fix: Remove custom metadata from A2A response events

PiperOrigin-RevId: 857331378

Author: google-genai-bot

src/google/adk/agents/remote_a2a_agent.py

@@ -504,8 +504,6 @@ async def _handle_a2a_response(
             invocation_id=ctx.invocation_id,
             branch=ctx.branch,
         )
-      event.custom_metadata = event.custom_metadata or {}
-      event.custom_metadata[A2A_METADATA_PREFIX + "response"] = True
       return event
     except A2AClientError as e:
       logger.error("Failed to handle A2A response: %s", e)

src/google/adk/evaluation/local_eval_service.py

@@ -268,22 +268,6 @@ async def _evaluate_single_inference_result(
         else 'test_user_id'
     )
 
-    if (
-        inference_result.status == InferenceStatus.FAILURE
-        or inference_result.inferences is None
-    ):
-      logger.error(
-          'Evaluation attempted on failed inference for eval case `%s`.'
-          ' Error: %s',
-          inference_result.eval_case_id,
-          inference_result.error_message,
-      )
-      eval_case_result = await self._build_not_evaluated_eval_case_result(
-          inference_result=inference_result,
-          user_id=user_id,
-      )
-      return (inference_result, eval_case_result)
-
     if eval_case.conversation_scenario is None and len(
         inference_result.inferences
     ) != len(eval_case.conversation):
@@ -480,31 +464,6 @@ def _generate_final_eval_status(
 
     return final_eval_status
 
-  async def _build_not_evaluated_eval_case_result(
-      self,
-      *,
-      inference_result: InferenceResult,
-      user_id: str,
-  ) -> EvalCaseResult:
-    """Constructs an EvalCaseResult for cases that could not be evaluated."""
-    session_details = await self._session_service.get_session(
-        app_name=inference_result.app_name,
-        user_id=user_id,
-        session_id=inference_result.session_id,
-    )
-
-    return EvalCaseResult(
-        eval_set_file=inference_result.eval_set_id,
-        eval_set_id=inference_result.eval_set_id,
-        eval_id=inference_result.eval_case_id,
-        final_eval_status=EvalStatus.NOT_EVALUATED,
-        overall_eval_metric_results=[],
-        eval_metric_result_per_invocation=[],
-        session_id=inference_result.session_id,
-        session_details=session_details,
-        user_id=user_id,
-    )
-
   async def _perform_inference_single_eval_item(
       self,
       app_name: str,

tests/unittests/evaluation/test_local_eval_service.py

@@ -325,82 +325,6 @@ async def test_evaluate_success(
   assert mock_eval_set_results_manager.save_eval_set_result.call_count == 2
 
 
-@pytest.mark.asyncio
-async def test_evaluate_skips_failed_inference_results(
-    eval_service, mock_eval_sets_manager, mock_eval_set_results_manager, mocker
-):
-  invocation = Invocation(
-      user_content=genai_types.Content(
-          parts=[genai_types.Part(text="test user content.")]
-      ),
-      final_response=genai_types.Content(
-          parts=[genai_types.Part(text="test final response.")]
-      ),
-  )
-  inference_results = [
-      InferenceResult(
-          app_name="test_app",
-          eval_set_id="test_eval_set",
-          eval_case_id="case_failure",
-          inferences=None,
-          session_id="session_fail",
-          status=InferenceStatus.FAILURE,
-          error_message="simulated failure",
-      ),
-      InferenceResult(
-          app_name="test_app",
-          eval_set_id="test_eval_set",
-          eval_case_id="case_success",
-          inferences=[invocation.model_copy(deep=True)],
-          session_id="session_success",
-          status=InferenceStatus.SUCCESS,
-      ),
-      InferenceResult(
-          app_name="test_app",
-          eval_set_id="test_eval_set",
-          eval_case_id="case_unknown",
-          inferences=[invocation.model_copy(deep=True)],
-          session_id="session_unknown",
-          status=InferenceStatus.UNKNOWN,
-      ),
-  ]
-  eval_metric = EvalMetric(metric_name="fake_metric", threshold=0.5)
-  evaluate_request = EvaluateRequest(
-      inference_results=inference_results,
-      evaluate_config=EvaluateConfig(eval_metrics=[eval_metric], parallelism=2),
-  )
-
-  mock_eval_case = mocker.MagicMock(spec=EvalCase)
-  mock_eval_case.conversation = [invocation.model_copy(deep=True)]
-  mock_eval_case.conversation_scenario = None
-  mock_eval_case.session_input = None
-  mock_eval_sets_manager.get_eval_case.return_value = mock_eval_case
-
-  results = []
-  async for result in eval_service.evaluate(evaluate_request):
-    results.append(result)
-
-  assert len(results) == 3
-  results_by_case = {result.eval_id: result for result in results}
-
-  failure_result = results_by_case["case_failure"]
-  assert failure_result.final_eval_status == EvalStatus.NOT_EVALUATED
-  assert failure_result.overall_eval_metric_results == []
-  assert failure_result.eval_metric_result_per_invocation == []
-
-  for case_id in ["case_success", "case_unknown"]:
-    case_result = results_by_case[case_id]
-    assert case_result.final_eval_status == EvalStatus.PASSED
-    assert len(case_result.overall_eval_metric_results) == 1
-    assert (
-        case_result.overall_eval_metric_results[0].metric_name == "fake_metric"
-    )
-    assert case_result.overall_eval_metric_results[0].score == 0.9
-
-  assert mock_eval_sets_manager.get_eval_case.call_count == 3
-  assert mock_eval_set_results_manager.save_eval_set_result.call_count == 3
-
-
 @pytest.mark.asyncio
 async def test_evaluate_eval_case_not_found(
     eval_service,
@@ -494,93 +418,6 @@ async def test_evaluate_single_inference_result(
     assert metric_result.eval_status == EvalStatus.PASSED
 
