feat: Remove overall_eval_status calculation from _CustomMetricEvaluator and add threshold to custom metric function expected signature

Co-authored-by: Joseph Pagadora <jcpagadora@google.com>
PiperOrigin-RevId: 861268984

src/google/adk/evaluation/custom_metric_evaluator.py

@@ -24,7 +24,6 @@ from typing_extensions import override
 from .eval_case import ConversationScenario
 from .eval_case import Invocation
 from .eval_metrics import EvalMetric
-from .eval_metrics import EvalStatus
 from .evaluator import EvaluationResult
 from .evaluator import Evaluator
 
@@ -44,12 +43,6 @@ def _get_metric_function(
     ) from e
 
 
-def _get_eval_status(score: Optional[float], threshold: float) -> EvalStatus:
-  if score is None:
-    return EvalStatus.NOT_EVALUATED
-  return EvalStatus.PASSED if score >= threshold else EvalStatus.FAILED
-
-
 class _CustomMetricEvaluator(Evaluator):
   """Evaluator for custom metrics."""
 
@@ -64,16 +57,20 @@ class _CustomMetricEvaluator(Evaluator):
       expected_invocations: Optional[list[Invocation]],
       conversation_scenario: Optional[ConversationScenario] = None,
   ) -> EvaluationResult:
+    eval_metric = self._eval_metric.model_copy(deep=True)
+    eval_metric.threshold = None
     if inspect.iscoroutinefunction(self._metric_function):
       eval_result = await self._metric_function(
-          actual_invocations, expected_invocations, conversation_scenario
+          eval_metric,
+          actual_invocations,
+          expected_invocations,
+          conversation_scenario,
       )
     else:
       eval_result = self._metric_function(
-          actual_invocations, expected_invocations, conversation_scenario
+          eval_metric,
+          actual_invocations,
+          expected_invocations,
+          conversation_scenario,
       )
-
-    eval_result.overall_eval_status = _get_eval_status(
-        eval_result.overall_score, self._eval_metric.threshold
-    )
     return eval_result

src/google/adk/evaluation/eval_metrics.py

@@ -258,9 +258,11 @@ class EvalMetric(EvalBaseModel):
       description="The name of the metric.",
   )
 
-  threshold: float = Field(
+  threshold: Optional[float] = Field(
+      default=None,
       description=(
-          "A threshold value. Each metric decides how to interpret this"
+          "This field will be deprecated soon. Please use `criterion` instead."
+          " A threshold value. Each metric decides how to interpret this"
           " threshold."
       ),
   )

tests/unittests/evaluation/test_custom_metric_evaluator.py

@@ -0,0 +1,110 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from unittest import mock
+
+from google.adk.evaluation.custom_metric_evaluator import _CustomMetricEvaluator
+from google.adk.evaluation.custom_metric_evaluator import _get_metric_function
+from google.adk.evaluation.eval_case import ConversationScenario
+from google.adk.evaluation.eval_case import Invocation
+from google.adk.evaluation.eval_metrics import EvalMetric
+from google.adk.evaluation.evaluator import EvaluationResult
+import pytest
+
+
+def my_sync_metric_function(
+    eval_metric: EvalMetric,
+    actual_invocations: list[Invocation],
+    expected_invocations: list[Invocation] | None,
+    conversation_scenario: ConversationScenario | None,
+) -> EvaluationResult:
+  """Sync metric function for testing."""
+  return EvaluationResult(overall_score=1.0)
+
+
+async def my_async_metric_function(
+    eval_metric: EvalMetric,
+    actual_invocations: list[Invocation],
+    expected_invocations: list[Invocation] | None,
+    conversation_scenario: ConversationScenario | None,
+) -> EvaluationResult:
+  """Async metric function for testing."""
+  return EvaluationResult(overall_score=0.5)
+
+
+@mock.patch("importlib.import_module")
+def test_get_metric_function_success(mock_import_module):
+  """Tests that _get_metric_function successfully returns a function."""
+  mock_module = mock.MagicMock()
+  mock_module.my_sync_metric_function = my_sync_metric_function
+  mock_import_module.return_value = mock_module
+  func = _get_metric_function(
+      "test_custom_metric_evaluator.my_sync_metric_function"
+  )
+  assert func == my_sync_metric_function
+
+
+@mock.patch("importlib.import_module", side_effect=ImportError)
+def test_get_metric_function_module_not_found(mock_import_module):
+  """Tests that _get_metric_function raises ImportError for non-existent module."""
+  with pytest.raises(ImportError):
+    _get_metric_function("non_existent_module.my_sync_metric_function")
+
+
+@mock.patch("importlib.import_module")
+def test_get_metric_function_function_not_found(mock_import_module):
+  """Tests that _get_metric_function raises ImportError for non-existent function."""
+  mock_import_module.return_value = object()
+  with pytest.raises(ImportError):
+    _get_metric_function(
+        "google.adk.tests.unittests.evaluation.test_custom_metric_evaluator.non_existent_function"
+    )
+
+
+def test_get_metric_function_malformed_path():
+  """Tests that _get_metric_function raises ImportError for malformed path."""
+  with pytest.raises(ImportError):
+    _get_metric_function("malformed_path")
+
+
+@mock.patch(
+    "google.adk.evaluation.custom_metric_evaluator._get_metric_function",
+    return_value=my_sync_metric_function,
+)
+@pytest.mark.asyncio
+async def test_custom_metric_evaluator_sync_function(mock_get_metric_function):
+  """Tests that _CustomMetricEvaluator works with a sync metric function."""
+  eval_metric = EvalMetric(metric_name="sync_metric")
+  evaluator = _CustomMetricEvaluator(
+      eval_metric=eval_metric,
+      custom_function_path="google.adk.tests.unittests.evaluation.test_custom_metric_evaluator.my_sync_metric_function",
+  )
+  result = await evaluator.evaluate_invocations([], None)
+  assert result.overall_score == 1.0
+
+
+@mock.patch(
+    "google.adk.evaluation.custom_metric_evaluator._get_metric_function",
+    return_value=my_async_metric_function,
+)
+@pytest.mark.asyncio
+async def test_custom_metric_evaluator_async_function(mock_get_metric_function):
+  """Tests that _CustomMetricEvaluator works with an async metric function."""
+  eval_metric = EvalMetric(metric_name="async_metric")
+  evaluator = _CustomMetricEvaluator(
+      eval_metric=eval_metric,
+      custom_function_path="google.adk.tests.unittests.evaluation.test_custom_metric_evaluator.my_async_metric_function",
+  )
+  result = await evaluator.evaluate_invocations([], None)
+  assert result.overall_score == 0.5