demo.py

#!/usr/bin/env python3
"""
Demo script showing the Agent 2 Agent workflow structure without requiring API keys
This script demonstrates the flow and structure of the application
"""

import asyncio
from dataclasses import dataclass
from typing import List

@dataclass
class MockAgentResponse:
    """Mock response from an AI agent for demo purposes"""
    cloud_platform: str
    agent_name: str
    favorite_color: str
    message: str

class MockAgent2AgentDemo:
    """Demo implementation showing the Agent 2 Agent workflow structure"""
    
    def __init__(self):
        self.agents = self._create_mock_agents()
        self.workflow_history: List[MockAgentResponse] = []
    
    def _create_mock_agents(self) -> List[dict]:
        """Create mock agent configurations"""
        rainbow_colors = ["Red", "Orange", "Yellow", "Green", "Blue", "Indigo", "Violet"]
        
        agents = [
            {"platform": "AWS", "name": "Alexandra", "color": rainbow_colors[0]},
            {"platform": "Azure", "name": "Benjamin", "color": rainbow_colors[1]}, 
            {"platform": "GCP", "name": "Catherine", "color": rainbow_colors[2]},
            {"platform": "AWS", "name": "David", "color": rainbow_colors[3]},
            {"platform": "Azure", "name": "Elena", "color": rainbow_colors[4]},
            {"platform": "GCP", "name": "Francis", "color": rainbow_colors[5]},
            {"platform": "Multi-Cloud", "name": "Gabriel", "color": rainbow_colors[6]}
        ]
        
        return agents
    
    async def mock_agent_response(self, agent: dict, task: str) -> MockAgentResponse:
        """Generate a mock response from an agent"""
        # Simulate processing time
        await asyncio.sleep(0.5)
        
        mock_messages = {
            "Alexandra": f"Hello! I'm Alexandra from AWS. My favorite color is {agent['color']}. I'll handle the cloud infrastructure setup for our rainbow presentation using AWS services like EC2 and S3.",
            "Benjamin": f"Greetings! Benjamin here from Azure. I love the color {agent['color']}. I'll contribute by setting up Azure DevOps pipelines and Azure Functions for our collaborative project.",
            "Catherine": f"Hi everyone! Catherine from GCP reporting in. My favorite color is {agent['color']}. I'll utilize Google Cloud Run and BigQuery to add data analytics to our rainbow-themed presentation.",
            "David": f"Hey there! David from AWS. I'm passionate about {agent['color']}. I'll complement Alexandra's work by setting up AWS Lambda functions and API Gateway for our project.",
            "Elena": f"Hello team! Elena from Azure here. I absolutely love {agent['color']}. I'll work on Azure Cognitive Services integration to add AI capabilities to our presentation.",
            "Francis": f"Bonjour! Francis from GCP. My favorite color is {agent['color']}. I'll implement Google Cloud Storage and Pub/Sub messaging to ensure seamless communication between our services.",
            "Gabriel": f"Greetings all! Gabriel, your multi-cloud coordinator. I cherish the color {agent['color']}. I'll orchestrate the integration across all cloud platforms to bring our rainbow vision to life."
        }
        
        return MockAgentResponse(
            cloud_platform=agent["platform"],
            agent_name=agent["name"],
            favorite_color=agent["color"],
            message=mock_messages.get(agent["name"], f"I'm {agent['name']} from {agent['platform']} and my favorite color is {agent['color']}.")
        )
    
    async def execute_demo_workflow(self, main_task: str) -> List[MockAgentResponse]:
        """Execute the demo Agent 2 Agent workflow"""
        print(f"🚀 Starting Agent 2 Agent Demo Workflow: {main_task}")
        print("=" * 60)
        
        all_responses = []
        
        # Process each agent sequentially
        for i, agent in enumerate(self.agents, 1):
            print(f"\n📋 Step {i}: Delegating to {agent['name']} on {agent['platform']}")
            
            try:
                response = await self.mock_agent_response(agent, main_task)
                all_responses.append(response)
                self.workflow_history.append(response)
                
                print(f"✅ {agent['name']} ({agent['platform']}) completed their task")
                print(f"   Favorite Color: {agent['color']}")
                print(f"   Response: {response.message[:80]}...")
                
            except Exception as e:
                print(f"❌ Error with {agent['name']}: {str(e)}")
                continue
        
        print(f"\n🔄 Aggregating responses from {len(all_responses)} agents...")
        return all_responses
    
    def generate_demo_report(self, responses: List[MockAgentResponse]) -> str:
        """Generate demo report from all agent responses"""
        report = "\n" + "=" * 60
        report += "\n🌈 DEMO AGENT 2 AGENT WORKFLOW REPORT"
        report += "\n" + "=" * 60
        
        report += f"\n\n📊 Total Agents Participated: {len(responses)}"
        report += "\n\n🌟 Agent Summary:"
        
        for i, response in enumerate(responses, 1):
            report += f"\n\n{i}. Agent: {response.agent_name}"
            report += f"\n   Cloud Platform: {response.cloud_platform}"
            report += f"\n   Favorite Color: {response.favorite_color}"
            report += f"\n   Message: {response.message}"
        
        # Group by cloud platform
        cloud_summary = {}
        for response in responses:
            if response.cloud_platform not in cloud_summary:
                cloud_summary[response.cloud_platform] = []
            cloud_summary[response.cloud_platform].append(response)
        
        report += "\n\n☁️ Cloud Platform Summary:"
        for cloud, agents in cloud_summary.items():
            report += f"\n\n{cloud}:"
            for agent in agents:
                report += f"\n  - {agent.agent_name} (Color: {agent.favorite_color})"
        
        report += "\n\n🎯 Next Steps:"
        report += "\n1. Configure your Azure OpenAI credentials in .env file"
        report += "\n2. Run 'python main.py' to execute the real Agent 2 Agent workflow"
        report += "\n3. Watch as real AI agents collaborate across cloud platforms!"
        
        return report

async def main():
    """Main demo function"""
    print("🎭 Semantic Kernel Agent 2 Agent Protocol - DEMO MODE")
    print("=" * 55)
    print("This demo shows the workflow structure without requiring API keys")
    print("=" * 55)
    
    # Initialize the demo
    demo = MockAgent2AgentDemo()
    
    # Define the main task
    main_task = "Create a collaborative rainbow-themed presentation where each agent contributes their expertise from their respective cloud platform"
    
    try:
        # Execute the demo workflow
        responses = await demo.execute_demo_workflow(main_task)
        
        # Generate and display demo report
        demo_report = demo.generate_demo_report(responses)
        print(demo_report)
        
        print(f"\n✨ Demo completed successfully with {len(responses)} agent responses!")
        
    except Exception as e:
        print(f"❌ Demo failed: {str(e)}")

if __name__ == "__main__":
    asyncio.run(main())