crewAI/lib/crewai/tests/test_task.py

"""Test Agent creation and execution basic functionality."""

import ast
import json
import os
import time
from functools import partial
from hashlib import md5
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.conditional_task import ConditionalTask
from crewai.tasks.task_output import TaskOutput
from crewai.utilities.converter import Converter
from crewai.utilities.string_utils import interpolate_only


def test_task_tool_reflect_agent_tools():
    from crewai.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.",
        expected_output="Bullet point list of 5 ideas.",
        agent=researcher,
    )

    assert task.tools == [fake_tool]


def test_task_tool_takes_precedence_over_agent_tools():
    from crewai.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.",
        expected_output="Bullet point list of 5 ideas.",
        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_sync(agent=researcher)
        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(
        name="Brainstorm",
        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_sync(agent=researcher)
        task_completed.assert_called_once_with(task.output)

        assert task.output.description == task.description
        assert task.output.expected_output == task.expected_output
        assert task.output.name == task.name


def test_task_callback_returns_task_output():
    from crewai.tasks.output_format import OutputFormat

    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 an 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 = "exported_ok"
        task.execute_sync(agent=researcher)
        # Ensure the callback is called with a TaskOutput object serialized to JSON
        task_completed.assert_called_once()
        callback_data = task_completed.call_args[0][0]

        if isinstance(callback_data, TaskOutput):
            callback_data = json.dumps(callback_data.model_dump())

        assert isinstance(callback_data, str)
        output_dict = json.loads(callback_data)
        expected_output = {
            "description": task.description,
            "raw": "exported_ok",
            "pydantic": None,
            "json_dict": None,
            "agent": researcher.role,
            "summary": "Give me a list of 5 interesting ideas to explore...",
            "name": task.name or task.description,
            "expected_output": "Bullet point list of 5 interesting ideas.",
            "output_format": OutputFormat.RAW,
            "messages": [],
            "tool_failures": [],
        }
        assert output_dict == expected_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_sync(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:
        execution = task.execute_async(agent=researcher)
        result = execution.result()
        assert result.raw == "ok"
        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,
        )


def test_guardrail_type_error():
    desc = "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."
    # Lambda function
    Task(
        description=desc,
        expected_output=expected_output,
        guardrail=lambda x: (True, x),
    )

    # Function
    def guardrail_fn(x: TaskOutput) -> tuple[bool, TaskOutput]:
        return (True, x)

    Task(
        description=desc,
        expected_output=expected_output,
        guardrail=guardrail_fn,
    )

    class Object:
        def guardrail_fn(self, x: TaskOutput) -> tuple[bool, TaskOutput]:
            return (True, x)

        @classmethod
        def guardrail_class_fn(cls, x: TaskOutput) -> tuple[bool, str]:
            return (True, x)

        @staticmethod
        def guardrail_static_fn(x: TaskOutput) -> tuple[bool, str | TaskOutput]:
            return (True, x)

    obj = Object()
    # Method
    Task(
        description=desc,
        expected_output=expected_output,
        guardrail=obj.guardrail_fn,
    )
    Task(
        description=desc,
        expected_output=expected_output,
        guardrail=Object.guardrail_class_fn,
    )
    # Static method
    Task(
        description=desc,
        expected_output=expected_output,
        guardrail=Object.guardrail_static_fn,
    )

    def error_fn(x: TaskOutput, y: bool) -> tuple[bool, TaskOutput]:
        return (y, x)

    Task(
        description=desc,
        expected_output=expected_output,
        guardrail=partial(error_fn, y=True),
    )

    with pytest.raises(ValidationError):
        Task(
            description=desc,
            expected_output=expected_output,
            guardrail=error_fn,
        )


@pytest.mark.vcr()
def test_output_pydantic_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_pydantic=ScoreOutput,
        agent=scorer,
    )

    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()
def test_output_pydantic_hierarchical():
    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="gpt-4o",
    )
    result = crew.kickoff()
    assert isinstance(result.pydantic, ScoreOutput)
    assert result.to_dict() == {"score": 4}


