https://github.com/RapidAI/RapidRAG
QA based on local knowledge and LLM.
https://github.com/RapidAI/RapidRAG
chatglm langchain llm local-knowledge qa
Last synced: 9 months ago
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QA based on local knowledge and LLM.
- Host: GitHub
- URL: https://github.com/RapidAI/RapidRAG
- Owner: RapidAI
- License: apache-2.0
- Created: 2023-04-18T00:20:31.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2025-01-02T06:04:08.000Z (over 1 year ago)
- Last Synced: 2025-01-09T05:08:03.727Z (over 1 year ago)
- Topics: chatglm, langchain, llm, local-knowledge, qa
- Language: Python
- Homepage: https://rapidai.github.io/Knowledge-QA-LLM/docs/
- Size: 10.6 MB
- Stars: 201
- Watchers: 8
- Forks: 42
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
🧐 Rapid RAG
[简体中文](./docs/README_zh.md) | English
### 📣 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.
### Documentation
Full documentation can be found on [docs](https://rapidai.github.io/RapidRAG/docs/), in Chinese.
### TODO
- [ ] Support keyword + vector hybrid search.
- [ ] Vue.js based UI .
### Code Contributors
### 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.
### License
[Apache 2.0](https://choosealicense.com/licenses/apache-2.0/)