Native Deployment \u2013 \\n Simplified + rule execution in cloud \\n \\n A\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":35,\"index\":185,\"start\":36272,\"end\":36578},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"866f34bfe00a53e9265df7699d9b264b\",\"field_type\":\"f\",\"field\":\"866f34bfe00a53e9265df7699d9b264b\",\"text\":\"stling + urban environment with dynamic light trails indicating high-speed traffic. + \\n\\n\\n \\n Practices are changing \\n \\n \u2022 Market analysis \\n \u2022 + Feature definition \\n \u2022 Threat modelling \\n \u2022 Code suggestions + \\n \u2022 Code analysis \\n \u2022 UI scaffolding \\n \u2022 Test coverage + \\n \u2022 Penetra\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":8,\"index\":32,\"start\":6770,\"end\":7035},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"866f34bfe00a53e9265df7699d9b264b\",\"field_type\":\"f\",\"field\":\"866f34bfe00a53e9265df7699d9b264b\",\"text\":\"sformation + \\n \\n Roadmap Updates - Keep \\n \\n customers informed of upcoming \\n + releases. \\n \\n Community - Events, \\n forums, newsletters, and \\n \\n + personalized communication. \\n \\n \xC7\xC7 \\n \\n Enhancements \\n \\n + Intuitive Knowledge Model \\n Manager \u2013 Modernized UI for \\n broader + team participation. \\n \\n Smarter Semantic Search \u2013 \\n \\n Enhanced + vector and ontology-based \\n discovery for accuracy. \\n \\n Project-Based + Workspace \u2013 Unified \\n environment for managing enrichment \\n \\n and + classif\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":43,\"index\":214,\"start\":43147,\"end\":43615},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"866f34bfe00a53e9265df7699d9b264b\",\"field_type\":\"f\",\"field\":\"866f34bfe00a53e9265df7699d9b264b\",\"text\":\"he + segments are labeled Product 360\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":56,\"index\":266,\"start\":53032,\"end\":53067},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"866f34bfe00a53e9265df7699d9b264b\",\"field_type\":\"f\",\"field\":\"866f34bfe00a53e9265df7699d9b264b\",\"text\":\" + indicating the speed and flow of traffic. The scene is set in a bustling urban + area, likely a city center, with illuminated buildings and streets in the + background. \\n\\n\\n \\n Progress Data Platform: Vertical Concentration + \\n \\n \xC7\xC7 \\n \\n Manufacturing \\n \\n \xC7\xC7 \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":48,\"index\":240,\"start\":47858,\"end\":48111},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"866f34bfe00a53e9265df7699d9b264b\",\"field_type\":\"f\",\"field\":\"866f34bfe00a53e9265df7699d9b264b\",\"text\":\"\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":61,\"index\":296,\"start\":58608,\"end\":58608},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"866f34bfe00a53e9265df7699d9b264b\",\"field_type\":\"f\",\"field\":\"866f34bfe00a53e9265df7699d9b264b\",\"text\":\"ce?\\n+ + PDC Product Deployment Process\\n+ Exploration - Need is identified for product + to be hosted\\n+ Preparation - Product and PDC teams create implementati...\\n\\n+ + Product Updates - Product team implements required cha...\\n\\n+ PDC Review + - PDC team reviews design documentation an...\\n+ PDC Integration - PDC deploys + pro\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":58,\"index\":283,\"start\":56177,\"end\":56491},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"866f34bfe00a53e9265df7699d9b264b\",\"field_type\":\"f\",\"field\":\"866f34bfe00a53e9265df7699d9b264b\",\"text\":\"\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":0,\"index\":1,\"start\":86,\"end\":86},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"866f34bfe00a53e9265df7699d9b264b\",\"field_type\":\"f\",\"field\":\"866f34bfe00a53e9265df7699d9b264b\",\"text\":\"cene + with a focus on the intersection of two roads. Visible objects include cars, + pedestrians, and buildings. The scene captures a moment of everyday life, + highlighting urban dynamics and human activity. \\n\\n\\n \\n\\n\\n a logo, + featuring a gear with arrows pointing downwards. The gear is yellow with black + teeth, and the arrows are blue. The background is green. Visible objects include + \",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":28,\"index\":136,\"start\":26541,\"end\":26922},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"866f34bfe00a53e9265df7699d9b264b\",\"field_type\":\"f\",\"field\":\"866f34bfe00a53e9265df7699d9b264b\",\"text\":\"tion + \\n \\n \u2022 Customer 360 \\n \\n \u2022 Claims Mngmt \\n \\n \u2022 Program + \\n Entitlements \\n \\n \u2022 Criminal \\n \\n Database \\n \\n \u2022 No + Fly lists \\n \\n \u2022 Search \\n \\n \u2022 Content \\n \\n Monetization + \\n \\n \u2022 Advertising \\n \\n \u2022 Personalization \\n \\n \u2022 Fraud + \\n \\n \u2022 Payment \\n \\n Standard \\n \\n \u2022 Policy \\n Management + \\n \\n \u2022 Customer 360 \\n \\n \u2022 Data \\n Management \\n\",\"labels\":[],\"start_seconds\":null,\"end_seconds\":null,\"position\":{\"page_number\":49,\"index\":243,\"start\":48609,\"end\":48921},\"fuzzy_result\":false},{\"score\":0.0,\"rid\":\"866f34bfe00a53e9265df7699d9b264b\",\"field_type\":\"f\",\"field\":\"866f34bfe00a53e9265df7699d9b264b\",\"text\":\"DE\\n\u201CTUsEBALI + NOW_16 2050 G-\u20ACARAEE\\n[DEWAUS EG TO NELIMAL LK\\nENIOY @0F9 UN JOURTEY. + \\n\\n\\n a digital interface displaying an image of a car in a modern urban + setting. 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Your role is to provide accurate, clear, and well-structured - answers based strictly on the information provided to you.\nKey principles:\n- - Answer only using the information in the provided context\n- Do not use external - knowledge, assumptions, or prior experience\n- Maintain a professional and informative - tone\n- Be concise yet thorough\n- If information is insufficient, acknowledge - this clearly\n\nAlways follow any additional instructions provided about format, - style, or domain-specific behavior.", "chat_history": [], "context": [], "query_context": - {}, "query_context_order": {}, "truncate": true, "user_prompt": {"prompt": "\n## - Question\nNew employees at ADP\n\n## Provided Context\n[START OF CONTEXT]\n## - Retrieval on nuclia-sync Knowledge Box\n\n# New employees at ADP\n\n New employees - at ADP include Vamshi Shanigala, Coop/Intern Technical 2, located in Hyderabad; - Nathan Van Gheem, Enterprise Architect, located in Raleigh; Shivabalu Thouta, - Software Engineer, Senior, located in Hyderabad; Aleix Ruiz de Villa, Scientific - Advisor, located in Spain; and Casimiro Pio Carrino, Scientific Advisor, located - in Spain.\n[END OF CONTEXT]\n\n## Answering Guidelines\n- Carefully read all - context; it may be lengthy or detailed\n- Do not omit or overlook any relevant - information\n- Existing context summaries are answer attempts produced by retrieval - agents. 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Senior Manager, Software Engineering \\n \\n Brian Tang + USA Quicksilver Software Engineer, Principal \\n \\n Hari Krishna Tirunagari + Hyderabad Mangalayan QA Engineer, Principal 3 \\n \\n Hemanandh S Hyderabad + Avengers Software Engineer, Principal 3 \\n \\n Jonathan Miller USA Kalimba + Software Engineer, Senior \\n \\n Kunal Basarkar Hyderabad Avengers Software + Engineer, Senior Principal \\n \\n Nitesh Mehta Hyderabad Harmonica Software + Engineer, Senior Principal \\n \\n Saivenkat Chepuri Hyderabad Conquerors + Software Engineer, Principal 1 \\n \\n Sathyanarayana Gundoji Hyderabad Mangalayan + Software Engineer, Senior 1 \\n \\n Srikar Veeramallu Hyderabad Atlantis Software + Engineer, Principal 1 \\n \\n Stephen Brown USA Apollo Software Engineer, + Principal \\n \\n Sumit Pritmani Hyderabad Transformers Software Engineer, + Senior 2 \\n \\n Vikram Reddy Deva Hyderabad Avengers QA Engineer, Senior + 2 \\n \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4766-6189\",\"labels\":[],\"position\":{\"page_number\":6,\"index\":27,\"start\":4766,\"end\":6189,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\":{\"score\":0.0029121784027665854,\"score_type\":\"RERANKER\",\"order\":1,\"text\":\" + \\n 5\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Welcome to the Team \\n \\n Vamshi Shanigala + \\n Coop/Intern Technical 2 \\n \\n MarkLogic \\n Hyderabad \\n \\n Nathan + Van Gheem \\n Enterprise Architect \\n \\n PDP \\n Raleigh \\n \\n Shivabalu + Thouta \\n Software Engineer, Senior \\n \\n MarkLogic \\n Hyderabad \\n \\n + https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":4,\"index\":14,\"start\":3054,\"end\":3424,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\":{\"score\":0.0012893283274024725,\"score_type\":\"RERANKER\",\"order\":2,\"text\":\" + \\n 24\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Progress ADP: GTM Motions \\n \\n Expansion: + \\n Cross-sell & Upsell \\n \\n Increase account \\n \\n value through \\n + \\n added ADP \\n \\n products or \\n \\n leveling up tiers \\n \\n \xC7\xC7 + \\n \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\",\"labels\":[],\"position\":{\"page_number\":23,\"index\":83,\"start\":16815,\"end\":17085,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\":{\"score\":0.00049553596181795,\"score_type\":\"RERANKER\",\"order\":3,\"text\":\" + \\n 6\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Welcome to the Team \\n \\n Aleix Ruiz de Villa + \\n Scientific Advisor \\n \\n PDP \\n Spain \\n \\n Casimiro Pio Carrino + \\n Scientific Advisor \\n \\n PDP \\n Spain \\n \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":5,\"index\":21,\"start\":4148,\"end\":4399,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\":{\"score\":0.00012533752305898815,\"score_type\":\"RERANKER\",\"order\":4,\"text\":\" + \\n 26\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Progress OpenEdge \\n \\n \xC7\xC7 \\n \\n Modernization + Services & Plus Ones Engagement \\n \\n OpenEdge 13 \u2013 Latest version + \\n supporting FIPS compliance \\n \\n 12 and GenAI Workshops \u2013 Free + \\n hands-on training \\n \\n QSM \u2013 Quality and security \\n management + tools \\n \\n MCP Connector for ABL - AI Code \\n Assistant to improve code + quality \\n \\n Agentic RAG \u2013 AI-driven contextual \\n knowledge retrieval + \\n \\n Forrester Total Economic Impact \u2013 \\n Validated ROI and business + value \\n \\n PUG Challenge \u2013 Community- \\n \\n driven learning and + networking \\n \\n Customer Advisory Board \u2013 Customer \\n \\n advisory + for strategic alignment \\n \\n World Tour \u2013 Global events \\n showcasing + OpenEdge innovation \\n \\n Community - Collaborative network for \\n learning, + sharing, and innovation \\n \\n Customer Validation Program - Early \\n access + to roadmap features and \\n \\n collaborative feedback. \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":25,\"index\":96,\"start\":19109,\"end\":20048,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\":{\"score\":0.00012339458044152707,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" + New \\n \\n Acquisition \\n \\n Win net new \\n \\n customers \\n \\n adopting + Progress \\n \\n Data Platform \\n \\n portfolio \\n \\n Customer \\n \\n + Renewal \\n \\n Retain existing \\n \\n customers by \\n \\n reinforcing ongoing + \\n \\n value of current \\n \\n product(s) in use \\n \\n https://www.progress.com/ + \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\",\"labels\":[],\"position\":{\"page_number\":23,\"index\":84,\"start\":17085,\"end\":17354,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\":{\"score\":0.00008818923379294574,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" + \\n and what qualifications staff require to apply it? \\n \\n Submit \\n + \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":18,\"index\":74,\"start\":14158,\"end\":14258,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\":{\"score\":0.00006014151585986838,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\"Celebrating + Innovation\\nfrom PI 3...