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3 Commits

Author SHA1 Message Date
Devin AI
3c1bcbe072 fix: correct event handler signatures to match event bus expectations
- Add source parameter to all event handler methods
- Handlers now match expected signature: Callable[[Any, EventTypes], None]
- Fixes remaining type-checker CI failures

Co-Authored-By: João <joao@crewai.com>
2025-08-03 17:23:25 +00:00
Devin AI
e4ba3f4c4c fix: resolve CI failures - remove unused imports and fix event bus registration
- Remove unused typing imports from execution_trace.py and execution_trace_collector.py
- Fix event bus registration by removing unregister_handler calls (method doesn't exist)
- Remove storing handler references since register_handler returns None
- Addresses lint and type-checker CI failures

Co-Authored-By: João <joao@crewai.com>
2025-08-03 17:20:37 +00:00
Devin AI
58fb717ab2 feat: implement execution tracing functionality for CrewAI
- Add ExecutionStep and ExecutionTrace models to track crew execution steps
- Add ExecutionTraceCollector to capture events and build execution traces
- Add trace_execution parameter to Crew class (disabled by default)
- Add execution_trace field to CrewOutput to return trace data
- Integrate trace collection into crew.kickoff() method
- Add comprehensive tests covering execution tracing functionality
- Add example demonstrating how to use execution tracing
- Export new classes in __init__.py

Addresses issue #3268: Users can now track the sequence of steps/actions
that a crew takes to complete a goal, including agent thoughts, tool calls,
and intermediate results, similar to LangGraph's conversation state.

Co-Authored-By: João <joao@crewai.com>
2025-08-03 17:13:03 +00:00
7 changed files with 566 additions and 0 deletions

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@@ -0,0 +1,49 @@
from crewai import Agent, Crew, Task, Process, LLM
researcher = Agent(
role="Researcher",
goal="Research and analyze information",
backstory="You are an expert researcher with years of experience.",
llm=LLM(model="gpt-4o-mini")
)
writer = Agent(
role="Writer",
goal="Write compelling content",
backstory="You are a skilled writer who creates engaging content.",
llm=LLM(model="gpt-4o-mini")
)
research_task = Task(
description="Research the latest trends in AI",
expected_output="A comprehensive report on AI trends",
agent=researcher
)
writing_task = Task(
description="Write an article based on the research",
expected_output="A well-written article about AI trends",
agent=writer
)
crew = Crew(
agents=[researcher, writer],
tasks=[research_task, writing_task],
process=Process.sequential,
trace_execution=True
)
result = crew.kickoff(inputs={"topic": "artificial intelligence"})
if result.execution_trace:
print(f"Total execution steps: {result.execution_trace.total_steps}")
print(f"Execution duration: {result.execution_trace.end_time - result.execution_trace.start_time}")
thoughts = result.execution_trace.get_steps_by_type("agent_thought")
print(f"Agent thoughts captured: {len(thoughts)}")
tool_calls = result.execution_trace.get_steps_by_type("tool_call_started")
print(f"Tool calls made: {len(tool_calls)}")
for step in result.execution_trace.steps:
print(f"{step.timestamp}: {step.step_type} - {step.agent_role or 'System'}")

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@@ -5,6 +5,7 @@ import urllib.request
from crewai.agent import Agent
from crewai.crew import Crew
from crewai.crews.crew_output import CrewOutput
from crewai.crews.execution_trace import ExecutionTrace, ExecutionStep
from crewai.flow.flow import Flow
from crewai.knowledge.knowledge import Knowledge
from crewai.llm import LLM
@@ -59,6 +60,8 @@ __all__ = [
"Agent",
"Crew",
"CrewOutput",
"ExecutionTrace",
"ExecutionStep",
"Process",
"Task",
"LLM",

