head to head · open source
generative-ai-for-beginners vs graphrag
generative-ai-for-beginners has 119,980 GitHub stars, 63,157 forks, 23 open issues and last shipped 2 days ago. graphrag has 36,022 stars, 3,795 forks, 47 open issues and last shipped 3 days ago. generative-ai-for-beginners leads on adoption by 233% (119,980 vs 36,022 stars). generative-ai-for-beginners is written in Jupyter Notebook under MIT; graphrag is written in Python under MIT. generative-ai-for-beginners has attracted 53% as many forks as stars, graphrag 11%. generative-ai-for-beginners was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (gpt, llms), 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 | graphrag | |
|---|---|---|
| GitHub stars | ★ 120K | ★ 36K |
| License | MIT | MIT |
| Written in | Jupyter Notebook | Python |
| Last push | 2026-09-17 | 2026-09-16 |
| Forks | ⑂ 63K | ⑂ 3.8K |
| 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 graphrag if
- You want the graphrag feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and graphrag 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 graphrag
GraphRAG is a modular, Python based, MIT licensed data pipeline and transformation suite from Microsoft Research that uses large language models to extract structured data from unstructured text, then exploits the resulting knowledge graph to form targeted context for question answering over private data.
read the full graphrag overview →
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Frequently asked questions
Is generative-ai-for-beginners or graphrag more popular?
generative-ai-for-beginners has 119,980 GitHub stars and graphrag has 36,022. generative-ai-for-beginners has the larger community by that measure.
Are generative-ai-for-beginners and graphrag free?
Both are open source. generative-ai-for-beginners is licensed under MIT and graphrag under MIT. Neither carries a licence fee.
What is the difference between generative-ai-for-beginners and graphrag?
generative-ai-for-beginners is written in Jupyter Notebook and graphrag in Python. 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 graphrag?
Choose generative-ai-for-beginners if you want the larger community (119,980 stars) or its MIT licence terms. Choose graphrag if its feature set, stack or MIT licence fits better. Both are self-hostable.