\\n\\nBrian Tang - FastTrack w/ MCP\\n\\nVanessa + Zhang - Al diff analysis\\n\\nShivali Tayal - 3rd party\\ndependency update + automation\\n\\nProgress\u2019\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\",\"labels\":[\"/k/ocr\"],\"position\":{\"page_number\":2,\"index\":11,\"start\":2193,\"end\":2360,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":\"image_2_0.jpg\",\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\":{\"score\":0.00005738759500673041,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" + \\n 2\xA9 2022 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Celebrating Q4 \\n \\n Releases \\n \\n ARC, + PostgreSQL, Oracle \\n \\n OpenAccess 9.0 for AIX \\n \\n Corticon 7.3.0 \\n + \\n Corticonjs 2.4.0 \\n \\n MarkLogic 11.3.2/3 \\n \\n MarkLogic IronBank + \\n \\n Operator 1.1.1 \\n \\n Progress Agentic RAG \\n \\n PDC 1.2.2/1.3.0 + \\n \\n Semaphore 5.8.6 \\n \\n Security \\n \\n Trufflehog \\n \\n SAMM Level + 2 \\n \\n Spy Attributes \\n Vulnerability \\n Resolution \\n \\n HDP 4.6.2 + \\n \\n Infrastructure \\n \\n Sonar Code \\n Coverage \\n \\n Innovation + \\n \\n Corticon AI \\n Generated User \\n Interface \\n \\n AI Video Production + \\n \\n Share your additional celebrations in the meeting chat! \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":1,\"index\":9,\"start\":1388,\"end\":2043,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\":{\"score\":0.000054759766499046236,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\" + \\n 48\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n PDC Priorities & Innovation \\n \\n \u2022 Functional + Expansion \u2013 Increase value proposition by on- \\n boarding additional + PDP (and other) services \\n \\n Business Priorities \\n \\n \u2022 MCP OpenEdge + ABL Service \\n \\n \u2022 Hybrid Data Pipeline Service \\n \\n \u2022 EULA + Acceptance Feedback Mechanism \\n \\n \u2022 Data Symphony Service \\n \\n + \u2022 Operational Support Shared Logging (CRIBL) \\n \\n Innovation Areas + \\n \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":47,\"index\":233,\"start\":46719,\"end\":47227,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\":{\"score\":0.00004985958003089763,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" + \\n Creation of a new enterprise \\n \\n architecture function led by \\n + \\n James Kerr with a first \\n \\n dedicated PDP level \\n \\n enterprise + architect: Nathan \\n van Gheem. \\n \\n \u2022 Nuclia \\n \\n \u2022 Reporting + line changes for \\n \\n HDP \\n \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\",\"labels\":[],\"position\":{\"page_number\":10,\"index\":41,\"start\":8847,\"end\":9067,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\":{\"score\":0.00004434627408045344,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\" + \\n \u2022 Expansion/New Logos - Supporting the AI Journey, Lowering TCO, + Supporting \\n Hybrid Deployment Options \\n \\n Business Priorities \\n \\n + \u2022 Graviton Support \\n \\n \u2022 Monitoring Agent \\n \\n \u2022 Nuclia-MarkLogic + Integration \\n \\n \u2022 MarkLogic Knowledge Hub \\n \\n \u2022 Flux as + PDC Service \\n \\n Innovation \\n \\n \u2022 Property Graphs \\n \\n \u2022 + Read from Replicas \\n \\n \u2022 Index Exclusion \\n \\n \u2022 Vector improvements + \\n \\n \u2022 Object storage improvement \\n \u2022 Support Kendo Theme Builder + in FastTrack \\n \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\",\"labels\":[],\"position\":{\"page_number\":50,\"index\":246,\"start\":49179,\"end\":49670,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\":{\"score\":0.00003822911094175652,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" + \\n 42\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. 42 \\n \\n Getting Started \\n \\n \u2022 Contact the + PDC PM/PO (Stephen Rice) to \\n \\n discuss \\n \\n \u27A2 Provide as many + details as required \\n \\n including timeframes \\n \\n \u27A2 Meeting will + be arranged between key \\n \\n stakeholders \\n \\n https://www.progress.com/ + \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":41,\"index\":209,\"start\":40988,\"end\":41333,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\":{\"score\":0.00003647853736765683,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" + \\n 59\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Corticon Priorities & Innovation \\n \\n \u2022 + Retention \u2013 Support, CVEs, encourage update to latest LTS \\n \\n \u2022 + Public Sector Expansion - Replicate success at State of Mississippi \\n \\n + \u2022 Platform Modernization - New UI and SaaS to enable more customer wins + \\n \\n Business Priorities \\n \\n \u2022 Modern UI \\n \\n \u2022 AI powered + user experience \\n \\n \u2022 SaaS offering in PDC \\n \\n \u2022 Symphony + rule deployment \\n \\n Innovation \\n \\n https://www.progress.com/ \\n \\n + \ \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\",\"labels\":[],\"position\":{\"page_number\":58,\"index\":281,\"start\":55634,\"end\":56168,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\":{\"score\":0.00003071818719035946,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" + \\n Performance & Reliability Upgrades \u2013 \\n \\n Faster queries and improved + resilience \\n \\n for mission-critical workloads. \\n \\n AI-Assistant \u2013 + Simplify the developer \\n \\n experience and lower the learning curve. \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":29,\"index\":140,\"start\":27462,\"end\":27669,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":null,\"is_a_table\":false,\"relevant_relations\":null},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\":{\"score\":0.000026480842279852368,\"score_type\":\"RERANKER\",\"order\":15,\"text\":\"a + digital photograph showing two people working at a desk. The man is seated, + looking at the computer screen, while the woman stands behind him, smiling. + Visible objects include a desktop computer with a keyboard and mouse, a pen + holder, and some documents on the desk. 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AI-driven contextual \\n knowledge retrieval + \\n \\n Forrester Total Economic Impact \u2013 \\n Validated ROI and business + value \\n \\n PUG Challenge \u2013 Community- \\n \\n driven learning and + networking \\n \\n Customer Advisory Board \u2013 Customer \\n \\n advisory + for strategic alignment \\n \\n World Tour \u2013 Global events \\n showcasing + OpenEdge innovation \\n \\n Community - Collaborative network for \\n learning, + sharing, and innovation \\n \\n Customer Validation Program - Early \\n access + to roadmap features and \\n \\n collaborative feedback. \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":25,\"index\":0,\"start\":19109,\"end\":20048,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\":{\"score\":0.00012339458044152707,\"score_type\":\"RERANKER\",\"order\":5,\"text\":\" + New \\n \\n Acquisition \\n \\n Win net new \\n \\n customers \\n \\n adopting + Progress \\n \\n Data Platform \\n \\n portfolio \\n \\n Customer \\n \\n + Renewal \\n \\n Retain existing \\n \\n customers by \\n \\n reinforcing ongoing + \\n \\n value of current \\n \\n product(s) in use \\n \\n https://www.progress.com/ + \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\",\"labels\":[],\"position\":{\"page_number\":23,\"index\":0,\"start\":17085,\"end\":17354,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\":{\"score\":0.00008818923379294574,\"score_type\":\"RERANKER\",\"order\":6,\"text\":\" + \\n and what qualifications staff require to apply it? \\n \\n Submit \\n + \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":18,\"index\":0,\"start\":14158,\"end\":14258,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\":{\"score\":0.00006014151585986838,\"score_type\":\"RERANKER\",\"order\":7,\"text\":\"Celebrating + Innovation\\nfrom PI 3...\\n\\nBrian Tang - FastTrack w/ MCP\\n\\nVanessa + Zhang - Al diff analysis\\n\\nShivali Tayal - 3rd party\\ndependency update + automation\\n\\nProgress\u2019\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\",\"labels\":[\"/k/ocr\"],\"position\":{\"page_number\":2,\"index\":0,\"start\":2193,\"end\":2360,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":\"image_2_0.jpg\",\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\":{\"score\":0.00005738759500673041,\"score_type\":\"RERANKER\",\"order\":8,\"text\":\" + \\n 2\xA9 2022 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Celebrating Q4 \\n \\n Releases \\n \\n ARC, + PostgreSQL, Oracle \\n \\n OpenAccess 9.0 for AIX \\n \\n Corticon 7.3.0 \\n + \\n Corticonjs 2.4.0 \\n \\n MarkLogic 11.3.2/3 \\n \\n MarkLogic IronBank + \\n \\n Operator 1.1.1 \\n \\n Progress Agentic RAG \\n \\n PDC 1.2.2/1.3.0 + \\n \\n Semaphore 5.8.6 \\n \\n Security \\n \\n Trufflehog \\n \\n SAMM Level + 2 \\n \\n Spy Attributes \\n Vulnerability \\n Resolution \\n \\n HDP 4.6.2 + \\n \\n Infrastructure \\n \\n Sonar Code \\n Coverage \\n \\n Innovation + \\n \\n Corticon AI \\n Generated User \\n Interface \\n \\n AI Video Production + \\n \\n Share your additional celebrations in the meeting chat! \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":1,\"index\":0,\"start\":1388,\"end\":2043,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\":{\"score\":0.000054759766499046236,\"score_type\":\"RERANKER\",\"order\":9,\"text\":\" + \\n 48\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n PDC Priorities & Innovation \\n \\n \u2022 Functional + Expansion \u2013 Increase value proposition by on- \\n boarding additional + PDP (and other) services \\n \\n Business Priorities \\n \\n \u2022 MCP OpenEdge + ABL Service \\n \\n \u2022 Hybrid Data Pipeline Service \\n \\n \u2022 EULA + Acceptance Feedback Mechanism \\n \\n \u2022 Data Symphony Service \\n \\n + \u2022 Operational Support Shared Logging (CRIBL) \\n \\n Innovation Areas + \\n \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":47,\"index\":0,\"start\":46719,\"end\":47227,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\":{\"score\":0.00004985958003089763,\"score_type\":\"RERANKER\",\"order\":10,\"text\":\" + \\n Creation of a new enterprise \\n \\n architecture function led by \\n + \\n James Kerr with a first \\n \\n dedicated PDP level \\n \\n enterprise + architect: Nathan \\n van Gheem. \\n \\n \u2022 Nuclia \\n \\n \u2022 Reporting + line changes for \\n \\n HDP \\n \\n\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\",\"labels\":[],\"position\":{\"page_number\":10,\"index\":0,\"start\":8847,\"end\":9067,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\":{\"score\":0.00004434627408045344,\"score_type\":\"RERANKER\",\"order\":11,\"text\":\" + \\n \u2022 Expansion/New Logos - Supporting the AI Journey, Lowering TCO, + Supporting \\n Hybrid Deployment Options \\n \\n Business Priorities \\n \\n + \u2022 Graviton Support \\n \\n \u2022 Monitoring Agent \\n \\n \u2022 Nuclia-MarkLogic + Integration \\n \\n \u2022 MarkLogic Knowledge Hub \\n \\n \u2022 Flux as + PDC Service \\n \\n Innovation \\n \\n \u2022 Property Graphs \\n \\n \u2022 + Read from Replicas \\n \\n \u2022 Index Exclusion \\n \\n \u2022 Vector improvements + \\n \\n \u2022 Object storage improvement \\n \u2022 Support Kendo Theme Builder + in FastTrack \\n \\n https://www.progress.com/ \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\",\"labels\":[],\"position\":{\"page_number\":50,\"index\":0,\"start\":49179,\"end\":49670,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\":{\"score\":0.00003822911094175652,\"score_type\":\"RERANKER\",\"order\":12,\"text\":\" + \\n 42\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. 