Address PR feedback: Fix ForwardRef issues, improve error messages, enhance docs

Co-Authored-By: Joe Moura <joao@crewai.com>
Add task decomposition feature (Issue #2717 )
2026-01-07 23:28:30 +00:00 · 2025-04-29 13:25:40 +00:00 · 2025-04-29 13:19:17 +00:00
10 changed files with 621 additions and 297 deletions
--- a/examples/task_decomposition_example.py
+++ b/examples/task_decomposition_example.py
@@ -0,0 +1,47 @@
+"""
+Example of using task decomposition in CrewAI.
+
+This example demonstrates how to use the task decomposition feature
+to break down complex tasks into simpler sub-tasks.
+
+Feature introduced in CrewAI v1.x.x
+"""
+
+from crewai import Agent, Task, Crew
+
+researcher = Agent(
+    role="Researcher",
+    goal="Research effectively",
+    backstory="You're an expert researcher with skills in breaking down complex topics.",
+)
+
+research_task = Task(
+    description="Research the impact of AI on various industries",
+    expected_output="A comprehensive report covering multiple industries",
+    agent=researcher,
+)
+
+sub_tasks = research_task.decompose(
+    descriptions=[
+        "Research AI impact on healthcare industry",
+        "Research AI impact on finance industry",
+        "Research AI impact on education industry",
+    ],
+    expected_outputs=[
+        "A report on AI in healthcare",
+        "A report on AI in finance",
+        "A report on AI in education",
+    ],
+    names=["Healthcare", "Finance", "Education"],
+)
+
+crew = Crew(
+    agents=[researcher],
+    tasks=[research_task],
+)
+
+result = crew.kickoff()
+print("Final result:", result)
+
+for i, sub_task in enumerate(research_task.sub_tasks):
+    print(f"Sub-task {i+1} result: {sub_task.output.raw if hasattr(sub_task, 'output') and sub_task.output else 'No output'}")
--- a/src/crewai/crew.py
+++ b/src/crewai/crew.py
@@ -16,8 +16,6 @@ from pydantic import (
    field_validator,
    model_validator,
 )
-
-from crewai.llm import LLM
 from pydantic_core import PydanticCustomError

 from crewai.agent import Agent
@@ -1077,41 +1075,19 @@ class Crew(BaseModel):
    def test(
        self,
        n_iterations: int,
-        llm: Optional[Union[str, InstanceOf[LLM], Any]] = None,
-        openai_model_name: Optional[str] = None,  # For backward compatibility
+        openai_model_name: Optional[str] = None,
        inputs: Optional[Dict[str, Any]] = None,
    ) -> None:
-        """Test and evaluate the Crew with the given inputs for n iterations.
-
-        This method runs tests to evaluate the performance of the crew using the specified
-        language model. It supports both string model names and LLM instances for flexibility.
-
-        Args:
-            n_iterations: Number of test iterations to run
-            llm: Language model configuration (preferred). Can be:
-                - A string model name (e.g., "gpt-4")
-                - An LLM instance
-                - Any object with model_name or deployment_name attributes
-            openai_model_name: Legacy parameter for backward compatibility.
-                Deprecated: Will be removed in future versions. Use `llm` instead.
-            inputs: Optional dictionary of inputs to be used during testing
-
-        Note:
-            The `openai_model_name` parameter is deprecated and will be removed in
-            future versions. Use the more flexible `llm` parameter instead, which
-            supports any LLM implementation.
-        """
+        """Test and evaluate the Crew with the given inputs for n iterations concurrently using concurrent.futures."""
        test_crew = self.copy()

-        # For backward compatibility, convert openai_model_name to llm
-        model_name = llm or openai_model_name or "gpt-4o-mini"
        self._test_execution_span = test_crew._telemetry.test_execution_span(
            test_crew,
            n_iterations,
            inputs,
-            model_name,
-        )
-        evaluator = CrewEvaluator(test_crew, llm=model_name)
+            openai_model_name,  # type: ignore[arg-type]
+        )  # type: ignore[arg-type]
+        evaluator = CrewEvaluator(test_crew, openai_model_name)  # type: ignore[arg-type]

        for i in range(1, n_iterations + 1):
            evaluator.set_iteration(i)
--- a/src/crewai/task.py
+++ b/src/crewai/task.py
@@ -19,6 +19,7 @@ from typing import (
    Tuple,
    Type,
    Union,
+    ForwardRef,
 )

 from opentelemetry.trace import Span
@@ -137,6 +138,16 @@ class Task(BaseModel):
        default=0,
        description="Current number of retries"
    )
+    parent_task: Optional['Task'] = Field(
+        default=None,
+        description="Parent task that this task was decomposed from.",
+        exclude=True,
+    )
+    sub_tasks: List['Task'] = Field(
+        default_factory=list,
+        description="Sub-tasks that this task was decomposed into.",
+        exclude=True,
+    )

