ContextPrecision¶
- class opik.evaluation.metrics.ContextPrecision(model: str | OpikBaseModel | None = None, name: str = 'context_precision_metric', few_shot_examples: List[FewShotExampleContextPrecision] | None = None)¶
Bases:
BaseMetric
A metric that evaluates the context precision of an input-output pair using an LLM.
This metric uses a language model to assess how well the given output aligns with the provided context for the given input. It returns a score between 0.0 and 1.0, where higher values indicate better context precision.
- Parameters:
model – The language model to use for evaluation. Can be a string (model name) or a CometBaseModel instance.
name – The name of the metric. Defaults to “context_precision_metric”.
few_shot_examples – A list of few-shot examples to provide to the model. If None, uses the default few-shot examples.
Example
>>> from opik.evaluation.metrics import ContextPrecision >>> context_precision_metric = ContextPrecision() >>> result = context_precision_metric.score("What's the capital of France?", "The capital of France is Paris.", "Paris", ["France is a country in Europe."]) >>> print(result.value) 1.0 >>> print(result.reason) The provided output perfectly matches the expected output of 'Paris' and accurately identifies it as the capital of France. ...
- score(input: str, output: str, expected_output: str, context: List[str], **ignored_kwargs: Any) ScoreResult ¶
Calculate the context precision score for the given input-output pair.
- Parameters:
input – The input text to be evaluated.
output – The output text to be evaluated.
expected_output – The expected output for the given input.
context – A list of context strings relevant to the input.
**ignored_kwargs – Additional keyword arguments that are ignored.
- Returns:
A ScoreResult object containing the context precision score (between 0.0 and 1.0) and a reason for the score.
- Return type:
score_result.ScoreResult
- async ascore(input: str, output: str, expected_output: str, context: List[str], **ignored_kwargs: Any) ScoreResult ¶
Asynchronously calculate the context precision score for the given input-output pair.
This method is the asynchronous version of
score()
. For detailed documentation, please refer to thescore()
method.- Parameters:
input – The input text to be evaluated.
output – The output text to be evaluated.
expected_output – The expected output for the given input.
context – A list of context strings relevant to the input.
**ignored_kwargs – Additional keyword arguments that are ignored.
- Returns:
A ScoreResult object with the context precision score and reason.
- Return type:
score_result.ScoreResult