head to head · open source
PageIndex vs rag_api
PageIndex has 35,765 GitHub stars, 3,152 forks, 103 open issues and last shipped yesterday. rag_api has 901 stars, 404 forks, 45 open issues and last shipped 1 months ago. PageIndex leads on adoption by 3,869% (35,765 vs 901 stars). PageIndex is written in Python under MIT; rag_api is written in Python under MIT. PageIndex has attracted 9% as many forks as stars, rag_api 45%. PageIndex 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.
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Side by side
| PageIndex | rag_api | |
|---|---|---|
| GitHub stars | ★ 36K | ★ 901 |
| License | MIT | MIT |
| Written in | Python | Python |
| Last push | 2026-09-19 | 2026-08-15 |
| Forks | ⑂ 3.2K | ⑂ 404 |
| 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 rag_api if
- You want the rag_api feature set and don't need the biggest community
- You prefer the MIT license terms
- Your stack matches Python
- You evaluated both and rag_api 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 rag_api
rag api is an MIT licensed Python FastAPI service that indexes documents into embeddings by file id and serves ID based retrieval augmented generation over Langchain and PostgreSQL/pgvector, built primarily for LibreChat deployments but usable by any application that stores embeddings at the file level.
read the full rag_api overview →
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Frequently asked questions
Is PageIndex or rag_api more popular?
PageIndex has 35,765 GitHub stars and rag_api has 901. PageIndex has the larger community by that measure.
Are PageIndex and rag_api free?
Both are open source. PageIndex is licensed under MIT and rag_api under MIT. Neither carries a licence fee.
What is the difference between PageIndex and rag_api?
PageIndex is written in Python and rag_api 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 rag_api?
Choose PageIndex if you want the larger community (35,765 stars) or its MIT licence terms. Choose rag_api if its feature set, stack or MIT licence fits better. Both are self-hostable.