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@@ -81,6 +81,7 @@ from crewai.utilities.llm_utils import create_llm
from crewai.utilities.planning_handler import CrewPlanner
from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler
from crewai.utilities.training_handler import CrewTrainingHandler
from crewai.utilities.execution_trace_collector import ExecutionTraceCollector
warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
@@ -205,6 +206,9 @@ class Crew(FlowTrackable, BaseModel):
default_factory=list,
description="List of callbacks to be executed after crew kickoff. It may be used to adjust the output of the crew.",
)
trace_execution: bool = Field(
default=False, description="Whether to trace the execution steps of the crew"
)
max_rpm: Optional[int] = Field(
default=None,
description="Maximum number of requests per minute for the crew execution to be respected.",
@@ -621,6 +625,11 @@ class Crew(FlowTrackable, BaseModel):
self,
inputs: Optional[Dict[str, Any]] = None,
) -> CrewOutput:
trace_collector = None
if self.trace_execution:
trace_collector = ExecutionTraceCollector()
trace_collector.start_collecting()
ctx = baggage.set_baggage(
"crew_context", CrewContext(id=str(self.id), key=self.key)
)
@@ -678,6 +687,10 @@ class Crew(FlowTrackable, BaseModel):
result = after_callback(result)
self.usage_metrics = self.calculate_usage_metrics()
if trace_collector:
execution_trace = trace_collector.stop_collecting()
result.execution_trace = execution_trace
return result
except Exception as e:
@@ -1086,6 +1099,7 @@ class Crew(FlowTrackable, BaseModel):
json_dict=final_task_output.json_dict,
tasks_output=task_outputs,
token_usage=token_usage,
execution_trace=None,
)
def _process_async_tasks(

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@@ -6,6 +6,7 @@ from pydantic import BaseModel, Field
from crewai.tasks.output_format import OutputFormat
from crewai.tasks.task_output import TaskOutput
from crewai.types.usage_metrics import UsageMetrics
from crewai.crews.execution_trace import ExecutionTrace
class CrewOutput(BaseModel):
@@ -22,6 +23,9 @@ class CrewOutput(BaseModel):
description="Output of each task", default=[]
)
token_usage: UsageMetrics = Field(description="Processed token summary", default={})
execution_trace: Optional[ExecutionTrace] = Field(
description="Detailed execution trace of crew steps", default=None
)
@property
def json(self) -> Optional[str]:

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@@ -0,0 +1,34 @@
from datetime import datetime
from typing import Any, Dict, List, Optional
from pydantic import BaseModel, Field
class ExecutionStep(BaseModel):
"""Represents a single step in the crew execution trace."""
timestamp: datetime = Field(description="When this step occurred")
step_type: str = Field(description="Type of step: agent_thought, tool_call, tool_result, task_start, task_complete, etc.")
agent_role: Optional[str] = Field(description="Role of the agent performing this step", default=None)
task_description: Optional[str] = Field(description="Description of the task being executed", default=None)
content: Dict[str, Any] = Field(description="Step-specific content (thought, tool args, result, etc.)", default_factory=dict)
metadata: Dict[str, Any] = Field(description="Additional metadata for this step", default_factory=dict)
class ExecutionTrace(BaseModel):
"""Complete execution trace for a crew run."""
steps: List[ExecutionStep] = Field(description="Ordered list of execution steps", default_factory=list)
total_steps: int = Field(description="Total number of steps in the trace", default=0)
start_time: Optional[datetime] = Field(description="When execution started", default=None)
end_time: Optional[datetime] = Field(description="When execution completed", default=None)
def add_step(self, step: ExecutionStep) -> None:
"""Add a step to the trace."""
self.steps.append(step)
self.total_steps = len(self.steps)
def get_steps_by_type(self, step_type: str) -> List[ExecutionStep]:
"""Get all steps of a specific type."""
return [step for step in self.steps if step.step_type == step_type]
def get_steps_by_agent(self, agent_role: str) -> List[ExecutionStep]:
"""Get all steps performed by a specific agent."""
return [step for step in self.steps if step.agent_role == agent_role]

