// Agent System Demo: Using dist_agent_lang Syntax
// Demonstrating AI agent and workflow management capabilities
// Simplified to work with current language features
@trust("hybrid")
@chain("ethereum")
service AgentSystemDemo {
demo_agents: map<string, string> = {};
coordination_examples: map<string, any> = {};
fn initialize() {
log::info("agent_demo", {
"event": "initializing_agent_system_demo",
"message": "Demonstrating AI agent system with dist_agent_lang"
});
self.demo_agents = {};
self.coordination_examples = {};
// Initialize demo scenarios
self.setup_agent_lifecycle_demo();
self.setup_coordination_demo();
self.setup_communication_demo();
self.setup_evolution_demo();
}
fn setup_agent_lifecycle_demo() {
print("🔄 Agent Lifecycle Demo");
print("========================");
// Demonstrate agent creation using AI module
let agent_config = {
"name": "CodeAssistant",
"role": "Senior Software Architect",
"capabilities": "code_generation,architecture_design,testing,documentation",
"trust_level": "hybrid",
"learning_enabled": "true",
"communication_enabled": "true",
"coordination_enabled": "true",
"metadata": {
"specialization": "rust_development",
"experience_level": "expert",
"preferred_patterns": "async_await,builder_pattern,strategy_pattern"
}
};
// Create agent using AI module
let agent_instance = ai::create_agent(agent_config);
let coordinator = ai::create_agent_coordinator();
let agent_id = ai::add_agent_to_coordinator(coordinator, agent_instance);
print("✅ Created AI Agent: " + agent_id);
print(" - Type: AI Agent");
print(" - Role: Senior Software Architect");
print(" - Capabilities: Code Generation, Architecture Design, Testing");
print("");
// Store for later demonstrations
self.demo_agents["code_assistant"] = agent_id;
}
fn setup_coordination_demo() {
print("🤝 Agent Coordination Demo");
print("==========================");
// Create multiple agents for coordination
let analyst_config = {
"name": "DataAnalyst",
"role": "Data Analysis Specialist",
"capabilities": "data_analysis,pattern_recognition,insights_generation",
"trust_level": "hybrid"
};
let executor_config = {
"name": "TaskExecutor",
"role": "Task Execution Specialist",
"capabilities": "task_execution,automation,workflow_management",
"trust_level": "standard"
};
let coordinator = ai::create_agent_coordinator();
let analyst_instance = ai::create_agent(analyst_config);
let executor_instance = ai::create_agent(executor_config);
let analyst_id = ai::add_agent_to_coordinator(coordinator, analyst_instance);
let executor_id = ai::add_agent_to_coordinator(coordinator, executor_instance);
print("✅ Created Analyst Agent: " + analyst_id);
print("✅ Created Executor Agent: " + executor_id);
print("");
// Demonstrate coordination through workflow
let workflow_config = {
"workflow_id": "coordination_workflow_001",
"name": "Data Analysis Workflow",
"steps": "data_analysis,task_execution"
};
let workflow = ai::create_workflow(coordinator, workflow_config);
let coordination_result = ai::execute_workflow(coordinator, "coordination_workflow_001");
print("✅ Coordination Result: " + coordination_result);
print("");
// Store coordination example
let example_key = "coordination_" + analyst_id;
self.coordination_examples[example_key] = {
"analyst": analyst_id,
"executor": executor_id,
"task": "behavior_analysis",
"result": coordination_result
};
}
fn setup_communication_demo() {
print("💬 Agent Communication Demo");
print("===========================");
// Get agents from previous demos
let code_assistant = self.demo_agents["code_assistant"];
// Create a system agent for communication demo
let system_config = {
"name": "SystemMonitor",
"role": "System Monitoring Agent",
"capabilities": "monitoring,alerts,performance_tracking",
"trust_level": "standard"
};
let coordinator = ai::create_agent_coordinator();
let system_agent_instance = ai::create_agent(system_config);
let system_agent_id = ai::add_agent_to_coordinator(coordinator, system_agent_instance);
// Demonstrate structured communication through tasks
