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    Pythonlangchain-classicevaluationstring_distancebaseStringDistanceEvalChain
    Class●Since v1.0

    StringDistanceEvalChain

    Compute string distances between the prediction and the reference.

    Examples:

    from langchain_classic.evaluation import StringDistanceEvalChain evaluator = StringDistanceEvalChain() evaluator.evaluate_strings( prediction="Mindy is the CTO", reference="Mindy is the CEO", )

    Using the load_evaluator function:

    from langchain_classic.evaluation import load_evaluator evaluator = load_evaluator("string_distance") evaluator.evaluate_strings( prediction="The answer is three", reference="three", )

    Copy
    StringDistanceEvalChain()

    Bases

    StringEvaluator_RapidFuzzChainMixin

    Attributes

    attribute
    requires_input: bool

    This evaluator does not require input.

    attribute
    requires_reference: bool

    This evaluator does not require a reference.

    attribute
    input_keys: list[str]

    Get the input keys.

    attribute
    evaluation_name: str

    Get the evaluation name.

    Inherited fromStringEvaluator

    Methods

    Mevaluate_strings
    —

    Evaluate Chain or LLM output, based on optional input and label.

    Maevaluate_strings
    —

    Asynchronously evaluate Chain or LLM output, based on optional input and label.

    View source on GitHub