head to head · open source
llama_index vs autoflow
llama_index has 52,206 GitHub stars, 8,165 forks, 770 open issues and last shipped today. autoflow has 2,973 stars, 193 forks, 74 open issues and last shipped 5 months ago. llama_index leads on adoption by 1,656% (52,206 vs 2,973 stars). llama_index is written in Python under MIT; autoflow is written in TypeScript under Apache-2.0. llama_index has attracted 16% as many forks as stars, autoflow 6%. llama_index was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (rag, vector-database), 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.
← all 8884 open source comparisons
Side by side
| llama_index | autoflow | |
|---|---|---|
| GitHub stars | ★ 52K | ★ 3.0K |
| License | MIT | Apache-2.0 |
| Written in | Python | TypeScript |
| Last push | 2026-09-18 | 2026-04-27 |
| Forks | ⑂ 8.2K | ⑂ 193 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick llama_index if
- You weight community size — 52K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick autoflow if
- You want the autoflow feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches TypeScript
- You evaluated both and autoflow fits your workflow better
About llama_index
LlamaIndex is an MIT licensed, open source Python framework for building agentic applications — retrieval augmented generation systems, agents and multi agent workflows — on top of private documents and data, and it is aimed at AI engineers and teams who need to connect large language models to their own sources of context.
read the full llama_index overview →
About autoflow
AutoFlow [!WARNING] Autoflow is still in the early stages of development. And we are actively working on it, the next move is to make it to a python package and make it a RAG solution e.g. pip install autoflow ai . If you have any questions or suggestions, please feel free to contact us on Discussion. Introduction AutoFlow is an open source graph rag (graphrag: knowledge graph rag) based knowledge base tool built on top of TiDB Vector and LlamaIndex and DSPy. Live Demo : Deployment Docs : Deployment Docs Features 1. Perplexity style Conversational Search page : Our platform features an advanced built in website c…
read the full autoflow overview →
More in AI & Machine Learning
Related comparisons
More Machine Learning Infrastructure projects
Compare either of these against the rest of the Machine Learning Infrastructure field.
Frequently asked questions
Is llama_index or autoflow more popular?
llama_index has 52,206 GitHub stars and autoflow has 2,973. llama_index has the larger community by that measure.
Are llama_index and autoflow free?
Both are open source. llama_index is licensed under MIT and autoflow under Apache-2.0. Neither carries a licence fee.
What is the difference between llama_index and autoflow?
llama_index is written in Python and autoflow in TypeScript. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, llama_index or autoflow?
Choose llama_index if you want the larger community (52,206 stars) or its MIT licence terms. Choose autoflow if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.