42 \\n \\n Getting Started \\n \\n \u2022 Contact the + PDC PM/PO (Stephen Rice) to \\n \\n discuss \\n \\n \u27A2 Provide as many + details as required \\n \\n including timeframes \\n \\n \u27A2 Meeting will + be arranged between key \\n \\n stakeholders \\n \\n https://www.progress.com/ + \\n \\n \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\",\"labels\":[\"/k/text\"],\"position\":{\"page_number\":41,\"index\":0,\"start\":40988,\"end\":41333,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\":{\"score\":0.00003647853736765683,\"score_type\":\"RERANKER\",\"order\":13,\"text\":\" + \\n 59\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Corticon Priorities & Innovation \\n \\n \u2022 + Retention \u2013 Support, CVEs, encourage update to latest LTS \\n \\n \u2022 + Public Sector Expansion - Replicate success at State of Mississippi \\n \\n + \u2022 Platform Modernization - New UI and SaaS to enable more customer wins + \\n \\n Business Priorities \\n \\n \u2022 Modern UI \\n \\n \u2022 AI powered + user experience \\n \\n \u2022 SaaS offering in PDC \\n \\n \u2022 Symphony + rule deployment \\n \\n Innovation \\n \\n https://www.progress.com/ \\n \\n + \ \",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\",\"labels\":[],\"position\":{\"page_number\":58,\"index\":0,\"start\":55634,\"end\":56168,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\":{\"score\":0.00003071818719035946,\"score_type\":\"RERANKER\",\"order\":14,\"text\":\" + \\n Performance & Reliability Upgrades \u2013 \\n \\n Faster queries and improved + resilience \\n \\n for mission-critical workloads. \\n \\n AI-Assistant \u2013 + Simplify the developer \\n \\n experience and lower the learning curve. 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The man is seated, + looking at the computer screen, while the woman stands behind him, smiling. + Visible objects include a desktop computer with a keyboard and mouse, a pen + holder, and some documents on the desk. The background features a green wall + with charts and graphs.\",\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\",\"labels\":[\"/k/inception\"],\"position\":{\"page_number\":8,\"index\":0,\"start\":7044,\"end\":7374,\"start_seconds\":[],\"end_seconds\":[]},\"fuzzy_result\":false,\"page_with_visual\":true,\"reference\":\"image_8_0.jpg\",\"is_a_table\":false},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31881-32155\":{\"score\":0.000018925147742265835,\"score_type\":\"RERANKER\",\"order\":16,\"text\":\" + \\n \u2713 Faster Contract Approvals \u2013 Streamlined deal desk and legal + alignment for quicker turnaround. \\n \\n \u2713 Transparent Pricing Models + \u2013 Unified price list and predictable cost structures. \\n \\n \u2713 + Starter Bundles for Simplicity \u2013 Upcoming PDP SKU for easier entry and + adoption. 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+ \\n \\n PDP \\n Spain \\n \\n https:/\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4399-4431\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4440-4616\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4440-4616\",\"text\":\"progress.com/ + \\n \\n \\n\\n\\n \\n\\n\\n a portrait of a person smiling at the camera. + Visible objects include the person's face, hair, and smile. The background + consists of a stone wall wi\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4440-4616\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4626-4761\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4626-4761\",\"text\":\"me + decorative elements. \\n\\n\\n \\n\\n\\n a portrait photo of a man with a + beard and wavy hair. He is wearing a dark shirt with a floral pattern\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4626-4761\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6193-6467\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6193-6467\",\"text\":\"tps://www.progress.com/ + \\n \\n \\n\\n\\n \\n 8\xA9 2025 Progress Software Corporation and/or its + subsidiaries or affiliates. All rights reserved. \\n \\n AI is no longer optional. + \\n It is the engine of \\n transformation. \\n \\n 8\xA9 2025 Progress Software + Corporation and/or its subsidiaries or a\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6193-6467\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6467-6501\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6467-6501\",\"text\":\"ffiliates. + All rights reserved. \\n \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6467-6501\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6510-6765\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6510-6765\",\"text\":\"ps://www.progress.com/ + \\n \\n \\n\\n\\n \\n\\n\\n a blurred motion photograph, capturing the rapid + movement of city streets at night. Visible objects include tall buildings, + streetlights, and vehicles. The scene depicts a bustling urban environment + with dynamic light \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6510-6765\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6770-7035\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6770-7035\",\"text\":\"s + indicating high-speed traffic. \\n\\n\\n \\n Practices are changing \\n \\n + \u2022 Market analysis \\n \u2022 Feature definition \\n \u2022 Threat modelling + \\n \u2022 Code suggestions \\n \u2022 Code analysis \\n \u2022 UI scaffolding + \\n \u2022 Test coverage \\n \u2022 Penetration testing \\n \u2022 Documentation + \\n \u2022 Defect analysi\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/6770-7035\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2053-2189\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2053-2189\",\"text\":\" + \\n \\n \\n\\n\\n \\n 3\xA9 2025 Progress Software Corporation and/or its + subsidiaries or affiliates. All rights reserved. \\n \\n https://www.progress.\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2053-2189\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2365-2680\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2365-2680\",\"text\":\"ress\u2019 + \\n\\n\\n a slide from a presentation titled \\\"Celebrating Innovation from + PI 3...\\\". The slide features a festive background with colorful confetti. + Visible objects include the title text, bullet points, and a logo at the bottom + left corner. The scene shows a celebration atmosphere with bright colors and + decorative\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2365-2680\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2685-3050\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2685-3050\",\"text\":\"ents. + \\n\\n\\n \\n 4\xA9 2025 Progress Software Corporation and/or its subsidiaries + or affiliates. All rights reserved. \\n \\n Important Dates \\n \\n 11 December + (Thursday) \\n \\n Draft Plan Presentations \\n \\n 15 December (Monday) \\n + \\n Final Plan Presentations \\n \\n 17 December (Wednesday) \\n \\n Start + of PI 2026.1 \\n \\n 18 December (Thursday) \\n \\n Innovation Demos \\n \\n + https://www.progress.\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2685-3050\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3433-3678\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3433-3678\",\"text\":\"\\n + \\n \\n\\n\\n \\n\\n\\n a portrait photograph of a man smiling at the camera. + He is wearing a yellow shirt with a patterned background. Visible objects + include his face, shirt, and background. The scene is likely an indoor setting, + possibly a conference o\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3433-3678\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3688-3804\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3688-3804\",\"text\":\"nt + space. \\n\\n\\n \\n\\n\\n a portrait of a smiling man with short hair and + a beard. He is wearing a black shirt. The backgro\\n\\nDOCUMENT METADATA AT + ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context + and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3688-3804\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15013-15646\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15013-15646\",\"text\":\"rights + reserved. \\n \\n What is the best damp-proofing product for \\n concrete + piles that are in constant contact with \\n standing water, is it available, + how is it applied, \\n \\n Hi, how can I help? \\n \\n and what qualifications + staff require to apply it? \\n \\n Submit \\n \\n https://www.progress.com/ + \\n \\n \\n\\n\\n \\n\\n\\n a photograph of two construction workers standing + near a body of water, likely a lake or river, with several concrete pillars + marked with numbers in the background. They are wearing safety helmets and + high-visibility jackets. The scene depicts them observing or discussing something + on a clipboard. Visible objects include the con\\n\\nDOCUMENT METADATA AT + ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context + and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15013-15646\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15646-15680\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15646-15680\",\"text\":\"crete + pillars, the water, and the \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15646-15680\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15684-16349\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15684-16349\",\"text\":\" + Context suggests they are involved in a construction project. \\n\\n\\n \\n + 20\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n ?Documents \\n \\n Searching for a Suitable Product + \\n \\n + damp-proofing \\n \\n + concrete piles \\n \\n + standing water + \\n \\n damp-proofing \\n \\n concrete piles \\n \\n standing water \\n \\n + https://www.progress.com/ \\n \\n \\n\\n\\n \\n 21\xA9 2025 Progress Software + Corporation and/or its subsidiaries or affiliates. All rights reserved. \\n + \\n Comprehensive \\n \\n and actionable \\n \\n answer \\n \\n Searching + for a Suitable Product \\n \\n Scan tech specs to \\n \\n find suitable products + \\n \\n Retrieve additional \\n \\n information about \\n \\n \\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/15684-16349\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16353-16582\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16353-16582\",\"text\":\"ication, + safety and \\n \\n qualifications \\n \\n Check stock management \\n \\n system + to see if a suitable \\n \\n product is in stock \\n \\n What is the best + damp-proofing \\n \\n product for concrete piles that are \\n \\n in constant + contact with sta\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16353-16582\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16582-16809\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16582-16809\",\"text\":\"nding + \\n \\n water, is it available, how is it \\n \\n applied, and what qualifications + \\n \\n staff require to apply it? \\n \\n https://www.progress.com/ \\n \\n + \ \\n\\n\\n \\n 22\xA9 2025 Progress Software Corporation and/or its subsidiaries + or affilia\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16582-16809\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17363-17604\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17363-17604\",\"text\":\"ion + \\n \\n https://www.progress.com/ \\n \\n \\n\\n\\n \\n Pro \\n duct 360 + \\n \\n P \\n u \\n \\n b \\n lic \\n \\n S \\n a \\n fe \\n \\n ty \\n \\n + Self-service Policy \\n Search \\n \\n K \\n n \\n \\n o \\n w \\n \\n le + \\n d \\n \\n g \\n e \\n \\n M \\n a \\n n \\n \\n a \\n g \\n \\n e \\n + m \\n \\n e \\n n \\n \\n t \\n \\n Fraud \\n \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17363-17604\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17614-17855\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17614-17855\",\"text\":\"ity + \\n \\n Search & \\n Dis \\n \\n cover \\n y \\n \\n Software (ISV/OEM) \\n + \\n Manufacturing \\n \\n Government \\n \\n (SL/Fed) \\n \\n Life \\n \\n + Sciences \\n \\n Pharma \\n \\n Biotech \\n \\n Financial \\n \\n Services + & \\n \\n Insurance \\n \\n Managed \\n \\n Healthcare \\n \\n Media & \\n + \\n Publ\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17614-17855\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3814-4143\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3814-4143\",\"text\":\"s + plain white. \\n\\n\\n \\n\\n\\n a portrait photograph of a young man wearing + a light blue shirt. He has dark hair and a friendly expression. The background + is plain white, providing no distractions from the subject. Visible objects + include his face and shirt. Context suggests he might be a student or professional + in a field related to \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3814-4143\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18146-18464\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18146-18464\",\"text\":\"w + \\n \\n Acquisition \\n \\n Win net new \\n \\n customers \\n \\n adopting + Progress \\n \\n Data Platform \\n \\n portfolio \\n \\n Customer \\n \\n + Renewal \\n \\n Retain existing \\n \\n customers by \\n \\n reinforcing ongoing + \\n \\n value of current \\n \\n product(s) in use \\n \\n https://www.progress.com/ + \\n \\n \\n\\n\\n \\n\\n\\n a digital artwork depicting a street scene \\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18146-18464\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18474-18816\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18474-18816\",\"text\":\"a + focus on the intersection of two roads. Visible objects include cars, pedestrians, + and buildings. The scene captures a moment of everyday life, highlighting + urban dynamics and human activity. \\n\\n\\n \\n\\n\\n a digital artwork + depicting a street scene with a focus on the intersection of two roads. Visible + objects include cars, pedestrians, and bu\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18474-18816\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18826-19104\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18826-19104\",\"text\":\"gs. + The scene captures a moment of everyday life, highlighting urban dynamics + and human activity. \\n\\n\\n \\n 25\xA9 2025 Progress Software Corporation + and/or its subsidiaries or affiliates. All rights reserved. \\n \\n Long-standing + Innovation \\n \\n Customer \\n \\n Renewal \\n Expansion \\n \\n Cust\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/18826-19104\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20048-20404\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20048-20404\",\"text\":\"ometric + shapes representing buildings, windows, and roofs. The scene shows a modern + architectural design with green accents. \\n\\n\\n \\n 26\xA9 2025 Progress + Software Corporation and/or its subsidiaries or affiliates. All rights reserved. + \\n \\n Progress OpenEdge \\n \\n \xC7\xC7 \\n \\n Modernization Services + & Plus Ones Engagement \\n \\n OpenEdge 13 \u2013 Latest version \\n supporting + \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20048-20404\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20413-20634\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20413-20634\",\"text\":\"compliance + \\n \\n 12 and GenAI Workshops \u2013 Free \\n hands-on training \\n \\n QSM + \u2013 Quality and security \\n management tools \\n \\n MCP Connector for + ABL - AI Code \\n Assistant to improve code quality \\n \\n Agentic RAG \u2013 + AI-driven contex\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20413-20634\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20644-20865\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20644-20865\",\"text\":\"\\n + knowledge retrieval \\n \\n Forrester Total Economic Impact \u2013 \\n Validated + ROI and business value \\n \\n PUG Challenge \u2013 Community- \\n \\n driven + learning and networking \\n \\n Customer Advisory Board \u2013 Customer \\n + \\n advisory for stra\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/20644-20865\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17860-18137\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17860-18137\",\"text\":\"g + \\n \\n \\n \\n\\n\\n \\n 24\xA9 2025 Progress Software Corporation and/or + its subsidiaries or affiliates. All rights reserved. \\n \\n Progress ADP: + GTM Motions \\n \\n Expansion: \\n Cross-sell & Upsell \\n \\n Increase account + \\n \\n value through \\n \\n added ADP \\n \\n products or \\n \\n leveling + up tiers \\n \\n \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17860-18137\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13313-13602\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13313-13602\",\"text\":\" + a modern urban setting. Visible objects include the car's front view, a city + skyline in the background, and a person standing in front of the vehicle. + The context suggests a professional environment, possibly related to automotive + services or technology. \\n\\n\\n \\n 18\xA9 2025 Progress Software\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13313-13602\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13612-13874\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13612-13874\",\"text\":\"oration + and/or its subsidiaries or affiliates. All rights reserved. \\n \\n https://www.progress.com/ + \\n \\n \\n\\n\\n \\n\\n\\n a geometric shape, likely a polygon or a three-dimensional + object, rendered in yellow with black outlines. It shows a simple scene with + a few objects:\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13612-13874\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13879-14158\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13879-14158\",\"text\":\"ctangular + box-like structure and a small square inside it. The background is black. + \\n\\n\\n \\n\\n\\n a digital artwork depicting a street scene with a focus + on a person walking down the sidewalk. Visible objects include a person, a + car, and various urban elements such as buildings, tree\\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/13879-14158\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14267-14697\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14267-14697\",\"text\":\"d + street signs. The scene captures a moment of everyday life in an urban environment. + \\n\\n\\n \\n\\n\\n a digital artwork that appears to be a still life composition. + Visible objects include a bowl, a spoon, a knife, and various fruits such + as apples and oranges. The scene depicts a kitchen setting with a focus on + the fruit bowl, suggesting a theme of healthy eating or culinary preparation. + \\n\\n\\n \\n\\n\\n a green arrow pointing to the right,\\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14267-14697\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14702-15009\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14702-15009\",\"text\":\"cating + movement or direction. Visible objects include the arrow itself and a few + indistinct shapes that might be part of the background. The scene shows a + blurred, dark background with a green arrow pointing to the right. \\n\\n\\n + \ \\n 19\xA9 2025 Progress Software Corporation and/or its subsidiaries or + affiliates. \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14702-15009\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/694-1044\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/694-1044\",\"text\":\" + \\n\\n\\n a geometric abstract artwork featuring a three-dimensional shape + composed of overlapping triangles in varying shades of green. The scene shows + a modern, minimalist interior with a black background. Visible objects include + a sleek, black chair and a small table with a simple design. Context suggests + a contemporary living space or office environ\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/694-1044\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1054-1383\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1054-1383\",\"text\":\" + \\n\\n\\n \\n\\n\\n a geometric abstract graphic with a three-dimensional + cube-like shape composed of green and yellow gradients. It shows a modern, + minimalist design with clean lines and a vibrant color palette. Visible objects + include the cube and its gradient colors. The scene is set against a black + background, emphasizing the geometr\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1054-1383\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/398-684\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/398-684\",\"text\":\"a + signature, likely from a person's handwritten document or digital representation. + Visible objects include the signature itself and possibly some ink residue. + The scene shows a close-up view of a person's handwriting, with the signature + prominently displayed against a dark background.\\n\\nDOCUMENT METADATA AT + ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context + and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/398-684\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/45637-46038\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/45637-46038\",\"text\":\"ftware + Corporation and/or its subsidiaries or affiliates. All rights reserved. \\n + \\n Leverage our \\n \\n GenAI \\n \\n Developments \\n \\n Harness the power + of \\n artificial intelligence \\n \\n and drive your AI \\n \\n strategy. + \\n \\n Adopt Our Latest Releases \\n \\n Security & \\n \\n Compliance \\n + \\n Protect your systems \\n \\n and your data with up- \\n to-date security + \\n \\n patches, dependency \\n updates, and regulatory \\n complian\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/45637-46038\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46048-46463\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46048-46463\",\"text\":\"ignment. + \\n \\n Platform \\n \\n Support \\n \\n Stay current with the \\n \\n latest + platforms, \\n frameworks, and \\n \\n standards to ensure \\n compatibility + and long- \\n \\n term support \\n \\n \xC7\xC7 \\n Modernization and \\n + \\n Future-Readiness \\n \\n Embrace our latest \\n \\n features and \\n advancements + and \\n \\n accelerate your data \\n agility journey. \\n \\n Performance + & \\n \\n Reliability \\n \\n Benefit from ongoing \\n \\n fixes and optimizations + \\n that del\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46048-46463\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46473-46714\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46473-46714\",\"text\":\"a + more \\n \\n resilient platform. \\n \\n https://www.progress.com/ \\n \\n + \ \\n\\n\\n \\n\\n\\n a digital artwork that appears to be a still life composition. + Visible objects include a bowl, a spoon, a knife, and various fruits such + as apples and oranges. The sc\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46473-46714\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47236-47409\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47236-47409\",\"text\":\"epicts + a kitchen setting with a focus on the fruit bowl, suggesting a theme of healthy + eating or culinary preparation. \\n\\n\\n \\n\\n\\n a digital artwork that + appears to be a still \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47236-47409\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47414-47476\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47414-47476\",\"text\":\"composition. + Visible objects include a bowl, a spoon, a knife,\\n\\nDOCUMENT METADATA AT + ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context + and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47414-47476\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47485-47848\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47485-47848\",\"text\":\"various + fruits such as apples and oranges. The scene depicts a kitchen setting with + a focus on the fruit bowl, suggesting a theme of healthy eating or culinary + preparation. \\n\\n\\n \\n\\n\\n a digital artwork that appears to be a still + life composition. Visible objects include a bowl, a spoon, a knife, and various + fruits such as apples and oranges. The scene depicts a k\\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/47485-47848\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7384-7671\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7384-7671\",\"text\":\" + https://www.progress.com/ \\n \\n \\n\\n\\n \\n\\n\\n a digital photograph + showing two people working at a desk. The man is seated, looking at the computer + screen, while the woman stands behind him, smiling. Visible objects include + a desktop computer with a keyboard and mouse, a pen holder, and some\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7384-7671\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7676-8136\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7676-8136\",\"text\":\"ments + on the desk. The background features a green wall with charts and graphs. + \\n\\n\\n \\n\\n\\n a geometric logo consisting of three overlapping hexagons + arranged in a triangular formation. The background is black, and the logo + is rendered in shades of green. Visible objects include the hexagons and their + intersecting lines. Context suggests a modern, tech-oriented brand identity. + \\n\\n\\n \\n 10\xA9 2025 Progress Software Corporation and/or its subsidiaries + or affiliates\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7676-8136\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8145-8477\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8145-8477\",\"text\":\" + rights reserved.