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Merge branch 'bugfix/kickoff-for-each-usage-metrics' into feature/kickoff-consistent-output

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Brandon Hancock
2024-07-01 18:27:05 -04:00
parent 5775ed3fcb 0bfa549477
commit 053d8a0449
57 changed files with 414522 additions and 6456 deletions
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54
tests/agent_test.py
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@@ -1,5 +1,6 @@
"""Test Agent creation and execution basic functionality."""
from unittest import mock
from unittest.mock import patch
import pytest
@@ -732,7 +733,7 @@ def test_agent_llm_uses_token_calc_handler_with_llm_has_model_name():
assert len(agent1.llm.callbacks) == 1
assert agent1.llm.callbacks[0].__class__.__name__ == "TokenCalcHandler"
assert agent1.llm.callbacks[0].model == "gpt-4o"
assert agent1.llm.callbacks[0].model_name == "gpt-4o"
assert (
agent1.llm.callbacks[0].token_cost_process.__class__.__name__ == "TokenProcess"
)
@@ -842,3 +843,54 @@ Thought:
"""
)
@patch("crewai.agent.CrewTrainingHandler")
def test_agent_training_handler(crew_training_handler):
task_prompt = "What is 1 + 1?"
agent = Agent(
role="test role",
goal="test goal",
backstory="test backstory",
verbose=True,
)
crew_training_handler().load.return_value = {
f"{str(agent.id)}": {"0": {"human_feedback": "good"}}
}
result = agent._training_handler(task_prompt=task_prompt)
assert result == "What is 1 + 1?You MUST follow these feedbacks: \n good"
crew_training_handler.assert_has_calls(
[mock.call(), mock.call("training_data.pkl"), mock.call().load()]
)
@patch("crewai.agent.CrewTrainingHandler")
def test_agent_use_trained_data(crew_training_handler):
task_prompt = "What is 1 + 1?"
agent = Agent(
role="researcher",
goal="test goal",
backstory="test backstory",
verbose=True,
)
crew_training_handler().load.return_value = {
agent.role: {
"suggestions": [
"The result of the math operatio must be right.",
"Result must be better than 1.",
]
}
}
result = agent._use_trained_data(task_prompt=task_prompt)
assert (
result == "What is 1 + 1?You MUST follow these feedbacks: \n "
"The result of the math operatio must be right.\n - Result must be better than 1."
)
crew_training_handler.assert_has_calls(
[mock.call(), mock.call("trained_agents_data.pkl"), mock.call().load()]
)

790
tests/cassettes/test_agent_without_max_rpm_respet_crew_rpm.yaml
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1885
tests/cassettes/test_code_execution_flag_adds_code_tool_upon_kickoff.yaml Normal file
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585
tests/cassettes/test_crew_async_kickoff_for_each_full_ouput.yaml Normal file
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@@ -0,0 +1,585 @@
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400750
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tests/cassettes/test_increment_delegations_for_hierarchical_process.yaml
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493
tests/crew_test.py
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@@ -2,6 +2,8 @@
import json
from concurrent.futures import Future
from unittest import mock
from unittest.mock import patch
import pydantic_core
import pytest
@@ -409,6 +411,43 @@ def test_api_calls_throttling(capsys):
moveon.assert_called()
@pytest.mark.vcr(filter_headers=["authorization"])
def test_crew_full_ouput():
agent = Agent(
role="test role",
goal="test goal",
backstory="test backstory",
allow_delegation=False,
verbose=True,
)
task1 = Task(
description="just say hi!",
expected_output="your greeting",
agent=agent,
)
task2 = Task(
description="just say hello!",
expected_output="your greeting",
agent=agent,
)
crew = Crew(agents=[agent], tasks=[task1, task2], full_output=True)
result = crew.kickoff()
assert result == {
"final_output": "Hello!",
"tasks_outputs": [task1.output, task2.output],
"usage_metrics": {
"total_tokens": 517,
"prompt_tokens": 466,
"completion_tokens": 51,
"successful_requests": 3,
},
}
def test_agents_rpm_is_never_set_if_crew_max_RPM_is_not_set():
agent = Agent(
role="test role",
@@ -585,40 +624,85 @@ def test_three_task_with_async_execution():
assert result.raw_output().count("\n\n----------\n\n") == 2
def test_wait_for_async_execution_before_sync_execution():
researcher_agent = Agent(
role="Researcher",
goal="Make the best research and analysis on content about AI and AI agents",
backstory="You're an expert researcher, specialized in technology, software engineering, AI and startups. You work as a freelancer and is now working on doing research and analysis for a new customer.",