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@@ -0,0 +1,152 @@
from datetime import datetime
from typing import Any
from crewai.crews.execution_trace import ExecutionStep, ExecutionTrace
from crewai.utilities.events.crewai_event_bus import crewai_event_bus
from crewai.utilities.events.agent_events import (
AgentExecutionStartedEvent,
AgentExecutionCompletedEvent,
AgentLogsExecutionEvent,
)
from crewai.utilities.events.tool_usage_events import (
ToolUsageStartedEvent,
ToolUsageFinishedEvent,
)
from crewai.utilities.events.task_events import (
TaskStartedEvent,
TaskCompletedEvent,
)
class ExecutionTraceCollector:
"""Collects execution events and builds an execution trace."""
def __init__(self):
self.trace = ExecutionTrace()
self.is_collecting = False
def start_collecting(self) -> None:
"""Start collecting execution events."""
self.is_collecting = True
self.trace = ExecutionTrace(start_time=datetime.now())
crewai_event_bus.register_handler(TaskStartedEvent, self._handle_task_started)
crewai_event_bus.register_handler(TaskCompletedEvent, self._handle_task_completed)
crewai_event_bus.register_handler(AgentExecutionStartedEvent, self._handle_agent_started)
crewai_event_bus.register_handler(AgentExecutionCompletedEvent, self._handle_agent_completed)
crewai_event_bus.register_handler(AgentLogsExecutionEvent, self._handle_agent_logs)
crewai_event_bus.register_handler(ToolUsageStartedEvent, self._handle_tool_started)
crewai_event_bus.register_handler(ToolUsageFinishedEvent, self._handle_tool_finished)
def stop_collecting(self) -> ExecutionTrace:
"""Stop collecting and return the execution trace."""
self.is_collecting = False
self.trace.end_time = datetime.now()
return self.trace
def _handle_agent_started(self, source: Any, event: AgentExecutionStartedEvent) -> None:
if not self.is_collecting:
return
step = ExecutionStep(
timestamp=datetime.now(),
step_type="agent_execution_started",
agent_role=event.agent.role if hasattr(event.agent, 'role') else None,
task_description=getattr(event.task, 'description', None) if event.task else None,
content={
"task_prompt": event.task_prompt,
"tools": [tool.name for tool in event.tools] if event.tools else [],
}
)
self.trace.add_step(step)
def _handle_agent_completed(self, source: Any, event: AgentExecutionCompletedEvent) -> None:
if not self.is_collecting:
return
step = ExecutionStep(
timestamp=datetime.now(),
step_type="agent_execution_completed",
agent_role=event.agent.role if hasattr(event.agent, 'role') else None,
content={
"output": event.output,
}
)
self.trace.add_step(step)
def _handle_agent_logs(self, source: Any, event: AgentLogsExecutionEvent) -> None:
if not self.is_collecting:
return
step = ExecutionStep(
timestamp=datetime.now(),
step_type="agent_thought",
agent_role=event.agent_role,
content={
"formatted_answer": str(event.formatted_answer),
}
)
self.trace.add_step(step)
def _handle_tool_started(self, source: Any, event: ToolUsageStartedEvent) -> None:
if not self.is_collecting:
return
step = ExecutionStep(
timestamp=datetime.now(),
step_type="tool_call_started",
agent_role=event.agent_role,
content={
"tool_name": event.tool_name,
"tool_args": event.tool_args,
"tool_class": event.tool_class,
}
)
self.trace.add_step(step)
def _handle_tool_finished(self, source: Any, event: ToolUsageFinishedEvent) -> None:
if not self.is_collecting:
return
step = ExecutionStep(
timestamp=datetime.now(),
step_type="tool_call_completed",
agent_role=event.agent_role,
content={
"tool_name": event.tool_name,
"output": event.output,
"from_cache": event.from_cache,
"duration": (event.finished_at - event.started_at).total_seconds() if hasattr(event, 'started_at') and hasattr(event, 'finished_at') else None,
}
)
self.trace.add_step(step)
def _handle_task_started(self, source: Any, event: TaskStartedEvent) -> None:
if not self.is_collecting:
return
step = ExecutionStep(
timestamp=datetime.now(),
step_type="task_started",
task_description=getattr(event.task, 'description', None) if hasattr(event, 'task') and event.task else None,
content={
"task_id": getattr(event.task, 'id', None) if hasattr(event, 'task') and event.task else None,
"context": getattr(event, 'context', None),
}
)
self.trace.add_step(step)
def _handle_task_completed(self, source: Any, event: TaskCompletedEvent) -> None:
if not self.is_collecting:
return
step = ExecutionStep(
timestamp=datetime.now(),
step_type="task_completed",
task_description=getattr(event.task, 'description', None) if hasattr(event, 'task') and event.task else None,
content={
"task_id": getattr(event.task, 'id', None) if hasattr(event, 'task') and event.task else None,
"output": event.output.raw if hasattr(event, 'output') and event.output else None,
}
)
self.trace.add_step(step)

