# Knowledge-QA-LLM

**Repository Path**: ivy2021/Knowledge-QA-LLM

## Basic Information

- **Project Name**: Knowledge-QA-LLM
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-01-10
- **Last Updated**: 2024-01-10

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

<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>
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  [简体中文](./docs/README_zh.md) | 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](https://github.com/chatchat-space/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](https://mp.weixin.qq.com/s/movaNCWjJGBaes6KxhpYpg), 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.

### Demo
⚠️ If you have Baidu Account, you can visit the [online demo](https://aistudio.baidu.com/projectdetail/6675380?contributionType=1) 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](https://rapidai.github.io/Knowledge-QA-LLM/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](https://swhl.github.io/RapidVideOCR/docs/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>

### License
[Apache 2.0](https://choosealicense.com/licenses/apache-2.0/)