head to head · open source
generative-ai-for-beginners vs langgraph
generative-ai-for-beginners has 122,853 GitHub stars, 65,741 forks, 23 open issues and last shipped yesterday. langgraph has 44,336 stars, 7,622 forks, 786 open issues and last shipped yesterday. generative-ai-for-beginners leads on adoption by 177% (122,853 vs 44,336 stars). generative-ai-for-beginners is written in Jupyter Notebook under MIT; langgraph is written in Python under MIT. generative-ai-for-beginners has attracted 54% as many forks as stars, langgraph 17%. langgraph was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 3 topic tags (ai, chatgpt, generative-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 | langgraph | |
|---|---|---|
| GitHub stars | ★ 123K | ★ 44K |
| License | MIT | MIT |
| Written in | Jupyter Notebook | Python |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 66K | ⑂ 7.6K |
| 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 langgraph if
- You want the langgraph feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and langgraph 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 langgraph
Low level orchestration framework for building stateful agents. Trusted by companies shaping the future of agents – including Klarna, Replit, Elastic, and more – LangGraph is a low level orchestration framework for building, managing, and deploying long running, stateful agents. [!TIP] If you're looking to quickly build agents, check out Deep Agents — a higher level package built on LangGraph for agents that can plan, use subagents, and leverage file systems for complex tasks. For an equivalent JS/TS library, check out LangGraph.js and the JS docs. Why use LangGraph? LangGraph provides low level supporting…
read the full langgraph overview →
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Frequently asked questions
Is generative-ai-for-beginners or langgraph more popular?
generative-ai-for-beginners has 122,853 GitHub stars and langgraph has 44,336. generative-ai-for-beginners has the larger community by that measure.
Are generative-ai-for-beginners and langgraph free?
Both are open source. generative-ai-for-beginners is licensed under MIT and langgraph under MIT. Neither carries a licence fee.
What is the difference between generative-ai-for-beginners and langgraph?
generative-ai-for-beginners is written in Jupyter Notebook and langgraph 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 langgraph?
Choose generative-ai-for-beginners if you want the larger community (122,853 stars) or its MIT licence terms. Choose langgraph if its feature set, stack or MIT licence fits better. Both are self-hostable.