allow_delegation=False,
@pytest.mark.vcr(filter_headers=["authorization"])
def test_crew_kickoff_for_each_full_ouput():
inputs = [
{"topic": "dog"},
{"topic": "cat"},
{"topic": "apple"},
]
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
)
writer_agent = Agent(
role="Writer",
goal="Write the best content about AI and AI agents.",
backstory="You're a writer, specialized in technology, software engineering, AI and startups. You work as a freelancer and are now working on writing content for a new customer.",
allow_delegation=False,
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
bullet_list = Task(
description="Generate a list of 5 interesting ideas to explore for an article, where each bulletpoint is under 15 words.",
expected_output="Bullet point list of 5 important events. No additional commentary.",
agent=researcher_agent,
async_execution=True,
)
article_writer = Task(
description="Convert a bulleted list into a 1 paragraph article.",
expected_output="A paragraph article with 5 sentences.",
agent=writer_agent,
async_execution=False,
crew = Crew(agents=[agent], tasks=[task], full_output=True)
results = crew.kickoff_for_each(inputs=inputs)
assert len(results) == len(inputs)
for result in results:
assert "usage_metrics" in result
assert isinstance(result["usage_metrics"], dict)
# Assert that all required keys are in usage_metrics and their values are not None
for key in [
"total_tokens",
"prompt_tokens",
"completion_tokens",
"successful_requests",
]:
assert key in result["usage_metrics"]
assert result["usage_metrics"][key] > 0
@pytest.mark.vcr(filter_headers=["authorization"])
@pytest.mark.asyncio
async def test_crew_async_kickoff_for_each_full_ouput():
inputs = [
{"topic": "dog"},
{"topic": "cat"},
{"topic": "apple"},
]
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
)
crew = Crew(
agents=[researcher_agent, writer_agent],
process=Process.sequential,
tasks=[bullet_list, article_writer],
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
crew = Crew(agents=[agent], tasks=[task], full_output=True)
results = await crew.kickoff_for_each_async(inputs=inputs)
assert len(results) == len(inputs)
for result in results:
assert "usage_metrics" in result
assert isinstance(result["usage_metrics"], dict)
# Assert that all required keys are in usage_metrics and their values are not None
for key in [
"total_tokens",
"prompt_tokens",
"completion_tokens",
"successful_requests",
]:
assert key in result["usage_metrics"]
# TODO: FIX THIS WHEN USAGE METRICS ARE RE-DONE
# assert result["usage_metrics"][key] > 0
@pytest.mark.vcr(filter_headers=["authorization"])
def test_async_task_execution_call_count():
@@ -674,6 +758,262 @@ def test_async_task_execution_call_count():
assert mock_execute_sync.call_count == 1
@pytest.mark.vcr(filter_headers=["authorization"])
def test_kickoff_for_each_single_input():
"""Tests if kickoff_for_each works with a single input."""
from unittest.mock import patch
inputs = [{"topic": "dog"}]
expected_outputs = ["Dogs are loyal companions and popular pets."]
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
)
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
with patch.object(Agent, "execute_task") as mock_execute_task:
mock_execute_task.side_effect = expected_outputs
crew = Crew(agents=[agent], tasks=[task])
results = crew.kickoff_for_each(inputs=inputs)
assert len(results) == 1
assert results == expected_outputs
@pytest.mark.vcr(filter_headers=["authorization"])
def test_kickoff_for_each_multiple_inputs():
"""Tests if kickoff_for_each works with multiple inputs."""
from unittest.mock import patch
inputs = [
{"topic": "dog"},
{"topic": "cat"},
{"topic": "apple"},
]
expected_outputs = [
"Dogs are loyal companions and popular pets.",
"Cats are independent and low-maintenance pets.",
"Apples are a rich source of dietary fiber and vitamin C.",
]
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
)
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
with patch.object(Agent, "execute_task") as mock_execute_task:
mock_execute_task.side_effect = expected_outputs
crew = Crew(agents=[agent], tasks=[task])
results = crew.kickoff_for_each(inputs=inputs)
assert len(results) == len(inputs)
for i, res in enumerate(results):
assert res == expected_outputs[i]
@pytest.mark.vcr(filter_headers=["authorization"])
def test_kickoff_for_each_empty_input():
"""Tests if kickoff_for_each handles an empty input list."""