    @field_validator("guardrail")
    @classmethod
@@ -246,13 +257,151 @@ class Task(BaseModel):
            )
        return self

+    def decompose(
+        self,
+        descriptions: List[str],
+        expected_outputs: Optional[List[str]] = None,
+        names: Optional[List[str]] = None
+    ) -> List['Task']:
+        """
+        Decompose a complex task into simpler sub-tasks.
+        
+        Args:
+            descriptions: List of descriptions for each sub-task.
+            expected_outputs: Optional list of expected outputs for each sub-task.
+            names: Optional list of names for each sub-task.
+            
+        Returns:
+            List of created sub-tasks.
+            
+        Raises:
+            ValueError: If descriptions is empty, or if expected_outputs or names
+                       have different lengths than descriptions.
+                       
+        Side Effects:
+            Modifies self.sub_tasks by adding newly created sub-tasks.
+        """
+        if not descriptions:
+            raise ValueError("At least one sub-task description is required.")
+            
+        if expected_outputs and len(expected_outputs) != len(descriptions):
+            raise ValueError(
+                f"If provided, expected_outputs must have the same length as descriptions. "
+                f"Got {len(expected_outputs)} expected outputs and {len(descriptions)} descriptions."
+            )
+            
+        if names and len(names) != len(descriptions):
+            raise ValueError(
+                f"If provided, names must have the same length as descriptions. "
+                f"Got {len(names)} names and {len(descriptions)} descriptions."
+            )
+            
+        for i, description in enumerate(descriptions):
+            sub_task = Task(
+                description=description,
+                expected_output=expected_outputs[i] if expected_outputs else self.expected_output,
+                name=names[i] if names else None,
+                agent=self.agent,  # Inherit the agent from the parent task
+                tools=self.tools,  # Inherit the tools from the parent task
+                context=[self],    # Set the parent task as context for the sub-task
+                parent_task=self,  # Reference back to the parent task
+            )
+            self.sub_tasks.append(sub_task)
+            
+        return self.sub_tasks
+        
+    def combine_sub_task_results(self) -> str:
+        """
+        Combine the results from all sub-tasks into a single result for this task.
+        
+        This method uses the task's agent to intelligently combine the results from
+        all sub-tasks. It requires an agent capable of coherent text summarization
+        and is designed for stateless prompt execution.
+        
+        Returns:
+            The combined result as a string.
+            
+        Raises:
+            ValueError: If the task has no sub-tasks or no agent assigned.
+            
+        Side Effects:
+            None. This method does not modify the task's state.
+        """
+        if not self.sub_tasks:
+            raise ValueError("Task has no sub-tasks to combine results from.")
+            
+        if not self.agent:
+            raise ValueError("Task has no agent to combine sub-task results.")
+            
+        sub_task_results = "\n\n".join([
+            f"Sub-task: {sub_task.description}\nResult: {sub_task.output.raw if sub_task.output else 'No result'}"
+            for sub_task in self.sub_tasks
+        ])
+        
+        combine_prompt = f"""
+        You have completed the following sub-tasks for the main task: "{self.description}"
+        
+        {sub_task_results}
+        
+        Based on all these sub-tasks, please provide a consolidated final answer for the main task.
+        Expected output format: {self.expected_output if self.expected_output else 'Not specified'}
+        """
+        
+        result = self.agent.execute_task(
+            task=self,
+            context=combine_prompt,
+            tools=self.tools or []
+        )
+        
+        return result
+    
    def execute_sync(
        self,
        agent: Optional[BaseAgent] = None,
        context: Optional[str] = None,
        tools: Optional[List[BaseTool]] = None,
    ) -> TaskOutput:
-        """Execute the task synchronously."""
+        """
+        Execute the task synchronously.
+        
+        If the task has sub-tasks and no output yet, this method will:
+        1. Execute all sub-tasks first
+        2. Combine their results using the agent
+        3. Set the combined result as this task's output
+        
+        Args:
+            agent: Optional agent to execute the task with.
+            context: Optional context to pass to the task.
+            tools: Optional tools to pass to the task.
+            
+        Returns:
+            TaskOutput: The result of the task execution.
+            
+        Side Effects:
+            Sets self.output with the execution result.
+        """
+        if self.sub_tasks and not self.output:
+            for sub_task in self.sub_tasks:
+                sub_task.execute_sync(
+                    agent=sub_task.agent or agent,
+                    context=context,
+                    tools=sub_task.tools or tools or [],
+                )
+            
+            # Combine the results from sub-tasks
+            result = self.combine_sub_task_results()
+            
+            self.output = TaskOutput(
+                description=self.description,
+                name=self.name,
+                expected_output=self.expected_output,
+                raw=result,
+                agent=self.agent.role if self.agent else None,
+                output_format=self.output_format,
+            )
+            
+            return self.output
+        
        return self._execute_core(agent, context, tools)

