What it does
All-in-RAG is a tutorial on RAG, short for retrieval-augmented generation. RAG is a way of letting an AI look things up in your own documents or data before it answers, so its answers are based on that material.
The course walks through each stage: loading and splitting documents, turning text into searchable form, storing it in a vector database (a database built for this kind of search), improving search results, and checking how well the system works. It ends with hands-on projects.
It is written mainly in Chinese, with an English README, and can be read online.
Who it's for
Developers with basic Python skills who want to learn to build question-answering systems over their own data.
Can I use it without coding?
Developers only. It is reading material, but the exercises need Python, Docker and some command-line use. New to this? Start here.
Can I run it?
- Cost
- FreeNothing to pay or sign up for.
- Runs on
- Web browser
- Computer
- An ordinary computer is fine
- API key
- Not needed
Try it
- Open the online version of the course from the project page.
- Start with chapter one, which explains what RAG is and how to set up your computer for the exercises.
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