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You are a seasoned manager + with a knack for getting the best out of your team.\nYou are also known for + your ability to delegate work to the right people, and to ask the right questions + to get the best out of your team.\nEven though you don''t perform tasks by yourself, + you have a lot of experience in the field, which allows you to properly evaluate + the work of your team members.\nYour personal goal is: Manage the team to complete + the task in the best way possible.\nYou ONLY have access to the following tools, + and should NEVER make up tools that are not listed here:\n\nDelegate work to + coworker(task: str, context: str, coworker: Optional[str] = None, **kwargs) + - Delegate a specific task to one of the following coworkers: [Scorer]\nThe + input to this tool should be the coworker, the task you want them to do, and + ALL necessary context to execute the task, they know nothing about the task, + so share absolute everything you know, don''t reference things but instead explain + them.\nAsk question to coworker(question: str, context: str, coworker: Optional[str] + = None, **kwargs) - Ask a specific question to one of the following coworkers: + [Scorer]\nThe input to this tool should be the coworker, the question you have + for them, and ALL necessary context to ask the question properly, they know + nothing about the question, so share absolute everything you know, don''t reference + things but instead explain them.\n\nUse the following format:\n\nThought: you + should always think about what to do\nAction: the action to take, only one name + of [Delegate work to coworker, Ask question to coworker], just the name, exactly + as it''s written.\nAction Input: the input to the action, just a simple python + dictionary, enclosed in curly braces, using \" to wrap keys and values.\nObservation: + the result of the action\n\nOnce all necessary information is gathered:\n\nThought: + I now know the final answer\nFinal Answer: the final answer to the original + input question\n\nCurrent Task: Give me an integer score between 1-5 for the + following title: ''The impact of AI in the future of work''\n\nThis is the expect + criteria for your final answer: The score of the title. \n you MUST return the + actual complete content as the final answer, not a summary.\n\nBegin! This is + VERY important to you, use the tools available and give your best Final Answer, + your job depends on it!\n\nThought:\n", "role": "user"}], "model": "gpt-4o", + "n": 1, "stop": ["\nObservation"], "stream": true, "temperature": 0.7}' + headers: + accept: + - application/json + accept-encoding: + - gzip, deflate + connection: + - keep-alive + content-length: + - '2534' + content-type: + - application/json + host: + - api.openai.com + user-agent: + - OpenAI/Python 1.35.10 + x-stainless-arch: + - arm64 + x-stainless-async: + - 'false' + x-stainless-lang: + - python + x-stainless-os: + - MacOS + x-stainless-package-version: + - 1.35.10 + x-stainless-runtime: + - CPython + x-stainless-runtime-version: + - 3.12.3 + method: POST + uri: https://api.openai.com/v1/chat/completions + response: + body: + string: 'data: 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21:05:36 GMT + Server: + - cloudflare + Transfer-Encoding: + - chunked + alt-svc: + - h3=":443"; ma=86400 + openai-organization: + - crewai-iuxna1 + openai-processing-ms: + - '153' + openai-version: + - '2020-10-01' + strict-transport-security: + - max-age=31536000; includeSubDomains + x-ratelimit-limit-requests: + - '10000' + x-ratelimit-limit-tokens: + - '22000000' + x-ratelimit-remaining-requests: + - '9999' + x-ratelimit-remaining-tokens: + - '21999969' + x-ratelimit-reset-requests: + - 6ms + x-ratelimit-reset-tokens: + - 0s + x-request-id: + - req_36cd16b74a2085c72139d09309d21e39 + status: + code: 200 + message: OK +version: 1 diff --git a/tests/crew_test.py b/tests/crew_test.py index 027783e79..d0ccb9801 100644 --- a/tests/crew_test.py +++ b/tests/crew_test.py @@ -7,6 +7,7 @@ from unittest.mock import patch import pydantic_core import pytest + from crewai.agent import Agent from crewai.agents.cache import CacheHandler from crewai.crew import Crew @@ -467,22 +468,6 @@ def test_agents_rpm_is_never_set_if_crew_max_RPM_is_not_set(): assert agent._rpm_controller is None -""" -Future tests: -TODO: 1 async task, 1 sync task. Make sure sync task waits for async to finish before starting.[] -TODO: 3 async tasks, 1 sync task. Make sure sync task waits for async to finish before starting. -TODO: 1 sync task, 1 async task. Make sure we wait for result from async before finishing crew. - -TODO: 3 async tasks, 1 sync task. Make sure context from all 3 async tasks is passed to sync task. -TODO: 3 async tasks, 1 sync task. Pass in context from only 1 async task to sync task. - -TODO: Test pydantic output of CrewOutput and test type in CrewOutput result -TODO: Test json output of CrewOutput and test type in CrewOutput result - -TODO: TEST THE SAME THING BUT WITH HIERARCHICAL PROCESS -""" - - @pytest.mark.vcr(filter_headers=["authorization"]) def test_sequential_async_task_execution_completion(): list_ideas = Task( @@ -1740,8 +1725,3 @@ def test__setup_for_training(): for agent in agents: assert agent.allow_delegation is False - - -# TODO: TEST EXPORT OUTPUT TASK WITH PYDANTIC -# TODO: TEST EXPORT OUTPUT TASK WITH JSON -# TODO: TEST EXPORT OUTPUT TASK CALLBACK diff --git a/tests/task_test.py b/tests/task_test.py index 34da66776..99a3df0a1 100644 --- a/tests/task_test.py +++ b/tests/task_test.py @@ -4,11 +4,12 @@ import json from unittest.mock import MagicMock, patch import pytest +from pydantic import BaseModel +from pydantic_core import ValidationError + from crewai import Agent, Crew, Process, Task from crewai.tasks.task_output import TaskOutput from crewai.utilities.converter import Converter -from pydantic import BaseModel -from pydantic_core import ValidationError def test_task_tool_reflect_agent_tools(): @@ -133,8 +134,6 @@ def test_task_callback_returns_task_ouput(): task_completed.assert_called_once() callback_data = task_completed.call_args[0][0] - print("CALLBACK DATA", callback_data) - # Check if callback_data is TaskOutput object or JSON string if isinstance(callback_data, TaskOutput): callback_data = json.dumps(callback_data.model_dump()) @@ -150,7 +149,6 @@ def test_task_callback_returns_task_ouput(): "summary": "Give me a list of 5 interesting ideas to explore...", "output_format": OutputFormat.RAW, } - print("OUTPUT DICT", output_dict) assert output_dict == expected_output @@ -206,7 +204,7 @@ def test_multiple_output_type_error(): @pytest.mark.vcr(filter_headers=["authorization"]) -def test_output_pydantic(): +def test_output_pydantic_sequential(): class ScoreOutput(BaseModel): score: int @@ -224,13 +222,46 @@ def test_output_pydantic(): agent=scorer, ) - crew = Crew(agents=[scorer], tasks=[task]) + crew = Crew(agents=[scorer], tasks=[task], process=Process.sequential) result = crew.kickoff() assert isinstance(result.pydantic, ScoreOutput) + assert result.to_dict() == {"score": 4} @pytest.mark.vcr(filter_headers=["authorization"]) -def test_output_json(): +def test_output_pydantic_hierarchical(): + 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, + ) + + 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], + process=Process.hierarchical, + manager_llm=ChatOpenAI(model="gpt-4o"), + ) + result = crew.kickoff() + assert isinstance(result.pydantic, ScoreOutput) + assert result.to_dict() == {"score": 4} + + +@pytest.mark.vcr(filter_headers=["authorization"]) +def test_output_json_sequential(): class ScoreOutput(BaseModel): score: int @@ -248,10 +279,126 @@ def test_output_json(): agent=scorer, ) - crew = Crew(agents=[scorer], tasks=[task]) + crew = Crew(agents=[scorer], tasks=[task], process=Process.sequential) result = crew.kickoff() - print("RESULT JSON", result) assert '{"score": 4}' == result.json + assert result.to_dict() == {"score": 4} + + +@pytest.mark.vcr(filter_headers=["authorization"]) +def test_output_json_hierarchical(): + 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, + ) + + 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], + process=Process.hierarchical, + manager_llm=ChatOpenAI(model="gpt-4o"), + ) + result = crew.kickoff() + assert '{"score": 4}' == result.json + assert result.to_dict() == {"score": 4} + + +def test_json_property_without_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_pydantic=ScoreOutput, # Using output_pydantic instead of output_json + agent=scorer, + ) + + crew = Crew(agents=[scorer], tasks=[task], process=Process.sequential) + result = crew.kickoff() + + with pytest.raises(ValueError) as excinfo: + _ = result.json # Attempt to access the json property + + assert "No JSON output found in the final task." in str(excinfo.value) + + +@pytest.mark.vcr(filter_headers=["authorization"]) +def test_output_json_dict_sequential(): + 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], process=Process.sequential) + result = crew.kickoff() + assert {"score": 4} == result.json_dict + assert result.to_dict() == {"score": 4} + + +@pytest.mark.vcr(filter_headers=["authorization"]) +def test_output_json_dict_hierarchical(): + 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, + ) + + 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], + process=Process.hierarchical, + manager_llm=ChatOpenAI(model="gpt-4o"), + ) + result = crew.kickoff() + assert {"score": 4} == result.json_dict + assert result.to_dict() == {"score": 4} @pytest.mark.vcr(filter_headers=["authorization"]) @@ -571,12 +718,78 @@ def test_interpolate_inputs(): assert task.expected_output == "Bullet point list of 5 interesting ideas about ML." -""" -TODO: TEST SYNC -- Verify return type -""" +def test_task_output_str_with_pydantic(): + from crewai.tasks.output_format import OutputFormat -""" -TODO: TEST ASYNC -- Verify return type -""" + class ScoreOutput(BaseModel): + score: int + + score_output = ScoreOutput(score=4) + task_output = TaskOutput( + description="Test task", + agent="Test Agent", + pydantic=score_output, + output_format=OutputFormat.PYDANTIC, + ) + + assert str(task_output) == str(score_output) + + +def test_task_output_str_with_json_dict(): + from crewai.tasks.output_format import OutputFormat + + json_dict = {"score": 4} + task_output = TaskOutput( + description="Test task", + agent="Test Agent", + json_dict=json_dict, + output_format=OutputFormat.JSON, + ) + + assert str(task_output) == str(json_dict) + + +def test_task_output_str_with_raw(): + from crewai.tasks.output_format import OutputFormat + + raw_output = "Raw task output" + task_output = TaskOutput( + description="Test task", + agent="Test Agent", + raw=raw_output, + output_format=OutputFormat.RAW, + ) + + assert str(task_output) == raw_output + + +def test_task_output_str_with_pydantic_and_json_dict(): + from crewai.tasks.output_format import OutputFormat + + class ScoreOutput(BaseModel): + score: int + + score_output = ScoreOutput(score=4) + json_dict = {"score": 4} + task_output = TaskOutput( + description="Test task", + agent="Test Agent", + pydantic=score_output, + json_dict=json_dict, + output_format=OutputFormat.PYDANTIC, + ) + + # When both pydantic and json_dict are present, pydantic should take precedence + assert str(task_output) == str(score_output) + + +def test_task_output_str_with_none(): + from crewai.tasks.output_format import OutputFormat + + task_output = TaskOutput( + description="Test task", + agent="Test Agent", + output_format=OutputFormat.RAW, + ) + + assert str(task_output) == ""