let task_id = ai::create_task(system_agent_id, "status_update", "Send system status update", {
"cpu_usage": "45",
"memory_usage": "67",
"active_tasks": "12",
"system_health": "good"
});
let message_result = ai::execute_task(system_agent_id, task_id);
print("✅ Communication Result: " + message_result);
print(" - From: System Monitor Agent");
print(" - To: Code Assistant Agent");
print(" - Type: Status Update");
print("");
}
fn setup_evolution_demo() {
print("🧬 Agent Evolution Demo");
print("=======================");
let base_agent_config = {
"name": "LearningAgent",
"role": "Adaptive Learning Agent",
"capabilities": "basic_learning,pattern_recognition",
"trust_level": "hybrid",
"learning_enabled": "true"
};
let coordinator = ai::create_agent_coordinator();
let learning_agent_instance = ai::create_agent(base_agent_config);
let learning_agent_id = ai::add_agent_to_coordinator(coordinator, learning_agent_instance);
// Demonstrate evolution through learning tasks
let evolution_task_id = ai::create_task(learning_agent_id, "learning", "Learn new capabilities", {
"new_capabilities": "advanced_analytics,predictive_modeling",
"improved_skills": "data_visualization,report_generation",
"performance_improvements": "response_time,accuracy,reliability",
"learning_context": {
"tasks_completed": "150",
"success_rate": "0.94",
"user_feedback": "excellent_adaptive_behavior"
}
});
let evolution_result = ai::execute_task(learning_agent_id, evolution_task_id);
print("✅ Evolution Result: " + evolution_result);
print(" - Base Capabilities: Basic Learning, Pattern Recognition");
print(" - New Capabilities: Advanced Analytics, Predictive Modeling");
print(" - Performance Improvements: Response Time, Accuracy, Reliability");
print("");
}
fn demonstrate_capability_validation() {
print("✅ Agent Capability Validation");
print("==============================");
// Test different agent types and their capabilities
let test_case1 = {
"agent_type": "ai",
"required_capabilities": "code_generation,architecture_design,testing",
"expected_result": "true"
};
let test_case2 = {
"agent_type": "system",
"required_capabilities": "monitoring,resource_management",
"expected_result": "true"
};
let test_case3 = {
"agent_type": "worker",
"required_capabilities": "task_execution,automation",
"expected_result": "true"
};
let test_case4 = {
"agent_type": "ai",
"required_capabilities": "advanced_quantum_computing,time_travel",
"expected_result": "false"
};
// Process first test case
let test_case = test_case1;
let agent_config = {
"name": "TestAgent",
"role": "Test Role",
"capabilities": test_case["required_capabilities"],
"trust_level": "standard"
};
try {
let coordinator = ai::create_agent_coordinator();
let agent_instance = ai::create_agent(agent_config);
let agent_id = ai::add_agent_to_coordinator(coordinator, agent_instance);
let status = "✅ PASS";
print(" " + status + " " + test_case["agent_type"] + " agent with capabilities: " + test_case["required_capabilities"]);
} catch (error) {
let status = "❌ FAIL";
print(" " + status + " " + test_case["agent_type"] + " agent with capabilities: " + test_case["required_capabilities"]);
}
print("");
}
fn demonstrate_task_management() {
print("📋 Task Management Demo");
print("========================");
// Create various types of tasks
let coordinator = ai::create_agent_coordinator();
let agent_instance = ai::create_agent({
"name": "TaskManager",
"role": "Task Management Specialist",
"capabilities": "task_management,automation",
"trust_level": "standard"
});
let agent_id = ai::add_agent_to_coordinator(coordinator, agent_instance);
// Create tasks individually
let task1 = ai::create_task(agent_id, "implementation", "Implement user authentication system", { "level": "high" });
let task2 = ai::create_task(agent_id, "optimization", "Optimize database queries for performance", { "level": "medium" });
let task3 = ai::create_task(agent_id, "documentation", "Write comprehensive API documentation", { "level": "low" });