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@@ -0,0 +1,310 @@
import pytest
from unittest.mock import Mock, patch
from datetime import datetime
from crewai import Agent, Crew, Task, Process
from crewai.crews.execution_trace import ExecutionStep, ExecutionTrace
from crewai.utilities.execution_trace_collector import ExecutionTraceCollector
from crewai.tools.base_tool import BaseTool
class MockTool(BaseTool):
name: str = "mock_tool"
description: str = "A mock tool for testing"
def _run(self, query: str) -> str:
return f"Mock result for: {query}"
@pytest.fixture
def mock_llm():
llm = Mock()
llm.call.return_value = "Test response"
llm.supports_stop_words.return_value = True
llm.stop = []
return llm
@pytest.fixture
def test_agent(mock_llm):
return Agent(
role="Test Agent",
goal="Test goal",
backstory="Test backstory",
llm=mock_llm,
tools=[MockTool()]
)
@pytest.fixture
def test_task(test_agent):
return Task(
description="Test task description",
expected_output="Test expected output",
agent=test_agent
)
def test_execution_step_creation():
"""Test creating an ExecutionStep."""
step = ExecutionStep(
timestamp=datetime.now(),
step_type="agent_thought",
agent_role="Test Agent",
task_description="Test task",
content={"thought": "I need to think about this"},
metadata={"iteration": 1}
)
assert step.step_type == "agent_thought"
assert step.agent_role == "Test Agent"
assert step.content["thought"] == "I need to think about this"
assert step.metadata["iteration"] == 1
def test_execution_trace_creation():
"""Test creating an ExecutionTrace."""
trace = ExecutionTrace()
step1 = ExecutionStep(
timestamp=datetime.now(),
step_type="task_started",
content={"task_id": "1"}
)
step2 = ExecutionStep(
timestamp=datetime.now(),
step_type="agent_thought",
agent_role="Test Agent",
content={"thought": "Starting work"}
)
trace.add_step(step1)
trace.add_step(step2)
assert trace.total_steps == 2
assert len(trace.steps) == 2
assert trace.get_steps_by_type("task_started") == [step1]
assert trace.get_steps_by_agent("Test Agent") == [step2]
def test_execution_trace_collector():
"""Test the ExecutionTraceCollector."""
collector = ExecutionTraceCollector()
collector.start_collecting()
assert collector.is_collecting is True
assert collector.trace.start_time is not None
trace = collector.stop_collecting()
assert collector.is_collecting is False
assert trace.end_time is not None
assert isinstance(trace, ExecutionTrace)
@patch('crewai.crew.crewai_event_bus')
def test_crew_with_execution_trace_enabled(mock_event_bus, test_agent, test_task, mock_llm):
"""Test crew execution with trace_execution=True."""
crew = Crew(
agents=[test_agent],
tasks=[test_task],
process=Process.sequential,
trace_execution=True
)
with patch.object(test_task, 'execute_sync') as mock_execute:
from crewai.tasks.task_output import TaskOutput
mock_output = TaskOutput(
description="Test task description",
raw="Test output",
agent="Test Agent"
)
mock_execute.return_value = mock_output
result = crew.kickoff()
assert result.execution_trace is not None
assert isinstance(result.execution_trace, ExecutionTrace)
assert result.execution_trace.start_time is not None
assert result.execution_trace.end_time is not None
@patch('crewai.crew.crewai_event_bus')
def test_crew_without_execution_trace(mock_event_bus, test_agent, test_task, mock_llm):
"""Test crew execution with trace_execution=False (default)."""
crew = Crew(
agents=[test_agent],
tasks=[test_task],
process=Process.sequential,
trace_execution=False
)
with patch.object(test_task, 'execute_sync') as mock_execute:
from crewai.tasks.task_output import TaskOutput
mock_output = TaskOutput(
description="Test task description",
raw="Test output",
agent="Test Agent"
)
mock_execute.return_value = mock_output
result = crew.kickoff()
