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    Pythonlangchain-corevectorstoresbaseVectorStoresimilarity_search_with_relevance_scores
    Methodā—Since v0.2

    similarity_search_with_relevance_scores

    Copy
    similarity_search_with_relevance_scores(
      self,
      query: str,
      k: int = 4,
      **kwargs: Any
    View source on GitHub
    =
    {
    }
    )
    ->
    list
    [
    tuple
    [
    Document
    ,
    float
    ]
    ]

    Parameters

    NameTypeDescription
    query*str
    kint
    Default:4
    **kwargsAny
    Default:{}

    Return docs and relevance scores in the range [0, 1].

    0 is dissimilar, 1 is most similar.

    Input text.

    Number of Document objects to return.

    Kwargs to be passed to similarity search.

    Should include score_threshold, an optional floating point value between 0 to 1 to filter the resulting set of retrieved docs.