[Documentation] Indicate dense vs sparse search in HybridSearchConfig

[alberto-agudo]

The current configuration of HybridSearch mentions primary_search and secondary_search:

langchain-postgres/langchain_postgres/v2/hybrid_search_config.py

Lines 19 to 22 in 18b1bcd

	primary_search_results: A list of (document, distance) tuples from
	the primary search.
	secondary_search_results: A list of (document, distance) tuples from
	the secondary search.

Even if you'd think primary search is dense (embeddings-based) and secondary is sparse (keyword-based), there's no guarantee in the class definition that it works this way. There's no need to mention this in the actual function arguments, but I think it is necessary in the docstring.

I didn't realize the actual meaning of primary and secondary until I found the following lines when digging in the code:

langchain-postgres/langchain_postgres/v2/async_vectorstore.py

Lines 669 to 673 in 18b1bcd

	combined_results = hybrid_search_config.fusion_function(
	dense_results,
	sparse_results,
	**hybrid_search_config.fusion_function_parameters,
	)

Due to the current lack of documentation, it would greatly help others with the current lack of documentation to just change these lines in the HybridSearchConfig definition.

[dishaprakash]

@alberto-agudo Thank you for opening the issue! We have recently updated the documentation for Hybrid Search. For more information see the how-to guide.

[alberto-agudo]

@dishaprakash Thanks for the new docs! They seem quite helpful. In any case, I think it would be worth adding a small comment to the how-to guide mentioning that primary=dense (embedding-based) and secondary=sparse (full-text based).

[dishaprakash]

@alberto-agudo This has been resolved in #251.

Thank you for the contribution! Closing this issue now.