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Return documents closest to the given embedding.
similarity_search_by_vector( self, embedding: Union[List[float], str], k: int = 4, filter: Optional[str] = None, *, namespace: Optional[str] = None, **kwargs: Any = {} ) -> List[Document]
embedding
Union[List[float], str]
Embedding to look up documents similar to.
k
int
4
Number of Documents to return. Defaults to 4.
filter
Optional[str]
None
Optional metadata filter in str format
namespace
Namespace to use from the index.