    @property
@@ -278,6 +427,55 @@ class Task(BaseModel):
        ).start()
        return future

+    def execute_sub_tasks_async(
+        self,
+        agent: Optional[BaseAgent] = None,
+        context: Optional[str] = None,
+        tools: Optional[List[BaseTool]] = None,
+    ) -> List[Future[TaskOutput]]:
+        """
+        Execute all sub-tasks asynchronously.
+        
+        This method starts the execution of all sub-tasks in parallel and returns
+        futures that can be awaited. After all futures are complete, you should call
+        combine_sub_task_results() to aggregate the results.
+        
+        Example:
+            ```python
+            futures = task.execute_sub_tasks_async()
+            
+            for future in futures:
+                future.result()
+                
+            # Combine the results
+            result = task.combine_sub_task_results()
+            ```
+        
+        Args:
+            agent: Optional agent to execute the sub-tasks with.
+            context: Optional context to pass to the sub-tasks.
+            tools: Optional tools to pass to the sub-tasks.
+            
+        Returns:
+            List of futures for the sub-task executions.
+            
+        Raises:
+            ValueError: If the task has no sub-tasks.
+        """
+        if not self.sub_tasks:
+            return []
+            
+        futures = []
+        for sub_task in self.sub_tasks:
+            future = sub_task.execute_async(
+                agent=sub_task.agent or agent,
+                context=context,
+                tools=sub_task.tools or tools or [],
+            )
+            futures.append(future)
+            
+        return futures
+        
    def _execute_task_async(
        self,
        agent: Optional[BaseAgent],
@@ -434,6 +632,8 @@ class Task(BaseModel):
            "agent",
            "context",
            "tools",
+            "parent_task",
+            "sub_tasks",
        }

        copied_data = self.model_dump(exclude=exclude)
@@ -457,6 +657,7 @@ class Task(BaseModel):
            agent=cloned_agent,
            tools=cloned_tools,
        )
+        

        return copied_task

@@ -526,3 +727,6 @@ class Task(BaseModel):

    def __repr__(self):
        return f"Task(description={self.description}, expected_output={self.expected_output})"
+
+
+Task.model_rebuild()
--- a/src/crewai/utilities/evaluators/crew_evaluator_handler.py
+++ b/src/crewai/utilities/evaluators/crew_evaluator_handler.py
@@ -1,19 +1,11 @@
 from collections import defaultdict
-from typing import Any, Dict, List, Union

-from pydantic import (
-    BaseModel,
-    Field,
-    InstanceOf,
-    PrivateAttr,
-    model_validator,
-)
+from pydantic import BaseModel, Field
 from rich.box import HEAVY_EDGE
 from rich.console import Console
 from rich.table import Table

 from crewai.agent import Agent
-from crewai.llm import LLM
 from crewai.task import Task
 from crewai.tasks.task_output import TaskOutput
 from crewai.telemetry import Telemetry
@@ -25,74 +17,27 @@ class TaskEvaluationPydanticOutput(BaseModel):
    )


-class CrewEvaluator(BaseModel):
+class CrewEvaluator:
    """
    A class to evaluate the performance of the agents in the crew based on the tasks they have performed.

    Attributes:
        crew (Crew): The crew of agents to evaluate.
-        llm (Union[str, InstanceOf[LLM], Any]): The language model to use for evaluating the performance of the agents.
+        openai_model_name (str): The model to use for evaluating the performance of the agents (for now ONLY OpenAI accepted).
        tasks_scores (defaultdict): A dictionary to store the scores of the agents for each task.
        iteration (int): The current iteration of the evaluation.
    """

-    crew: Any = Field(description="The crew of agents to evaluate.")
-    llm: Union[str, InstanceOf[LLM], Any] = Field(
-        description="Language model that will run the evaluation."
-    )
-    tasks_scores: Dict[int, List[float]] = Field(
-        default_factory=lambda: defaultdict(list),
-        description="Dictionary to store the scores of the agents for each task."
-    )
-    run_execution_times: Dict[int, List[int]] = Field(
-        default_factory=lambda: defaultdict(list),
-        description="Dictionary to store execution times for each run."
-    )
-    iteration: int = Field(
-        default=0,
-        description="Current iteration of the evaluation."
-    )
+    tasks_scores: defaultdict = defaultdict(list)
+    run_execution_times: defaultdict = defaultdict(list)
+    iteration: int = 0

