head to head · open source
graphify vs GenerativeAIExamples
graphify has 119,123 GitHub stars, 11,519 forks, 1,350 open issues and last shipped 2 days ago. GenerativeAIExamples has 4,183 stars, 1,098 forks, 84 open issues and last shipped 9 days ago. graphify leads on adoption by 2,748% (119,123 vs 4,183 stars). graphify is written in Python under Apache-2.0; GenerativeAIExamples is written in Jupyter Notebook under Apache-2.0. graphify has attracted 10% as many forks as stars, GenerativeAIExamples 26%. graphify was the more recently maintained of the two, and both are self-hostable with no licence fee.
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
| graphify | GenerativeAIExamples | |
|---|---|---|
| GitHub stars | ★ 119K | ★ 4.2K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | Jupyter Notebook |
| Last push | 2026-09-16 | 2026-09-09 |
| Forks | ⑂ 12K | ⑂ 1.1K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick graphify if
- You weight community size — 119K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick GenerativeAIExamples if
- You want the GenerativeAIExamples feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Jupyter Notebook
- You evaluated both and GenerativeAIExamples fits your workflow better
About graphify
graphify is an Apache 2.0 Python CLI and /graphify skill that turns a whole project — code, docs, SQL schemas, configs, PDFs, images, and video — into a queryable knowledge graph, built for developers and AI agent users in Claude Code, Cursor, Codex, and Gemini CLI who want to query a codebase instead of grepping through files.
read the full graphify overview →
About GenerativeAIExamples
NVIDIA Generative AI Examples This repository is a starting point for developers looking to integrate with the NVIDIA software ecosystem to speed up their generative AI systems. Whether you are building RAG pipelines, agentic workflows, or fine tuning models, this repository will help you integrate NVIDIA, seamlessly and natively, with your development stack. Table of Contents What's New? Data Flywheel Safer Agentic AI Knowledge Graph RAG Agentic Workflows with Llama 3.1 RAG with Local NIM Deployment and LangChain Vision NIM Workflows Try it Now! Data Flywheel Tool Calling Notebooks RAG RAG Notebooks RAG Examples…
read the full GenerativeAIExamples overview →
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Frequently asked questions
Is graphify or GenerativeAIExamples more popular?
graphify has 119,123 GitHub stars and GenerativeAIExamples has 4,183. graphify has the larger community by that measure.
Are graphify and GenerativeAIExamples free?
Both are open source. graphify is licensed under Apache-2.0 and GenerativeAIExamples under Apache-2.0. Neither carries a licence fee.
What is the difference between graphify and GenerativeAIExamples?
graphify is written in Python and GenerativeAIExamples in Jupyter Notebook. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, graphify or GenerativeAIExamples?
Choose graphify if you want the larger community (119,123 stars) or its Apache-2.0 licence terms. Choose GenerativeAIExamples if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.