 
-@pytest.mark.asyncio
-async def test_evaluate_single_inference_result_handles_failed_inference(
-    eval_service, mock_eval_sets_manager, mocker
-):
-  invocation = Invocation(
-      user_content=genai_types.Content(
-          parts=[genai_types.Part(text="test user content.")]
-      ),
-      final_response=genai_types.Content(
-          parts=[genai_types.Part(text="test final response.")]
-      ),
-  )
-  inference_result = InferenceResult(
-      app_name="test_app",
-      eval_set_id="test_eval_set",
-      eval_case_id="case1",
-      inferences=None,
-      session_id="session1",
-      status=InferenceStatus.FAILURE,
-      error_message="simulated inference failure",
-  )
-  eval_metric = EvalMetric(metric_name="fake_metric", threshold=0.5)
-  evaluate_config = EvaluateConfig(eval_metrics=[eval_metric], parallelism=1)
-
-  mock_eval_case = mocker.MagicMock(spec=EvalCase)
-  mock_eval_case.conversation = [invocation.model_copy(deep=True)]
-  mock_eval_case.conversation_scenario = None
-  mock_eval_case.session_input = None
-  mock_eval_sets_manager.get_eval_case.return_value = mock_eval_case
-
-  _, result = await eval_service._evaluate_single_inference_result(
-      inference_result=inference_result, evaluate_config=evaluate_config
-  )
-
-  assert isinstance(result, EvalCaseResult)
-  assert result.eval_id == "case1"
-  assert result.final_eval_status == EvalStatus.NOT_EVALUATED
-  assert result.overall_eval_metric_results == []
-  assert result.eval_metric_result_per_invocation == []
-  mock_eval_sets_manager.get_eval_case.assert_called_once_with(
-      app_name="test_app", eval_set_id="test_eval_set", eval_case_id="case1"
-  )
-
-
-@pytest.mark.asyncio
-async def test_evaluate_single_inference_result_handles_missing_inferences(
-    eval_service, mock_eval_sets_manager, mocker
-):
-  invocation = Invocation(
-      user_content=genai_types.Content(
-          parts=[genai_types.Part(text="test user content.")]
-      ),
-      final_response=genai_types.Content(
-          parts=[genai_types.Part(text="test final response.")]
-      ),
-  )
-  inference_result = InferenceResult(
-      app_name="test_app",
-      eval_set_id="test_eval_set",
-      eval_case_id="case1",
-      inferences=None,
-      session_id="session1",
-      status=InferenceStatus.SUCCESS,
-  )
-  eval_metric = EvalMetric(metric_name="fake_metric", threshold=0.5)
-  evaluate_config = EvaluateConfig(eval_metrics=[eval_metric], parallelism=1)
-
-  mock_eval_case = mocker.MagicMock(spec=EvalCase)
-  mock_eval_case.conversation = [invocation.model_copy(deep=True)]
-  mock_eval_case.conversation_scenario = None
-  mock_eval_case.session_input = None
-  mock_eval_sets_manager.get_eval_case.return_value = mock_eval_case
-
-  _, result = await eval_service._evaluate_single_inference_result(
-      inference_result=inference_result, evaluate_config=evaluate_config
-  )
-
-  assert isinstance(result, EvalCaseResult)
-  assert result.eval_id == "case1"
-  assert result.final_eval_status == EvalStatus.NOT_EVALUATED
-  assert result.overall_eval_metric_results == []
-  assert result.eval_metric_result_per_invocation == []
-  mock_eval_sets_manager.get_eval_case.assert_called_once_with(
-      app_name="test_app", eval_set_id="test_eval_set", eval_case_id="case1"
-  )
-
-
 @pytest.mark.asyncio
 async def test_evaluate_single_inference_result_for_conversation_scenario(
     eval_service, mock_eval_sets_manager, mocker