-    @model_validator(mode="after")
-    def validate_llm(self):
-        """Validates that the LLM is properly configured."""
-        if not self.llm:
-            raise ValueError("LLM configuration is required")
-        return self
-
-    _telemetry: Telemetry = PrivateAttr(default_factory=Telemetry)
-
-    def __init__(self, crew, llm: Union[str, InstanceOf[LLM], Any]):
-        # Initialize Pydantic model with validated fields
-        super().__init__(crew=crew, llm=llm)
+    def __init__(self, crew, openai_model_name: str):
+        self.crew = crew
+        self.openai_model_name = openai_model_name
+        self._telemetry = Telemetry()
        self._setup_for_evaluating()

-    @model_validator(mode="before")
-    def init_llm(cls, values):
-        """Initialize LLM before Pydantic validation."""
-        llm = values.get("llm")
-        try:
-            if isinstance(llm, str):
-                values["llm"] = LLM(model=llm)
-            elif isinstance(llm, LLM):
-                values["llm"] = llm
-            else:
-                # For any other type, attempt to extract relevant attributes
-                llm_params = {
-                    "model": getattr(llm, "model_name", None)
-                    or getattr(llm, "deployment_name", None)
-                    or str(llm),
-                    "temperature": getattr(llm, "temperature", None),
-                    "max_tokens": getattr(llm, "max_tokens", None),
-                    "timeout": getattr(llm, "timeout", None),
-                }
-                # Remove None values
-                llm_params = {k: v for k, v in llm_params.items() if v is not None}
-                values["llm"] = LLM(**llm_params)
-        except Exception as e:
-            raise ValueError(f"Invalid LLM configuration: {str(e)}") from e
-        return values
-
    def _setup_for_evaluating(self) -> None:
        """Sets up the crew for evaluating."""
        for task in self.crew.tasks:
@@ -106,7 +51,7 @@ class CrewEvaluator(BaseModel):
            ),
            backstory="Evaluator agent for crew evaluation with precise capabilities to evaluate the performance of the agents in the crew based on the tasks they have performed",
            verbose=False,
-            llm=self.llm,
+            llm=self.openai_model_name,
        )

    def _evaluation_task(
@@ -236,7 +181,7 @@ class CrewEvaluator(BaseModel):
                self.crew,
                evaluation_result.pydantic.quality,
                current_task._execution_time,
-                self.llm.model if isinstance(self.llm, LLM) else self.llm,
+                self.openai_model_name,
            )
            self.tasks_scores[self.iteration].append(evaluation_result.pydantic.quality)
            self.run_execution_times[self.iteration].append(
--- a/tests/cassettes/test_agent_human_input.yaml
+++ b/tests/cassettes/test_agent_human_input.yaml
@@ -1,87 +1,4 @@
 interactions:
- request:
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@@ -300,15 +300,6 @@ def test_hierarchical_process():
    )


-@mock.patch("crewai.crew.CrewEvaluator")
-@mock.patch("crewai.crew.Crew.copy")
-def test_crew_test_backward_compatibility(mock_copy, mock_evaluator):
-    crew = Crew(agents=[researcher], tasks=[Task(description="test", expected_output="test output", agent=researcher)])
-    crew.test(2, openai_model_name="gpt-4")
-    mock_evaluator.assert_called_once()
-    _, kwargs = mock_evaluator.call_args
-    assert kwargs["llm"] == "gpt-4"
-
 def test_manager_llm_requirement_for_hierarchical_process():
    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.",
@@ -1132,7 +1123,7 @@ def test_kickoff_for_each_empty_input():
    assert results == []


-@pytest.mark.vcr(filter_headeruvs=["authorization"])
+@pytest.mark.vcr(filter_headers=["authorization"])
 def test_kickoff_for_each_invalid_input():
    """Tests if kickoff_for_each raises TypeError for invalid input types."""

@@ -2846,7 +2837,7 @@ def test_crew_testing_function(kickoff_mock, copy_mock, crew_evaluator):

