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feat: Implement formal responsibility tracking system for CrewAI
- Add capability-based agent hierarchy with mathematical scoring - Implement responsibility assignment algorithms (greedy, balanced, optimal) - Add comprehensive accountability logging and tracking - Implement performance-based capability adjustment with learning rates - Integrate with existing Agent and Crew classes seamlessly - Add 58 comprehensive tests covering all functionality - Include example usage demonstrating all features Addresses issue #3491 with four key features: 1. Capability-Based Agent Hierarchy 2. Mathematical Responsibility Assignment 3. Accountability Logging 4. Performance-Based Capability Adjustment The system is fully backward compatible and optional - existing crews continue to work without modification. Co-Authored-By: João <joao@crewai.com>
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Devin AI
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examples/responsibility_tracking_example.py
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297
examples/responsibility_tracking_example.py
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"""
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Example demonstrating the formal responsibility tracking system in CrewAI.
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This example shows how to:
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1. Set up agents with capabilities
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2. Use responsibility-based task assignment
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3. Monitor accountability and performance
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4. Generate system insights and recommendations
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"""
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from crewai import Agent, Crew, Task
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from crewai.responsibility.models import AgentCapability, CapabilityType, TaskRequirement
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from crewai.responsibility.system import ResponsibilitySystem
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from crewai.responsibility.assignment import AssignmentStrategy
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def create_agents_with_capabilities():
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"""Create agents with defined capabilities."""
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python_capabilities = [
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AgentCapability(
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name="Python Programming",
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capability_type=CapabilityType.TECHNICAL,
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proficiency_level=0.9,
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confidence_score=0.8,
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description="Expert in Python development and scripting",
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keywords=["python", "programming", "development", "scripting"]
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),
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AgentCapability(
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name="Web Development",
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capability_type=CapabilityType.TECHNICAL,
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proficiency_level=0.7,
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confidence_score=0.7,
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description="Experience with web frameworks",
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keywords=["web", "flask", "django", "fastapi"]
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)
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]
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python_agent = Agent(
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role="Python Developer",
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goal="Develop high-quality Python applications and scripts",
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backstory="Experienced Python developer with expertise in various frameworks",
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capabilities=python_capabilities
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)
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analysis_capabilities = [
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AgentCapability(
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name="Data Analysis",
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capability_type=CapabilityType.ANALYTICAL,
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proficiency_level=0.9,
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confidence_score=0.9,
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description="Expert in statistical analysis and data interpretation",
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keywords=["data", "analysis", "statistics", "pandas", "numpy"]
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),
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AgentCapability(
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name="Machine Learning",
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capability_type=CapabilityType.ANALYTICAL,
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proficiency_level=0.8,
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confidence_score=0.7,
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description="Experience with ML algorithms and model building",
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keywords=["machine learning", "ml", "scikit-learn", "tensorflow"]
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)
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]
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analyst_agent = Agent(
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role="Data Analyst",
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goal="Extract insights from data and build predictive models",
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backstory="Data scientist with strong statistical background",
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capabilities=analysis_capabilities
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)
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management_capabilities = [
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AgentCapability(
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name="Project Management",
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capability_type=CapabilityType.LEADERSHIP,
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proficiency_level=0.8,
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confidence_score=0.9,
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description="Experienced in managing technical projects",
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keywords=["project management", "coordination", "planning"]
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),
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AgentCapability(
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name="Communication",
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capability_type=CapabilityType.COMMUNICATION,
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proficiency_level=0.9,
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confidence_score=0.8,
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description="Excellent communication and coordination skills",
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keywords=["communication", "coordination", "stakeholder management"]
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)
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]
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manager_agent = Agent(
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role="Project Manager",
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goal="Coordinate team efforts and ensure project success",
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backstory="Experienced project manager with technical background",
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capabilities=management_capabilities
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)
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return [python_agent, analyst_agent, manager_agent]
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def create_tasks_with_requirements():
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"""Create tasks with specific capability requirements."""
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data_processing_requirements = [
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TaskRequirement(
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capability_name="Python Programming",
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capability_type=CapabilityType.TECHNICAL,
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minimum_proficiency=0.7,
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weight=1.0,
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keywords=["python", "programming"]
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),
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TaskRequirement(
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capability_name="Data Analysis",
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capability_type=CapabilityType.ANALYTICAL,
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minimum_proficiency=0.6,
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weight=0.8,
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keywords=["data", "analysis"]
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)
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]
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data_task = Task(
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description="Create a Python script to process and analyze customer data",
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expected_output="A Python script that processes CSV data and generates summary statistics"
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)
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web_dashboard_requirements = [
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TaskRequirement(
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capability_name="Web Development",
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capability_type=CapabilityType.TECHNICAL,
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minimum_proficiency=0.6,
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weight=1.0,
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keywords=["web", "development"]
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),
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TaskRequirement(
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capability_name="Python Programming",
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capability_type=CapabilityType.TECHNICAL,
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minimum_proficiency=0.5,
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weight=0.7,
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keywords=["python", "programming"]
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)
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]
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web_task = Task(
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description="Create a web dashboard to visualize data analysis results",
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expected_output="A web application with interactive charts and data visualization"
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)
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coordination_requirements = [
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TaskRequirement(
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capability_name="Project Management",
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capability_type=CapabilityType.LEADERSHIP,
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minimum_proficiency=0.7,
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weight=1.0,
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keywords=["project management", "coordination"]
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),
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TaskRequirement(
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capability_name="Communication",
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capability_type=CapabilityType.COMMUNICATION,
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minimum_proficiency=0.8,
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weight=0.9,
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keywords=["communication", "coordination"]
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)
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]
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coordination_task = Task(
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description="Coordinate the team efforts and ensure project milestones are met",
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expected_output="Project status report with timeline and deliverable tracking"
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)
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return [
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(data_task, data_processing_requirements),
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(web_task, web_dashboard_requirements),
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(coordination_task, coordination_requirements)
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]
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def demonstrate_responsibility_tracking():
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"""Demonstrate the complete responsibility tracking workflow."""
