feat: FAISS in OpenSearch: Support HNSW for cosine

[tstadel]

Related Issues

• closes FAISS in OpenSearch: Support HNSW for cosine #2913

Proposed Changes:

• normalize vectors manually at index time
• normalize vectors manually at query time
• use dot_product space under the hood
• make normalization more efficient by using two-dimensional numpy array instead of normalizing each vector separately
• run cosine tests for all document stores
• run all document_store integration tests (not only OpenSearch)
• fix test_faiss_and_milvus.py tests not running

pushed to another PR:

• streamline validation of embedding shape across all document stores (BaseDocumentStore_validate_embeddings_shape)
• introduce DenseRetriever abstraction to facilitate usage of retrievers in document store's update_embeddings

How did you test it?

• made test test_cosine_similarity of test_faiss_and_milvus.py generic to run on all document stores

Notes for the reviewer

Checklist

• I have read the contributors guidelines and the code of conduct
• I have updated the related issue with new insights and changes
• I added tests that demonstrate the correct behavior of the change
• I've used the conventional commit convention for my PR title
• I documented my code
• I ran pre-commit hooks and fixed any issue

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[bogdankostic]

There seem to be some conflicts, otherwise LGTM! Also, I added a comment wrt #3102

[bogdankostic]

This is probably out of scope for this PR, just a reminder that at some point we should probably allow to set custom values for ef_search (see also #3102)