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For Python I believe Chroma [1] can be used embedded.
For Go I recently started building chromem-go, inspired by the Chroma interface: https://github.com/philippgille/chromem-go
It's neither advanced nor for scale yet, but the RAG demo works.
[1] https://github.com/chroma-core/chroma
For Python I believe Chroma [1] can be used embedded.
For Go I recently started building chromem-go, inspired by the Chroma interface: https://github.com/philippgille/chromem-go
It's neither advanced nor for scale yet, but the RAG demo works.
[1] https://github.com/chroma-core/chroma
You don't need a dedicated vector db, you can use pgvector.
You could maybe use Cube for euclidean space search, but you're better off using optimized algorithms for embedding space search.
https://github.com/pgvector/pgvector
I've used usearch successfully for a small project: https://github.com/unum-cloud/usearch/
The qdrant clients support a local mode where you point to a file[0].
[0] -- https://github.com/qdrant/qdrant-client#local-mode
There are options such as Google's ScaNN that may let you go farther before needing to consider specialized databases.
https://github.com/google-research/google-research/blob/mast...