@pytest.mark.vcr()
def test_output_json_sequential():
    import uuid

    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,
    )

    output_file = f"score_{uuid.uuid4()}.json"
    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,
        output_file=output_file,
        agent=scorer,
    )

    crew = Crew(agents=[scorer], tasks=[task], process=Process.sequential)
    result = crew.kickoff()
    assert '{"score": 4}' == result.json
    assert result.to_dict() == {"score": 4}

    if os.path.exists(output_file):
        os.remove(output_file)


@pytest.mark.vcr()
def test_output_json_hierarchical():
    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="gpt-4o",
    )
    result = crew.kickoff()
    assert result.json == '{"score": 4}'
    assert result.to_dict() == {"score": 4}


@pytest.mark.vcr()
def test_inject_date():
    reporter = Agent(
        role="Reporter",
        goal="Report the date",
        backstory="You're an expert reporter, specialized in reporting the date.",
        allow_delegation=False,
        inject_date=True,
    )

    task = Task(
        description="What is the date today?",
        expected_output="The date today as you were told, same format as the date you were told.",
        agent=reporter,
    )

    crew = Crew(
        agents=[reporter],
        tasks=[task],
        process=Process.sequential,
    )
    result = crew.kickoff()
    assert "2025-05-21" in result.raw


@pytest.mark.vcr()
def test_inject_date_custom_format():
    reporter = Agent(
        role="Reporter",
        goal="Report the date",
        backstory="You're an expert reporter, specialized in reporting the date.",
        allow_delegation=False,
        inject_date=True,
        date_format="%B %d, %Y",
    )

    task = Task(
        description="What is the date today?",
        expected_output="The date today.",
        agent=reporter,
    )

    crew = Crew(
        agents=[reporter],
        tasks=[task],
        process=Process.sequential,
    )
    result = crew.kickoff()
    assert "May 21, 2025" in result.raw


@pytest.mark.vcr()
def test_no_inject_date():
    reporter = Agent(
        role="Reporter",
        goal="Report the date",
        backstory="You're an expert reporter, specialized in reporting the date.",
        allow_delegation=False,
        inject_date=False,
    )

    task = Task(
        description="What is the date today?",
        expected_output="The date today.",
        agent=reporter,
    )

    crew = Crew(
        agents=[reporter],
        tasks=[task],
        process=Process.sequential,
    )
    result = crew.kickoff()
    assert "2025-05-21" not in result.raw


@pytest.mark.vcr()
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,
        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()
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()
def test_output_json_dict_hierarchical():
    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="gpt-4o",
    )
    result = crew.kickoff()
    assert {"score": 4} == result.json_dict
    assert result.to_dict() == {"score": 4}


@pytest.mark.vcr()
def test_output_pydantic_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,
        llm="gpt-4o",
        function_calling_llm="gpt-4o",
        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=True)
    result = crew.kickoff()
    pydantic_result = result.pydantic
    assert isinstance(pydantic_result, ScoreOutput), (
        "Expected pydantic result to be of type ScoreOutput"
    )
    assert pydantic_result.score == 5


@pytest.mark.vcr()
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 '{"score": 3}' == result.json


@pytest.mark.vcr()
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()
def test_save_task_json_output():
    from unittest.mock import patch

    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])

    # Mock only the _save_file method to avoid actual file I/O
    with patch.object(Task, "_save_file") as mock_save:
        result = crew.kickoff()
        assert result is not None
        mock_save.assert_called_once()

        call_args = mock_save.call_args
        if call_args:
            saved_content = call_args[0][0]
            if isinstance(saved_content, str):
                data = json.loads(saved_content)
                assert "score" in data


@pytest.mark.vcr()
def test_save_task_pydantic_output(tmp_path, monkeypatch):
    """Test saving pydantic output to a file.

