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community[patch]: ElasticsearchStore enable max inner product (#16393)

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Enable max inner product for approximate retrieval strategy. For exact
strategy we lack the necessary `maxInnerProduct` function in the
Painless scripting language, this is why we do not add it there.

Similarity docs:
https://www.elastic.co/guide/en/elasticsearch/reference/current/dense-vector.html#dense-vector-params

---------

Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Joe McElroy <joseph.mcelroy@elastic.co>
This commit is contained in:
Max Jakob 2024-01-22 20:26:18 +01:00 committed by GitHub
parent fc196cab12
commit 8569b8f680
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1 changed files with 6 additions and 2 deletions
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8
libs/community/langchain_community/vectorstores/elasticsearch.py
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@ -214,6 +214,8 @@ class ApproxRetrievalStrategy(BaseRetrievalStrategy):
similarityAlgo = "l2_norm" similarityAlgo = "l2_norm"
elif similarity is DistanceStrategy.DOT_PRODUCT: elif similarity is DistanceStrategy.DOT_PRODUCT:
similarityAlgo = "dot_product" similarityAlgo = "dot_product"
elif similarity is DistanceStrategy.MAX_INNER_PRODUCT:
similarityAlgo = "max_inner_product"
else: else:
raise ValueError(f"Similarity {similarity} not supported.") raise ValueError(f"Similarity {similarity} not supported.")
@ -412,7 +414,7 @@ class ElasticsearchStore(VectorStore):
distance_strategy: Optional. Distance strategy to use when distance_strategy: Optional. Distance strategy to use when
searching the index. searching the index.
Defaults to COSINE. Can be one of COSINE, Defaults to COSINE. Can be one of COSINE,
EUCLIDEAN_DISTANCE, or DOT_PRODUCT. EUCLIDEAN_DISTANCE, MAX_INNER_PRODUCT or DOT_PRODUCT.
If you want to use a cloud hosted Elasticsearch instance, you can pass in the If you want to use a cloud hosted Elasticsearch instance, you can pass in the
cloud_id argument instead of the es_url argument. cloud_id argument instead of the es_url argument.
@ -508,6 +510,7 @@ class ElasticsearchStore(VectorStore):
DistanceStrategy.COSINE, DistanceStrategy.COSINE,
DistanceStrategy.DOT_PRODUCT, DistanceStrategy.DOT_PRODUCT,
DistanceStrategy.EUCLIDEAN_DISTANCE, DistanceStrategy.EUCLIDEAN_DISTANCE,
DistanceStrategy.MAX_INNER_PRODUCT,
] ]
] = None, ] = None,
strategy: BaseRetrievalStrategy = ApproxRetrievalStrategy(), strategy: BaseRetrievalStrategy = ApproxRetrievalStrategy(),
@ -1128,7 +1131,8 @@ class ElasticsearchStore(VectorStore):
distance_strategy: Optional. Name of the distance distance_strategy: Optional. Name of the distance
strategy to use. Defaults to "COSINE". strategy to use. Defaults to "COSINE".
can be one of "COSINE", can be one of "COSINE",
"EUCLIDEAN_DISTANCE", "DOT_PRODUCT". "EUCLIDEAN_DISTANCE", "DOT_PRODUCT",
"MAX_INNER_PRODUCT".
bulk_kwargs: Optional. Additional arguments to pass to bulk_kwargs: Optional. Additional arguments to pass to
Elasticsearch bulk. Elasticsearch bulk.
""" """