mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-01-09 16:18:30 +00:00
2607f5361c
- Renamed TestEvent to SampleEvent in test_crewai_event_bus.py - Renamed TestModel to SampleModel in test_training_converter.py
98 lines
3.8 KiB
Python
98 lines
3.8 KiB
Python
from unittest.mock import MagicMock, patch
|
|
|
|
from pydantic import BaseModel, Field
|
|
from typing import List
|
|
|
|
from crewai.utilities.converter import ConverterError
|
|
from crewai.utilities.training_converter import TrainingConverter
|
|
|
|
|
|
class SampleModel(BaseModel):
|
|
string_field: str = Field(description="A simple string field")
|
|
list_field: List[str] = Field(description="A list of strings")
|
|
number_field: float = Field(description="A number field")
|
|
|
|
|
|
class TestTrainingConverter:
|
|
|
|
def setup_method(self):
|
|
self.llm_mock = MagicMock()
|
|
self.test_text = "Sample text for evaluation"
|
|
self.test_instructions = "Convert to JSON format"
|
|
self.converter = TrainingConverter(
|
|
llm=self.llm_mock,
|
|
text=self.test_text,
|
|
model=SampleModel,
|
|
instructions=self.test_instructions
|
|
)
|
|
|
|
@patch("crewai.utilities.converter.Converter.to_pydantic")
|
|
def test_fallback_to_field_by_field(self, parent_to_pydantic_mock):
|
|
parent_to_pydantic_mock.side_effect = ConverterError("Failed to convert directly")
|
|
|
|
llm_responses = {
|
|
"string_field": "test string value",
|
|
"list_field": "- item1\n- item2\n- item3",
|
|
"number_field": "8.5"
|
|
}
|
|
|
|
def llm_side_effect(messages):
|
|
prompt = messages[1]["content"]
|
|
if "string_field" in prompt:
|
|
return llm_responses["string_field"]
|
|
elif "list_field" in prompt:
|
|
return llm_responses["list_field"]
|
|
elif "number_field" in prompt:
|
|
return llm_responses["number_field"]
|
|
return "unknown field"
|
|
|
|
self.llm_mock.call.side_effect = llm_side_effect
|
|
|
|
result = self.converter.to_pydantic()
|
|
|
|
assert result.string_field == "test string value"
|
|
assert result.list_field == ["item1", "item2", "item3"]
|
|
assert result.number_field == 8.5
|
|
|
|
parent_to_pydantic_mock.assert_called_once()
|
|
assert self.llm_mock.call.call_count == 3
|
|
|
|
def test_ask_llm_for_field(self):
|
|
field_name = "test_field"
|
|
field_description = "This is a test field description"
|
|
expected_response = "Test response"
|
|
self.llm_mock.call.return_value = expected_response
|
|
response = self.converter._ask_llm_for_field(field_name, field_description)
|
|
|
|
assert response == expected_response
|
|
self.llm_mock.call.assert_called_once()
|
|
|
|
call_args = self.llm_mock.call.call_args[0][0]
|
|
assert call_args[0]["role"] == "system"
|
|
assert f"Extract the {field_name}" in call_args[0]["content"]
|
|
assert call_args[1]["role"] == "user"
|
|
assert field_name in call_args[1]["content"]
|
|
assert field_description in call_args[1]["content"]
|
|
|
|
def test_process_field_value_string(self):
|
|
response = " This is a string with extra whitespace "
|
|
result = self.converter._process_field_value(response, str)
|
|
assert result == "This is a string with extra whitespace"
|
|
|
|
def test_process_field_value_list_with_bullet_points(self):
|
|
response = "- Item 1\n- Item 2\n- Item 3"
|
|
result = self.converter._process_field_value(response, List[str])
|
|
assert result == ["Item 1", "Item 2", "Item 3"]
|
|
|
|
def test_process_field_value_list_with_json(self):
|
|
response = '["Item 1", "Item 2", "Item 3"]'
|
|
with patch("crewai.utilities.training_converter.json.loads") as json_mock:
|
|
json_mock.return_value = ["Item 1", "Item 2", "Item 3"]
|
|
result = self.converter._process_field_value(response, List[str])
|
|
assert result == ["Item 1", "Item 2", "Item 3"]
|
|
|
|
def test_process_field_value_float(self):
|
|
response = "The quality score is 8.5 out of 10"
|
|
result = self.converter._process_field_value(response, float)
|
|
assert result == 8.5
|