Source code for langchain.evaluation.exact_match.base

import string
from typing import Any, List

from langchain.evaluation.schema import StringEvaluator


[docs] class ExactMatchStringEvaluator(StringEvaluator): """Compute an exact match between the prediction and the reference. Examples ---------- >>> evaluator = ExactMatchChain() >>> evaluator.evaluate_strings( prediction="Mindy is the CTO", reference="Mindy is the CTO", ) # This will return {'score': 1.0} >>> evaluator.evaluate_strings( prediction="Mindy is the CTO", reference="Mindy is the CEO", ) # This will return {'score': 0.0} """
[docs] def __init__( self, *, ignore_case: bool = False, ignore_punctuation: bool = False, ignore_numbers: bool = False, **kwargs: Any, ): super().__init__() self.ignore_case = ignore_case self.ignore_punctuation = ignore_punctuation self.ignore_numbers = ignore_numbers
@property def requires_input(self) -> bool: """ This evaluator does not require input. """ return False @property def requires_reference(self) -> bool: """ This evaluator requires a reference. """ return True @property def input_keys(self) -> List[str]: """ Get the input keys. Returns: List[str]: The input keys. """ return ["reference", "prediction"] @property def evaluation_name(self) -> str: """ Get the evaluation name. Returns: str: The evaluation name. """ return "exact_match" def _evaluate_strings( # type: ignore[arg-type,override] self, *, prediction: str, reference: str, **kwargs: Any, ) -> dict: """ Evaluate the exact match between the prediction and the reference. Args: prediction (str): The prediction string. reference (Optional[str], optional): The reference string. Returns: dict: The evaluation results containing the score. """ if self.ignore_case: prediction = prediction.lower() reference = reference.lower() if self.ignore_punctuation: prediction = prediction.translate(str.maketrans("", "", string.punctuation)) reference = reference.translate(str.maketrans("", "", string.punctuation)) if self.ignore_numbers: prediction = prediction.translate(str.maketrans("", "", string.digits)) reference = reference.translate(str.maketrans("", "", string.digits)) return {"score": int(prediction == reference)}