let task4 = ai::create_task(agent_id, "security", "Fix critical security vulnerability", { "level": "critical" });
print("✅ Created task: implementation");
print("✅ Created task: optimization");
print("✅ Created task: documentation");
print("✅ Created task: security");
print("");
}
fn run_complete_demo() -> map<string, any> {
print("🚀 Complete Agent System Demo");
print("==============================");
print("");
// Run all demonstrations
self.setup_agent_lifecycle_demo();
self.setup_coordination_demo();
self.setup_communication_demo();
self.setup_evolution_demo();
self.demonstrate_capability_validation();
self.demonstrate_task_management();
// Summary
print("🎉 Demo Complete!");
print("");
print("📊 Summary:");
print(" - Created demo agents");
print(" - Demonstrated coordination examples");
print(" - Showed structured agent lifecycle management");
print(" - Demonstrated agent communication patterns");
print(" - Illustrated agent evolution and learning");
print(" - Validated agent capabilities and configurations");
print("");
print("💡 Key Benefits of dist_agent_lang AI System:");
print(" - Clear, structured API design");
print(" - Consistent configuration patterns");
print(" - Proper separation of concerns");
print(" - Comprehensive validation and error handling");
print(" - Built-in workflow management");
print(" - Native AI integration");
print("");
return {
"demo_agents_created": "multiple",
"coordination_examples": "demonstrated",
"pattern_benefits": "structured_api_design,consistent_configuration,separation_of_concerns,comprehensive_validation,workflow_management,ai_integration",
"status": "demo_completed_successfully"
};
}
}
// =====================================================
// PRACTICAL USAGE EXAMPLES
// =====================================================
@trust("hybrid")
@chain("ethereum")
service PracticalAgentUsage {
// Example: AI-Powered Code Review System
fn create_code_review_system() -> map<string, any> {
// Create specialized agents for code review
let config1 = {
"name": "SecurityReviewer",
"role": "Security Code Reviewer",
"capabilities": "security_analysis,vulnerability_detection,compliance_checking",
"specialization": "security_focused"
};
let config2 = {
"name": "PerformanceReviewer",
"role": "Performance Code Reviewer",
"capabilities": "performance_analysis,optimization_suggestions,bottleneck_identification",
"specialization": "performance_focused"
};
let config3 = {
"name": "QualityReviewer",
"role": "Code Quality Reviewer",
"capabilities": "code_quality_analysis,best_practices_check,maintainability_assessment",
"specialization": "quality_focused"
};
// Spawn reviewer agents
let coordinator = ai::create_agent_coordinator();
let reviewers = {};
let agent1 = ai::create_agent(config1);
let agent_id1 = ai::add_agent_to_coordinator(coordinator, agent1);
reviewers["reviewer1"] = agent_id1;
let agent2 = ai::create_agent(config2);
let agent_id2 = ai::add_agent_to_coordinator(coordinator, agent2);
reviewers["reviewer2"] = agent_id2;
let agent3 = ai::create_agent(config3);
let agent_id3 = ai::add_agent_to_coordinator(coordinator, agent3);
reviewers["reviewer3"] = agent_id3;
return {
"system_name": "MultiAgentCodeReview",
"reviewers": reviewers,
"capabilities": "comprehensive_analysis,specialized_feedback,coordinated_review",
"status": "ready_for_code_review"
};
}
// Example: Intelligent Task Management System
fn create_task_management_system() -> map<string, any> {
// Create task management agents
let planner_config = {
"name": "TaskPlanner",
"role": "Task Planning Specialist",
"capabilities": "task_breakdown,importance_assessment,dependency_analysis",
"coordination_enabled": "true"
};
let executor_config = {
"name": "TaskExecutor",
"role": "Task Execution Specialist",
"capabilities": "task_execution,progress_tracking,status_reporting",
"automation_focused": "true"
};
let monitor_config = {
"name": "ProgressMonitor",
"role": "Progress Monitoring Agent",
"capabilities": "progress_tracking,bottleneck_detection,performance_analysis",
"monitoring_focused": "true"
};
// Spawn the agents
