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Pgvector for postgres and vector search in Elasticsearch would be two ways to do it without adopting some new untested product.

Milvus (https://milvus.io) and Vespa (https://vespa.ai) are great choices if you're looking for hardened, scalable, and production-ready vector databases.

We (Milvus) also have `milvus-lite` if you'd like something pip installable: python3 -m pip install milvus

Not sure which one, but if you are after a vector search engine (not just a database) then I can recommend this https://github.com/marqo-ai/marqo. Includes inference, transformations, schema's, multi-modal search, multi-modal queries, multi-modal representations, text chunking and more.

This article also has some other methods for hallucination and reference checking by using cross-encoders https://github.com/marqo-ai/marqo/blob/mainline/examples/GPT.... It is not perfect but can be easily modified to make it more robust.

Potentially Chroma https://www.trychroma.com/ ?

CozoDB? https://news.ycombinator.com/item?id=35641164

Popular examples are Weaviate and Qdrant