What it does
RAG (retrieval-augmented generation) is a common method where an AI first looks up relevant passages in your documents and then writes an answer from them. This project collects many techniques for doing that well.
Each technique comes as a runnable notebook, a document that mixes explanation and code you can run step by step. The topics go from basic set-ups to more advanced methods.
It is community-driven. The README also promotes a paid course, a book and a newsletter from the author.
Who it's for
Developers and students who want to learn how to build better document question-answering systems.
Can I use it without coding?
Developers only. The tutorials are Python notebooks that you run and edit. New to this? Start here.
Can I run it?
- Cost
- FreeNothing to pay or sign up for.
- API key
- Not needed
Try it
Using Claude Code, Cursor or another AI coding assistant? Paste the prompt and it will walk you through the setup.New to this?
Before you install
- Only download from the official GitHub page. Copies with similar names exist for many popular projects.
- No standard license listed. Check the GitHub page before using it for business.
- More on staying safe