\xA9 2025 Progress Software Corporation and/or its subsidiaries + or affiliates. All rights reserved. \\n \\n From Triad to Quartet \\n \\n + Product Management \\n \\n Viability & Scope \\n \\n Engineering \\n \\n Feasibility + & Delivery \\n \\n Architecture \\n \\n Sustainability & Scale \\n \\n Customer + Experience \\n \\n Desirability \\n \\n https://www.pro\\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8145-8477\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8482-8847\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8482-8847\",\"text\":\".com/ + \\n https://www.progress.com/ \\n \\n \\n\\n\\n \\n\\n\\n a digital thumbs-up + icon. It shows a thumbs-up gesture with the thumb extended upwards and the + index finger curled into a triangle. Visible objects include the thumbnail + icon itself, the thumb, and the index finger. The context is likely a digital + interface or a social media platform where users can express approval\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8482-8847\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9067-9162\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9067-9162\",\"text\":\"emporary + reporting \\n \\n structure while we select a \\n \\n product leadership team, + \\n \\n and align P\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9067-9162\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9171-9392\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9171-9392\",\"text\":\"d + \\n \\n OpenEdge product \\n management and product \\n \\n operations. \\n + \\n Creation of a new enterprise \\n \\n architecture function led by \\n + \\n James Kerr with a first \\n \\n dedicated PDP level \\n \\n enterprise + architect: Nathan \\n van \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9171-9392\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9402-9623\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9402-9623\",\"text\":\". + \\n \\n \u2022 Nuclia \\n \\n \u2022 Reporting line changes for \\n \\n HDP + \\n \\n \u2022 Temporary structure for \\n \\n the documentation \\n function + \\n \\n https://www.progress.com/ \\n \\n \\n\\n\\n \\n\\n\\n a digital + artwork depicting a street scene with various el\\n\\nDOCUMENT METADATA AT + ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context + and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/9402-9623\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48116-48383\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48116-48383\",\"text\":\" + oranges. The scene depicts a kitchen setting with a focus on the fruit bowl, + suggesting a theme of healthy eating or culinary preparation. \\n\\n\\n \\n\\n\\n + a digital artwork that appears to be a still life composition. Visible objects + include a bowl, a spoon, a knife, and v\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48116-48383\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48383-48609\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48383-48609\",\"text\":\"arious + fruits such as apples and oranges. The scene depicts a kitchen setting with + a focus on the fruit bowl, suggesting a theme of healthy eating or culinary + preparation. \\n\\n\\n \\n Integrate \\n Our Teams \\n \\n Our Products \\n + \\n Our \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48383-48609\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48609-48921\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48609-48921\",\"text\":\"Use + Cases \\n \\n https://www.progress.com/ \\n \\n \\n\\n\\n Software (ISV/OEM)\\nManufacturing\\n\\nLife\\nSciences\\nPharma\\nBiotech\\n\\n&\\nS\\n@\\n<\\noO\\n=\\no\\ni=)\\n3\\ncc\\n3\\nS\\nt\\n\\nFinancial\\nServices + &\\nInsurance\\n\\nManaged\\nHealthcare\\n\\nGovernment\\nim (SL/Fed)\\n\\nMedia + &\\nPublishing\\n\\nMayes oyand \\n\\n\\n a circular diagram with six segments, + each representing \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48609-48921\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48921-48955\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48921-48955\",\"text\":\"a + different aspect of security man\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48921-48955\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48959-49179\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48959-49179\",\"text\":\"ent. + The segments are labeled Product 360, Self-service Policy Search, Managed + Healthcare, Government (SL/Fed), Public Safety, Fraud Identity, and Financial + Services & Insurance. Visible objects include icons for Softwar\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/48959-49179\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49679-49855\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49679-49855\",\"text\":\"V/OEM) + Manufacturing, Life Sciences Pharma Biotech, Media & Publishing, and Fraud + Identity. The scene shows a globe centered within the circle, surrounded by + these six segments\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49679-49855\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49860-49896\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49860-49896\",\"text\":\" + @uHHEERy\\n\\nquxx== \xA9\\n\\nERB EBB BEEBE B\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49860-49896\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49900-50107\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49900-50107\",\"text\":\" + wm \xAE\\n\\nSd\\n\\n@nunuun 8 \\n\\n\\n a flowchart or diagram that illustrates + the process of data integration. Visible objects include arrows representing + different stages, icons indicating various processes, and a circu\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49900-50107\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/50107-50141\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/50107-50141\",\"text\":\"lar + loop symbolizing a continuous \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/50107-50141\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/39868-40218\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/39868-40218\",\"text\":\"a + digital graphic artifact, likely representing a logo or branding element. + It shows a stylized green geometric shape with three arrows pointing upwards, + set against a white background. Visible objects include the green shapes and + arrows, as well as some black elements that could represent additional details + or text. The scene context suggests a mo\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/39868-40218\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40223-40271\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40223-40271\",\"text\":\" + tech-oriented environment, possibly related to \\n\\nDOCUMENT METADATA AT + ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context + and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40223-40271\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40275-40528\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40275-40528\",\"text\":\"nology + or innovation. \\n\\n\\n \\n\\n\\n a digital graphic artifact, likely a logo + or an icon. It shows a green geometric shape with three arrows pointing upwards, + set against a white background. Visible objects include the green shapes and + arrows, as well as som\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40275-40528\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40528-40589\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40528-40589\",\"text\":\"e + black elements that could represent additional details or t\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40528-40589\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40593-40984\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40593-40984\",\"text\":\" + The scene is minimalistic, focusing on the geometric shapes and their directional + emphasis. \\n\\n\\n \\n 33\xA9 2025 Progress Software Corporation and/or + its subsidiaries or affiliates. All rights reserved. \\n \\n Progress Data + Platform \\n \\n \xC7\xC7 \\n \\n \u2713 Simplified Licensing Terms \u2013 + Harmonized EULA and clear discounting guidelines. \\n \\n \u2713 Faster Contract + Approvals \u2013 Streamlined deal desk and legal alignme\\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40593-40984\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41337-41738\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41337-41738\",\"text\":\"ion + for faster provisioning and order accuracy. \\n \\n \u2713 Unified UI \u2013 + Improved experience across product set to increase efficiency and user engagement. + \\n \\n Customer Experience \\n \\n https://www.progress.com/ \\n \\n \\n\\n\\n + \ \\n\\n\\n a graphic illustration featuring three stylized icons: a wave + symbol, a green checkmark icon, and a smiley face icon. The scene shows a + modern digital interface with these icons, sugg\\n\\nDOCUMENT METADATA AT + ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context + and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41337-41738\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41738-41772\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41738-41772\",\"text\":\"esting + a focus on user feedback or\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41738-41772\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/42209-43142\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/42209-43142\",\"text\":\"althy + eating or culinary preparation. \\n\\n\\n \\n\\n\\n a digital image of a + landscape scene. Visible objects include trees, grass, rocks, and water. The + scene depicts a serene natural environment with lush greenery and calm waters. + \\n\\n\\n \\n 34\xA9 2025 Progress Software Corporation and/or its subsidiaries + or affiliates. All rights reserved. \\n \\n Intersection of \\n Moment-in-Time + \\n Pain and Long-term \\n Business Impact \\n \\n Long-Term \\n \\n Transformation + \\n Help to solve today's pains \\n \\n repeatedly \\n \\n until long-term + impact \\n \\n becomes instilled. \\n \\n AI-Driven \\n \\n Foundation \\n + Build a robust AI \\n \\n foundation that \\n \\n accelerates insights and + \\n \\n decision-making \\n for long-term success. \\n \\n Customer-Centric + \\n \\n Approach \\n Focus on meeting \\n \\n customers at their \\n \\n current + state to address \\n \\n immediate \\n pain points effectively. \\n \\n https://www.progress.com/ + \\n \\n \\n\\n\\n \\n\\n\\n a long-exposure photograph capturing the dynamic + movement of vehic\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/42209-43142\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43147-43615\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43147-43615\",\"text\":\"n + an intricate highway network at night. Visible objects include multiple intersecting + highways with light trails indicating the speed and flow of traffic. The scene + is set in a bustling urban area, likely a city center, with illuminated buildings + and streets in the background. \\n\\n\\n \\n Progress Data Platform: Vertical + Concentration \\n \\n \xC7\xC7 \\n \\n Manufacturing \\n \\n \xC7\xC7 \\n + \\n Healthcare \\n \\n \xC7\xC7 \\n \\n Government \\n \\n \xC7\xC7 \\n \\n + Media & \\n \\n Publishing \\n \\n \xC7\xC7 \\n \\n FinServ/ \\n \\n Insuranc\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43147-43615\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54700-54989\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54700-54989\",\"text\":\"ions + team with \\n advanced tools to better \\n assist clients and drive \\n \\n + revenue generation \\n \\n Continuous monitoring \\n \\n and enhancement of + \\n security measures to \\n \\n safeguard customer data \\n \\n integrity + \\n \\n https://www.progress.com/ \\n \\n \\n\\n\\n \\n\\n\\n a digital + artwork depicting a street