    Uses tmp_path fixture and monkeypatch to change directory to avoid
    file system race conditions on enterprise systems.
    """
    from pathlib import Path

    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,
    )

    monkeypatch.chdir(tmp_path)

    output_file = "score_output.json"
    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=output_file,
        output_pydantic=ScoreOutput,
        agent=scorer,
    )

    crew = Crew(agents=[scorer], tasks=[task])
    crew.kickoff()

    output_path = Path(output_file).resolve()
    assert output_path.exists()
    assert {"score": 4} == json.loads(output_path.read_text())


@pytest.mark.vcr()
def test_custom_converter_cls():
    class ScoreOutput(BaseModel):
        score: int

    class ScoreConverter(Converter):
        pass

    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,
        converter_cls=ScoreConverter,
        agent=scorer,
    )

    crew = Crew(agents=[scorer], tasks=[task])

    # so the converter is bypassed. Verify the output is valid instead.
    result = crew.kickoff()
    assert isinstance(result.pydantic, ScoreOutput)
    assert isinstance(result.pydantic.score, int)


@pytest.mark.vcr()
def test_increment_delegations_for_hierarchical_process():
    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.",
    )

    crew = Crew(
        agents=[scorer],
        tasks=[task],
        process=Process.hierarchical,
        manager_llm="gpt-4o",
    )

    with patch.object(Task, "increment_delegations") as increment_delegations:
        increment_delegations.return_value = None
        crew.kickoff()
        increment_delegations.assert_called_once()


@pytest.mark.vcr()
def test_increment_delegations_for_sequential_process():
    manager = Agent(
        role="Manager",
        goal="Coordinate scoring processes",
        backstory="You're great at delegating work about scoring.",
        allow_delegation=True,
    )

    scorer = Agent(
        role="Scorer",
        goal="Score the title",
        backstory="You're an expert scorer, specialized in scoring titles.",
        allow_delegation=True,
    )

    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.",
        agent=manager,
    )

    crew = Crew(
        agents=[manager, scorer],
        tasks=[task],
        process=Process.sequential,
    )

    with patch.object(Task, "increment_delegations") as increment_delegations:
        increment_delegations.return_value = None
        crew.kickoff()
        increment_delegations.assert_called_once()


@pytest.mark.vcr()
def test_increment_tool_errors():
    from crewai.tools import tool

    @tool
    def scoring_examples() -> None:
        "Useful examples for scoring titles."
        raise Exception("Error")

    scorer = Agent(
        role="Scorer",
        goal="Score the title",
        backstory="You're an expert scorer, specialized in scoring titles.",
        tools=[scoring_examples],
    )

    task = Task(
        description="Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work', check examples to based your evaluation.",
        expected_output="The score of the title.",
    )

    crew = Crew(
        agents=[scorer],
        tasks=[task],
        process=Process.hierarchical,
        manager_llm="gpt-4-0125-preview",
    )

    with patch.object(Task, "increment_tools_errors") as increment_tools_errors:
        increment_tools_errors.return_value = None
        crew.kickoff()
        assert len(increment_tools_errors.mock_calls) > 0


def test_task_definition_based_on_dict():
    config = {
        "description": "Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work', check examples to based your evaluation.",
        "expected_output": "The score of the title.",
    }

    task = Task(**config)

    assert task.description == config["description"]
    assert task.expected_output == config["expected_output"]
    assert task.agent is None


def test_conditional_task_definition_based_on_dict():
    config = {
        "description": "Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work', check examples to based your evaluation.",
        "expected_output": "The score of the title.",
    }

    task = ConditionalTask(**config, condition=lambda x: True)

    assert task.description == config["description"]
    assert task.expected_output == config["expected_output"]
    assert task.agent is None


def test_conditional_task_copy_preserves_type():
    task_config = {
        "description": "Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work', check examples to based your evaluation.",
        "expected_output": "The score of the title.",
    }
    original_task = Task(**task_config)
    copied_task = original_task.copy(agents=[], task_mapping={})
    assert isinstance(copied_task, Task)

    original_conditional_config = {
        "description": "Give me an integer score between 1-5 for the following title: 'The impact of AI in the future of work'. Check examples to base your evaluation on.",
        "expected_output": "The score of the title.",
        "condition": lambda x: True,
    }
    original_conditional_task = ConditionalTask(**original_conditional_config)
    copied_conditional_task = original_conditional_task.copy(agents=[], task_mapping={})
    assert isinstance(copied_conditional_task, ConditionalTask)


def test_interpolate_inputs(tmp_path):
    task = Task(
        description="Give me a list of 5 interesting ideas about {topic} to explore for an article, what makes them unique and interesting.",
        expected_output="Bullet point list of 5 interesting ideas about {topic}.",
        output_file=str(tmp_path / "{topic}" / "output_{date}.txt"),
    )

