example.py

"""
Plugin Architecture Pattern - Complete Example

Demonstrates:
- Creating production plugins with dependency injection
- Registering plugins with Semantic Kernel
- Invoking plugin functions
- Function composition
- Metrics and observability

Usage:
    python example.py
"""

import asyncio
from compliance_plugin import (
    CompliancePlugin,
    CompliancePluginConfig,
    PolicyDatabase,
    EmailService
)
from base_plugin import PluginDependency


async def main():
    print("=" * 60)
    print("SEMANTIC KERNEL PLUGIN ARCHITECTURE PATTERN")
    print("=" * 60)
    print()

    # Step 1: Set up dependencies
    print("📦 Setting up dependencies...")
    policy_db = PolicyDatabase()
    email_service = EmailService()

    # Optional: Use dependency injection container
    container = PluginDependency()
    container.register("policy_database", policy_db)
    container.register("email_service", email_service)

    print("   ✓ Policy database initialized")
    print("   ✓ Email service initialized")
    print()

    # Step 2: Create plugin with configuration
    print("🔌 Creating Compliance Plugin...")
    config = CompliancePluginConfig(
        plugin_name="Compliance",
        enabled=True,
        timeout_seconds=30,
        email_notifications=True,
        audit_logging=True
    )

    plugin = CompliancePlugin(
        config=config,
        policy_database=container.resolve("policy_database"),
        email_service=container.resolve("email_service")
    )

    # Initialize plugin (load resources)
    await plugin.initialize()
    print("   ✓ Plugin initialized")
    print()

    # Step 3: Example 1 - Check Policy
    print("=" * 60)
    print("EXAMPLE 1: Check Policy")
    print("=" * 60)
    print()

    query1 = "What is the refund policy?"
    print(f"Query: {query1}")
    print()

    result1 = await plugin.check_policy(
        query=query1,
        user_id="analyst_001"
    )

    print(result1)
    print()

    # Step 4: Example 2 - Get Approval Requirements
    print("=" * 60)
    print("EXAMPLE 2: Get Approval Requirements")
    print("=" * 60)
    print()

    print("Request: Expense approval for $2,500")
    result2 = plugin.get_approval_requirements(
        request_type="expense",
        amount="$2,500"
    )

    print(result2)
    print()

    # Step 5: Example 3 - Submit Approval Request
    print("=" * 60)
    print("EXAMPLE 3: Submit Approval Request")
    print("=" * 60)
    print()

    result3 = await plugin.submit_approval_request(
        request_type="expense",
        amount="$2500",
        user_id="manager_001",
        justification="Travel expenses for client meeting in New York"
    )

    print(result3)
    print()

    # Step 6: Example 4 - Composite Function
    print("=" * 60)
    print("EXAMPLE 4: Composite Function (Validate + Submit)")
    print("=" * 60)
    print()

    result4 = await plugin.validate_and_notify(
        request_type="expense",
        amount="$450",
        user_id="employee_001"
    )

    print(result4)
    print()

    # Step 7: Show Plugin Metrics
    print("=" * 60)
    print("PLUGIN METRICS")
    print("=" * 60)
    print()

    metrics = plugin.get_metrics_summary()
    print(f"Plugin Name: {metrics['plugin_name']}")
    print(f"Total Calls: {metrics['total_calls']}")
    print(f"Successful: {metrics['successful_calls']}")
    print(f"Failed: {metrics['failed_calls']}")
    print(f"Success Rate: {metrics['success_rate']:.1%}")
    print(f"Avg Execution Time: {metrics['avg_execution_time_ms']:.2f}ms")
    print(f"Max Execution Time: {metrics['max_execution_time_ms']:.2f}ms")
    print(f"Min Execution Time: {metrics['min_execution_time_ms']:.2f}ms")
    print()

    # Step 8: Cleanup
    print("🧹 Cleaning up plugin resources...")
    await plugin.cleanup()
    print("   ✓ Cleanup complete")
    print()

    # Summary
    print("=" * 60)
    print("PRODUCTION BENEFITS")
    print("=" * 60)
    print()
    print("✓ Dependency Injection: Easy testing and mocking")
    print("✓ Input Validation: Pydantic models prevent errors")
    print("✓ Metrics Tracking: Automatic performance monitoring")
    print("✓ Error Handling: Structured exception handling")
    print("✓ Lifecycle Management: Proper resource initialization/cleanup")
    print("✓ Observability: Built-in logging for debugging")
    print("✓ Composability: Functions can call other functions")
    print()


async def example_with_semantic_kernel():
    """
    Example showing integration with actual Semantic Kernel

    NOTE: Requires Azure OpenAI configuration in .env file
    """
    print("=" * 60)
    print("INTEGRATION WITH SEMANTIC KERNEL")
    print("=" * 60)
    print()

    try:
        import os
        from semantic_kernel import Kernel
        from semantic_kernel.connectors.ai.open_ai import AzureChatCompletion

        # Check if configured
        if not os.getenv("AZURE_OPENAI_ENDPOINT"):
            print("⚠️ Azure OpenAI not configured. Skipping SK integration example.")
            print("   Configure in .env file to run this example.")
            return

        # Create Semantic Kernel
        kernel = Kernel()

        # Add Azure OpenAI service
        kernel.add_service(
            AzureChatCompletion(
                service_id="azure_openai",
                deployment_name=os.getenv("AZURE_OPENAI_DEPLOYMENT", "gpt-4o"),
                endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
                api_key=os.getenv("AZURE_OPENAI_KEY")
            )
        )

        # Create and register plugin
        policy_db = PolicyDatabase()
        email_service = EmailService()

        config = CompliancePluginConfig(plugin_name="Compliance")
        plugin = CompliancePlugin(config, policy_db, email_service)

        await plugin.initialize()

        kernel.add_plugin(
            plugin=plugin,
            plugin_name="CompliancePlugin"
        )

        print("✓ Semantic Kernel configured")
        print("✓ CompliancePlugin registered")
        print()

        # Invoke function via Semantic Kernel
        print("Invoking check_policy via Semantic Kernel...")
        check_policy_func = kernel.get_function(
            plugin_name="CompliancePlugin",
            function_name="check_policy"
        )

        result = await kernel.invoke(
            function=check_policy_func,
            query="What are the expense approval thresholds?",
            user_id="sk_user_001"
        )

        print(f"Result: {result}")
        print()

        # Cleanup
        await plugin.cleanup()

    except ImportError:
        print("⚠️ Semantic Kernel not installed. Install with:")
        print("   pip install semantic-kernel azure-identity")
        print()
    except Exception as e:
        print(f"❌ Error: {e}")
        print()


if __name__ == "__main__":
    # Run standalone example
    asyncio.run(main())

    # Run Semantic Kernel integration example
    asyncio.run(example_with_semantic_kernel())