    crew_evaluator.assert_has_calls(
        [
-            mock.call(crew, llm="gpt-4o-mini"),
+            mock.call(crew, "gpt-4o-mini"),
            mock.call().set_iteration(1),
            mock.call().set_iteration(2),
            mock.call().print_crew_evaluation_result(),
@@ -3134,4 +3125,4 @@ def test_multimodal_agent_live_image_analysis():
    # Verify we got a meaningful response
    assert isinstance(result.raw, str)
    assert len(result.raw) > 100  # Expecting a detailed analysis
-    assert "error" not in result.raw.lower()  # No error messages in response
+    assert "error" not in result.raw.lower()  # No error messages in response
--- a/tests/test_task_decomposition.py
+++ b/tests/test_task_decomposition.py
@@ -0,0 +1,157 @@
+import pytest
+from unittest.mock import Mock, patch
+
+from crewai import Agent, Task
+
+
+def test_task_decomposition_structure():
+    """Test that task decomposition creates the proper parent-child relationship."""
+    agent = Agent(
+        role="Researcher",
+        goal="Research effectively",
+        backstory="You're an expert researcher",
+    )
+    
+    parent_task = Task(
+        description="Research the impact of AI on various industries",
+        expected_output="A comprehensive report",
+        agent=agent,
+    )
+    
+    sub_task_descriptions = [
+        "Research AI impact on healthcare",
+        "Research AI impact on finance",
+        "Research AI impact on education",
+    ]
+    
+    sub_tasks = parent_task.decompose(
+        descriptions=sub_task_descriptions,
+        expected_outputs=["Healthcare report", "Finance report", "Education report"],
+        names=["Healthcare", "Finance", "Education"],
+    )
+    
+    assert len(sub_tasks) == 3
+    assert len(parent_task.sub_tasks) == 3
+    
+    for sub_task in sub_tasks:
+        assert sub_task.parent_task == parent_task
+        assert parent_task in sub_task.context
+
+
+def test_task_execution_with_sub_tasks():
+    """Test that executing a task with sub-tasks executes the sub-tasks first."""
+    agent = Agent(
+        role="Researcher",
+        goal="Research effectively",
+        backstory="You're an expert researcher",
+    )
+    
+    parent_task = Task(
+        description="Research the impact of AI on various industries",
+        expected_output="A comprehensive report",
+        agent=agent,
+    )
+    
+    sub_task_descriptions = [
+        "Research AI impact on healthcare",
+        "Research AI impact on finance",
+        "Research AI impact on education",
+    ]
+    
+    parent_task.decompose(
+        descriptions=sub_task_descriptions,
+        expected_outputs=["Healthcare report", "Finance report", "Education report"],
+    )
+    
+    with patch.object(Agent, 'execute_task', return_value="Mock result") as mock_execute_task:
+        result = parent_task.execute_sync()
+        
+        assert mock_execute_task.call_count >= 3
+        
+        for sub_task in parent_task.sub_tasks:
+            assert sub_task.output is not None
+        
+        assert result is not None
+        assert result.raw is not None
+
+
+def test_combine_sub_task_results():
+    """Test that combining sub-task results works correctly."""
+    agent = Agent(
+        role="Researcher",
+        goal="Research effectively",
+        backstory="You're an expert researcher",
+    )
+    
+    parent_task = Task(
+        description="Research the impact of AI on various industries",
+        expected_output="A comprehensive report",
+        agent=agent,
+    )
+    
+    sub_tasks = parent_task.decompose([
+        "Research AI impact on healthcare",
+        "Research AI impact on finance",
+    ])
+    
+    for sub_task in sub_tasks:
+        sub_task.output = Mock()
+        sub_task.output.raw = f"Result for {sub_task.description}"
+    
+    with patch.object(Agent, 'execute_task', return_value="Combined result") as mock_execute_task:
+        result = parent_task.combine_sub_task_results()
+        
+        assert mock_execute_task.called
+        assert result == "Combined result"
+
+
+def test_task_decomposition_validation():
+    """Test that task decomposition validates inputs correctly."""
+    parent_task = Task(
+        description="Research the impact of AI",
+        expected_output="A report",
+    )
+    
+    with pytest.raises(ValueError, match="At least one sub-task description is required"):
+        parent_task.decompose([])
+    
+    with pytest.raises(ValueError, match="expected_outputs must have the same length"):
+        parent_task.decompose(
+            ["Task 1", "Task 2"], 
+            expected_outputs=["Output 1"]
+        )
+    
+    with pytest.raises(ValueError, match="names must have the same length"):
