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.
- Parameters:
flags (int) –
kwargs (Any) –
- async aevaluate_strings(*, prediction: str, reference: str | None = None, input: str | None = None, **kwargs: Any) dict #
Asynchronously evaluate Chain or LLM output, based on optional input and label.
- Parameters:
prediction (str) – The LLM or chain prediction to evaluate.
reference (Optional[str], optional) – The reference label to evaluate against.
input (Optional[str], optional) – The input to consider during evaluation.
kwargs (Any) – Additional keyword arguments, including callbacks, tags, etc.
- Returns:
The evaluation results containing the score or value.
- Return type:
dict
- evaluate_strings(*, prediction: str, reference: str | None = None, input: str | None = None, **kwargs: Any) dict #
Evaluate Chain or LLM output, based on optional input and label.
- Parameters:
prediction (str) – The LLM or chain prediction to evaluate.
reference (Optional[str], optional) – The reference label to evaluate against.
input (Optional[str], optional) – The input to consider during evaluation.
kwargs (Any) – Additional keyword arguments, including callbacks, tags, etc.
- Returns:
The evaluation results containing the score or value.
- Return type:
dict