LangChat

Quickly Build Enterprise-level AIGC Projects

LangChat is an enterprise-level AIGC project solution in the Java ecosystem. Based on the RBAC permission system, it integrates AIGC large model functionalities to help enterprises quickly customize knowledge bases and enterprise robots.

中文

Website Docs：http://langchat.cn/
Backend Preview：http://backend.langchat.cn/
Front Preview：http://front.langchat.cn/
LangChat Source：https://github.com/tycoding/langchat
LangChat.cn Source：https://github.com/tycoding/langchat.cn

Note: LangChat is still under continuous development and may have some bugs and imperfections. The author will fix them as soon as possible.

Welcome Star, fork to continue to pay attention

Features

Multimodal: Supports integration with dozens of AI large models from both domestic and international sources.
Dynamic Configuration: Allows visual dynamic configuration of large model parameters, keys, etc. on the page, with seamless refresh and no need to restart the service each time.
Knowledge Base: Supports vectorized knowledge base documents and customized Prompt dialogue scenarios.
Advanced RAG: Supports embedding models for precise searches within the knowledge base; integrates RAG plugins like Web Search.
Function Call: Supports customized tool classes for local function calls, loading data from third parties, and providing them to LLM.
Multi-channel Release: Plans to encapsulate a Web SDK to quickly embed AI smart customer service into any third-party web application; plans to support messaging channels such as WeChat, Feishu, DingTalk, etc. (to be improved).
Workflows: Plans to develop a visual LLM process designer for highly customized robot execution processes (to be improved).
Provides AIGC client applications to quickly manage client data
More features...

Sponsorship

Due to limited author resources, the project development documentation may be lacking. You can join my Java WeChat group: LangChainChat (please specify the purpose).

If you have any development questions about LangChat or need secondary development customization, you can buy the author a cup of coffee and join my LangChat group:

Add WeChat: LangChainChat (remark: sponsorship)