head to head · open source
generative-ai-for-beginners vs ragflow
generative-ai-for-beginners has 122,853 GitHub stars, 65,741 forks, 23 open issues and last shipped yesterday. ragflow has 93,365 stars, 11,207 forks, 1,525 open issues and last shipped yesterday. generative-ai-for-beginners leads on adoption by 32% (122,853 vs 93,365 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 54% as many forks as stars, ragflow 12%. generative-ai-for-beginners 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 | ★ 123K | ★ 93K |
| License | MIT | Apache-2.0 |
| Written in | Jupyter Notebook | Go |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 66K | ⑂ 11K |
| 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 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
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 ragflow
Cloud Documentation Roadmap Discord 📕 Table of Contents 💡 What is RAGFlow? 🎮 Get Started 🔥 Latest Updates 🌟 Key Features 🔎 System Architecture 🎬 Self Hosting 🔧 Configurations 🔧 Build a Docker Image 🔨 Launch Service from Source for Development 📚 Documentation 📜 Roadmap 🏄 Community 🙌 Contributing 💡 What is RAGFlow? RAGFlow is a leading open source Retrieval Augmented Generation (RAG) engine that fuses cutting edge RAG with Agent capabilities to create a superior context layer for LLMs. It offers a streamlined RAG workflow adaptable to enterprises of any scale. Powered by a converged context engine…
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 122,853 GitHub stars and ragflow has 93,365. 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 (122,853 stars) or its MIT licence terms. Choose ragflow if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.