assert result.execution_trace is None
def test_execution_trace_with_multiple_agents_and_tasks(mock_llm):
"""Test execution trace with multiple agents and tasks."""
agent1 = Agent(
role="Agent 1",
goal="Goal 1",
backstory="Backstory 1",
llm=mock_llm
)
agent2 = Agent(
role="Agent 2",
goal="Goal 2",
backstory="Backstory 2",
llm=mock_llm
)
task1 = Task(
description="Task 1",
expected_output="Output 1",
agent=agent1
)
task2 = Task(
description="Task 2",
expected_output="Output 2",
agent=agent2
)
crew = Crew(
agents=[agent1, agent2],
tasks=[task1, task2],
process=Process.sequential,
trace_execution=True
)
with patch.object(task1, 'execute_sync') as mock_execute1, \
patch.object(task2, 'execute_sync') as mock_execute2:
from crewai.tasks.task_output import TaskOutput
mock_output1 = TaskOutput(
description="Task 1",
raw="Output 1",
agent="Agent 1"
)
mock_output2 = TaskOutput(
description="Task 2",
raw="Output 2",
agent="Agent 2"
)
mock_execute1.return_value = mock_output1
mock_execute2.return_value = mock_output2
result = crew.kickoff()
assert result.execution_trace is not None
agent1_steps = result.execution_trace.get_steps_by_agent("Agent 1")
agent2_steps = result.execution_trace.get_steps_by_agent("Agent 2")
assert len(agent1_steps) >= 0
assert len(agent2_steps) >= 0
def test_execution_trace_step_types():
"""Test that different step types are properly categorized."""
trace = ExecutionTrace()
steps_data = [
("task_started", "Task 1", {}),
("agent_thought", "Agent 1", {"thought": "I need to analyze this"}),
("tool_call_started", "Agent 1", {"tool_name": "search", "args": {"query": "test"}}),
("tool_call_completed", "Agent 1", {"tool_name": "search", "output": "results"}),
("agent_execution_completed", "Agent 1", {"output": "Final answer"}),
("task_completed", "Task 1", {"output": "Task complete"}),
]
for step_type, agent_role, content in steps_data:
step = ExecutionStep(
timestamp=datetime.now(),
step_type=step_type,
agent_role=agent_role if "agent" in step_type or "tool" in step_type else None,
task_description="Task 1" if "task" in step_type else None,
content=content
)
trace.add_step(step)
assert len(trace.get_steps_by_type("task_started")) == 1
assert len(trace.get_steps_by_type("agent_thought")) == 1
assert len(trace.get_steps_by_type("tool_call_started")) == 1
assert len(trace.get_steps_by_type("tool_call_completed")) == 1
assert len(trace.get_steps_by_type("agent_execution_completed")) == 1
assert len(trace.get_steps_by_type("task_completed")) == 1
agent_steps = trace.get_steps_by_agent("Agent 1")
assert len(agent_steps) == 4
def test_execution_trace_with_async_tasks(mock_llm):
"""Test execution trace with async tasks."""
agent = Agent(
role="Async Agent",
goal="Async goal",
backstory="Async backstory",
llm=mock_llm
)
task = Task(
description="Async task",
expected_output="Async output",
agent=agent,
async_execution=True
)
crew = Crew(
agents=[agent],
tasks=[task],
process=Process.sequential,
trace_execution=True
)
with patch.object(task, 'execute_async') as mock_execute_async:
from concurrent.futures import Future
from crewai.tasks.task_output import TaskOutput
future = Future()
mock_output = TaskOutput(
description="Async task",
raw="Async output",
agent="Async Agent"
)
future.set_result(mock_output)
mock_execute_async.return_value = future
result = crew.kickoff()
assert result.execution_trace is not None
assert isinstance(result.execution_trace, ExecutionTrace)
def test_execution_trace_error_handling():
"""Test execution trace handles errors gracefully."""
collector = ExecutionTraceCollector()
collector.start_collecting()
mock_event = Mock()
mock_event.agent = Mock()
mock_event.agent.role = "Test Agent"
collector._handle_agent_started(mock_event)
trace = collector.stop_collecting()
assert isinstance(trace, ExecutionTrace)