feat: use json schema for tool argument serialization

- Replace Python representation with JsonSchema for tool arguments
  - Remove deprecated PydanticSchemaParser in favor of direct schema generation
  - Add handling for VAR_POSITIONAL and VAR_KEYWORD parameters
  - Improve tool argument schema collection

lib/crewai/tests/utilities/evaluators/test_task_evaluator.py

@@ -1,4 +1,3 @@
-from unittest import mock
 from unittest.mock import MagicMock, patch
 
 from crewai.utilities.converter import ConverterError
@@ -44,26 +43,26 @@ def test_evaluate_training_data(converter_mock):
     )
 
     assert result == function_return_value
-    converter_mock.assert_has_calls(
-        [
-            mock.call(
-                llm=original_agent.llm,
-                text="Assess the quality of the training data based on the llm output, human feedback , and llm "
-                "output improved result.\n\nIteration: data1\nInitial Output:\nInitial output 1\n\nHuman Feedback:\nHuman feedback "
-                "1\n\nImproved Output:\nImproved output 1\n\n------------------------------------------------\n\nIteration: data2\nInitial Output:\nInitial output 2\n\nHuman "
-                "Feedback:\nHuman feedback 2\n\nImproved Output:\nImproved output 2\n\n------------------------------------------------\n\nPlease provide:\n- Provide "
-                "a list of clear, actionable instructions derived from the Human Feedbacks to enhance the Agent's "
-                "performance. Analyze the differences between Initial Outputs and Improved Outputs to generate specific "
-                "action items for future tasks. Ensure all key and specificpoints from the human feedback are "
-                "incorporated into these instructions.\n- A score from 0 to 10 evaluating on completion, quality, and "
-                "overall performance from the improved output to the initial output based on the human feedback\n",
-                model=TrainingTaskEvaluation,
-                instructions="I'm gonna convert this raw text into valid JSON.\n\nThe json should have the "
-                "following structure, with the following keys:\n{\n    suggestions: List[str],\n    quality: float,\n    final_summary: str\n}",
-            ),
-            mock.call().to_pydantic(),
-        ]
-    )
+
+    # Verify the converter was called with correct arguments
+    converter_mock.assert_called_once()
+    call_kwargs = converter_mock.call_args.kwargs
+
+    assert call_kwargs["llm"] == original_agent.llm
+    assert call_kwargs["model"] == TrainingTaskEvaluation
+    assert "Iteration: data1" in call_kwargs["text"]
+    assert "Iteration: data2" in call_kwargs["text"]
+
+    instructions = call_kwargs["instructions"]
+    assert "I'm gonna convert this raw text into valid JSON." in instructions
+    assert "OpenAPI schema" in instructions
+    assert '"type": "json_schema"' in instructions
+    assert '"name": "TrainingTaskEvaluation"' in instructions
+    assert '"suggestions"' in instructions
+    assert '"quality"' in instructions
+    assert '"final_summary"' in instructions
+
+    converter_mock.return_value.to_pydantic.assert_called_once()
 
 
 @patch("crewai.utilities.converter.Converter.to_pydantic")