# langchat
**Repository Path**: mail6562/langchat
## Basic Information
- **Project Name**: langchat
- **Description**: LangChat: Java LLMs/AI Project, Supports Multi AI Providers( OpenAI / Gemini / Ollama / Bedrock / Azure / Mistral), Java生态下AI大模型产品解决方案，快速构建企业级AI应用
- **Primary Language**: Java
- **License**: AGPL-3.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 21
- **Created**: 2024-07-25
- **Last Updated**: 2024-07-25
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# 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](./README.md)
- Website Docs：[http://langchat.cn/](http://langchat.cn/)
- Backend Preview：[http://backend.langchat.cn/](http://backend.langchat.cn/)
- Front Preview：[http://front.langchat.cn/](http://front.langchat.cn/)
- LangChat Source：[https://github.com/tycoding/langchat](https://github.com/tycoding/langchat)
- LangChat.cn Source：[https://github.com/tycoding/langchat.cn](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
1. Multimodal: Supports integration with dozens of AI large models from both domestic and international sources.
2. 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.
3. Knowledge Base: Supports vectorized knowledge base documents and customized Prompt dialogue scenarios.
4. Advanced RAG: Supports embedding models for precise searches within the knowledge base; integrates RAG plugins like Web Search.
5. Function Call: Supports customized tool classes for local function calls, loading data from third parties, and providing them to LLM.
6. 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).
7. Workflows: Plans to develop a visual LLM process designer for highly customized robot execution processes (to be improved).
8. Provides AIGC client applications to quickly manage client data
9. 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)
## Copyright and License
Licensed under the GNU License (GPL) v3.
Copyright (c) 2024-present, TyCoding.
Support personal free access to learn to use, commercial applications please contact the author authorization
## Preview
## Thanks
- [LangChain4j](https://github.com/langchain4j/langchain4j)
## Contact
- Blog: https://tycoding.cn
- Github: https://github.com/tycoding
- Email: langchat@outlook.com
- WeChat: LangChainChat