PR community:Removing knn beta content in mongodb atlas vectorstore (#15865)

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manishsahni2000 2024-01-12 16:40:54 +11:00 committed by GitHub
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@ -221,12 +221,11 @@ class MongoDBAtlasVectorSearch(VectorStore):
) -> List[Tuple[Document, float]]: ) -> List[Tuple[Document, float]]:
"""Return MongoDB documents most similar to the given query and their scores. """Return MongoDB documents most similar to the given query and their scores.
Uses the knnBeta Operator available in MongoDB Atlas Search. Uses the $vectorSearch stage
This feature is in early access and available only for evaluation purposes, to performs aNN search on a vector in the specified field.
validate functionality, and to gather feedback from a small closed group of Index the field as "vector" using Atlas Vector Search "vectorSearch" index type
early access users. It is not recommended for production deployments as we
may introduce breaking changes. For more info : https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-stage/
For more: https://www.mongodb.com/docs/atlas/atlas-search/knn-beta
Args: Args:
query: Text to look up documents similar to. query: Text to look up documents similar to.
@ -234,7 +233,7 @@ class MongoDBAtlasVectorSearch(VectorStore):
pre_filter: (Optional) dictionary of argument(s) to prefilter document pre_filter: (Optional) dictionary of argument(s) to prefilter document
fields on. fields on.
post_filter_pipeline: (Optional) Pipeline of MongoDB aggregation stages post_filter_pipeline: (Optional) Pipeline of MongoDB aggregation stages
following the knnBeta vector search. following the vector Search.
Returns: Returns:
List of documents most similar to the query and their scores. List of documents most similar to the query and their scores.
@ -258,12 +257,11 @@ class MongoDBAtlasVectorSearch(VectorStore):
) -> List[Document]: ) -> List[Document]:
"""Return MongoDB documents most similar to the given query. """Return MongoDB documents most similar to the given query.
Uses the knnBeta Operator available in MongoDB Atlas Search. Uses the $vectorSearch stage
This feature is in early access and available only for evaluation purposes, to performs aNN search on a vector in the specified field.
validate functionality, and to gather feedback from a small closed group of Index the field as "vector" using Atlas Vector Search "vectorSearch" index type
early access users. It is not recommended for production deployments as we
may introduce breaking changes. For more info : https://www.mongodb.com/docs/atlas/atlas-vector-search/vector-search-stage/
For more: https://www.mongodb.com/docs/atlas/atlas-search/knn-beta
Args: Args:
query: Text to look up documents similar to. query: Text to look up documents similar to.
@ -271,7 +269,7 @@ class MongoDBAtlasVectorSearch(VectorStore):
pre_filter: (Optional) dictionary of argument(s) to prefilter document pre_filter: (Optional) dictionary of argument(s) to prefilter document
fields on. fields on.
post_filter_pipeline: (Optional) Pipeline of MongoDB aggregation stages post_filter_pipeline: (Optional) Pipeline of MongoDB aggregation stages
following the knnBeta vector search. following the vector search.
Returns: Returns:
List of documents most similar to the query and their scores. List of documents most similar to the query and their scores.
@ -311,7 +309,7 @@ class MongoDBAtlasVectorSearch(VectorStore):
pre_filter: (Optional) dictionary of argument(s) to prefilter on document pre_filter: (Optional) dictionary of argument(s) to prefilter on document
fields. fields.
post_filter_pipeline: (Optional) pipeline of MongoDB aggregation stages post_filter_pipeline: (Optional) pipeline of MongoDB aggregation stages
following the knnBeta vector search. following the vector search.
Returns: Returns:
List of documents selected by maximal marginal relevance. List of documents selected by maximal marginal relevance.
""" """