sc\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54700-54989\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54999-55330\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54999-55330\",\"text\":\"ith + a focus on the intersection of two roads. Visible objects include cars, pedestrians, + and buildings. The scene captures a moment of everyday life, highlighting + urban dynamics and human activity. \\n\\n\\n \\n\\n\\n a digital artwork + depicting a street scene with a focus on the intersection of two roads. Visible + objects include cars, pede\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54999-55330\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55340-55629\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55340-55629\",\"text\":\"ns, + and buildings. The scene captures a moment of everyday life, highlighting + urban dynamics and human activity. \\n\\n\\n \\n\\n\\n a digital artwork + depicting a street scene with a focus on the intersection of two roads. Visible + objects include cars, pedestrians, and buildings. The scene captures \\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55340-55629\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56177-56491\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56177-56491\",\"text\":\"ent + of everyday life, highlighting urban dynamics and human activity. \\n\\n\\n + \ \\n\\n\\n a digital illustration featuring a gear-like blue background with + interconnected lines and nodes, symbolizing technology and data management. + In the foreground, there are two open books: one with a brain diagram on the + left and another\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56177-56491\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56501-56608\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56501-56608\",\"text\":\" + a yellow brain icon on the right. Below the books, there is a graph showing + data trends. The scene suggest\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56501-56608\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56613-56634\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56613-56634\",\"text\":\"ocus + on information t\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/56613-56634\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26541-26922\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26541-26922\",\"text\":\" + alignment \\n \\n World Tour \u2013 Global events \\n showcasing OpenEdge + innovation \\n \\n Community - Collaborative network for \\n learning, sharing, + and innovation \\n \\n Customer Validation Program - Early \\n access to roadmap + features and \\n \\n collaborative feedback. \\n \\n AppMod \u2013 Separating + US from \\n \\n database and business logic and API \\n enablement \\n \\n + Managed Database Administration \\n (MDB\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26541-26922\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26932-27153\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26932-27153\",\"text\":\"Proactive + DB monitoring \\n \\n and expert management \\n \\n Security Assessment \u2013 + Identify \\n \\n vulnerabilities and strengthen \\n protection \\n \\n Cloud + Migration \u2013 Move OpenEdge \\n workloads to cloud \\n \\n https://www.progress.com/ + \\n\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/26932-27153\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27158-27462\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27158-27462\",\"text\":\"\\n\\n + \ \\n\\n\\n a digital artwork depicting a street scene with various elements. + Visible objects include buildings, trees, and pedestrians. The scene captures + the essence of urban life, highlighting the blend of architecture and nature. + \\n\\n\\n \\n\\n\\n a digital artwork depicting a street scene with various + elements.\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27158-27462\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27669-27911\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27669-27911\",\"text\":\"or + its subsidiaries or affiliates. All rights reserved. \\n \\n The Solution: + Trusted, Intelligent Insights \\n \\n \xC7\xC7 \\n \\n MCP Server \\n \\n + AI You Can \\n \\n TRUST \\n \u2022 Unified Intelligence \\n \\n \u2022 Faster + Modernization \\n \\n \u2022 Trusted, Governed AI \\n \\n https://\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27669-27911\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27911-28181\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27911-28181\",\"text\":\"www.progress.com/ + \\n \\n \\n\\n\\n \\n\\n\\n a graphic representation of a light bulb with + bright yellow glow and sparkles around it. The scene shows a sunny day with + a clear blue sky, and the light bulb is placed on a surface with a few decorative + elements like stars and flowers. \\n\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27911-28181\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28181-28534\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28181-28534\",\"text\":\"\\n\\n + \ \\n\\n\\n a digital artwork depicting a street scene with a focus on the + intersection of two roads. Visible objects include cars, pedestrians, and + buildings. The scene captures a moment of everyday life, highlighting urban + dynamics and human activity. \\n\\n\\n \\n\\n\\n a logo, featuring a gear + with arrows pointing downwards. The gear is yellow with black teeth, \\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28181-28534\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28534-28568\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28534-28568\",\"text\":\"and + the arrows are blue. The backg\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/28534-28568\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/30837-31265\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/30837-31265\",\"text\":\" + is green. Visible objects include the gear and arrows. Context shows a factory + setting with machinery and equipment. \\n\\n\\n \\n\\n\\n a digital artwork + depicting a street scene with a focus on the intersection of two roads. Visible + objects include cars, pedestrians, and buildings. The scene captures a moment + of everyday life, highlighting urban dynamics and human activity. \\n\\n\\n + \ \\n\\n\\n a stylized graphic representation of a motorcyclis\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/30837-31265\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31275-31654\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31275-31654\",\"text\":\"ing + fast, likely on a racetrack. Visible objects include the rider's silhouette, + the motorcycle, and dynamic motion lines indicating speed. The scene captures + the thrill and intensity of racing, emphasizing rapid movement and speed. + \\n\\n\\n \\n\\n\\n a digital artwork that depicts a street scene with various + elements. Visible objects include buildings, trees, and vehicles. The scene + ca\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31275-31654\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31659-31881\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31659-31881\",\"text\":\"s + the essence of urban life, highlighting the contrast between nature and architecture. + \\n\\n\\n \\n 28\xA9 2025 Progress Software Corporation and/or its subsidiaries + or affiliates. All rights reserved. \\n \\n Progress Corticon \\n \\n \xC7\xC7\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31659-31881\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32155-32457\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32155-32457\",\"text\":\"ity + with modern platforms \\n \\n Unified Data + Rules \u2013 Decision logic \\n + \\n with real-time, governed data for more \\n accurate outcomes \\n \\n Accelerated + Compliance \u2013 Regulatory \\n requirements faster and with greater \\n + \\n confidence \\n \\n Future-Ready Architecture for \\n \\n Scalability \u2013 + Modern, scalable \\n founda\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32155-32457\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32457-32515\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32457-32515\",\"text\":\"tion + for advanced analytics and AI \\n \\n Targeted U.S. State\\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32457-32515\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32524-32916\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32524-32916\",\"text\":\" + https://www.progress.com/ \\n \\n \\n\\n\\n \\n\\n\\n a digital artwork + depicting a street scene with various elements such as buildings, trees, and + vehicles. Visible objects include a building with a large window, a tree with + green leaves, and a car parked on the side of the road. The scene captures + a typical urban environment with a mix of architectural styles and natural + elements. \\n\\n\\n \\n\\n\\n a graphic\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/32524-32916\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43620-43649\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43620-43649\",\"text\":\" + \xC7\xC7 \\n \\n Pharma \\n \\n \u2022 R&D \u2013 pr\\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43620-43649\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43653-43816\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43653-43816\",\"text\":\"t + \\n design, test, \\n \\n pricing, etc. \\n \\n \u2022 Knowledge \\n \\n management + \\n \\n \u2022 Supply chain \\n \\n management and \\n \\n logistics \\n \\n + \u2022 Safety \\n \\n \u2022 Compliance \\n \\n Provider: \\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43653-43816\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43820-43841\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43820-43841\",\"text\":\"Clinical + coding \\n \\n \u2022\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/43820-43841\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52072-52252\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52072-52252\",\"text\":\"nes + \\n \\n document describes the process and the \\n \\n technical details for + deploying a new \\n \\n product/service in PDC (contact Stephen \\n \\n Rice + for details) \\n \\n https://www.progress.\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52072-52252\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52256-52411\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52256-52411\",\"text\":\" + \\n \\n \\n\\n\\n Alltools Edit\\n1c)\\n\\n= menu) \xA5y Product Hosting + Guideli. x @ \xA9 # Signin - a x\\nConvert E-Sign Findtextortoo Q 6% a 8\\n| + @\\nProduct Hosting Guidelines\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52256-52411\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52415-53028\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52415-53028\",\"text\":\"t + updated by | Stephen Rice | 3 Dec 2025 at 14:36 GMT i(k)\\n\\nZ.\\n\\n2\\n\\nContents\\n* + Introduction\\n+ Terminology and Overview\\n+ Product Hosting Features\\n+ + Is PDC the correct place to host your service?\\n+ PDC Product Deployment + Process\\n+ Exploration - Need is identified for product to be hosted\\n+ + Preparation - Product and PDC teams create implementati...\\n\\n+ Product + Updates - Product team implements required cha...\\n\\n+ PDC Review - PDC + team reviews design documentation an...\\n+ PDC Integration - PDC deploys + product and performs inte..\\n\\n+ Operations On-boarding - Operations team + is provided wi...\\n+ Retrospective - Revi\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/52415-53028\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53032-53067\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53032-53067\",\"text\":\"rocess + and discuss how any issues..\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53032-53067\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53071-53354\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53071-53354\",\"text\":\"Technical + Requirements\\n\\n+ Reverse Proxy Support\\n\\n+ specif .