ObsidianRAG
Ask questions of your Obsidian notes with private, local AI RAG.
OpenDocumentsは、joungminsungが公開しているオープンソースのRAG・知識ベースプロジェクトです(GitHub: joungminsung/OpenDocuments)。GitHubスターは115、フォークは21で、MITライセンスの下で公開されています。GitHubでの最終更新は2026年7月26日です。
Self-hosted RAG search across GitHub, Drive, Notion, and local files.
Download the source and enter the folder.
Pull the Node packages it needs.
Link GitHub, Drive, Notion, or local folders.
Ask questions and get sourced answers.
GitHub, Drive, Notion, local files, and web.
Every answer links back to its sources.
Your documents stay on your infrastructure.
Semantic search over your content.
Modern codebase to extend.
Shared search for people and agents.
Download the source and move into the project folder.
git clone https://github.com/joungminsung/OpenDocuments.git
cd OpenDocumentsPull the Node packages it needs.
npm installStart the app after configuring sources.
npm run devIt is an open-source project at joungminsung/OpenDocuments with 21 forks.
Yes. It is MIT licensed.
GitHub, Notion, Google Drive, local files, and web sources.
Yes. Citations back to source documents are a core feature.
Yes. It is designed as a self-hosted RAG platform.
Ask questions of your Obsidian notes with private, local AI RAG.
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context…
Transparent Python RAG reference with FAISS + BM25 hybrid retrieval.
Self-hosted rag & knowledge: 🧠 the brain for your ai — local-first memory engine for.
Self-hosted rag & knowledge: cometchat docs search + implementation bundles: add cha.
Federated AI search and RAG across 100+ apps — answers with sources, without moving your data
LibreAIカタログに掲載されたRAG・知識ベースプロジェクトの中で最もスターの多いもの — OpenDocumentsが合わなかった場合に検討したい、現実的な候補リストです。
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or…
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context…
Lightweight OCR toolkit turning PDFs and images into structured, LLM-ready data in 100+ languages
MinerU — turns PDFs and Office documents into LLM-ready Markdown and JSON for agents and RAG pipelines, Apache-2.0 plus terms
Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience
カタログの中でOpenDocumentsとスター数が近いRAG・知識ベースプロジェクト — 前後の棚もそのまま見て回れます。
Local AI-driven document search and editing with first-in-class hybrid retrieval
Open rag & knowledge for this repo accelerates development of rag applications w.
High-performance PDF conversion library for macOS apps.
Self-hosted rag & knowledge: turn your own pdf textbooks into an ai-searchable knowl.
Internal Q&A and knowledge base for Backstage.
Open rag & knowledge for "autonomie" is a highly semantic, responsive, accessibl.