document-assistant

RAG based Document Assistant for Search

🤖 Agentic RAG - An intelligent document assistant with semantic chunking, hybrid search (vector + BM25), multi-format support (PDF, Word, CSV, Excel), and multi-channel bots (Telegram, WhatsApp). Built with FastAPI, React, PostgreSQL/pgvector, and LangChain.

🧠 Secure AI Assistant to chat with your documents. Isolated vector data storage with full citation tracing built using FastAPI and Flutter.

An intelligent academic document assistant for scholarly research and analysis.

RAG-based AI document assistant using Spring Boot, Spring AI, Ollama, and React for intelligent document Q&A.

Offline PDF and Word document assistant with local Ollama, cited answers, React/FastAPI, and portable deployment.

An AI-powered document analysis system that enables users to upload PDFs, search document content, and ask questions using Retrieval-Augmented Generation (RAG), semantic embeddings, vector search, and Large Language Models (LLMs).

A private AI assistant for your company's documents - runs entirely on your own hardware. Source-available so your IT can audit the privacy claim.

This repository contains materials for studying and implementing Agentic AI from ReadyTensor.

SmartDoc Query — PDF, OCR and semantic document assistance for iOS. Private-source product case study.

Indexes documentation and answers questions using retrieval-augmented generation with OpenAI, Claude, Gemini, Groq, or Ollama through a CLI or web interface.

Top AI Document Assistant Summarization (Opensource) Star if you like it!

AI-powered document assistant with semantic search and context-aware question answering using Gemini, FAISS, React, and Flask.

NovaDocs is a multi-workspace document assistant. Upload text, Markdown, or PDF files into isolated workspaces, then ask questions grounded in your own content. Answers include citations, honest refusals when the corpus does not support a claim, and optional tools to save tasks or post Slack summaries.

Local-first private document assistant for macOS

A lightweight Document Q&A chatbot using RAG. Built from scratch with FastAPI, pgvector, and local (Ollama) or remote (OpenAI) LLMs.

Small AI document assistant prototype using Python, Streamlit, prompt design, and basic document retrieval.

Belgeleri buluta göndermeden tamamen yerel çalışan, PDF ve TXT dosyalarındaki sorulara yalnızca belge içeriğine dayanarak yanıt veren RAG tabanlı yapay zeka belge asistanı.

Fully local RAG-powered document and code assistant built with LlamaIndex - hybrid ChromaDB + BM25 retrieval, query routing and expansion, and an on-device DeepSeek LLM via Streamlit UI and CLI, with no cloud APIs required.

Full-stack AI document Q&A app — upload PDFs (+ scanned OCR), chat with documents using local LLM (RAG pipeline). Built with Next.js, FastAPI, MongoDB Atlas & Ollama.