txtai is an all-in-one embeddings database for semantic search, LLM orchestration and language model workflows.

Embeddings databases are a union of vector indexes (sparse and dense), graph networks and relational databases. This enables vector search with SQL, topic modeling and retrieval augmented generation.

txtai adopts a local-first approach. A production-ready instance can be run locally within a single Python instance. It can also scale out when needed.

txtai can use Faiss, Hnswlib or Annoy as it's vector index backend. This is relevant in terms of the ANN-Benchmarks scores.

Disclaimer: I am the author of txtai