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Documentation Index

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Returns documents most similar to the query text. 
similarity_search(
    query: str,
    k: int = 4,
    filter: Optional[Dict[str, Any]] = None,
    **kwargs
) -> List[Document]

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Parameters

ParameterTypeDescription
querystrQuery text to search for
kintNumber of documents to return (default: 4)
filterOptional[Dict[str, Any]](Optional) Metadata filters to apply
**kwargsAnyAdditional keyword arguments (currently unused)

​
Returns

List[Document]: List of most similar Document objects

​
Example Usage

# Basic similarity search
results = store.similarity_search("machine learning algorithms", k=5)
for doc in results:
    print(f"Content: {doc.page_content[:100]}...")
    print(f"Metadata: {doc.metadata}")

# Search with metadata filter
filter_dict = {"language": "python", "level": "beginner"}
results = store.similarity_search(
    "python tutorial",
    k=3,
    filter=filter_dict
)