head to head · open source
generative-ai-for-beginners vs graphrag
generative-ai-for-beginners has 122,853 GitHub stars, 65,741 forks, 23 open issues and last shipped yesterday. graphrag has 36,531 stars, 3,867 forks, 47 open issues and last shipped yesterday. generative-ai-for-beginners leads on adoption by 236% (122,853 vs 36,531 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 54% 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 | ★ 123K | ★ 37K |
| License | MIT | MIT |
| Written in | Jupyter Notebook | Python |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 66K | ⑂ 3.9K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick generative-ai-for-beginners if
- You weight community size — 123K 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
21 Lessons teaching everything you need to know to start building Generative AI applications 🌐 Multi Language Support Supported via GitHub Action (Automated & Always Up to Date) Arabic Bengali Bulgarian Burmese (Myanmar) Chinese (Simplified) Chinese (Traditional, Hong Kong) Chinese (Traditional, Macau) Chinese (Traditional, Taiwan) Croatian Czech Danish Dutch Estonian Finnish French German Greek Hebrew Hindi Hungarian Indonesian Italian Japanese Kannada Khmer Korean Lithuanian Malay Malayalam Marathi Nepali Nigerian Pidgin Norwegian Persian (Farsi) Polish Portuguese (Brazil) Portuguese (Portugal) Punjabi…
read the full generative-ai-for-beginners overview →
About graphrag
GraphRAG [!WARNING] GraphRAG is a research project that explores the functional use of graphs to form a targeted context for question answering. Since our first release in July 2024 the capabilities of frontier models have changed dramatically, and our portfolio of research projects has diversified to match. This project is largely in maintenance mode, and won't be accepting new PRs or implementing new features. We'll perform bug fixes and dependency updates as appropriate, particularly to address CVEs as they arise. 👉 Microsoft Research Blog Post 👉 Read the docs 👉 GraphRAG Arxiv Overview The GraphRAG project…
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 122,853 GitHub stars and graphrag has 36,531. 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 (122,853 stars) or its MIT licence terms. Choose graphrag if its feature set, stack or MIT licence fits better. Both are self-hostable.