chore: import upstream snapshot with attribution

docs-website/reference_versioned_docs/version-2.30/integrations-api/deepeval.md

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+---
+title: "DeepEval"
+id: integrations-deepeval
+description: "DeepEval integration for Haystack"
+slug: "/integrations-deepeval"
+---
+
+<a id="haystack_integrations.components.evaluators.deepeval.evaluator"></a>
+
+## Module haystack\_integrations.components.evaluators.deepeval.evaluator
+
+<a id="haystack_integrations.components.evaluators.deepeval.evaluator.DeepEvalEvaluator"></a>
+
+### DeepEvalEvaluator
+
+A component that uses the [DeepEval framework](https://docs.confident-ai.com/docs/evaluation-introduction)
+to evaluate inputs against a specific metric. Supported metrics are defined by `DeepEvalMetric`.
+
+Usage example:
+```python
+from haystack_integrations.components.evaluators.deepeval import DeepEvalEvaluator, DeepEvalMetric
+
+evaluator = DeepEvalEvaluator(
+    metric=DeepEvalMetric.FAITHFULNESS,
+    metric_params={"model": "gpt-4"},
+)
+output = evaluator.run(
+    questions=["Which is the most popular global sport?"],
+    contexts=[
+        [
+            "Football is undoubtedly the world's most popular sport with"
+            "major events like the FIFA World Cup and sports personalities"
+            "like Ronaldo and Messi, drawing a followership of more than 4"
+            "billion people."
+        ]
+    ],
+    responses=["Football is the most popular sport with around 4 billion" "followers worldwide"],
+)
+print(output["results"])
+```
+
+<a id="haystack_integrations.components.evaluators.deepeval.evaluator.DeepEvalEvaluator.__init__"></a>
+
+#### DeepEvalEvaluator.\_\_init\_\_
+
+```python
+def __init__(metric: str | DeepEvalMetric,
+             metric_params: dict[str, Any] | None = None)
+```
+
+Construct a new DeepEval evaluator.
+
+**Arguments**:
+
+- `metric`: The metric to use for evaluation.
+- `metric_params`: Parameters to pass to the metric's constructor.
+Refer to the `RagasMetric` class for more details
+on required parameters.
+
+<a id="haystack_integrations.components.evaluators.deepeval.evaluator.DeepEvalEvaluator.run"></a>
+
+#### DeepEvalEvaluator.run
+
+```python
+@component.output_types(results=list[list[dict[str, Any]]])
+def run(**inputs: Any) -> dict[str, Any]
+```
+
+Run the DeepEval evaluator on the provided inputs.
+
+**Arguments**:
+
+- `inputs`: The inputs to evaluate. These are determined by the
+metric being calculated. See `DeepEvalMetric` for more
+information.
+
+**Returns**:
+
+A dictionary with a single `results` entry that contains
+a nested list of metric results. Each input can have one or more
+results, depending on the metric. Each result is a dictionary
+containing the following keys and values:
+- `name` - The name of the metric.
+- `score` - The score of the metric.
+- `explanation` - An optional explanation of the score.
+
+<a id="haystack_integrations.components.evaluators.deepeval.evaluator.DeepEvalEvaluator.to_dict"></a>
+
+#### DeepEvalEvaluator.to\_dict
+
+```python
+def to_dict() -> dict[str, Any]
+```
+
+Serializes the component to a dictionary.
+
+**Raises**:
+
+- `DeserializationError`: If the component cannot be serialized.
+
+**Returns**:
+
+Dictionary with serialized data.
+
+<a id="haystack_integrations.components.evaluators.deepeval.evaluator.DeepEvalEvaluator.from_dict"></a>
+
+#### DeepEvalEvaluator.from\_dict
+
+```python
+@classmethod
+def from_dict(cls, data: dict[str, Any]) -> "DeepEvalEvaluator"
+```
+
+Deserializes the component from a dictionary.
+
+**Arguments**:
+
+- `data`: Dictionary to deserialize from.
+
+**Returns**:
+
+Deserialized component.
+
+<a id="haystack_integrations.components.evaluators.deepeval.metrics"></a>
+
+## Module haystack\_integrations.components.evaluators.deepeval.metrics
+
+<a id="haystack_integrations.components.evaluators.deepeval.metrics.DeepEvalMetric"></a>
+
+### DeepEvalMetric
+
+Metrics supported by DeepEval.
+
+All metrics require a `model` parameter, which specifies
+the model to use for evaluation. Refer to the DeepEval
+documentation for information on the supported models.
+
+<a id="haystack_integrations.components.evaluators.deepeval.metrics.DeepEvalMetric.ANSWER_RELEVANCY"></a>
+
+#### ANSWER\_RELEVANCY
+
+Answer relevancy.\
+Inputs - `questions: List[str], contexts: List[List[str]], responses: List[str]`
+
+<a id="haystack_integrations.components.evaluators.deepeval.metrics.DeepEvalMetric.FAITHFULNESS"></a>
+
+#### FAITHFULNESS
+
+Faithfulness.\
+Inputs - `questions: List[str], contexts: List[List[str]], responses: List[str]`
+
+<a id="haystack_integrations.components.evaluators.deepeval.metrics.DeepEvalMetric.CONTEXTUAL_PRECISION"></a>
+
+#### CONTEXTUAL\_PRECISION
+
+Contextual precision.\
+Inputs - `questions: List[str], contexts: List[List[str]], responses: List[str], ground_truths: List[str]`\
+The ground truth is the expected response.
+
+<a id="haystack_integrations.components.evaluators.deepeval.metrics.DeepEvalMetric.CONTEXTUAL_RECALL"></a>
+
+#### CONTEXTUAL\_RECALL
+
+Contextual recall.\
+Inputs - `questions: List[str], contexts: List[List[str]], responses: List[str], ground_truths: List[str]`\
+The ground truth is the expected response.\
+
+<a id="haystack_integrations.components.evaluators.deepeval.metrics.DeepEvalMetric.CONTEXTUAL_RELEVANCE"></a>
+
+#### CONTEXTUAL\_RELEVANCE
+
+Contextual relevance.\
+Inputs - `questions: List[str], contexts: List[List[str]], responses: List[str]`
+
+<a id="haystack_integrations.components.evaluators.deepeval.metrics.DeepEvalMetric.from_str"></a>
+
+#### DeepEvalMetric.from\_str
+
+```python
+@classmethod
+def from_str(cls, string: str) -> "DeepEvalMetric"
+```
+
+Create a metric type from a string.
+
+**Arguments**:
+
+- `string`: The string to convert.
+
+**Returns**:
+
+The metric.
+