head to head · open source
serviette vs txtai
serviette has 58,774 GitHub stars, 1,515 forks, 8 open issues and last shipped 9 days ago. txtai has 13,029 stars, 947 forks, 9 open issues and last shipped 3 days ago. serviette leads on adoption by 351% (58,774 vs 13,029 stars). serviette is written in Python under MIT; txtai is written in Python under Apache-2.0. serviette has attracted 3% as many forks as stars, txtai 7%. txtai was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (llm), 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 20902 open source comparisons
Side by side
| serviette | txtai | |
|---|---|---|
| GitHub stars | ★ 59K | ★ 13K |
| License | MIT | Apache-2.0 |
| Written in | Python | Python |
| Last push | 2026-10-16 | 2026-10-22 |
| Forks | ⑂ 1.5K | ⑂ 947 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick serviette if
- You weight community size — 59K 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 serviette
serviette Looking for llm app templates? All templates, cookbooks and examples are still available in full in the Pathway repository under examples/llm app . A no code, always up to date RAG server for any vector database — built on the Pathway Live Data Framework. Point serviette at a folder of documents, pick a vector database and an embedder in one YAML file, and run two commands: you get a chat and a REST API that answer from those documents and cite their sources. From then on, any change to the documents — an edit, a new file, a deletion — is reflected in the answers within seconds. serviette runs on…
read the full serviette overview →
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 →
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 serviette or txtai more popular?
serviette has 58,774 GitHub stars and txtai has 13,029. serviette has the larger community by that measure.
Are serviette and txtai free?
Both are open source. serviette is licensed under MIT and txtai under Apache-2.0. Neither carries a licence fee.
What is the difference between serviette and txtai?
serviette 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, serviette or txtai?
Choose serviette if you want the larger community (58,774 stars) or its MIT licence terms. Choose txtai if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.