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Apply automatic linting fixes to tests directory

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Co-Authored-By: Joe Moura <joao@crewai.com>
This commit is contained in:
Devin AI
2025-05-12 13:31:07 +00:00
parent ad1ea46bbb
commit 46621113af
62 changed files with 1738 additions and 1821 deletions
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26
tests/utilities/evaluators/test_crew_evaluator_handler.py
View File

@@ -25,15 +25,15 @@ class InternalCrewEvaluator:
return CrewEvaluator(crew, openai_model_name="gpt-4o-mini")
def test_setup_for_evaluating(self, crew_planner):
def test_setup_for_evaluating(self, crew_planner) -> None:
crew_planner._setup_for_evaluating()
assert crew_planner.crew.tasks[0].callback == crew_planner.evaluate
def test_set_iteration(self, crew_planner):
def test_set_iteration(self, crew_planner) -> None:
crew_planner.set_iteration(1)
assert crew_planner.iteration == 1
def test_evaluator_agent(self, crew_planner):
def test_evaluator_agent(self, crew_planner) -> None:
agent = crew_planner._evaluator_agent()
assert agent.role == "Task Execution Evaluator"
assert (
@@ -47,7 +47,7 @@ class InternalCrewEvaluator:
assert agent.verbose is False
assert agent.llm.model == "gpt-4o-mini"
def test_evaluation_task(self, crew_planner):
def test_evaluation_task(self, crew_planner) -> None:
evaluator_agent = Agent(
role="Evaluator Agent",
goal="Evaluate the performance of the agents in the crew",
@@ -60,11 +60,11 @@ class InternalCrewEvaluator:
)
task_output = "Task Output 1"
task = crew_planner._evaluation_task(
evaluator_agent, task_to_evaluate, task_output
evaluator_agent, task_to_evaluate, task_output,
)
assert task.description.startswith(
"Based on the task description and the expected output, compare and evaluate the performance of the agents in the crew based on the Task Output they have performed using score from 1 to 10 evaluating on completion, quality, and overall performance."
"Based on the task description and the expected output, compare and evaluate the performance of the agents in the crew based on the Task Output they have performed using score from 1 to 10 evaluating on completion, quality, and overall performance.",
)
assert task.agent == evaluator_agent
@@ -79,7 +79,7 @@ class InternalCrewEvaluator:
@mock.patch("crewai.utilities.evaluators.crew_evaluator_handler.Console")
@mock.patch("crewai.utilities.evaluators.crew_evaluator_handler.Table")
def test_print_crew_evaluation_result(self, table, console, crew_planner):
def test_print_crew_evaluation_result(self, table, console, crew_planner) -> None:
# Set up task scores and execution times
crew_planner.tasks_scores = {
1: [10, 9, 8],
@@ -97,10 +97,10 @@ class InternalCrewEvaluator:
]
crew_planner.crew.tasks = [
mock.Mock(
agent=crew_planner.crew.agents[0], processed_by_agents=["Agent 1"]
agent=crew_planner.crew.agents[0], processed_by_agents=["Agent 1"],
),
mock.Mock(
agent=crew_planner.crew.agents[1], processed_by_agents=["Agent 2"]
agent=crew_planner.crew.agents[1], processed_by_agents=["Agent 2"],
),
]
@@ -111,7 +111,7 @@ class InternalCrewEvaluator:
table.assert_has_calls(
[
mock.call(
title="Tasks Scores \n (1-10 Higher is better)", box=mock.ANY
title="Tasks Scores \n (1-10 Higher is better)", box=mock.ANY,
), # Title and styling
mock.call().add_column("Tasks/Crew/Agents", style="cyan"), # Columns
mock.call().add_column("Run 1", justify="center"),
@@ -125,15 +125,15 @@ class InternalCrewEvaluator:
# Add crew averages and execution times
mock.call().add_row("Crew", "9.00", "8.00", "8.5", ""),
mock.call().add_row("Execution Time (s)", "135", "155", "145", ""),
]
],
)
# Ensure the console prints the table
console.assert_has_calls([mock.call(), mock.call().print(table())])
def test_evaluate(self, crew_planner):
def test_evaluate(self, crew_planner) -> None:
task_output = TaskOutput(
description="Task 1", agent=str(crew_planner.crew.agents[0])
description="Task 1", agent=str(crew_planner.crew.agents[0]),
)
with mock.patch.object(Task, "execute_sync") as execute:

10
tests/utilities/evaluators/test_task_evaluator.py
View File

@@ -8,7 +8,7 @@ from crewai.utilities.evaluators.task_evaluator import (
@patch("crewai.utilities.evaluators.task_evaluator.Converter")
def test_evaluate_training_data(converter_mock):
def test_evaluate_training_data(converter_mock) -> None:
training_data = {
"agent_id": {
"data1": {
@@ -21,7 +21,7 @@ def test_evaluate_training_data(converter_mock):
"human_feedback": "Human feedback 2",
"improved_output": "Improved output 2",
},
}
},
}
agent_id = "agent_id"
original_agent = MagicMock()
@@ -30,7 +30,7 @@ def test_evaluate_training_data(converter_mock):
suggestions=[
"The initial output was already good, having a detailed explanation. However, the improved output "
"gave similar information but in a more professional manner using better vocabulary. For future tasks, "
"try to implement more elaborate language and precise terminology from the beginning."
"try to implement more elaborate language and precise terminology from the beginning.",
],
quality=8.0,
final_summary="The agent responded well initially. However, the improved output showed that there is room "
@@ -39,7 +39,7 @@ def test_evaluate_training_data(converter_mock):
)
converter_mock.return_value.to_pydantic.return_value = function_return_value
result = TaskEvaluator(original_agent=original_agent).evaluate_training_data(
training_data, agent_id
training_data, agent_id,
)
assert result == function_return_value
@@ -61,5 +61,5 @@ def test_evaluate_training_data(converter_mock):
"following structure, with the following keys:\n{\n suggestions: List[str],\n quality: float,\n final_summary: str\n}",
),
mock.call().to_pydantic(),
]
],
)