    task.interpolate_inputs_and_add_conversation_history(
        inputs={"topic": "AI", "date": "2025"}
    )
    assert (
        task.description
        == "Give me a list of 5 interesting ideas about AI to explore for an article, what makes them unique and interesting."
    )
    assert task.expected_output == "Bullet point list of 5 interesting ideas about AI."
    assert task.output_file == str(tmp_path / "AI" / "output_2025.txt")

    task.interpolate_inputs_and_add_conversation_history(
        inputs={"topic": "ML", "date": "2025"}
    )
    assert (
        task.description
        == "Give me a list of 5 interesting ideas about ML to explore for an article, what makes them unique and interesting."
    )
    assert task.expected_output == "Bullet point list of 5 interesting ideas about ML."
    assert task.output_file == str(tmp_path / "ML" / "output_2025.txt")


def test_interpolate_only():
    """Test the interpolate_only method for various scenarios including JSON structure preservation."""

    json_string = '{"info": "Look at {placeholder}", "nested": {"val": "{nestedVal}"}}'
    result = interpolate_only(
        input_string=json_string,
        inputs={"placeholder": "the data", "nestedVal": "something else"},
    )
    assert '"info": "Look at the data"' in result
    assert '"val": "something else"' in result
    assert "{placeholder}" not in result
    assert "{nestedVal}" not in result

    normal_string = "Hello {name}, welcome to {place}!"
    result = interpolate_only(
        input_string=normal_string, inputs={"name": "John", "place": "CrewAI"}
    )
    assert result == "Hello John, welcome to CrewAI!"

    result = interpolate_only(input_string="", inputs={"unused": "value"})
    assert result == ""

    no_placeholders = "Hello, this is a test"
    result = interpolate_only(input_string=no_placeholders, inputs={"unused": "value"})
    assert result == no_placeholders


def test_interpolate_only_with_dict_inside_expected_output():
    """Test the interpolate_only method for various scenarios including JSON structure preservation."""

    json_string = '{"questions": {"main_question": "What is the user\'s name?", "secondary_question": "What is the user\'s age?"}}'
    result = interpolate_only(
        input_string=json_string,
        inputs={
            "questions": {
                "main_question": "What is the user's name?",
                "secondary_question": "What is the user's age?",
            }
        },
    )
    assert '"main_question": "What is the user\'s name?"' in result
    assert '"secondary_question": "What is the user\'s age?"' in result
    assert result == json_string

    normal_string = "Hello {name}, welcome to {place}!"
    result = interpolate_only(
        input_string=normal_string, inputs={"name": "John", "place": "CrewAI"}
    )
    assert result == "Hello John, welcome to CrewAI!"

    result = interpolate_only(input_string="", inputs={"unused": "value"})
    assert result == ""

    no_placeholders = "Hello, this is a test"
    result = interpolate_only(input_string=no_placeholders, inputs={"unused": "value"})
    assert result == no_placeholders


def test_task_output_str_with_pydantic():
    from crewai.tasks.output_format import OutputFormat

    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) == ""


def test_key():
    original_description = "Give me a list of 5 interesting ideas about {topic} to explore for an article, what makes them unique and interesting."
    original_expected_output = "Bullet point list of 5 interesting ideas about {topic}."
    task = Task(
        description=original_description,
        expected_output=original_expected_output,
    )
    hash = md5(
        f"{original_description}|{original_expected_output}".encode(),
        usedforsecurity=False,
    ).hexdigest()

    assert task.key == hash, "The key should be the hash of the description."