\\n\\n+ Network Connections + Requirements\\n\\n+ Helm Charts\\n\\n+ Load Bala\\n\\n2 p \\n\\n\\n a screenshot + of a webpage titled \\\"Product Hosting Guidelines\\\". The page contains + a list of contents, including sections on introduction, product deplo\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53071-53354\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53655-53971\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53655-53971\",\"text\":\"r + images present. \\n\\n\\n \\n Product Innovation \\n \\n \\n \\n\\n\\n \\n + 46\xA9 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Progress \\n Data Cloud \\n \\n https://www.progress.com/ + \\n \\n \\n\\n\\n 3) Progress DataCloud \\n\\n\\n a logo for Progress DataCloud. + It shows a green square with a white \\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53655-53971\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53971-54093\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53971-54093\",\"text\":\"arrow + pointing upwards, indicating progress or growth. Visible objects include the + green square and the white arrow. The s\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53971-54093\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54102-54391\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54102-54391\",\"text\":\"shows + a modern office environment with a desk, chair, and computer monitor. \\n\\n\\n + \ \\n 47\xA9 2025 Progress Software Corporation and/or its subsidiaries or + affiliates. All rights reserved. \\n \\n Platform \\n \\n Functionality \\n + \\n Support \\n \\n Support for additional \\n \\n PDP products and \\n services + as we\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/54102-54391\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/10976-11113\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/10976-11113\",\"text\":\"eople + in a garage setting, likely a car repair shop. The woman is seated at a desk + writing on a clipboard, while the man stands behind he\\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/10976-11113\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11122-11484\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11122-11484\",\"text\":\"aning + slightly towards her. Visible objects include a vintage telephone, a metal + workbench with various tools and equipment, and a classic car parked in the + background. The context suggests a professional environment focused on automotive + repairs. \\n\\n\\n \\n 15\xA9 2025 Progress Software Corporation and/or its + subsidiaries or affiliates. All rights reserved. \\n \\n http\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11122-11484\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11489-11626\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11489-11626\",\"text\":\"ww.progress.com/ + \\n \\n \\n\\n\\n \\n\\n\\n a vintage photograph showing a woman working + at a computer desk in an automotive workshop. Visible objects\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11489-11626\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12075-12212\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12075-12212\",\"text\":\" + interface, specifically the Wineria Santine app. The screen displays various + menu options such as \\\"Rolls water transport,\\\" \\\"Faree 310,54\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12075-12212\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12216-12317\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12216-12317\",\"text\":\"04,00,00,\\\" + \\\"Sensitiveness,\\\" \\\"Revenue to market 280 mnx,\\\" \\\"Delivery schedule,\\\" + and \\\"New mascara-intern\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12216-12317\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12322-12628\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12322-12628\",\"text\":\"al + brands 06.\\\" Visible objects include a woman sitting on a bench holding + a smartphone, with storefronts in the background featuring signage in Hindi. + \\n\\n\\n \\n 17\xA9 2025 Progress Software Corporation and/or its subsidiaries + or affiliates. All rights reserved. \\n \\n https://www.progress.com/ \\n + \\n \\n\\n\\n AAPFOINFAE\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12322-12628\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12633-12770\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12633-12770\",\"text\":\"MFROMDE\\n\u201CTUsEBALI + NOW_16 2050 G-\u20ACARAEE\\n[DEWAUS EG TO NELIMAL LK\\nENIOY @0F9 UN JOURTEY. + \\n\\n\\n a digital interface displaying an image of a c\\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/12633-12770\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4766-6189\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4766-6189\",\"text\":\"7\xA9 + 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Congrats getting to the next level! \\n \\n Employee + Location Scrum Team New Position \\n Abhishek Tiwari Hyderabad Mangalayan + QA Engineer, Senior 2 \\n \\n Ajoy Soni Hyderabad Avengers Software Engineer, + Senior 1 \\n \\n Amit Anchaliya Hyderabad Atlantis Software Engineer, Principal + 1 \\n \\n Anshuman Singh Hyderabad Conquerors Software Engineer, Senior 1 + \\n \\n Bing Zhu USA Light QA Engineer, Senior Principal \\n \\n Brahmananda + Gouni Hyderabad - Senior Manager, Software Engineering \\n \\n Brian Tang + USA Quicksilver Software Engineer, Principal \\n \\n Hari Krishna Tirunagari + Hyderabad Mangalayan QA Engineer, Principal 3 \\n \\n Hemanandh S Hyderabad + Avengers Software Engineer, Principal 3 \\n \\n Jonathan Miller USA Kalimba + Software Engineer, Senior \\n \\n Kunal Basarkar Hyderabad Avengers Software + Engineer, Senior Principal \\n \\n Nitesh Mehta Hyderabad Harmonica Software + Engineer, Senior Principal \\n \\n Saivenkat Chepuri Hyderabad Conquerors + Software Engineer, Principal 1 \\n \\n Sathyanarayana Gundoji Hyderabad Mangalayan + Software Engineer, Senior 1 \\n \\n Srikar Veeramallu Hyderabad Atlantis Software + Engineer, Principal 1 \\n \\n Stephen Brown USA Apollo Software Engineer, + Principal \\n \\n Sumit Pritmani Hyderabad Transformers Software Engineer, + Senior 2 \\n \\n Vikram Reddy Deva Hyderabad Avengers QA Engineer, Senior + 2 \\n \\n https://www.progress.com/\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4766-6189\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\",\"text\":\"5\xA9 + 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Welcome to the Team \\n \\n Vamshi Shanigala + \\n Coop/Intern Technical 2 \\n \\n MarkLogic \\n Hyderabad \\n \\n Nathan + Van Gheem \\n Enterprise Architect \\n \\n PDP \\n Raleigh \\n \\n Shivabalu + Thouta \\n Software Engineer, Senior \\n \\n MarkLogic \\n Hyderabad \\n \\n + https://www.progress.com/\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\",\"text\":\"24\xA9 + 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Progress ADP: GTM Motions \\n \\n Expansion: + \\n Cross-sell & Upsell \\n \\n Increase account \\n \\n value through \\n + \\n added ADP \\n \\n products or \\n \\n leveling up tiers \\n \\n \xC7\xC7\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/16815-17085\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\",\"text\":\"6\xA9 + 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Welcome to the Team \\n \\n Aleix Ruiz de Villa + \\n Scientific Advisor \\n \\n PDP \\n Spain \\n \\n Casimiro Pio Carrino + \\n Scientific Advisor \\n \\n PDP \\n Spain\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\",\"text\":\"26\xA9 + 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Progress OpenEdge \\n \\n \xC7\xC7 \\n \\n Modernization + Services & Plus Ones Engagement \\n \\n OpenEdge 13 \u2013 Latest version + \\n supporting FIPS compliance \\n \\n 12 and GenAI Workshops \u2013 Free + \\n hands-on training \\n \\n QSM \u2013 Quality and security \\n management + tools \\n \\n MCP Connector for ABL - AI Code \\n Assistant to improve code + quality \\n \\n Agentic RAG \u2013 AI-driven contextual \\n knowledge retrieval + \\n \\n Forrester Total Economic Impact \u2013 \\n Validated ROI and business + value \\n \\n PUG Challenge \u2013 Community- \\n \\n driven learning and + networking \\n \\n Customer Advisory Board \u2013 Customer \\n \\n advisory + for strategic alignment \\n \\n World Tour \u2013 Global events \\n showcasing + OpenEdge innovation \\n \\n Community - Collaborative network for \\n learning, + sharing, and innovation \\n \\n Customer Validation Program - Early \\n access + to roadmap features and \\n \\n collaborative feedback.\\n\\nDOCUMENT METADATA + AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: Business + Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/19109-20048\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\",\"text\":\"New + \\n \\n Acquisition \\n \\n Win net new \\n \\n customers \\n \\n adopting + Progress \\n \\n Data Platform \\n \\n portfolio \\n \\n Customer \\n \\n + Renewal \\n \\n Retain existing \\n \\n customers by \\n \\n reinforcing ongoing + \\n \\n value of current \\n \\n product(s) in use \\n \\n https://www.progress.com/\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/17085-17354\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\",\"text\":\"and + what qualifications staff require to apply it? \\n \\n Submit \\n \\n https://www.progress.com/\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/14158-14258\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\",\"text\":\"Celebrating + Innovation\\nfrom PI 3...\\n\\nBrian Tang - FastTrack w/ MCP\\n\\nVanessa + Zhang - Al diff analysis\\n\\nShivali Tayal - 3rd party\\ndependency update + automation\\n\\nProgress\u2019\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/2193-2360\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\",\"text\":\"2\xA9 + 2022 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Celebrating Q4 \\n \\n Releases \\n \\n ARC, + PostgreSQL, Oracle \\n \\n OpenAccess 9.0 for AIX \\n \\n Corticon 7.3.0 \\n + \\n Corticonjs 2.4.0 \\n \\n MarkLogic 11.3.2/3 \\n \\n MarkLogic IronBank + \\n \\n Operator 1.1.1 \\n \\n Progress Agentic RAG \\n \\n PDC 1.2.2/1.3.0 + \\n \\n Semaphore 5.8.6 \\n \\n Security \\n \\n Trufflehog \\n \\n SAMM Level + 2 \\n \\n Spy Attributes \\n Vulnerability \\n Resolution \\n \\n HDP 4.6.2 + \\n \\n Infrastructure \\n \\n Sonar Code \\n Coverage \\n \\n Innovation + \\n \\n Corticon AI \\n Generated User \\n Interface \\n \\n AI Video Production + \\n \\n Share your additional celebrations in the meeting chat!\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/1388-2043\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\",\"text\":\"48\xA9 + 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n PDC Priorities & Innovation \\n \\n \u2022 Functional + Expansion \u2013 Increase value proposition by on- \\n boarding additional + PDP (and other) services \\n \\n Business Priorities \\n \\n \u2022 MCP OpenEdge + ABL Service \\n \\n \u2022 Hybrid Data Pipeline Service \\n \\n \u2022 EULA + Acceptance Feedback Mechanism \\n \\n \u2022 Data Symphony Service \\n \\n + \u2022 Operational Support Shared Logging (CRIBL) \\n \\n Innovation Areas + \\n \\n https://www.progress.com/\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/46719-47227\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\",\"text\":\"Creation + of a new enterprise \\n \\n architecture function led by \\n \\n James Kerr + with a first \\n \\n dedicated PDP level \\n \\n enterprise architect: Nathan + \\n van Gheem. \\n \\n \u2022 Nuclia \\n \\n \u2022 Reporting line changes + for \\n \\n HDP\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/8847-9067\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\",\"text\":\"\u2022 + Expansion/New Logos - Supporting the AI Journey, Lowering TCO, Supporting + \\n Hybrid Deployment Options \\n \\n Business Priorities \\n \\n \u2022 Graviton + Support \\n \\n \u2022 Monitoring Agent \\n \\n \u2022 Nuclia-MarkLogic Integration + \\n \\n \u2022 MarkLogic Knowledge Hub \\n \\n \u2022 Flux as PDC Service + \\n \\n Innovation \\n \\n \u2022 Property Graphs \\n \\n \u2022 Read from + Replicas \\n \\n \u2022 Index Exclusion \\n \\n \u2022 Vector improvements + \\n \\n \u2022 Object storage improvement \\n \u2022 Support Kendo Theme Builder + in FastTrack \\n \\n https://www.progress.com/\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: + 2025-12-11 15:41:54.970000+00:00\\nfilename: Business Context and Product + Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: + Test folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/49179-49670\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\",\"text\":\"42\xA9 + 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. 