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community: OpenSearchVectorStore: use engine set at init() time by default (#28147)

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Description:
* Updated the OpenSearchVectorStore to use the `engine` parameter
captured at `init()` time as the default when adding documents to the
store.

Formatted, Linted, and Tested.
This commit is contained in:
Eric Pinzur 2024-11-16 23:07:42 +01:00 committed by GitHub
parent e6fe8cc2fb
commit 0a57fc0016
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1 changed files with 4 additions and 4 deletions
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8
libs/community/langchain_community/vectorstores/opensearch_vector_search.py
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@ -401,7 +401,7 @@ class OpenSearchVectorSearch(VectorStore):
self.is_aoss = _is_aoss_enabled(http_auth=http_auth) self.is_aoss = _is_aoss_enabled(http_auth=http_auth)
self.client = _get_opensearch_client(opensearch_url, **kwargs) self.client = _get_opensearch_client(opensearch_url, **kwargs)
self.async_client = _get_async_opensearch_client(opensearch_url, **kwargs) self.async_client = _get_async_opensearch_client(opensearch_url, **kwargs)
self.engine = kwargs.get("engine") self.engine = kwargs.get("engine", "nmslib")
@property @property
def embeddings(self) -> Embeddings: def embeddings(self) -> Embeddings:
@ -420,7 +420,7 @@ class OpenSearchVectorSearch(VectorStore):
index_name = kwargs.get("index_name", self.index_name) index_name = kwargs.get("index_name", self.index_name)
text_field = kwargs.get("text_field", "text") text_field = kwargs.get("text_field", "text")
dim = len(embeddings[0]) dim = len(embeddings[0])
engine = kwargs.get("engine", "nmslib") engine = kwargs.get("engine", self.engine)
space_type = kwargs.get("space_type", "l2") space_type = kwargs.get("space_type", "l2")
ef_search = kwargs.get("ef_search", 512) ef_search = kwargs.get("ef_search", 512)
ef_construction = kwargs.get("ef_construction", 512) ef_construction = kwargs.get("ef_construction", 512)
@ -461,7 +461,7 @@ class OpenSearchVectorSearch(VectorStore):
index_name = kwargs.get("index_name", self.index_name) index_name = kwargs.get("index_name", self.index_name)
text_field = kwargs.get("text_field", "text") text_field = kwargs.get("text_field", "text")
dim = len(embeddings[0]) dim = len(embeddings[0])
engine = kwargs.get("engine", "nmslib") engine = kwargs.get("engine", self.engine)
space_type = kwargs.get("space_type", "l2") space_type = kwargs.get("space_type", "l2")
ef_search = kwargs.get("ef_search", 512) ef_search = kwargs.get("ef_search", 512)
ef_construction = kwargs.get("ef_construction", 512) ef_construction = kwargs.get("ef_construction", 512)
@ -530,7 +530,7 @@ class OpenSearchVectorSearch(VectorStore):
) )
if is_appx_search: if is_appx_search:
engine = kwargs.get("engine", "nmslib") engine = kwargs.get("engine", self.engine)
space_type = kwargs.get("space_type", "l2") space_type = kwargs.get("space_type", "l2")
ef_search = kwargs.get("ef_search", 512) ef_search = kwargs.get("ef_search", 512)
ef_construction = kwargs.get("ef_construction", 512) ef_construction = kwargs.get("ef_construction", 512)