    task.interpolate_inputs_and_add_conversation_history(inputs={"topic": "AI"})
    assert task.key == hash, (
        "The key should be the hash of the non-interpolated description."
    )


def test_output_file_validation(tmp_path):
    """Test output file path validation."""
    assert (
        Task(
            description="Test task",
            expected_output="Test output",
            output_file="output.txt",
        ).output_file
        == "output.txt"
    )
    temp_file = tmp_path / "output.txt"
    assert (
        Task(
            description="Test task",
            expected_output="Test output",
            output_file=str(temp_file),
        ).output_file
        == str(temp_file).lstrip("/")  # Remove leading slash to match expected behavior
    )
    assert (
        Task(
            description="Test task",
            expected_output="Test output",
            output_file="{dir}/output_{date}.txt",
        ).output_file
        == "{dir}/output_{date}.txt"
    )

    with pytest.raises(ValueError, match="Path traversal"):
        Task(
            description="Test task",
            expected_output="Test output",
            output_file="../output.txt",
        )
    with pytest.raises(ValueError, match="Path traversal"):
        Task(
            description="Test task",
            expected_output="Test output",
            output_file="folder/../output.txt",
        )
    with pytest.raises(ValueError, match="Shell special characters"):
        Task(
            description="Test task",
            expected_output="Test output",
            output_file="output.txt | rm -rf /",
        )
    with pytest.raises(ValueError, match="Shell expansion"):
        Task(
            description="Test task",
            expected_output="Test output",
            output_file="~/output.txt",
        )
    with pytest.raises(ValueError, match="Shell expansion"):
        Task(
            description="Test task",
            expected_output="Test output",
            output_file="$HOME/output.txt",
        )
    with pytest.raises(ValueError, match="Invalid template variable"):
        Task(
            description="Test task",
            expected_output="Test output",
            output_file="{invalid-name}/output.txt",
        )


def test_create_directory_true():
    """Test that directories are created when create_directory=True."""
    from pathlib import Path

    output_path = "test_create_dir/output.txt"

    task = Task(
        description="Test task",
        expected_output="Test output",
        output_file=output_path,
        create_directory=True,
    )

    resolved_path = Path(output_path).expanduser().resolve()
    resolved_dir = resolved_path.parent

    if resolved_path.exists():
        resolved_path.unlink()
    if resolved_dir.exists():
        import shutil

        shutil.rmtree(resolved_dir)

    assert not resolved_dir.exists()

    task._save_file("test content")

    assert resolved_dir.exists()
    assert resolved_path.exists()

    if resolved_path.exists():
        resolved_path.unlink()
    if resolved_dir.exists():
        import shutil

        shutil.rmtree(resolved_dir)


def test_create_directory_false():
    """Test that directories are not created when create_directory=False."""
    from pathlib import Path

    output_path = "nonexistent_test_dir/output.txt"

    task = Task(
        description="Test task",
        expected_output="Test output",
        output_file=output_path,
        create_directory=False,
    )

    resolved_path = Path(output_path).expanduser().resolve()
    resolved_dir = resolved_path.parent

    if resolved_dir.exists():
        import shutil

        shutil.rmtree(resolved_dir)

    assert not resolved_dir.exists()

    with pytest.raises(
        RuntimeError, match=r"Directory .* does not exist and create_directory is False"
    ):
        task._save_file("test content")


def test_create_directory_default():
    """Test that create_directory defaults to True for backward compatibility."""
    task = Task(
        description="Test task",
        expected_output="Test output",
        output_file="output.txt",
    )

    assert task.create_directory is True


def test_create_directory_with_existing_directory():
    """Test that create_directory=False works when directory already exists."""
    from pathlib import Path

    output_path = "existing_test_dir/output.txt"

    resolved_path = Path(output_path).expanduser().resolve()
    resolved_dir = resolved_path.parent
    resolved_dir.mkdir(parents=True, exist_ok=True)

    task = Task(
        description="Test task",
        expected_output="Test output",
        output_file=output_path,
        create_directory=False,
    )

    task._save_file("test content")
    assert resolved_path.exists()

    if resolved_path.exists():
        resolved_path.unlink()
    if resolved_dir.exists():
        import shutil

        shutil.rmtree(resolved_dir)


def test_github_issue_3149_reproduction():
    """Test that reproduces the exact issue from GitHub issue #3149."""
    task = Task(
        description="Test task for issue reproduction",
        expected_output="Test output",
        output_file="test_output.txt",
        create_directory=True,
    )

    assert task.create_directory is True
    assert task.output_file == "test_output.txt"


