Langchain-Chatchat

This project provides a local knowledge-based question-answering system built on Langchain and Chinese-centric open source LLMs such as ChatGLM, Qwen, and Llama. It supports offline deployment with vector search over documents using embeddings and multiple retrieval methods including BM25 and KNN, integrating through FastAPI or Streamlit interfaces. Unlike cloud-dependent RAG solutions, it fully embraces open source models and private data, targeting Chinese language scenarios with optimised agents for ChatGLM3 and Qwen. It supports multimodal dialogue and external APIs like Wolfram Alpha, which adds versatility beyond plain text Q&A. With over 37,000 stars and a recent commit in November 2025, it is actively maintained but the growth history is not significant yet. Teams needing a fully offline, Chinese-language friendly RAG system with open source models will benefit most. It is not suitable if your priority is a turnkey, cloud-based solution with extensive model tuning or if you require large-scale commercial support, where alternatives like Haystack or Langchain with OpenAI models might be better choices.

Choose this project when you need a locally deployable RAG system focused on Chinese language support and open source LLMs with flexible retrieval options and agent workflows. If you prefer cloud-hosted services or require extensive fine-tuning capabilities, consider alternatives like Haystack for broader language support or Langchain integrated with OpenAI GPT for managed APIs.

Typically used for internal knowledge base Q&A systems in Chinese environments, such as document search and interactive chatbots over private corpora. It fits teams building offline RAG applications with multimodal inputs or integrating external APIs for enhanced dialogue capabilities.

Latest commit: 2025-11-10. Activity data is based on daily RepoPi snapshots of the GitHub repository.