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INTPYTHON-605 Removed unused vector_index_name from docstring and a unit test #140

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Merged
merged 1 commit into from
May 23, 2025
Merged

INTPYTHON-605 Removed unused vector_index_name from docstring and a unit test #140

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1 change: 0 additions & 1 deletion libs/langchain-mongodb/langchain_mongodb/vectorstores.py
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Original file line number Diff line number Diff line change
Expand Up @@ -219,7 +219,6 @@ def __init__(
text_key: MongoDB field that will contain the text for each document
index_name: Existing Atlas Vector Search Index
embedding_key: Field that will contain the embedding for each document
vector_index_name: Name of the Atlas Vector Search index
relevance_score_fn: The similarity score used for the index
Currently supported: 'euclidean', 'cosine', and 'dotProduct'
dimensions: Number of dimensions in embedding. If the value is set and
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10 changes: 5 additions & 5 deletions libs/langchain-mongodb/tests/unit_tests/test_vectorstores.py
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Original file line number Diff line number Diff line change
Expand Up @@ -96,7 +96,7 @@ def test_from_documents(
documents,
embedding_openai,
collection=collection,
vector_index_name=INDEX_NAME,
index_name=INDEX_NAME,
)
self._validate_search(
vectorstore, collection, metadata=documents[2].metadata["c"]
Expand All @@ -117,7 +117,7 @@ def test_from_texts(
texts,
embedding_openai,
collection=collection,
vector_index_name=INDEX_NAME,
index_name=INDEX_NAME,
)
self._validate_search(vectorstore, collection, metadata=None)

Expand All @@ -136,7 +136,7 @@ def test_from_texts_with_metadatas(
embedding_openai,
metadatas=metadatas,
collection=collection,
vector_index_name=INDEX_NAME,
index_name=INDEX_NAME,
)
self._validate_search(vectorstore, collection, metadata=metadatas[2]["c"])

Expand All @@ -155,7 +155,7 @@ def test_from_texts_with_metadatas_and_pre_filter(
embedding_openai,
metadatas=metadatas,
collection=collection,
vector_index_name=INDEX_NAME,
index_name=INDEX_NAME,
)
collection._aggregate_result = list(
filter(
Expand All @@ -177,7 +177,7 @@ def test_mmr(
texts,
embedding=embedding_openai,
collection=collection,
vector_index_name=INDEX_NAME,
index_name=INDEX_NAME,
)
query = "foo"
self._validate_search(
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