#Document-qa
Showing 9 of 9 repositories tagged #document-qa, ranked by stars
Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A
🧠 纯原生 Python 实现的 RAG 框架 | FAISS + BM25 混合检索 | 支持 Ollama / SiliconFlow | 适合新手入门学习
Self-hosted RAG platform for AI document search across GitHub, Notion, Google Drive, local files, and web sources with citations.
Extends pageIndex into an AI document workspace with multi-format parsing, OCR, visual TOC, custom models, citations, and agentic QA.
A simple, local-first RAG framework for building document Q&A applications
PDFs you can talk to.
Production-ready RAG framework for Python — multi-tenant chatbots with streaming, tool calling, agent mode (LangGraph), vector search (FAISS), and persistent MongoDB memory. Built on LangChain.
Deterministic RAG pipeline - AI powered troubleshooting for ground support equipment. Deterministic RAG pipeline that ingests OEM maintenance manuals, answers with cited sources, and refuses when the documentation doesn't support a claim. Runs fully on-premises, no cloud APIs
Open-source RAG engine for ingesting, indexing, and querying unstructured documents