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chore: deepeval - fix types #3346

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anakin87 merged 2 commits into from
May 26, 2026
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chore: deepeval - fix types #3346

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chore: deepeval - fix types
anakin87 May 25, 2026
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anakin87 May 25, 2026
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30 changes: 16 additions & 14 deletions integrations/deepeval/src/haystack_integrations/components/evaluators/deepeval/metrics.py
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Original file line number Diff line number Diff line change
Expand Up @@ -234,8 +234,9 @@ def question_context_response(
An iterable of `LLMTestCase` objects.
"""
InputConverters._validate_input_elements(questions=questions, contexts=contexts, responses=responses)
for q, c, r in zip(questions, contexts, responses, strict=True): # type: ignore
test_case = LLMTestCase(input=q, actual_output=r, retrieval_context=c)
for q, c, r in zip(questions, contexts, responses, strict=True):
# for retrieval_context, deepeval expects list[str | RetrievedContextData]; we pass list[str]
test_case = LLMTestCase(input=q, actual_output=r, retrieval_context=c) # type: ignore[arg-type]
yield test_case

@staticmethod
Expand All @@ -257,8 +258,9 @@ def question_context_response_ground_truth(
An iterable of `LLMTestCase` objects.
"""
InputConverters._validate_input_elements(questions=questions, contexts=contexts, responses=responses)
for q, c, r, gt in zip(questions, contexts, responses, ground_truths, strict=True): # type: ignore
test_case = LLMTestCase(input=q, actual_output=r, retrieval_context=c, expected_output=gt)
for q, c, r, gt in zip(questions, contexts, responses, ground_truths, strict=True):
# for retrieval_context, deepeval expects list[str | RetrievedContextData]; we pass list[str]
test_case = LLMTestCase(input=q, actual_output=r, retrieval_context=c, expected_output=gt) # type: ignore[arg-type]
yield test_case


Expand Down Expand Up @@ -297,31 +299,31 @@ def inner(output: TestResult, metric: DeepEvalMetric) -> list[MetricResult]:
DeepEvalMetric.ANSWER_RELEVANCY: MetricDescriptor.new(
DeepEvalMetric.ANSWER_RELEVANCY,
AnswerRelevancyMetric,
InputConverters.question_context_response, # type: ignore
init_parameters={"model": str | None}, # type: ignore
InputConverters.question_context_response, # type: ignore[arg-type]
init_parameters={"model": str | None}, # type: ignore[dict-item]
),
DeepEvalMetric.FAITHFULNESS: MetricDescriptor.new(
DeepEvalMetric.FAITHFULNESS,
FaithfulnessMetric,
InputConverters.question_context_response, # type: ignore
init_parameters={"model": str | None}, # type: ignore
InputConverters.question_context_response, # type: ignore[arg-type]
init_parameters={"model": str | None}, # type: ignore[dict-item]
),
DeepEvalMetric.CONTEXTUAL_PRECISION: MetricDescriptor.new(
DeepEvalMetric.CONTEXTUAL_PRECISION,
ContextualPrecisionMetric,
InputConverters.question_context_response_ground_truth, # type: ignore
init_parameters={"model": str | None}, # type: ignore
InputConverters.question_context_response_ground_truth, # type: ignore[arg-type]
init_parameters={"model": str | None}, # type: ignore[dict-item]
),
DeepEvalMetric.CONTEXTUAL_RECALL: MetricDescriptor.new(
DeepEvalMetric.CONTEXTUAL_RECALL,
ContextualRecallMetric,
InputConverters.question_context_response_ground_truth, # type: ignore
init_parameters={"model": str | None}, # type: ignore
InputConverters.question_context_response_ground_truth, # type: ignore[arg-type]
init_parameters={"model": str | None}, # type: ignore[dict-item]
),
DeepEvalMetric.CONTEXTUAL_RELEVANCE: MetricDescriptor.new(
DeepEvalMetric.CONTEXTUAL_RELEVANCE,
ContextualRelevancyMetric,
InputConverters.question_context_response, # type: ignore
init_parameters={"model": str | None}, # type: ignore
InputConverters.question_context_response, # type: ignore[arg-type]
init_parameters={"model": str | None}, # type: ignore[dict-item]
),
}
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