rag-zero-to-hero-guide vs rag-from-scratch
Two notebook-based guides to retrieval-augmented generation
Both projects teach retrieval-augmented generation through educational materials rather than offering a ready-to-deploy RAG application. rag-from-scratch centers on a step-by-step introduction to indexing, retrieval, and generation, while rag-zero-to-hero-guide covers a broader set of topics, examples, evaluation resources, and research links.
rag-zero-to-hero-guide: Learn Retrieval-Augmented Generation
A learning guide to retrieval-augmented generation, from core concepts to evaluation and advanced approaches. It combines explanations, Jupyter notebook implementations, tool references, and survey papers for learners building RAG knowledge.
rag-from-scratch: Learn Retrieval-Augmented Generation Step by Step
A Jupyter notebook series that teaches the building blocks of retrieval-augmented generation, from indexing and retrieval to generation. It is aimed at learners who want to understand RAG concepts through an educational progression rather than adopt a ready-made application.
| rag-zero-to-hero-guide | rag-from-scratch | |
|---|---|---|
| Language | Jupyter Notebook | Jupyter Notebook |
| License | Apache-2.0 | — |
| Stars | 1.4k | 9.4k |
| Forks | 350 | 2.2k |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- rag-from-scratch focuses on core RAG stages, while rag-zero-to-hero-guide also covers evaluation, agentic and graph RAG, and related research.
- rag-from-scratch connects its notebooks to a video playlist; rag-zero-to-hero-guide offers a learning roadmap, toolkit directory, and survey-paper index.
- rag-zero-to-hero-guide includes examples using LangChain and CrewAI, as well as website and YouTube transcript content; rag-from-scratch emphasizes the building blocks of RAG.
- rag-zero-to-hero-guide lists an Apache-2.0 license; rag-from-scratch does not list a license in the provided project details.
- rag-from-scratch has 9.4k stars and 2.2k forks, compared with 1.4k stars and 350 forks for rag-zero-to-hero-guide.
Choose rag-zero-to-hero-guide if you…
- want a broader learning path from RAG fundamentals to evaluation and advanced approaches.
- need notebook examples involving websites, YouTube transcripts, or frameworks such as LangChain and CrewAI.
- want categorized tool references and links to RAG survey papers.
Choose rag-from-scratch if you…
- want a focused introduction to indexing, retrieval, and generation.
- prefer to pair notebook lessons with an accompanying video playlist.
- need a step-by-step resource for understanding RAG fundamentals before choosing an implementation.
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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.