@pytest.mark.vcr()
def test_task_execution_times():
    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,
    )

    assert task.start_time is None
    assert task.end_time is None
    assert task.execution_duration is None

    task.execute_sync(agent=researcher)

    assert task.start_time is not None
    assert task.end_time is not None
    assert task.execution_duration == (task.end_time - task.start_time).total_seconds()


def test_interpolate_with_list_of_strings():
    input_str = "Available items: {items}"
    inputs = {"items": ["apple", "banana", "cherry"]}
    result = interpolate_only(input_str, inputs)
    assert result == f"Available items: {inputs['items']}"

    empty_list_input = {"items": []}
    result = interpolate_only(input_str, empty_list_input)
    assert result == "Available items: []"


def test_interpolate_with_list_of_dicts():
    input_data = {
        "people": [
            {"name": "Alice", "age": 30, "skills": ["Python", "AI"]},
            {"name": "Bob", "age": 25, "skills": ["Java", "Cloud"]},
        ]
    }
    result = interpolate_only("{people}", input_data)

    parsed_result = ast.literal_eval(result)
    assert isinstance(parsed_result, list)
    assert len(parsed_result) == 2
    assert parsed_result[0]["name"] == "Alice"
    assert parsed_result[0]["age"] == 30
    assert parsed_result[0]["skills"] == ["Python", "AI"]
    assert parsed_result[1]["name"] == "Bob"
    assert parsed_result[1]["age"] == 25
    assert parsed_result[1]["skills"] == ["Java", "Cloud"]


def test_interpolate_with_nested_structures():
    input_data = {
        "company": {
            "name": "TechCorp",
            "departments": [
                {
                    "name": "Engineering",
                    "employees": 50,
                    "tools": ["Git", "Docker", "Kubernetes"],
                },
                {"name": "Sales", "employees": 20, "regions": {"north": 5, "south": 3}},
            ],
        }
    }
    result = interpolate_only("{company}", input_data)
    parsed = ast.literal_eval(result)

    assert parsed["name"] == "TechCorp"
    assert len(parsed["departments"]) == 2
    assert parsed["departments"][0]["tools"] == ["Git", "Docker", "Kubernetes"]
    assert parsed["departments"][1]["regions"]["north"] == 5


def test_interpolate_with_special_characters():
    input_data = {
        "special_data": {
            "quotes": """This has "double" and 'single' quotes""",
            "unicode": "文字化けテスト",
            "symbols": "!@#$%^&*()",
            "empty": "",
        }
    }
    result = interpolate_only("{special_data}", input_data)
    parsed = ast.literal_eval(result)

    assert parsed["quotes"] == """This has "double" and 'single' quotes"""
    assert parsed["unicode"] == "文字化けテスト"
    assert parsed["symbols"] == "!@#$%^&*()"
    assert parsed["empty"] == ""


def test_interpolate_mixed_types():
    input_data = {
        "data": {
            "name": "Test Dataset",
            "samples": 1000,
            "features": ["age", "income", "location"],
            "metadata": {
                "source": "public",
                "validated": True,
                "tags": ["demo", "test", "temp"],
            },
        }
    }
    result = interpolate_only("{data}", input_data)
    parsed = ast.literal_eval(result)

    assert parsed["name"] == "Test Dataset"
    assert parsed["samples"] == 1000
    assert parsed["metadata"]["tags"] == ["demo", "test", "temp"]


def test_interpolate_complex_combination():
    input_data = {
        "report": [
            {
                "month": "January",
                "metrics": {"sales": 15000, "expenses": 8000, "profit": 7000},
                "top_products": ["Product A", "Product B"],
            },
            {
                "month": "February",
                "metrics": {"sales": 18000, "expenses": 8500, "profit": 9500},
                "top_products": ["Product C", "Product D"],
            },
        ]
    }
    result = interpolate_only("{report}", input_data)
    parsed = ast.literal_eval(result)

    assert len(parsed) == 2
    assert parsed[0]["month"] == "January"
    assert parsed[1]["metrics"]["profit"] == 9500
    assert "Product D" in parsed[1]["top_products"]


def test_interpolate_invalid_type_validation():
    with pytest.raises(ValueError) as excinfo:
        interpolate_only("{data}", {"data": set()})  # type: ignore we are purposely testing this failure

