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add reranking to azuresearch (#12454)

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-**Description** Adds returning the reranking score when using semantic
search
-**Issue:* #12317

---------

Co-authored-by: Adam Law <adamlaw@microsoft.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
This commit is contained in:
Adam Law 2023-10-27 14:14:09 -07:00 committed by GitHub
parent 389459af8f
commit df4960a6d8
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1 changed files with 22 additions and 3 deletions
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25
libs/langchain/langchain/vectorstores/azuresearch.py
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@ -474,14 +474,32 @@ class AzureSearch(VectorStore):
Returns:
List[Document]: A list of documents that are most similar to the query text.
"""
docs_and_scores = self.semantic_hybrid_search_with_score(
docs_and_scores = self.semantic_hybrid_search_with_score_and_rerank(
query, k=k, filters=kwargs.get("filters", None)
)
return [doc for doc, _ in docs_and_scores]
return [doc for doc, _, _ in docs_and_scores]
def semantic_hybrid_search_with_score(
self, query: str, k: int = 4, filters: Optional[str] = None
self, query: str, k: int = 4, **kwargs: Any
) -> List[Tuple[Document, float]]:
"""
Returns the most similar indexed documents to the query text.
Args:
query (str): The query text for which to find similar documents.
k (int): The number of documents to return. Default is 4.
Returns:
List[Document]: A list of documents that are most similar to the query text.
"""
docs_and_scores = self.semantic_hybrid_search_with_score_and_rerank(
query, k=k, filters=kwargs.get("filters", None)
)
return [(doc, score) for doc, score, _ in docs_and_scores]
def semantic_hybrid_search_with_score_and_rerank(
self, query: str, k: int = 4, filters: Optional[str] = None
) -> List[Tuple[Document, float, float]]:
"""Return docs most similar to query with an hybrid query.
Args:
@ -551,6 +569,7 @@ class AzureSearch(VectorStore):
},
),
float(result["@search.score"]),
float(result["@search.reranker_score"]),
)
for result in results
]