Kismet this is published today. We've just announced Zep's[0] new Document Vector Store[1] built on pgvector, and the embedding model we ship with is all-MiniLM-L6-v2. Very fast, low-memory, and surprisingly performant.

Our focus with Zep is on LLM app use cases, and in particular, searching over chat histories and documents for RAG apps. You can, however, use Zep to turn any Postgres instance into a vector store with great developer experience. pgvector index configuration and query tuning can be challenging. We've tried to do much of this work for developers.

Also, I'm super excited about the prospect of HNSW support in pgvector, slated for pgvector 0.5.[2]

[0] https://github.com/getzep/zep

[1] https://blog.getzep.com/introducing-the-zep-document-vector-...

[2] https://github.com/pgvector/pgvector/issues/181#issuecomment...