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print("🚀 CrewAI Formal Responsibility Tracking System Demo")
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print("=" * 60)
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print("\n1. Creating agents with defined capabilities...")
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agents = create_agents_with_capabilities()
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for agent in agents:
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print(f" ✓ {agent.role}: {len(agent.capabilities)} capabilities")
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print("\n2. Setting up crew with responsibility tracking...")
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crew = Crew(
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agents=agents,
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tasks=[],
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verbose=True
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)
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responsibility_system = crew.responsibility_system
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print(f" ✓ Responsibility system enabled: {responsibility_system.enabled}")
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print("\n3. System overview:")
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overview = responsibility_system.get_system_overview()
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print(f" • Total agents: {overview['total_agents']}")
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print(f" • Capability distribution: {overview['capability_distribution']}")
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print("\n4. Creating tasks with capability requirements...")
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tasks_with_requirements = create_tasks_with_requirements()
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print("\n5. Demonstrating responsibility assignment strategies...")
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for i, (task, requirements) in enumerate(tasks_with_requirements):
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print(f"\n Task {i+1}: {task.description[:50]}...")
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for strategy in [AssignmentStrategy.GREEDY, AssignmentStrategy.BALANCED, AssignmentStrategy.OPTIMAL]:
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assignment = responsibility_system.assign_task_responsibility(
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task, requirements, strategy
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)
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if assignment:
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agent = responsibility_system._get_agent_by_id(assignment.agent_id)
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print(f" • {strategy.value}: {agent.role} (score: {assignment.responsibility_score:.3f})")
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print(f" Capabilities matched: {', '.join(assignment.capability_matches)}")
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responsibility_system.complete_task(
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agent=agent,
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task=task,
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success=True,
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completion_time=1800.0,
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quality_score=0.85,
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outcome_description="Task completed successfully"
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)
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else:
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print(f" • {strategy.value}: No suitable agent found")
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print("\n6. Agent status and performance:")
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for agent in agents:
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status = responsibility_system.get_agent_status(agent)
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print(f"\n {agent.role}:")
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print(f" • Current workload: {status['current_workload']}")
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if status['performance']:
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perf = status['performance']
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print(f" • Success rate: {perf['success_rate']:.2f}")
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print(f" • Quality score: {perf['quality_score']:.2f}")
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print(f" • Total tasks: {perf['total_tasks']}")
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print("\n7. Accountability tracking:")
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for agent in agents:
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report = responsibility_system.accountability.generate_accountability_report(agent=agent)
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if report['total_records'] > 0:
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print(f"\n {agent.role} accountability:")
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print(f" • Total records: {report['total_records']}")
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print(f" • Action types: {list(report['action_counts'].keys())}")
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print(f" • Recent actions: {len(report['recent_actions'])}")
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print("\n8. System recommendations:")
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recommendations = responsibility_system.generate_recommendations()
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if recommendations:
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for rec in recommendations:
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print(f" • {rec['type']}: {rec['description']} (Priority: {rec['priority']})")
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else:
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print(" • No recommendations at this time")
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print("\n9. Demonstrating task delegation:")
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if len(agents) >= 2:
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delegation_task = Task(
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description="Complex task requiring delegation",
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expected_output="Delegated task completion report"
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)
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responsibility_system.delegate_task(
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delegating_agent=agents[0],
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receiving_agent=agents[1],
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task=delegation_task,
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reason="Specialized expertise required"
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)
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print(f" ✓ Delegated task from {agents[0].role} to {agents[1].role}")
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delegation_records = responsibility_system.accountability.get_delegation_chain(delegation_task)
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print(f" • Delegation chain length: {len(delegation_records)}")
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print("\n" + "=" * 60)
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print("🎉 Responsibility tracking demonstration completed!")
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print("\nKey features demonstrated:")
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print("• Capability-based agent hierarchy")
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print("• Mathematical responsibility assignment")
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print("• Accountability logging")
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print("• Performance-based capability adjustment")
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if __name__ == "__main__":
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try:
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demonstrate_responsibility_tracking()
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print("\n✅ All demonstrations completed successfully!")
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except Exception as e:
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print(f"\n❌ Error during demonstration: {str(e)}")
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import traceback
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traceback.print_exc()
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