fix: Check that mean_score is a valid float value

In some cases, Vertex AI evaluation returns nan values for the metrics. That was not handled correctly. PiperOrigin-RevId: 785514456

Author: ankursharmas

src/google/adk/evaluation/vertex_ai_eval_facade.py

@@ -14,6 +14,7 @@
 
 from __future__ import annotations
 
+import math
 import os
 from typing import Optional
 
@@ -112,7 +113,12 @@ def _get_text(self, content: Optional[genai_types.Content]) -> str:
  return ""
 
  def _get_score(self, eval_result) -> Optional[float]:
- if eval_result and eval_result.summary_metrics:
+ if (
+ eval_result
+ and eval_result.summary_metrics
+ and isinstance(eval_result.summary_metrics[0].mean_score, float)
+ and not math.isnan(eval_result.summary_metrics[0].mean_score)
+ ):
  return eval_result.summary_metrics[0].mean_score
 
  return None

tests/unittests/evaluation/test_vertex_ai_eval_facade.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 """Tests for the Response Evaluator."""
+import math
 import random
 from unittest.mock import patch
 
@@ -122,7 +123,18 @@ def test_evaluate_invocations_metric_failed(self, mock_perform_eval):
  vertexai_types.PrebuiltMetric.COHERENCE.name
  ]
 
- def test_evaluate_invocations_metric_no_score(self, mock_perform_eval):
+ @pytest.mark.parametrize(
+ "summary_metric_with_no_score",
+ [
+ ([]),
+ ([vertexai_types.AggregatedMetricResult(mean_score=float("nan"))]),
+ ([vertexai_types.AggregatedMetricResult(mean_score=None)]),
+ ([vertexai_types.AggregatedMetricResult(mean_score=math.nan)]),
+ ],
+ )
+ def test_evaluate_invocations_metric_no_score(
+ self, mock_perform_eval, summary_metric_with_no_score
+ ):
  """Test evaluate_invocations function for a metric."""
  actual_invocations = [
  Invocation(
@@ -151,7 +163,7 @@ def test_evaluate_invocations_metric_no_score(self, mock_perform_eval):
  )
  # Mock the return value of _perform_eval
  mock_perform_eval.return_value = vertexai_types.EvaluationResult(
- summary_metrics=[],
+ summary_metrics=summary_metric_with_no_score,
  eval_case_results=[],
  )