head to head · open source
txtai vs autoflow
txtai has 13,064 GitHub stars, 962 forks, 9 open issues and last shipped yesterday. autoflow has 2,979 stars, 193 forks, 74 open issues and last shipped 2 days ago. txtai leads on adoption by 339% (13,064 vs 2,979 stars). txtai is written in Python under Apache-2.0; autoflow is written in TypeScript under Apache-2.0. txtai has attracted 7% as many forks as stars, autoflow 6%. txtai was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (rag), 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
| txtai | autoflow | |
|---|---|---|
| GitHub stars | ★ 13K | ★ 3.0K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Python | TypeScript |
| Last push | 2026-11-04 | 2026-11-03 |
| Forks | ⑂ 962 | ⑂ 193 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick txtai if
- You weight community size — 13K 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 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 txtai
All in one AI framework txtai is an all in one AI framework for semantic search, LLM orchestration and language model workflows. The key component of txtai is an embeddings database, which is a union of vector indexes (sparse and dense), graph networks and relational databases. This foundation enables vector search and/or serves as a powerful knowledge source for large language model (LLM) applications. Build autonomous agents, retrieval augmented generation (RAG) processes, multi model workflows and more. Summary of txtai features: 🔎 Vector search with SQL, object storage, topic modeling, graph analysis and…
read the full txtai 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…
read the full autoflow overview →
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Frequently asked questions
Is txtai or autoflow more popular?
txtai has 13,064 GitHub stars and autoflow has 2,979. txtai has the larger community by that measure.
Are txtai and autoflow free?
Both are open source. txtai is licensed under Apache-2.0 and autoflow under Apache-2.0. Neither carries a licence fee.
What is the difference between txtai and autoflow?
txtai 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, txtai or autoflow?
Choose txtai if you want the larger community (13,064 stars) or its Apache-2.0 licence terms. Choose autoflow if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.