feat: restructure project as UV workspace with crewai in lib/

tests/experimental/evaluation/metrics/test_semantic_quality_metrics.py

@@ -1,93 +0,0 @@
-from unittest.mock import patch, MagicMock
-
-from crewai.experimental.evaluation.base_evaluator import EvaluationScore
-from crewai.experimental.evaluation.metrics.semantic_quality_metrics import (
-    SemanticQualityEvaluator,
-)
-from tests.experimental.evaluation.metrics.test_base_evaluation_metrics import (
-    BaseEvaluationMetricsTest,
-)
-from crewai.utilities.llm_utils import LLM
-
-
-class TestSemanticQualityEvaluator(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 output is clear, coherent, and logically structured."
-        }
-        """
-        mock_create_llm.return_value = mock_llm
-
-        evaluator = SemanticQualityEvaluator(llm=mock_llm)
-
-        result = evaluator.evaluate(
-            agent=mock_agent,
-            task=mock_task,
-            execution_trace=execution_trace,
-            final_output="This is a well-structured analysis of the data.",
-        )
-
-        assert isinstance(result, EvaluationScore)
-        assert result.score == 8.5
-        assert "clear, coherent" 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_with_empty_output(
-        self, mock_create_llm, mock_agent, mock_task, execution_trace
-    ):
-        mock_llm = MagicMock(spec=LLM)
-        mock_llm.call.return_value = """
-        {
-            "score": 2.0,
-            "feedback": "The output is empty or minimal, lacking substance."
-        }
-        """
-        mock_create_llm.return_value = mock_llm
-
-        evaluator = SemanticQualityEvaluator(llm=mock_llm)
-
-        result = evaluator.evaluate(
-            agent=mock_agent,
-            task=mock_task,
-            execution_trace=execution_trace,
-            final_output="",
-        )
-
-        assert isinstance(result, EvaluationScore)
-        assert result.score == 2.0
-        assert "empty or minimal" in result.feedback
-
-    @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 = SemanticQualityEvaluator(llm=mock_llm)
-
-        result = evaluator.evaluate(
-            agent=mock_agent,
-            task=mock_task,
-            execution_trace=execution_trace,
-            final_output="This is the output.",
-        )
-
-        assert isinstance(result, EvaluationScore)
-        assert result.score is None
-        assert "Failed to parse" in result.feedback