feat: add crew Testing/Evaluating feature (#998)

* feat: add crew Testing/evalauting feature

* feat: add docs and add unit test

* feat: improve testing output table

* feat: add tests

* feat: fix type checking issue

* feat: add raise ValueError when testing if output is not the expected

* docs: add docs for Testing

* feat: improve tests and fix some issue

* feat: back to sync

* feat: change opdeai model

* feat: fix test
This commit is contained in:
Eduardo Chiarotti
2024-07-26 14:23:51 -03:00
committed by GitHub
parent 2d086ab596
commit 2d2154ed65
7 changed files with 350 additions and 4 deletions

View File

@@ -8,6 +8,7 @@ from unittest.mock import MagicMock, patch
import pydantic_core
import pytest
from crewai.agent import Agent
from crewai.agents.cache import CacheHandler
from crewai.crew import Crew
@@ -2499,3 +2500,34 @@ def test_conditional_should_execute():
assert condition_mock.call_count == 1
assert condition_mock() is True
assert mock_execute_sync.call_count == 2
@mock.patch("crewai.crew.CrewEvaluator")
@mock.patch("crewai.crew.Crew.kickoff")
def test_crew_testing_function(mock_kickoff, crew_evaluator):
task = Task(
description="Come up with a list of 5 interesting ideas to explore for an article, then write one amazing paragraph highlight for each idea that showcases how good an article about this topic could be. Return the list of ideas with their paragraph and your notes.",
expected_output="5 bullet points with a paragraph for each idea.",
agent=researcher,
)
crew = Crew(
agents=[researcher],
tasks=[task],
)
n_iterations = 2
crew.test(n_iterations, openai_model_name="gpt-4o-mini", inputs={"topic": "AI"})
assert len(mock_kickoff.mock_calls) == n_iterations
mock_kickoff.assert_has_calls(
[mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
)
crew_evaluator.assert_has_calls(
[
mock.call(crew, "gpt-4o-mini"),
mock.call().set_iteration(1),
mock.call().set_iteration(2),
mock.call().print_crew_evaluation_result(),
]
)

View File

@@ -0,0 +1,113 @@
from unittest import mock
import pytest
from crewai.agent import Agent
from crewai.crew import Crew
from crewai.task import Task
from crewai.tasks.task_output import TaskOutput
from crewai.utilities.evaluators.crew_evaluator_handler import (
CrewEvaluator,
TaskEvaluationPydanticOutput,
)
class TestCrewEvaluator:
@pytest.fixture
def crew_planner(self):
agent = Agent(role="Agent 1", goal="Goal 1", backstory="Backstory 1")
task = Task(
description="Task 1",
expected_output="Output 1",
agent=agent,
)
crew = Crew(agents=[agent], tasks=[task])
return CrewEvaluator(crew, openai_model_name="gpt-4o-mini")
def test_setup_for_evaluating(self, crew_planner):
crew_planner._setup_for_evaluating()
assert crew_planner.crew.tasks[0].callback == crew_planner.evaluate
def test_set_iteration(self, crew_planner):
crew_planner.set_iteration(1)
assert crew_planner.iteration == 1
def test_evaluator_agent(self, crew_planner):
agent = crew_planner._evaluator_agent()
assert agent.role == "Task Execution Evaluator"
assert (
agent.goal
== "Your goal is to evaluate the performance of the agents in the crew based on the tasks they have performed using score from 1 to 10 evaluating on completion, quality, and overall performance."
)
assert (
agent.backstory
== "Evaluator agent for crew evaluation with precise capabilities to evaluate the performance of the agents in the crew based on the tasks they have performed"
)
assert agent.verbose is False
assert agent.llm.model_name == "gpt-4o-mini"
def test_evaluation_task(self, crew_planner):
evaluator_agent = Agent(
role="Evaluator Agent",
goal="Evaluate the performance of the agents in the crew",
backstory="Master in Evaluation",
)
task_to_evaluate = Task(
description="Task 1",
expected_output="Output 1",
agent=Agent(role="Agent 1", goal="Goal 1", backstory="Backstory 1"),
)
task_output = "Task Output 1"
task = crew_planner._evaluation_task(
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."
)
assert task.agent == evaluator_agent
assert (
task.description
== "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.task_description: Task 1 task_expected_output: Output 1 "
"agent: Agent 1 agent_goal: Goal 1 Task Output: Task Output 1"
)
@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):
crew_planner.tasks_scores = {
1: [10, 9, 8],
2: [9, 8, 7],
}
crew_planner.print_crew_evaluation_result()
table.assert_has_calls(
[
mock.call(title="Tasks Scores \n (1-10 Higher is better)"),
mock.call().add_column("Tasks/Crew"),
mock.call().add_column("Run 1"),
mock.call().add_column("Run 2"),
mock.call().add_column("Avg. Total"),
mock.call().add_row("Task 1", "10", "9", "9.5"),
mock.call().add_row("Task 2", "9", "8", "8.5"),
mock.call().add_row("Task 3", "8", "7", "7.5"),
mock.call().add_row("Crew", "9.0", "8.0", "8.5"),
]
)
console.assert_has_calls([mock.call(), mock.call().print(table())])
def test_evaluate(self, crew_planner):
task_output = TaskOutput(
description="Task 1", agent=str(crew_planner.crew.agents[0])
)
with mock.patch.object(Task, "execute_sync") as execute:
execute().pydantic = TaskEvaluationPydanticOutput(quality=9.5)
crew_planner.evaluate(task_output)
assert crew_planner.tasks_scores[0] == [9.5]