test: add Agent eval tests

tests/evaluation/metrics/test_goal_metrics.py

@@ -0,0 +1,60 @@
+import pytest
+from unittest.mock import patch, MagicMock
+from tests.evaluation.metrics.base_evaluation_metrics_test import BaseEvaluationMetricsTest
+
+from crewai.evaluation.base_evaluator import EvaluationScore
+from crewai.evaluation.metrics.goal_metrics import GoalAlignmentEvaluator
+from crewai.utilities.llm_utils import LLM
+
+
+class TestGoalAlignmentEvaluator(BaseEvaluationMetricsTest):
+    @patch("crewai.utilities.llm_utils.create_llm")
+    def test_evaluate_success(self, mock_create_llm, mock_agent, mock_task, execution_trace):
+        mock_llm = MagicMock(spec=LLM)
+        mock_llm.call.return_value = """
+        {
+            "score": 8.5,
+            "feedback": "The agent correctly understood the task and produced relevant output."
+        }
+        """
+        mock_create_llm.return_value = mock_llm
+
+        evaluator = GoalAlignmentEvaluator(llm=mock_llm)
+
+        result = evaluator.evaluate(
+            agent=mock_agent,
+            task=mock_task,
+            execution_trace=execution_trace,
+            final_output="This is the final output"
+        )
+
+        assert isinstance(result, EvaluationScore)
+        assert result.score == 8.5
+        assert "correctly understood the task" in result.feedback
+
+        mock_llm.call.assert_called_once()
+        prompt = mock_llm.call.call_args[0][0]
+        assert len(prompt) >= 2
+        assert "system" in prompt[0]["role"]
+        assert "user" in prompt[1]["role"]
+        assert mock_agent.role in prompt[1]["content"]
+        assert mock_task.description in prompt[1]["content"]
+
+    @patch("crewai.utilities.llm_utils.create_llm")
+    def test_evaluate_error_handling(self, mock_create_llm, mock_agent, mock_task, execution_trace):
+        mock_llm = MagicMock(spec=LLM)
+        mock_llm.call.return_value = "Invalid JSON response"
+        mock_create_llm.return_value = mock_llm
+
+        evaluator = GoalAlignmentEvaluator(llm=mock_llm)
+
+        result = evaluator.evaluate(
+            agent=mock_agent,
+            task=mock_task,
+            execution_trace=execution_trace,
+            final_output="This is the final output"
+        )
+
+        assert isinstance(result, EvaluationScore)
+        assert result.score is None
+        assert "Failed to parse" in result.feedback