    assert "Unsupported type set" in str(excinfo.value)

    invalid_nested = {
        "profile": {
            "name": "John",
            "age": 30,
            "tags": {"a", "b", "c"},
        }
    }
    with pytest.raises(ValueError) as excinfo:
        interpolate_only("{data}", {"data": invalid_nested})
    assert "Unsupported type set" in str(excinfo.value)


def test_interpolate_custom_object_validation():
    class CustomObject:
        def __init__(self, value):
            self.value = value

        def __str__(self):
            return str(self.value)

    with pytest.raises(ValueError) as excinfo:
        interpolate_only("{obj}", {"obj": CustomObject(5)})  # type: ignore we are purposely testing this failure
    assert "Unsupported type CustomObject" in str(excinfo.value)

    with pytest.raises(ValueError) as excinfo:
        interpolate_only("{data}", {"data": {"valid": 1, "invalid": CustomObject(5)}})
    assert "Unsupported type CustomObject" in str(excinfo.value)

    with pytest.raises(ValueError) as excinfo:
        interpolate_only("{data}", {"data": [1, "valid", CustomObject(5)]})
    assert "Unsupported type CustomObject" in str(excinfo.value)

    with pytest.raises(ValueError) as excinfo:
        interpolate_only(
            "{data}", {"data": {"level1": {"level2": [{"level3": CustomObject(5)}]}}}
        )
    assert "Unsupported type CustomObject" in str(excinfo.value)


def test_interpolate_valid_complex_types():
    valid_data = {
        "name": "Valid Dataset",
        "stats": {
            "count": 1000,
            "distribution": [0.2, 0.3, 0.5],
            "features": ["age", "income"],
            "nested": {"deep": [1, 2, 3], "deeper": {"a": 1, "b": 2.5}},
        },
    }

    result = interpolate_only("{data}", {"data": valid_data})
    parsed = ast.literal_eval(result)
    assert parsed["name"] == "Valid Dataset"
    assert parsed["stats"]["nested"]["deeper"]["b"] == 2.5


def test_interpolate_edge_cases():
    assert interpolate_only("{}", {"data": {}}) == "{}"
    assert interpolate_only("[]", {"data": []}) == "[]"

    assert interpolate_only("{num}", {"num": 42}) == "42"
    assert interpolate_only("{num}", {"num": 3.14}) == "3.14"

    assert interpolate_only("{flag}", {"flag": True}) == "True"
    assert interpolate_only("{flag}", {"flag": False}) == "False"


def test_interpolate_valid_types():
    valid_data = {
        "name": "Test",
        "active": True,
        "deleted": False,
        "optional": None,
        "nested": {"flag": True, "empty": None},
    }

    result = interpolate_only("{data}", {"data": valid_data})
    parsed = ast.literal_eval(result)

    assert parsed["active"] is True
    assert parsed["deleted"] is False
    assert parsed["optional"] is None
    assert parsed["nested"]["flag"] is True
    assert parsed["nested"]["empty"] is None


def test_task_with_no_max_execution_time():
    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,
        max_execution_time=None,
    )

    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_without_timeout", return_value="ok") as execute:
        result = task.execute_sync(agent=researcher)
        assert result.raw == "ok"
        execute.assert_called_once()


@pytest.mark.vcr()
def test_task_with_max_execution_time():
    from crewai.tools import tool

    """Test that execution raises TimeoutError when max_execution_time is exceeded."""

    @tool("what amazing tool", result_as_answer=True)
    def my_tool() -> str:
        "My tool"
        time.sleep(1)
        return "okay"

    researcher = Agent(
        role="Researcher",
        goal="Make the best research and analysis on content about AI and AI agents. Use the tool provided to you.",
        backstory=(
            "You're an expert researcher, specialized in technology, software engineering, AI and startups. "
            "You work as a freelancer and are now working on doing research and analysis for a new customer."
        ),
        allow_delegation=False,
        tools=[my_tool],
        max_execution_time=4,
    )

    task = Task(
        description="Give me a list of 5 interesting ideas to explore for an article, what makes them unique and interesting.",
        expected_output="Bullet point list of 5 interesting ideas.",
        agent=researcher,
    )

    result = task.execute_sync(agent=researcher)
    assert result.raw == "okay"


@pytest.mark.vcr()
def test_task_with_max_execution_time_exceeded():
    from crewai.tools import tool

    """Test that execution raises TimeoutError when max_execution_time is exceeded."""