42 \\n \\n Getting Started \\n \\n \u2022 Contact the + PDC PM/PO (Stephen Rice) to \\n \\n discuss \\n \\n \u27A2 Provide as many + details as required \\n \\n including timeframes \\n \\n \u27A2 Meeting will + be arranged between key \\n \\n stakeholders \\n \\n https://www.progress.com/\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/40988-41333\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\",\"text\":\"59\xA9 + 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. \\n \\n Corticon Priorities & Innovation \\n \\n \u2022 + Retention \u2013 Support, CVEs, encourage update to latest LTS \\n \\n \u2022 + Public Sector Expansion - Replicate success at State of Mississippi \\n \\n + \u2022 Platform Modernization - New UI and SaaS to enable more customer wins + \\n \\n Business Priorities \\n \\n \u2022 Modern UI \\n \\n \u2022 AI powered + user experience \\n \\n \u2022 SaaS offering in PDC \\n \\n \u2022 Symphony + rule deployment \\n \\n Innovation \\n \\n https://www.progress.com/\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/55634-56168\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\",\"text\":\"Performance + & Reliability Upgrades \u2013 \\n \\n Faster queries and improved resilience + \\n \\n for mission-critical workloads. \\n \\n AI-Assistant \u2013 Simplify + the developer \\n \\n experience and lower the learning curve.\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/27462-27669\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\",\"text\":\"a + digital photograph showing two people working at a desk. The man is seated, + looking at the computer screen, while the woman stands behind him, smiling. + Visible objects include a desktop computer with a keyboard and mouse, a pen + holder, and some documents on the desk. The background features a green wall + with charts and graphs.\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/7044-7374\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31881-32155\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31881-32155\",\"text\":\"\u2713 + Faster Contract Approvals \u2013 Streamlined deal desk and legal alignment + for quicker turnaround. \\n \\n \u2713 Transparent Pricing Models \u2013 Unified + price list and predictable cost structures. \\n \\n \u2713 Starter Bundles + for Simplicity \u2013 Upcoming PDP SKU for easier entry and adoption.\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/31881-32155\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41776-42205\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41776-42205\",\"text\":\"44\xA9 + 2025 Progress Software Corporation and/or its subsidiaries or affiliates. + All rights reserved. 44 \\n \\n Product Hosting Notes \\n \\n \u2022 Current + lead times for product \\n \\n deployment are currently 3-6 months \\n \\n + \u2022 A Product Hosting Guidelines \\n \\n document describes the process + and the \\n \\n technical details for deploying a new \\n \\n product/service + in PDC (contact Stephen \\n \\n Rice for details) \\n \\n https://www.progress.com/\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/41776-42205\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53354-53655\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53354-53655\",\"text\":\"Modernize + the Corticon \\n \\n user experience with a \\n new Web UI for, \\n \\n designed + to simplify \\n \\n rule authoring and \\n accelerate adoption for \\n \\n + new projects. \\n \\n Accelerate rule \\n \\n automation and \\n delivery + with AI that \\n supports end-to-end \\n \\n project creation, \\n testing, + and \\n \\n maintenance.\\n\\nDOCUMENT METADATA AT ORIGIN:\\ncreated: 2025-12-11 + 15:41:54.970000+00:00\\nfilename: Business Context and Product Vision 2026 + 1_self_signed.pdf\\nmodified: 2025-12-11 15:42:05.133000+00:00\\npath: Test + folder/Test folder/Business Context and Product Vision 2026 1_self_signed.pdf\\nsource_id: + sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n auth_provider: + sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n file_id: + fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: ''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/53354-53655\",\"augmentation_type\":\"metadata_extension\"},\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11635-12070\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/11635-12070\",\"text\":\"a + digital screenshot of a mobile phone interface, specifically the Wineria Santine + app. The screen displays various menu options such as \\\"Rolls water transport,\\\" + \\\"Faree 310,54,64,04,00,00,\\\" \\\"Sensitiveness,\\\" \\\"Revenue to market + 280 mnx,\\\" \\\"Delivery schedule,\\\" and \\\"New mascara-international + brands 06.\\\" Visible objects include a woman sitting on a bench holding + a smartphone, with storefronts in the background featuring signage in Hindi.\\n\\nDOCUMENT + METADATA AT ORIGIN:\\ncreated: 2025-12-11 15:41:54.970000+00:00\\nfilename: + Business Context and Product Vision 2026 1_self_signed.pdf\\nmodified: 2025-12-11 + 15:42:05.133000+00:00\\npath: Test folder/Test folder/Business Context and + Product Vision 2026 1_self_signed.pdf\\nsource_id: sync_config_019cade7-c177-77c5-99c2-c8771f85cf91\\nsync_metadata:\\n + \ auth_provider: sharefile_oauth\\n content_hash: 866f34bfe00a53e9265df7699d9b264b\\n + \ file_id: fi3567d8-8bbe-96ac-4e21-132d539a9e53\\nurl: 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''\\n\",\"parent\":\"866f34bfe00a53e9265df7699d9b264b/a/title\",\"augmentation_type\":\"metadata_extension\"}},\"fields\":{\"866f34bfe00a53e9265df7699d9b264b/a/title\":{\"id\":\"866f34bfe00a53e9265df7699d9b264b/a/title\",\"text\":\"Business + Context and Product Vision 2026 1_self_signed.pdf\",\"augmentation_type\":\"field_extension\"}}}}}\n{\"item\":{\"type\":\"footnote_citations\",\"footnote_to_context\":{\"block-AB\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/3054-3424\",\"block-AD\":\"866f34bfe00a53e9265df7699d9b264b/f/866f34bfe00a53e9265df7699d9b264b/4148-4399\"}}}\n{\"item\":{\"type\":\"metadata\",\"tokens\":{\"input\":943,\"output\":10,\"input_nuclia\":0.943,\"output_nuclia\":0.01},\"timings\":{\"generative_first_chunk\":1.450395756000944,\"generative_total\":2.7534563170047477}}}\n{\"item\":{\"type\":\"consumption\",\"normalized_tokens\":{\"input\":0.94299,\"output\":0.00972,\"image\":0.0},\"customer_key_tokens\":{\"input\":0.0,\"output\":0.0,\"image\":0.0}}}\n" + headers: + Alt-Svc: + - h3=":443"; ma=2592000,h3-29=":443"; ma=2592000 Transfer-Encoding: - chunked access-control-expose-headers: - - X-NUCLIA-TRACE-ID + - NUCLIA-LEARNING-ID,X-NUCLIA-TRACE-ID content-type: - application/x-ndjson date: - - Wed, 05 Aug 2026 08:10:19 GMT + - Wed, 15 Jul 2026 08:11:46 GMT nuclia-learning-id: - - d62db6e7ca50459ea209701d038d5370 - nuclia-learning-model: - - chatgpt-azure-4o-mini + - d5de8633afd345d0b14bd067304be32b via: - 1.1 google x-envoy-upstream-service-time: - - '621' + - '2575' x-nuclia-trace-id: - - a75f3ef14029a9e0ffe13538b7ef022a + - ff0273c5d7ddd3d7462448d4c88ef51b status: code: 200 message: OK diff --git a/agents/nucliadb/tests/test_nucliadb.py b/agents/nucliadb/tests/test_nucliadb.py index ee9505de..eb9d4f95 100644 --- a/agents/nucliadb/tests/test_nucliadb.py +++ b/agents/nucliadb/tests/test_nucliadb.py @@ -26,26 +26,19 @@ NucliaDBConnection, ) - -def ignore_nucliadb_api(request): - if request.path.startswith("/api/v1/kb/"): - return None - return request - - NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.dp.progress.cloud/") +) or cassette_nua_key("https://europe-1.nuclia.cloud/") KB_DE48CFAA_3209_4041_BB64_8604AFF061FB = os.environ.get( "KB_DE48CFAA_3209_4041_BB64_8604AFF061FB" -) or cassette_nua_key("https://europe-1.dp.progress.cloud/") +) or cassette_nua_key("https://europe-1.nuclia.cloud/") KB_DF8B4C24_2807_4888_AD6C_AE97357A638B = os.environ.get( "KB_DF8B4C24_2807_4888_AD6C_AE97357A638B" -) or cassette_nua_key("https://europe-1.dp.progress.cloud/") +) or cassette_nua_key("https://europe-1.nuclia.cloud/") KB_F718BA84_2973_462F_9B15_F300BD260134 = os.environ.get( "KB_F718BA84_2973_462F_9B15_F300BD260134" -) or cassette_nua_key("https://europe-1.dp.progress.cloud/") +) or cassette_nua_key("https://europe-1.nuclia.cloud/") CONFIG = { @@ -68,8 +61,8 @@ def ignore_nucliadb_api(request): "provider": "nucliadb", "identifier": "nuclia-docs", "config": { - "url": "https://europe-1.dp.progress.cloud/api", - "manager": "https://europe-1.dp.progress.cloud/api", + "url": "https://europe-1.nuclia.cloud/api", + "manager": "https://europe-1.nuclia.cloud/api", "kbid": "df8b4c24-2807-4888-ad6c-ae97357a638b", "key": KB_DF8B4C24_2807_4888_AD6C_AE97357A638B, "filters": [], @@ -81,8 +74,8 @@ def ignore_nucliadb_api(request): "provider": "nucliadb", "identifier": "nuclia-web", "config": { - "url": "https://europe-1.dp.progress.cloud/api", - "manager": "https://europe-1.dp.progress.cloud/api", + "url": "https://europe-1.nuclia.cloud/api", + "manager": "https://europe-1.nuclia.cloud/api", "kbid": "f718ba84-2973-462f-9b15-f300bd260134", "key": KB_F718BA84_2973_462F_9B15_F300BD260134, "filters": [], @@ -144,8 +137,8 @@ def ignore_nucliadb_api(request): "provider": "nucliadb", "identifier": "nuclia-docs", "config": { - "url": "https://europe-1.dp.progress.cloud/api", - "manager": "https://europe-1.dp.progress.cloud/api", + "url": "https://europe-1.nuclia.cloud/api", + "manager": "https://europe-1.nuclia.cloud/api", "kbid": "df8b4c24-2807-4888-ad6c-ae97357a638b", "key": KB_DF8B4C24_2807_4888_AD6C_AE97357A638B, "filters": [], @@ -257,7 +250,7 @@ async def callback(obj: AragAnswer): @pytest.mark.asyncio -@pytest.mark.vcr(ignore_localhost=True, before_record_request=ignore_nucliadb_api) +@pytest.mark.vcr(ignore_localhost=True, ignore_hosts=["europe-1.dp.progress.cloud"]) async def test_nucliadb_agent_simple(): answers = [] @@ -283,7 +276,7 @@ async def callback(obj: AragAnswer): @pytest.mark.asyncio -@pytest.mark.vcr(ignore_localhost=True, before_record_request=ignore_nucliadb_api) +@pytest.mark.vcr(ignore_localhost=True, ignore_hosts=["europe-1.dp.progress.cloud"]) async def test_nucliadb_agent_simple_disable_ai_parameter_search(): question_memory = await arag_main( agent_id="default", @@ -301,7 +294,7 @@ async def test_nucliadb_agent_simple_disable_ai_parameter_search(): @pytest.mark.asyncio -@pytest.mark.vcr(ignore_localhost=True, before_record_request=ignore_nucliadb_api) +@pytest.mark.vcr(ignore_localhost=True, ignore_hosts=["europe-1.dp.progress.cloud"]) async def test_nucliadb_agent_basic_ask(): config = deepcopy(CONFIG_SIMPLE) @@ -449,7 +442,7 @@ def test_build_ask_request(): search_configuration="foobar", ) driver = NucliaDBConnection( - url="https://europe-1.dp.progress.cloud/api", + url="https://europe-1.nuclia.cloud/api", manager="foo", kbid="df8b4c24-2807-4888-ad6c-ae97357a638b", description="foo", diff --git a/agents/nucliadb/tests/test_sync.py b/agents/nucliadb/tests/test_sync.py index 02e52e3d..225f5a23 100644 --- a/agents/nucliadb/tests/test_sync.py +++ b/agents/nucliadb/tests/test_sync.py @@ -13,24 +13,17 @@ from hyperforge.minimal_fixtures import cassette_nua_key from hyperforge.pubsub import UserToAgentInteraction - -def ignore_nucliadb_api(request): - if request.path.startswith("/api/v1/kb/"): - return None - return request - - NUA_KEY = os.environ.get( "NUA_KEY", -) or cassette_nua_key("https://europe-1.dp.progress.cloud/") +) or cassette_nua_key("https://europe-1.nuclia.cloud/") KB_E103CAF3_F8CB_4161_A57C_AAD1192D0666 = os.environ.get( "KB_E103CAF3_F8CB_4161_A57C_AAD1192D0666" -) or cassette_nua_key("https://europe-1.dp.progress.cloud/") +) or cassette_nua_key("https://europe-1.nuclia.cloud/") pytestmark = [ - pytest.mark.vcr(ignore_localhost=True, before_record_request=ignore_nucliadb_api), + pytest.mark.vcr(ignore_localhost=True, ignore_hosts=["europe-1.dp.progress.cloud"]), pytest.mark.asyncio, ]