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
)
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
crew = Crew(agents=[agent], tasks=[task])
results = crew.kickoff_for_each(inputs=[])
assert results == []
@pytest.mark.vcr(filter_headers=["authorization"])
def test_kickoff_for_each_invalid_input():
"""Tests if kickoff_for_each raises TypeError for invalid input types."""
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
)
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
crew = Crew(agents=[agent], tasks=[task])
with pytest.raises(TypeError):
# Pass a string instead of a list
crew.kickoff_for_each("invalid input")
@pytest.mark.vcr(filter_headers=["authorization"])
def test_kickoff_for_each_error_handling():
"""Tests error handling in kickoff_for_each when kickoff raises an error."""
from unittest.mock import patch
inputs = [
{"topic": "dog"},
{"topic": "cat"},
{"topic": "apple"},
]
expected_outputs = [
"Dogs are loyal companions and popular pets.",
"Cats are independent and low-maintenance pets.",
"Apples are a rich source of dietary fiber and vitamin C.",
]
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
)
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
crew = Crew(agents=[agent], tasks=[task])
with patch.object(Crew, "kickoff") as mock_kickoff:
mock_kickoff.side_effect = expected_outputs[:2] + [
Exception("Simulated kickoff error")
]
with pytest.raises(Exception, match="Simulated kickoff error"):
crew.kickoff_for_each(inputs=inputs)
@pytest.mark.vcr(filter_headers=["authorization"])
@pytest.mark.asyncio
async def test_kickoff_async_basic_functionality_and_output():
"""Tests the basic functionality and output of kickoff_async."""
from unittest.mock import patch
inputs = {"topic": "dog"}
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
)
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
# Create the crew
crew = Crew(
agents=[agent],
tasks=[task],
)
expected_output = "This is a sample output from kickoff."
with patch.object(Crew, "kickoff", return_value=expected_output) as mock_kickoff:
result = await crew.kickoff_async(inputs)
assert isinstance(result, str), "Result should be a string"
assert result == expected_output, "Result should match expected output"
mock_kickoff.assert_called_once_with(inputs)
@pytest.mark.vcr(filter_headers=["authorization"])
@pytest.mark.asyncio
async def test_async_kickoff_for_each_async_basic_functionality_and_output():
"""Tests the basic functionality and output of akickoff_for_each_async."""
from unittest.mock import patch
inputs = [
{"topic": "dog"},
{"topic": "cat"},
{"topic": "apple"},
]
# Define expected outputs for each input
expected_outputs = [
"Dogs are loyal companions and popular pets.",
"Cats are independent and low-maintenance pets.",
"Apples are a rich source of dietary fiber and vitamin C.",
]
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
)
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
with patch.object(
Crew, "kickoff_async", side_effect=expected_outputs
) as mock_kickoff_async:
crew = Crew(agents=[agent], tasks=[task])
results = await crew.kickoff_for_each_async(inputs)
assert len(results) == len(inputs)
assert results == expected_outputs
for input_data in inputs:
mock_kickoff_async.assert_any_call(inputs=input_data)
@pytest.mark.vcr(filter_headers=["authorization"])
@pytest.mark.asyncio
async def test_async_kickoff_for_each_async_empty_input():
"""Tests if akickoff_for_each_async handles an empty input list."""
