head to head · open source
generative-ai-for-beginners vs ragflow
generative-ai-for-beginners has 119,956 GitHub stars, 63,149 forks, 23 open issues and last shipped yesterday. ragflow has 90,889 stars, 10,759 forks, 1,525 open issues and last shipped yesterday. generative-ai-for-beginners leads on adoption by 32% (119,956 vs 90,889 stars). generative-ai-for-beginners is written in Jupyter Notebook under MIT; ragflow is written in Go under Apache-2.0. generative-ai-for-beginners has attracted 53% as many forks as stars, ragflow 12%. ragflow was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (ai), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| generative-ai-for-beginners | ragflow | |
|---|---|---|
| GitHub stars | ★ 120K | ★ 91K |
| License | MIT | Apache-2.0 |
| Written in | Jupyter Notebook | Go |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 63K | ⑂ 11K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick generative-ai-for-beginners if
- You weight community size — 120K stars and counting
- You want the MIT license terms
- Your stack matches Jupyter Notebook
- You value the larger contributor base for long-term maintenance
pick ragflow if
- You want the ragflow feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Go
- You evaluated both and ragflow fits your workflow better
About generative-ai-for-beginners
Generative AI for Beginners is Microsoft's free, MIT licensed curriculum of 21 Jupyter Notebook lessons that teaches developers how to start building generative AI applications, aimed at newcomers who want a structured, self paced path instead of scattered documentation.
read the full generative-ai-for-beginners overview →
About ragflow
RAGFlow is an open source Retrieval Augmented Generation engine that fuses RAG with agent capabilities into a context layer for large language models, built for developers and teams that need to turn complex, unstructured documents into production AI systems.
read the full ragflow overview →
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Frequently asked questions
Is generative-ai-for-beginners or ragflow more popular?
generative-ai-for-beginners has 119,956 GitHub stars and ragflow has 90,889. generative-ai-for-beginners has the larger community by that measure.
Are generative-ai-for-beginners and ragflow free?
Both are open source. generative-ai-for-beginners is licensed under MIT and ragflow under Apache-2.0. Neither carries a licence fee.
What is the difference between generative-ai-for-beginners and ragflow?
generative-ai-for-beginners is written in Jupyter Notebook and ragflow in Go. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, generative-ai-for-beginners or ragflow?
Choose generative-ai-for-beginners if you want the larger community (119,956 stars) or its MIT licence terms. Choose ragflow if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.