+        parent_task.decompose(
+            ["Task 1", "Task 2"], 
+            names=["Name 1"]
+        )
+
+
+def test_execute_sub_tasks_async():
+    """Test that executing sub-tasks asynchronously works correctly."""
+    agent = Agent(
+        role="Researcher",
+        goal="Research effectively",
+        backstory="You're an expert researcher",
+    )
+    
+    parent_task = Task(
+        description="Research the impact of AI on various industries",
+        expected_output="A comprehensive report",
+        agent=agent,
+    )
+    
+    sub_tasks = parent_task.decompose([
+        "Research AI impact on healthcare",
+        "Research AI impact on finance",
+    ])
+    
+    with patch.object(Task, 'execute_async') as mock_execute_async:
+        mock_future = Mock()
+        mock_execute_async.return_value = mock_future
+        
+        futures = parent_task.execute_sub_tasks_async()
+        
+        assert mock_execute_async.call_count == 2
+        assert len(futures) == 2
--- a/tests/test_task_decomposition_edge_cases.py
+++ b/tests/test_task_decomposition_edge_cases.py
@@ -0,0 +1,109 @@
+import pytest
+from unittest.mock import Mock, patch
+
+from crewai import Agent, Task, TaskOutput
+
+
+def test_combine_sub_task_results_no_sub_tasks():
+    """Test that combining sub-task results raises an error when there are no sub-tasks."""
+    agent = Agent(
+        role="Researcher",
+        goal="Research effectively",
+        backstory="You're an expert researcher",
+    )
+    
+    parent_task = Task(
+        description="Research the impact of AI",
+        expected_output="A report",
+        agent=agent,
+    )
+    
+    with pytest.raises(ValueError, match="Task has no sub-tasks to combine results from"):
+        parent_task.combine_sub_task_results()
+
+
+def test_combine_sub_task_results_no_agent():
+    """Test that combining sub-task results raises an error when there is no agent."""
+    parent_task = Task(
+        description="Research the impact of AI",
+        expected_output="A report",
+    )
+    
+    sub_task = Task(
+        description="Research AI impact on healthcare",
+        expected_output="Healthcare report",
+        parent_task=parent_task,
+    )
+    parent_task.sub_tasks.append(sub_task)
+    
+    with pytest.raises(ValueError, match="Task has no agent to combine sub-task results"):
+        parent_task.combine_sub_task_results()
+
+
+def test_execute_sync_sets_output_after_combining():
+    """Test that execute_sync sets the output after combining sub-task results."""
+    agent = Agent(
+        role="Researcher",
+        goal="Research effectively",
+        backstory="You're an expert researcher",
+    )
+    
+    parent_task = Task(
+        description="Research the impact of AI",
+        expected_output="A report",
+        agent=agent,
+    )
+    
+    sub_tasks = parent_task.decompose([
+        "Research AI impact on healthcare",
+        "Research AI impact on finance",
+    ])
+    
+    with patch.object(Agent, 'execute_task', return_value="Combined result") as mock_execute_task:
+        result = parent_task.execute_sync()
+        
+        assert parent_task.output is not None
+        assert parent_task.output.raw == "Combined result"
+        assert result.raw == "Combined result"
+        
+        assert mock_execute_task.call_count >= 3
+
+
+def test_deep_cloning_prevents_shared_state():
+    """Test that deep cloning prevents shared mutable state between tasks."""
+    agent = Agent(
+        role="Researcher",
+        goal="Research effectively",
+        backstory="You're an expert researcher",
+    )
+    
+    parent_task = Task(
+        description="Research the impact of AI",
+        expected_output="A report",
+        agent=agent,
+    )
+    
+    copied_task = parent_task.copy()
+    
+    copied_task.description = "Modified description"
+    
+    assert parent_task.description == "Research the impact of AI"
+    assert copied_task.description == "Modified description"
+    
+    parent_task.decompose(["Sub-task 1", "Sub-task 2"])
+    
+    assert len(parent_task.sub_tasks) == 2
+    assert len(copied_task.sub_tasks) == 0
+
+
+def test_execute_sub_tasks_async_empty_sub_tasks():
+    """Test that execute_sub_tasks_async returns an empty list when there are no sub-tasks."""
+    parent_task = Task(
+        description="Research the impact of AI",
+        expected_output="A report",
+    )
+    
+    futures = parent_task.execute_sub_tasks_async()
+    
+    assert isinstance(futures, list)
+    assert len(futures) == 0
--- a/tests/utilities/evaluators/test_crew_evaluator_handler.py
+++ b/tests/utilities/evaluators/test_crew_evaluator_handler.py
@@ -4,7 +4,6 @@ import pytest

