langchain.evaluation.regex_match.base.RegexMatchStringEvaluator¶
class langchain.evaluation.regex_match.base.RegexMatchStringEvaluator(*, flags: int = 0, **kwargs: Any)[source]¶
Compute a regex match between the prediction and the reference.
Examples
>>> evaluator = RegexMatchStringEvaluator(flags=re.IGNORECASE)
>>> evaluator.evaluate_strings(
        prediction="Mindy is the CTO",
        reference="^mindy.*cto$",
    )  # This will return {'score': 1.0} due to the IGNORECASE flag
>>> evaluator = RegexMatchStringEvaluator()
>>> evaluator.evaluate_strings(
        prediction="Mindy is the CTO",
        reference="^Mike.*CEO$",
    )  # This will return {'score': 0.0}
>>> evaluator.evaluate_strings(
        prediction="Mindy is the CTO",
        reference="^Mike.*CEO$|^Mindy.*CTO$",
    )  # This will return {'score': 1.0} as the prediction matches the second pattern in the union
Attributes
evaluation_name
Get the evaluation name.
input_keys
Get the input keys.
requires_input
This evaluator does not require input.
requires_reference
This evaluator requires a reference.
Methods
__init__(*[, flags])
aevaluate_strings(*, prediction[, ...])
Asynchronously evaluate Chain or LLM output, based on optional input and label.
evaluate_strings(*, prediction[, reference, ...])
Evaluate Chain or LLM output, based on optional input and label.
__init__(*, flags: int = 0, **kwargs: Any)[source]¶
async aevaluate_strings(*, prediction: str, reference: Optional[str] = None, input: Optional[str] = None, **kwargs: Any) → dict¶