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crewAI/tests/task_test.py
2024-02-22 15:16:17 -03:00

350 lines
12 KiB
Python

"""Test Agent creation and execution basic functionality."""
from unittest.mock import MagicMock, patch
import pytest
from pydantic import BaseModel
from pydantic_core import ValidationError
from crewai import Agent, Crew, Task
def test_task_tool_reflect_agent_tools():
from langchain.tools import tool
@tool
def fake_tool() -> None:
"Fake tool"
researcher = 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.",
tools=[fake_tool],
allow_delegation=False,
)
task = Task(
description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
agent=researcher,
)
assert task.tools == [fake_tool]
def test_task_tool_takes_precedence_over_agent_tools():
from langchain.tools import tool
@tool
def fake_tool() -> None:
"Fake tool"
@tool
def fake_task_tool() -> None:
"Fake tool"
researcher = 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.",
tools=[fake_tool],
allow_delegation=False,
)
task = Task(
description="Give me a list of 5 interesting ideas to explore for an article, what makes them unique and interesting.",
agent=researcher,
tools=[fake_task_tool],
)
assert task.tools == [fake_task_tool]
def test_task_prompt_includes_expected_output():
researcher = 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,
)
task = Task(
description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
expected_output="Bullet point list of 5 interesting ideas.",
agent=researcher,
)
with patch.object(Agent, "execute_task") as execute:
execute.return_value = "ok"
task.execute()
execute.assert_called_once_with(task=task, context=None, tools=[])
def test_task_callback():
researcher = 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,
)
task_completed = MagicMock(return_value="done")
task = Task(
description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
expected_output="Bullet point list of 5 interesting ideas.",
agent=researcher,
callback=task_completed,
)
with patch.object(Agent, "execute_task") as execute:
execute.return_value = "ok"
task.execute()
task_completed.assert_called_once_with(task.output)
def test_execute_with_agent():
researcher = 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,
)
task = Task(
description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
expected_output="Bullet point list of 5 interesting ideas.",
)
with patch.object(Agent, "execute_task", return_value="ok") as execute:
task.execute(agent=researcher)
execute.assert_called_once_with(task=task, context=None, tools=[])
def test_async_execution():
researcher = 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,
)
task = Task(
description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
expected_output="Bullet point list of 5 interesting ideas.",
async_execution=True,
agent=researcher,
)
with patch.object(Agent, "execute_task", return_value="ok") as execute:
task.execute(agent=researcher)
execute.assert_called_once_with(task=task, context=None, tools=[])
def test_multiple_output_type_error():
class Output(BaseModel):
field: str
with pytest.raises(ValidationError):
Task(
description="Give me a list of 5 interesting ideas to explore for na article, what makes them unique and interesting.",
expected_output="Bullet point list of 5 interesting ideas.",
output_json=Output,
output_pydantic=Output,
)
@pytest.mark.vcr(filter_headers=["authorization"])
def test_output_pydantic():
class ScoreOutput(BaseModel):
score: int
scorer = Agent(
role="Scorer",
goal="Score the title",
backstory="You're an expert scorer, specialized in scoring titles.",
allow_delegation=False,
)
task = Task(
description="Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work'",
expected_output="The score of the title.",
output_pydantic=ScoreOutput,
agent=scorer,
)
crew = Crew(agents=[scorer], tasks=[task])
result = crew.kickoff()
assert isinstance(result, ScoreOutput)
@pytest.mark.vcr(filter_headers=["authorization"])
def test_output_json():
class ScoreOutput(BaseModel):
score: int
scorer = Agent(
role="Scorer",
goal="Score the title",
backstory="You're an expert scorer, specialized in scoring titles.",