 from crewai.agent import Agent
 from crewai.crew import Crew
-from crewai.llm import LLM
 from crewai.task import Task
 from crewai.tasks.task_output import TaskOutput
 from crewai.utilities.evaluators.crew_evaluator_handler import (
@@ -24,7 +23,7 @@ class TestCrewEvaluator:
        )
        crew = Crew(agents=[agent], tasks=[task])

-        return CrewEvaluator(crew, llm="gpt-4o-mini")
+        return CrewEvaluator(crew, openai_model_name="gpt-4o-mini")

    def test_setup_for_evaluating(self, crew_planner):
        crew_planner._setup_for_evaluating()
@@ -47,7 +46,6 @@ class TestCrewEvaluator:
        )
        assert agent.verbose is False
        assert agent.llm.model == "gpt-4o-mini"
-        assert isinstance(agent.llm, LLM)

    def test_evaluation_task(self, crew_planner):
        evaluator_agent = Agent(
@@ -133,17 +131,6 @@ class TestCrewEvaluator:
        # Ensure the console prints the table
        console.assert_has_calls([mock.call(), mock.call().print(table())])

-    def test_custom_llm_support(self):
-        agent = Agent(role="Agent 1", goal="Goal 1", backstory="Backstory 1")
-        task = Task(description="Task 1", expected_output="Output 1", agent=agent)
-        crew = Crew(agents=[agent], tasks=[task])
-        
-        custom_llm = LLM(model="custom-model")
-        evaluator = CrewEvaluator(crew, llm=custom_llm)
-        
-        assert evaluator.llm.model == "custom-model"
-        assert isinstance(evaluator.llm, LLM)
-
    def test_evaluate(self, crew_planner):
        task_output = TaskOutput(
            description="Task 1", agent=str(crew_planner.crew.agents[0])
--- a/uv.lock
+++ b/uv.lock
@@ -1,18 +1,10 @@
 version = 1
 requires-python = ">=3.10, <3.13"
 resolution-markers = [
-    "python_full_version < '3.11' and sys_platform == 'darwin'",
-    "python_full_version < '3.11' and platform_machine == 'aarch64' and sys_platform == 'linux'",
-    "(python_full_version < '3.11' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version < '3.11' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version == '3.11.*' and sys_platform == 'darwin'",
-    "python_full_version == '3.11.*' and platform_machine == 'aarch64' and sys_platform == 'linux'",
-    "(python_full_version == '3.11.*' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version == '3.11.*' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
-    "(python_full_version >= '3.12' and python_full_version < '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12' and python_full_version < '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
-    "python_full_version >= '3.12.4' and sys_platform == 'darwin'",
-    "python_full_version >= '3.12.4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
-    "(python_full_version >= '3.12.4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.12.4' and sys_platform != 'darwin' and sys_platform != 'linux')",
+    "python_full_version < '3.11'",
+    "python_full_version == '3.11.*'",
+    "python_full_version >= '3.12' and python_full_version < '3.12.4'",
+    "python_full_version >= '3.12.4'",
 ]