    @tool("what amazing tool", result_as_answer=True)
    def my_tool() -> str:
        "My tool"
        time.sleep(10)
        return "okay"

    researcher = Agent(
        role="Researcher",
        goal="Make the best research and analysis on content about AI and AI agents. Use the tool provided to you.",
        backstory=(
            "You're an expert researcher, specialized in technology, software engineering, AI and startups. "
            "You work as a freelancer and are now working on doing research and analysis for a new customer."
        ),
        allow_delegation=False,
        tools=[my_tool],
        max_execution_time=1,
    )

    task = Task(
        description="Give me a list of 5 interesting ideas to explore for an article, what makes them unique and interesting.",
        expected_output="Bullet point list of 5 interesting ideas.",
        agent=researcher,
    )

    with pytest.raises(TimeoutError):
        task.execute_sync(agent=researcher)


@pytest.mark.vcr()
def test_task_interpolation_with_hyphens():
    agent = Agent(
        role="Researcher",
        goal="be an assistant that responds with {interpolation-with-hyphens}",
        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="be an assistant that responds with {interpolation-with-hyphens}",
        expected_output="The response should be addressing: {interpolation-with-hyphens}",
        agent=agent,
    )
    crew = Crew(
        agents=[agent],
        tasks=[task],
        verbose=True,
    )
    result = crew.kickoff(inputs={"interpolation-with-hyphens": "say hello world"})
    assert "say hello world" in task.prompt()

    assert result.raw == "Hello, World!"


def test_task_copy_with_none_context():
    original_task = Task(
        description="Test task",
        expected_output="Test output",
        context=None
    )

    new_task = original_task.copy(agents=[], task_mapping={})
    assert original_task.context is None
    assert new_task.context is None


def test_task_copy_with_not_specified_context():
    from crewai.utilities.constants import NOT_SPECIFIED
    original_task = Task(
        description="Test task",
        expected_output="Test output",
    )

    new_task = original_task.copy(agents=[], task_mapping={})
    assert original_task.context is NOT_SPECIFIED
    assert new_task.context is NOT_SPECIFIED


def test_task_copy_with_list_context():
    """Test that copying a task with list context works correctly."""
    task1 = Task(
        description="Task 1",
        expected_output="Output 1"
    )
    task2 = Task(
        description="Task 2",
        expected_output="Output 2",
        context=[task1]
    )

    task_mapping = {task1.key: task1}

    copied_task2 = task2.copy(agents=[], task_mapping=task_mapping)

    assert isinstance(copied_task2.context, list)
    assert len(copied_task2.context) == 1
    assert copied_task2.context[0] is task1


@pytest.mark.vcr()
def test_task_output_includes_messages():
    """Test that TaskOutput includes messages from agent 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,
    )

    task1 = Task(
        description="Give me a list of 3 interesting ideas about AI.",
        expected_output="Bullet point list of 3 ideas.",
        agent=researcher,
    )

    task2 = Task(
        description="Summarize the ideas from the previous task.",
        expected_output="A summary of the ideas.",
        agent=researcher,
    )

    crew = Crew(agents=[researcher], tasks=[task1, task2], process=Process.sequential)
    result = crew.kickoff()

    assert len(result.tasks_output) == 2

    task1_output = result.tasks_output[0]
    assert hasattr(task1_output, "messages")
    assert isinstance(task1_output.messages, list)
    assert len(task1_output.messages) > 0

    task2_output = result.tasks_output[1]
    assert hasattr(task2_output, "messages")
    assert isinstance(task2_output.messages, list)
    assert len(task2_output.messages) > 0


def test_async_execution_fails():
    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(Task, "_execute_core", side_effect=RuntimeError("boom!")):
      with pytest.raises(RuntimeError, match="boom!"):
        execution = task.execute_async(agent=researcher)
        execution.result()