agent = Agent(
role="{topic} Researcher",
goal="Express hot takes on {topic}.",
backstory="You have a lot of experience with {topic}.",
)
task = Task(
description="Give me an analysis around {topic}.",
expected_output="1 bullet point about {topic} that's under 15 words.",
agent=agent,
)
# Create the crew
crew = Crew(
agents=[agent],
tasks=[task],
)
# Call the function we are testing
results = await crew.kickoff_for_each_async([])
# Assertion
assert results == [], "Result should be an empty list when input is empty"
def test_set_agents_step_callback():
from unittest.mock import patch
@@ -806,6 +1146,30 @@ def test_task_with_no_arguments():
assert result.raw_output() == "75"
def test_code_execution_flag_adds_code_tool_upon_kickoff():
from crewai_tools import CodeInterpreterTool
programmer = Agent(
role="Programmer",
goal="Write code to solve problems.",
backstory="You're a programmer who loves to solve problems with code.",
allow_delegation=False,
allow_code_execution=True,
)
task = Task(
description="How much is 2 + 2?",
expected_output="The result of the sum as an integer.",
agent=programmer,
)
crew = Crew(agents=[programmer], tasks=[task])
crew.kickoff()
assert len(programmer.tools) == 1
assert programmer.tools[0].__class__ == CodeInterpreterTool
@pytest.mark.vcr(filter_headers=["authorization"])
def test_delegation_is_not_enabled_if_there_are_only_one_agent():
from unittest.mock import patch
@@ -893,7 +1257,7 @@ def test_agent_usage_metrics_are_captured_for_hierarchical_process():
agents=[agent],
tasks=[task],
process=Process.hierarchical,
manager_llm=ChatOpenAI(temperature=0, model="gpt-4"),
manager_llm=ChatOpenAI(temperature=0, model="gpt-4o"),
)
result = crew.kickoff()
@@ -1308,7 +1672,10 @@ def test_manager_agent_with_tools_raises_exception():
crew.kickoff()
def test_crew_train_success():
@patch("crewai.crew.Crew.kickoff")
@patch("crewai.crew.CrewTrainingHandler")
@patch("crewai.crew.TaskEvaluator")
def test_crew_train_success(task_evaluator, crew_training_handler, kickoff):
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.",
@@ -1318,8 +1685,48 @@ def test_crew_train_success():
agents=[researcher, writer],
tasks=[task],
)
crew.train(n_iterations=2, inputs={"topic": "AI"})
task_evaluator.assert_has_calls(
[
mock.call(researcher),
mock.call().evaluate_training_data(
training_data=crew_training_handler().load(),
agent_id=str(researcher.id),
),
mock.call().evaluate_training_data().model_dump(),
mock.call(writer),
mock.call().evaluate_training_data(
training_data=crew_training_handler().load(),
agent_id=str(writer.id),
),
mock.call().evaluate_training_data().model_dump(),
]
)
crew.train(n_iterations=2)
crew_training_handler.assert_has_calls(
[
mock.call("training_data.pkl"),
mock.call().load(),
mock.call("trained_agents_data.pkl"),
mock.call().save_trained_data(
agent_id="Researcher",
trained_data=task_evaluator().evaluate_training_data().model_dump(),
),
mock.call("trained_agents_data.pkl"),
mock.call().save_trained_data(
agent_id="Senior Writer",
trained_data=task_evaluator().evaluate_training_data().model_dump(),
),
mock.call(),
mock.call().load(),
mock.call(),
mock.call().load(),
]
)
kickoff.assert_has_calls(
[mock.call(inputs={"topic": "AI"}), mock.call(inputs={"topic": "AI"})]
)
def test_crew_train_error():
@@ -1340,4 +1747,30 @@ def test_crew_train_error():
)
# TODO: Test delegation in heirarchical process
def test__setup_for_training():
researcher.allow_delegation = True
writer.allow_delegation = True
agents = [researcher, writer]
task = Task(
description="Come up with a list of 5 interesting ideas to explore for an article",
expected_output="5 bullet points with a paragraph for each idea.",
)
crew = Crew(
agents=agents,
tasks=[task],
)
assert crew._train is False
assert task.human_input is False
for agent in agents:
assert agent.allow_delegation is True
crew._setup_for_training()
assert crew._train is True
assert task.human_input is True
for agent in agents:
assert agent.allow_delegation is False

64
tests/utilities/evaluators/test_task_evaluator.py Normal file
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@@ -0,0 +1,64 @@
from unittest import mock
from unittest.mock import MagicMock, patch
from crewai.utilities.evaluators.task_evaluator import (
TaskEvaluator,
TrainingTaskEvaluation,
)
@patch("crewai.utilities.evaluators.task_evaluator.Converter")
def test_evaluate_training_data(converter_mock):
training_data = {
"agent_id": {
"data1": {
"initial_output": "Initial output 1",
"human_feedback": "Human feedback 1",
"improved_output": "Improved output 1",
},
"data2": {
"initial_output": "Initial output 2",
"human_feedback": "Human feedback 2",
"improved_output": "Improved output 2",
},
}
}
agent_id = "agent_id"
original_agent = MagicMock()
function_return_value = TrainingTaskEvaluation(
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."