 [[package]]
@@ -308,7 +300,7 @@ name = "build"
 version = "1.2.2.post1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "colorama", marker = "(os_name == 'nt' and platform_machine != 'aarch64' and sys_platform == 'linux') or (os_name == 'nt' and sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "colorama", marker = "os_name == 'nt'" },
    { name = "importlib-metadata", marker = "python_full_version < '3.10.2'" },
    { name = "packaging" },
    { name = "pyproject-hooks" },
@@ -543,7 +535,7 @@ name = "click"
 version = "8.1.7"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "colorama", marker = "sys_platform == 'win32'" },
+    { name = "colorama", marker = "platform_system == 'Windows'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/96/d3/f04c7bfcf5c1862a2a5b845c6b2b360488cf47af55dfa79c98f6a6bf98b5/click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de", size = 336121 }
 wheels = [
@@ -650,6 +642,7 @@ tools = [
 [package.dev-dependencies]
 dev = [
    { name = "cairosvg" },
+    { name = "crewai-tools" },
    { name = "mkdocs" },
    { name = "mkdocs-material" },
    { name = "mkdocs-material-extensions" },
@@ -703,6 +696,7 @@ requires-dist = [
 [package.metadata.requires-dev]
 dev = [
    { name = "cairosvg", specifier = ">=2.7.1" },
+    { name = "crewai-tools", specifier = ">=0.17.0" },
    { name = "mkdocs", specifier = ">=1.4.3" },
    { name = "mkdocs-material", specifier = ">=9.5.7" },
    { name = "mkdocs-material-extensions", specifier = ">=1.3.1" },
@@ -2468,7 +2462,7 @@ version = "1.6.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "click" },
-    { name = "colorama", marker = "sys_platform == 'win32'" },
+    { name = "colorama", marker = "platform_system == 'Windows'" },
    { name = "ghp-import" },
    { name = "jinja2" },
    { name = "markdown" },
@@ -2649,7 +2643,7 @@ version = "2.10.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "pygments" },
-    { name = "pywin32", marker = "sys_platform == 'win32'" },
+    { name = "pywin32", marker = "platform_system == 'Windows'" },
    { name = "tqdm" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/3a/93/80ac75c20ce54c785648b4ed363c88f148bf22637e10c9863db4fbe73e74/mpire-2.10.2.tar.gz", hash = "sha256:f66a321e93fadff34585a4bfa05e95bd946cf714b442f51c529038eb45773d97", size = 271270 }
@@ -2896,7 +2890,7 @@ name = "nvidia-cudnn-cu12"
 version = "9.1.0.70"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
 ]
 wheels = [
    { url = "https://files.pythonhosted.org/packages/9f/fd/713452cd72343f682b1c7b9321e23829f00b842ceaedcda96e742ea0b0b3/nvidia_cudnn_cu12-9.1.0.70-py3-none-manylinux2014_x86_64.whl", hash = "sha256:165764f44ef8c61fcdfdfdbe769d687e06374059fbb388b6c89ecb0e28793a6f", size = 664752741 },
@@ -2923,9 +2917,9 @@ name = "nvidia-cusolver-cu12"
 version = "11.4.5.107"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
-    { name = "nvidia-cusparse-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
-    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "nvidia-cublas-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
+    { name = "nvidia-cusparse-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
+    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
 ]
 wheels = [
    { url = "https://files.pythonhosted.org/packages/bc/1d/8de1e5c67099015c834315e333911273a8c6aaba78923dd1d1e25fc5f217/nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl", hash = "sha256:8a7ec542f0412294b15072fa7dab71d31334014a69f953004ea7a118206fe0dd", size = 124161928 },
@@ -2936,7 +2930,7 @@ name = "nvidia-cusparse-cu12"
 version = "12.1.0.106"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "nvidia-nvjitlink-cu12", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
 ]
 wheels = [
    { url = "https://files.pythonhosted.org/packages/65/5b/cfaeebf25cd9fdec14338ccb16f6b2c4c7fa9163aefcf057d86b9cc248bb/nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl", hash = "sha256:f3b50f42cf363f86ab21f720998517a659a48131e8d538dc02f8768237bd884c", size = 195958278 },
@@ -3486,7 +3480,7 @@ name = "portalocker"
 version = "2.10.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "pywin32", marker = "sys_platform == 'win32'" },
+    { name = "pywin32", marker = "platform_system == 'Windows'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/ed/d3/c6c64067759e87af98cc668c1cc75171347d0f1577fab7ca3749134e3cd4/portalocker-2.10.1.tar.gz", hash = "sha256:ef1bf844e878ab08aee7e40184156e1151f228f103aa5c6bd0724cc330960f8f", size = 40891 }
 wheels = [
@@ -5028,19 +5022,19 @@ dependencies = [
    { name = "fsspec" },
    { name = "jinja2" },
    { name = "networkx" },
-    { name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cusolver-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-cusparse-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
-    { name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
+    { name = "nvidia-cublas-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cuda-cupti-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cuda-nvrtc-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cuda-runtime-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cudnn-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cufft-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-curand-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cusolver-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-cusparse-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-nccl-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
+    { name = "nvidia-nvtx-cu12", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
    { name = "sympy" },
-    { name = "triton", marker = "platform_machine == 'x86_64' and sys_platform == 'linux'" },
+    { name = "triton", marker = "platform_machine == 'x86_64' and platform_system == 'Linux'" },
    { name = "typing-extensions" },
 ]
 wheels = [
@@ -5087,7 +5081,7 @@ name = "tqdm"
 version = "4.66.5"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "colorama", marker = "sys_platform == 'win32'" },
+    { name = "colorama", marker = "platform_system == 'Windows'" },
 ]
 sdist = { url = "https://files.pythonhosted.org/packages/58/83/6ba9844a41128c62e810fddddd72473201f3eacde02046066142a2d96cc5/tqdm-4.66.5.tar.gz", hash = "sha256:e1020aef2e5096702d8a025ac7d16b1577279c9d63f8375b63083e9a5f0fcbad", size = 169504 }
 wheels = [
@@ -5130,7 +5124,7 @@ version = "0.27.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
    { name = "attrs" },
-    { name = "cffi", marker = "(implementation_name != 'pypy' and os_name == 'nt' and platform_machine != 'aarch64' and sys_platform == 'linux') or (implementation_name != 'pypy' and os_name == 'nt' and sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "cffi", marker = "implementation_name != 'pypy' and os_name == 'nt'" },
    { name = "exceptiongroup", marker = "python_full_version < '3.11'" },
    { name = "idna" },
    { name = "outcome" },
@@ -5161,7 +5155,7 @@ name = "triton"
 version = "3.0.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
-    { name = "filelock", marker = "(platform_machine != 'aarch64' and sys_platform == 'linux') or (sys_platform != 'darwin' and sys_platform != 'linux')" },
+    { name = "filelock", marker = "(platform_machine != 'aarch64' and platform_system != 'Darwin') or (platform_system != 'Darwin' and platform_system != 'Linux')" },
 ]
 wheels = [
    { url = "https://files.pythonhosted.org/packages/45/27/14cc3101409b9b4b9241d2ba7deaa93535a217a211c86c4cc7151fb12181/triton-3.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:e1efef76935b2febc365bfadf74bcb65a6f959a9872e5bddf44cc9e0adce1e1a", size = 209376304 },