let coordinator = ai::create_agent_coordinator();
let planner_instance = ai::create_agent(planner_config);
let planner_id = ai::add_agent_to_coordinator(coordinator, planner_instance);
let executor_instance = ai::create_agent(executor_config);
let executor_id = ai::add_agent_to_coordinator(coordinator, executor_instance);
let monitor_instance = ai::create_agent(monitor_config);
let monitor_id = ai::add_agent_to_coordinator(coordinator, monitor_instance);
return {
"system_name": "IntelligentTaskManager",
"agents": {
"planner": planner_id,
"executor": executor_id,
"monitor": monitor_id
},
"workflow": "plan,execute,monitor,optimize",
"status": "task_management_system_ready"
};
}
// Example: Real-time Collaboration System
fn create_collaboration_system() -> map<string, any> {
// Create collaboration agents
let facilitator_config = {
"name": "CollaborationFacilitator",
"role": "Collaboration Facilitator",
"capabilities": "meeting_management,consensus_building,conflict_resolution",
"communication_focused": "true"
};
let scribe_config = {
"name": "MeetingScribe",
"role": "Meeting Documentation Specialist",
"capabilities": "note_taking,action_item_tracking,summary_generation",
"documentation_focused": "true"
};
let coordinator_config = {
"name": "TeamCoordinator",
"role": "Team Coordination Agent",
"capabilities": "resource_allocation,schedule_management,progress_sync",
"coordination_focused": "true"
};
// Spawn collaboration agents
let coordinator = ai::create_agent_coordinator();
let facilitator_instance = ai::create_agent(facilitator_config);
let facilitator_id = ai::add_agent_to_coordinator(coordinator, facilitator_instance);
let scribe_instance = ai::create_agent(scribe_config);
let scribe_id = ai::add_agent_to_coordinator(coordinator, scribe_instance);
let team_coordinator_instance = ai::create_agent(coordinator_config);
let team_coordinator_id = ai::add_agent_to_coordinator(coordinator, team_coordinator_instance);
return {
"system_name": "RealTimeCollaborationHub",
"agents": {
"facilitator": facilitator_id,
"scribe": scribe_id,
"coordinator": team_coordinator_id
},
"features": "real_time_collaboration,automated_documentation,intelligent_coordination",
"status": "collaboration_system_active"
};
}
}
// =====================================================
// DEMONSTRATION SCRIPT
// =====================================================
fn demonstrate_agent_system() {
print("🎯 Agent System Demo with dist_agent_lang");
print("=========================================");
print("");
// Initialize demo service
let demo = AgentSystemDemo::new();
demo.initialize();
let result = demo.run_complete_demo();
print("✅ Agent system demonstration completed successfully!");
print("📊 Results: " + result["status"]);
}
fn demonstrate_practical_usage() {
print("🏗️ Practical Agent Usage Examples");
print("==================================");
print("");
let practical = PracticalAgentUsage::new();
// Create different types of agent systems
let code_review_system = practical.create_code_review_system();
let task_management_system = practical.create_task_management_system();
let collaboration_system = practical.create_collaboration_system();
print("✅ Code Review System: " + code_review_system["status"]);
print("✅ Task Management System: " + task_management_system["status"]);
print("✅ Collaboration System: " + collaboration_system["status"]);
}
// Main demonstration
fn main() {
demonstrate_agent_system();
print("");
demonstrate_practical_usage();
print("");
print("🎉 All agent system demonstrations completed!");
print("");
print("💡 Key Takeaways:");
print(" • Agent system uses dist_agent_lang AI module");
print(" • Structured agent creation and management");
print(" • Consistent configuration patterns");
print(" • Clear separation of concerns");
print(" • Comprehensive validation and error handling");
print(" • Built-in workflow management");
print(" • Native AI integration capabilities");
print("");
print("🚀 The agent system demonstrates dist_agent_lang's AI capabilities!");
}