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113 lines
4.5 KiB
Python
113 lines
4.5 KiB
Python
import json
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from unittest.mock import Mock, patch
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import pytest
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from pydantic import BaseModel
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from crewai.llm import LLM
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from crewai.utilities.converter import Converter, ConverterError
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class SimpleModel(BaseModel):
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name: str
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age: int
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@pytest.fixture
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def mock_llm_with_function_calling():
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"""Create a mock LLM that supports function calling."""
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llm = Mock(spec=LLM)
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llm.supports_function_calling.return_value = True
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llm.call.return_value = '{"name": "John", "age": 30}'
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return llm
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@pytest.fixture
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def mock_instructor_with_error():
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"""Create a mock Instructor that raises the specific error."""
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mock_instructor = Mock()
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mock_instructor.to_json.side_effect = Exception(
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"Instructor does not support multiple tool calls, use List[Model] instead"
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)
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return mock_instructor
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class TestCustomOpenAIJson:
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def test_custom_openai_json_conversion_with_instructor_error(self, mock_llm_with_function_calling, mock_instructor_with_error):
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"""Test that JSON conversion works with custom OpenAI backends when Instructor raises an error."""
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# Create converter with mocked dependencies
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converter = Converter(
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llm=mock_llm_with_function_calling,
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text="Convert this to JSON",
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model=SimpleModel,
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instructions="Convert to JSON",
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)
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# Mock the _create_instructor method to return our mocked instructor
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with patch.object(converter, '_create_instructor', return_value=mock_instructor_with_error):
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# Call to_json method
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result = converter.to_json()
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# Verify that the fallback mechanism was used
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mock_llm_with_function_calling.call.assert_called_once()
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# The result should be a dictionary
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assert isinstance(result, dict)
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assert result.get("name") == "John"
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assert result.get("age") == 30
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def test_custom_openai_json_conversion_without_error(self, mock_llm_with_function_calling):
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"""Test that JSON conversion works normally when Instructor doesn't raise an error."""
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# Mock Instructor that returns JSON without error
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mock_instructor = Mock()
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mock_instructor.to_json.return_value = {"name": "John", "age": 30}
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# Create converter with mocked dependencies
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converter = Converter(
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llm=mock_llm_with_function_calling,
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text="Convert this to JSON",
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model=SimpleModel,
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instructions="Convert to JSON",
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)
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# Mock the _create_instructor method to return our mocked instructor
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with patch.object(converter, '_create_instructor', return_value=mock_instructor):
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# Call to_json method
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result = converter.to_json()
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# Verify that the normal path was used (no fallback)
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mock_llm_with_function_calling.call.assert_not_called()
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# Verify the result matches the expected output
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assert isinstance(result, dict)
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assert result == {"name": "John", "age": 30}
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def test_custom_openai_json_conversion_with_invalid_json(self, mock_llm_with_function_calling):
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"""Test that JSON conversion handles invalid JSON gracefully."""
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# Mock LLM to return invalid JSON
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mock_llm_with_function_calling.call.return_value = 'invalid json'
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# Mock Instructor that raises the specific error
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mock_instructor = Mock()
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mock_instructor.to_json.side_effect = Exception(
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"Instructor does not support multiple tool calls, use List[Model] instead"
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)
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# Create converter with mocked dependencies
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converter = Converter(
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llm=mock_llm_with_function_calling,
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text="Convert this to JSON",
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model=SimpleModel,
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instructions="Convert to JSON",
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max_attempts=1, # Set max_attempts to 1 to avoid retries
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)
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# Mock the _create_instructor method to return our mocked instructor
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with patch.object(converter, '_create_instructor', return_value=mock_instructor):
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# Call to_json method and expect it to raise a ConverterError
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with pytest.raises(ConverterError) as excinfo:
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converter.to_json()
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# Check the error message
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assert "invalid json" in str(excinfo.value).lower() or "expecting value" in str(excinfo.value).lower()
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