RAG・知識ベース
autoflow
Graph RAG conversational knowledge base built on TiDB Serverless vector storage
★ 3.0k スターApache-2.0
ガイドを見る →Langchain-Chatchatは、chatchat-space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: chatchat-space/Langchain-Chatchat）。GitHubスターは38,676、フォークは6,257で、Apache-2.0ライセンスの下で公開されています。GitHubでの最終更新は2025年11月10日です。
Local knowledge-base RAG and agent app built on LangChain with ChatGLM, Qwen and Llama models
Decide what you want from Langchain-Chatchat and check the README and requirements to confirm it fits your setup and Python environment.
Clone the repository from GitHub (github.com/chatchat-space/Langchain-Chatchat) or use the documented install channel if you do not need the source.
Follow the README quickstart to install dependencies and set any required configuration or credentials.
Work through the README's first example end to end, then adapt it to your own project or data.
Chat over your own documents using local models like ChatGLM, Qwen and Llama.
Combines retrieval-augmented generation with agent capabilities in one app.
Supports deployment frameworks including Ollama, Xinference and FastChat.
Works with FAISS and Milvus for embedding storage.
Ships a web UI for chatting with the knowledge base.
Can be deployed with pip or Docker, per the quick start.
Start by getting the source and entering the project directory.
git clone https://github.com/chatchat-space/Langchain-Chatchat.git
cd Langchain-ChatchatInstall the package from PyPI.
pip install langchain-chatchat -UFollow the quick start to initialize the knowledge base and launch the app.
chatchat init # see README for the exact command sequenceReaders working through the RAG & Knowledge shelf also stop at AppFlowy-Web, open-source AI workspace for projects, wikis, and team docs. compiiile renders and deploy a folder of markdown as a site in one move. The RAG & Knowledge shelf also holds backstage-plugin-qeta — Internal Q&A and knowledge base for Backstage.
It is maintained by chatchat-space and contributors on GitHub, where the repository github.com/chatchat-space/Langchain-Chatchat is the canonical home for code, issues and releases.
Yes — it is open source under the Apache-2.0 license. Read the license in the repository for what is permitted, including any conditions on redistribution or commercial use.
No paid key needed when using local models — you run ChatGLM, Qwen or Llama yourself.
Compared with PrivateGPT: Both do private local RAG; Chatchat is a full LangChain application with UI, while PrivateGPT focuses on an API layer.
Clone github.com/chatchat-space/Langchain-Chatchat, follow the README quickstart to install it, and run the documented first example before adapting it to your own work.
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カタログの中でLangchain-Chatchat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。
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