],
quality=8.0,
final_summary="The agent responded well initially. However, the improved output showed that there is room "
"for enhancement in terms of language usage, precision, and professionalism. For future tasks, the agent "
"should focus more on these points from the start to increase performance.",
)
converter_mock.return_value.to_pydantic.return_value = function_return_value
result = TaskEvaluator(original_agent=original_agent).evaluate_training_data(
training_data, agent_id
)
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\nInitial Output:\nInitial output 1\n\nHuman Feedback:\nHuman feedback "
"1\n\nImproved Output:\nImproved output 1\n\nInitial Output:\nInitial output 2\n\nHuman "
"Feedback:\nHuman feedback 2\n\nImproved Output:\nImproved output 2\n\nPlease provide:\n- "
"Based on the Human Feedbacks and the comparison between Initial Outputs and Improved outputs "
"provide action items based on human_feedback for future tasks\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- suggestions: List[str]\n- "
"quality: float\n- final_summary: str",
),
mock.call().to_pydantic(),
]
)

41
tests/utilities/test_file_handler.py Normal file
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@@ -0,0 +1,41 @@
import os
import unittest
import pytest
from crewai.utilities.file_handler import PickleHandler
class TestPickleHandler(unittest.TestCase):
def setUp(self):
self.file_name = "test_data.pkl"
self.file_path = os.path.join(os.getcwd(), self.file_name)
self.handler = PickleHandler(self.file_name)
def tearDown(self):
if os.path.exists(self.file_path):
os.remove(self.file_path)
def test_initialize_file(self):
assert os.path.exists(self.file_path) is True
assert os.path.getsize(self.file_path) >= 0
def test_save_and_load(self):
data = {"key": "value"}
self.handler.save(data)
loaded_data = self.handler.load()
assert loaded_data == data
def test_load_empty_file(self):
loaded_data = self.handler.load()
assert loaded_data == {}
def test_load_corrupted_file(self):
with open(self.file_path, "wb") as file:
file.write(b"corrupted data")
with pytest.raises(Exception) as exc:
self.handler.load()
assert str(exc.value) == "pickle data was truncated"
assert "<class '_pickle.UnpicklingError'>" == str(exc.type)

42
tests/utilities/test_training_handler.py Normal file
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@@ -0,0 +1,42 @@
import os
import unittest
from crewai.utilities.training_handler import CrewTrainingHandler
class TestCrewTrainingHandler(unittest.TestCase):
def setUp(self):
self.handler = CrewTrainingHandler("trained_data.pkl")
def tearDown(self):
os.remove("trained_data.pkl")
del self.handler
def test_save_trained_data(self):
agent_id = "agent1"
trained_data = {"param1": 1, "param2": 2}
self.handler.save_trained_data(agent_id, trained_data)
# Assert that the trained data is saved correctly
data = self.handler.load()
assert data[agent_id] == trained_data
def test_append_existing_agent(self):
train_iteration = 1
agent_id = "agent1"
new_data = {"param3": 3, "param4": 4}
self.handler.append(train_iteration, agent_id, new_data)
# Assert that the new data is appended correctly to the existing agent
data = self.handler.load()
assert data[agent_id][train_iteration] == new_data
def test_append_new_agent(self):
train_iteration = 1
agent_id = "agent2"
new_data = {"param5": 5, "param6": 6}
self.handler.append(train_iteration, agent_id, new_data)
# Assert that the new agent and data are appended correctly
data = self.handler.load()
assert data[agent_id][train_iteration] == new_data