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LANGCHAIN-CHATCHAT
Offline RAG and LLM platform with local model support and knowledge bases
Apache-2.0
ABOUT
Building a production RAG application that runs entirely offline requires integrating LLM inference, embedding models, vector storage, document parsing, and a chat interface — all working together reliably. Langchain-Chatchat provides a complete, self-contained platform that supports local LLM deployment (ChatGLM, Llama, Qwen, etc.), automatic document ingestion and chunking, vector-based knowledge retrieval, and a web-based chat UI — all without any external API calls or cloud dependencies.
INTEGRATION GUIDE
1. Deploy a fully offline enterprise knowledge base Q&A system with local LLMs and private documents
2. Build a document retrieval chatbot that answers questions from uploaded PDFs, Word docs, and markdown
3. Create a multi-tenant RAG platform where each team has its own isolated knowledge base
4. Integrate with local embedding models and vector stores for complete data sovereignty
5. Set up a conversational search interface over internal technical documentation and wikis
TAGS
pythonraglangchainllmknowledge-baselocalofflinechatglm