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txtai is an alternative approach to this. It builds a FAISS (also supports HNSW) index alongside a SQLite database. It works with sentence-transformers models. For example, this model https://huggingface.co/sentence-transformers/all-MiniLM-L6-v... is 384 dimensions and works great for semantic search.
https://github.com/neuml/txtai
https://neuml.github.io/txtai/embeddings/query/
There is a way of running disk-backed FAISS indexed that don't all fit in memory but I've not quite figured out how to do that yet: https://github.com/facebookresearch/faiss/issues/2675
you might check out some vector databases:
https://milvus.io/
AND
pinecone.io
there are others too