Awesome
<div align="center"> <div align="center"> <h1><b>🧐 Knowledge QA LLM</b></h1> </div> <a href=""><img src="https://img.shields.io/badge/Python->=3.8,<3.12-aff.svg"></a> <a href=""><img src="https://img.shields.io/badge/OS-Linux%2C%20Win%2C%20Mac-pink.svg"></a> <a href=""><img src="https://img.shields.io/github/v/release/RapidAI/QA-LocalKnowledge-LLM?logo=github"></a> <a href="https://semver.org/"><img alt="SemVer2.0" src="https://img.shields.io/badge/SemVer-2.0-brightgreen"></a> <a href="https://github.com/psf/black"><img src="https://img.shields.io/badge/code%20style-black-000000.svg"></a> <a href="https://choosealicense.com/licenses/apache-2.0/"><img alt="GitHub" src="https://img.shields.io/github/license/RapidAI/Knowledge-QA-LLM"></a>简体中文 | English
</div>📣 We're looking for front-end development engineers interested in Knowledge QA with LLM, who can help us achieve front-end and back-end separation with our current implementation.
Introduction
- Questions & Answers based on local knowledge base + LLM.
- Reason:
- The idea of this project comes from Langchain-Chatchat.
- I have used this project before, but it is not very flexible and deployment is not very friendly.
- Learn from the ideas in How to build a knowledge question answering system with a large language model, and try to use this as a practice.
- Advantage:
- The whole project is modularized and does not depend on the
lanchain
library, each part can be easily replaced, and the code is simple and easy to understand. - In addition to the large language model interface that needs to be deployed separately, other parts can use CPU.
- Support documents in common formats, including
txt, md, pdf, docx, pptx, excel
etc. Of course, other types of documents can also be customized and supported.
- The whole project is modularized and does not depend on the
Demo
⚠️ If you have Baidu Account, you can visit the online demo based on ERNIE Bot.
<div align="center"> <img src="https://github.com/RapidAI/Knowledge-QA-LLM/releases/download/v0.0.1/UIDemo.gif" width="100%" height="100%"> </div>Documentation
Full documentation can be found on docs, in Chinese.
TODO
- Support keyword + vector hybrid search.
- Vue.js based UI .
Code Contributors
<p align="left"> <a href="https://github.com/RapidAI/Knowledge-QA-LLM/graphs/contributors"> <img src="https://contrib.rocks/image?repo=RapidAI/Knowledge-QA-LLM" width="15%"/> </a> </p>Contributing
- Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
- Please make sure to update tests as appropriate.
Sponsor
If you want to sponsor the project, you can directly click the Buy me a coffee image, please write a note (e.g. your github account name) to facilitate adding to the sponsorship list below.
<div align="left"> <a href="https://www.buymeacoffee.com/SWHL"><img src="https://raw.githubusercontent.com/RapidAI/.github/main/assets/buymeacoffe.png" width="30%" height="30%"></a> </div>