head to head · open source
PageIndex vs txtai
PageIndex has 35,678 GitHub stars, 3,148 forks, 103 open issues and last shipped yesterday. txtai has 12,956 stars, 891 forks, 9 open issues and last shipped 3 days ago. PageIndex leads on adoption by 175% (35,678 vs 12,956 stars). PageIndex is written in Python under MIT; txtai is written in Python under Apache-2.0. PageIndex has attracted 9% as many forks as stars, txtai 7%. PageIndex was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 7 topic tags (agents, ai, ai-agents, information-retrieval), 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
| PageIndex | txtai | |
|---|---|---|
| GitHub stars | ★ 36K | ★ 13K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-09-17 | 2026-09-15 |
| Forks | ⑂ 3.1K | ⑂ 891 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick PageIndex if
- You weight community size — 36K stars and counting
- You want the MIT license terms
- Your stack matches Python
- You value the larger contributor base for long-term maintenance
pick txtai if
- You want the txtai feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Python
- You evaluated both and txtai fits your workflow better
About PageIndex
PageIndex is a vectorless, reasoning based retrieval augmented generation engine written in Python and released under the MIT license. It lives in the AI and machine learning infrastructure ecosystem, with topics spanning RAG, information retrieval, LLM reasoning, context engineering, and agentic AI. Instead of building a vector index, PageIndex generates a hierarchical tree index for each document and then lets a large language model reason its way through that tree, in the same way a human expert turns to the right section of a long report. The project ships as a Python SDK, a hosted cloud service, and a docume…
read the full PageIndex overview →
About txtai
txtai is an all in one AI framework for semantic search, LLM orchestration and language model workflows, written in Python and released under the Apache 2.0 license. It lives in the Python machine learning ecosystem and is built on Hugging Face Transformers, Sentence Transformers and FastAPI. The core component is an embeddings database, which is a union of vector indexes (both sparse and dense), graph networks and relational databases. That foundation enables vector search and also serves as a knowledge source for large language model applications.
read the full txtai overview →
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Frequently asked questions
Is PageIndex or txtai more popular?
PageIndex has 35,678 GitHub stars and txtai has 12,956. PageIndex has the larger community by that measure.
Are PageIndex and txtai free?
Both are open source. PageIndex is licensed under MIT and txtai under Apache-2.0. Neither carries a licence fee.
What is the difference between PageIndex and txtai?
PageIndex is written in Python and txtai 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, PageIndex or txtai?
Choose PageIndex if you want the larger community (35,678 stars) or its MIT licence terms. Choose txtai if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.