allow_delegation=False,
)
task = Task(
description="Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work'",
expected_output="The score of the title.",
output_json=ScoreOutput,
agent=scorer,
)
crew = Crew(agents=[scorer], tasks=[task])
result = crew.kickoff()
assert '{\n "score": 4\n}' == result
@pytest.mark.vcr(filter_headers=["authorization"])
def test_output_pydantic_to_another_task():
from langchain_openai import ChatOpenAI
class ScoreOutput(BaseModel):
score: int
scorer = Agent(
role="Scorer",
goal="Score the title",
backstory="You're an expert scorer, specialized in scoring titles.",
allow_delegation=False,
llm=ChatOpenAI(model="gpt-4-0125-preview"),
function_calling_llm=ChatOpenAI(model="gpt-3.5-turbo-0125"),
verbose=True,
)
task1 = Task(
description="Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work'",
expected_output="The score of the title.",
output_pydantic=ScoreOutput,
agent=scorer,
)
task2 = Task(
description="Given the score the title 'The impact of AI in the future of work' got, give me an integer score between 1-5 for the following title: 'Return of the Jedi', you MUST give it a score, use your best judgment",
expected_output="The score of the title.",
output_pydantic=ScoreOutput,
agent=scorer,
)
crew = Crew(agents=[scorer], tasks=[task1, task2], verbose=2)
result = crew.kickoff()
assert 5 == result.score
@pytest.mark.vcr(filter_headers=["authorization"])
def test_output_json_to_another_task():
class ScoreOutput(BaseModel):
score: int
scorer = Agent(
role="Scorer",
goal="Score the title",
backstory="You're an expert scorer, specialized in scoring titles.",
allow_delegation=False,
)
task1 = Task(
description="Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work'",
expected_output="The score of the title.",
output_json=ScoreOutput,
agent=scorer,
)
task2 = Task(
description="Given the score the title 'The impact of AI in the future of work' got, give me an integer score between 1-5 for the following title: 'Return of the Jedi'",
expected_output="The score of the title.",
output_json=ScoreOutput,
agent=scorer,
)
crew = Crew(agents=[scorer], tasks=[task1, task2])
result = crew.kickoff()
assert '{\n "score": 5\n}' == result
@pytest.mark.vcr(filter_headers=["authorization"])
def test_save_task_output():
scorer = Agent(
role="Scorer",
goal="Score the title",
backstory="You're an expert scorer, specialized in scoring titles.",
allow_delegation=False,
)
task = Task(
description="Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work'",
expected_output="The score of the title.",
output_file="score.json",
agent=scorer,
)
crew = Crew(agents=[scorer], tasks=[task])
with patch.object(Task, "_save_file") as save_file:
save_file.return_value = None
crew.kickoff()
save_file.assert_called_once()
@pytest.mark.vcr(filter_headers=["authorization"])
def test_save_task_json_output():
class ScoreOutput(BaseModel):
score: int
scorer = Agent(
role="Scorer",
goal="Score the title",
backstory="You're an expert scorer, specialized in scoring titles.",
allow_delegation=False,
)
task = Task(
description="Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work'",
expected_output="The score of the title.",
output_file="score.json",
output_json=ScoreOutput,
agent=scorer,
)
crew = Crew(agents=[scorer], tasks=[task])
with patch.object(Task, "_save_file") as save_file:
save_file.return_value = None
crew.kickoff()
save_file.assert_called_once_with('{\n "score": 4\n}')
@pytest.mark.vcr(filter_headers=["authorization"])
def test_save_task_pydantic_output():
class ScoreOutput(BaseModel):
score: int
scorer = Agent(
role="Scorer",
goal="Score the title",
backstory="You're an expert scorer, specialized in scoring titles.",
allow_delegation=False,
)
task = Task(
description="Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work'",
expected_output="The score of the title.",
output_file="score.json",
output_pydantic=ScoreOutput,
agent=scorer,
)
crew = Crew(agents=[scorer], tasks=[task])
with patch.object(Task, "_save_file") as save_file:
save_file.return_value = None
crew.kickoff()
save_file.assert_called_once_with('{"score":4}')