#!/usr/bin/env python3
"""
Agent2Robot - MCP Hackathon 2024 Submission
AI-Powered Vehicle Design Assistant with MCP Integration
"""

import os
import ssl
import json

# Minimal SSL fix for local development (won't affect HuggingFace Spaces)
try:
    # Only apply SSL fix if needed
    ssl._create_default_https_context = ssl._create_unverified_context
except:
    pass

import gradio as gr
from design_tools import VehicleDesigner

# Initialize the vehicle designer with MCP integration
designer = VehicleDesigner()

def design_vehicle_interface(vehicle_type, description):
    """
    Interface function for Gradio that uses MCP-integrated design tools
    """
    try:
        # Use the MCP-integrated designer with simulation
        report, json_output, simulation_info = designer.design_vehicle_with_simulation(vehicle_type, description)
        
        return report, json_output, simulation_info
        
    except Exception as e:
        error_msg = f"Error in design process: {str(e)}"
        return error_msg, "{\"error\": \"Design process failed\"}", "Simulation failed"

def get_mcp_status():
    """Get MCP server status for display"""
    status = designer.get_mcp_status()
    return f"MCP Server: {status['name']} v{status['version']} - Status: {status['status']}"

# Create Gradio interface
def create_app():
    with gr.Blocks(
        title="🤖🚁 Agent2Robot - MCP Hackathon 2024",
        theme=gr.themes.Soft()
    ) as app:
        
        # Header
        gr.HTML("""
        <div style="text-align: center; padding: 20px; background: linear-gradient(90deg, #667eea 0%, #764ba2 100%); color: white; border-radius: 10px; margin-bottom: 20px;">
            <h1>🤖🚁 Agent2Robot Design Assistant</h1>
            <p>AI-Powered Vehicle Design with MCP Integration</p>
            <p><strong>MCP Hackathon 2024 Submission</strong></p>
        </div>
        """)
        
        # MCP Status Display
        with gr.Row():
            gr.Markdown("### 🔗 MCP Server Status")
            mcp_status = gr.Textbox(
                value=get_mcp_status(),
                label="Server Connection",
                interactive=False
            )
        
        with gr.Row():
            # Input Section
            with gr.Column(scale=1):
                gr.Markdown("## 🎯 Design Parameters")
                
                vehicle_type = gr.Dropdown(
                    choices=["Robot", "Drone", "Autonomous Vehicle", "Robotic Arm"],
                    label="🚀 Vehicle Type",
                    value="Robot"
                )
                
                description = gr.Textbox(
                    label="📝 Design Requirements",
                    lines=6,
                    placeholder="Describe your vehicle requirements and specifications...\n\nExample: Design a warehouse robot for navigation and package delivery with 50kg payload capacity, 8-hour operation time, and obstacle avoidance.",
                    value="Design a robot for warehouse navigation and package delivery"
                )
                
                generate_btn = gr.Button("🚀 Generate Design with MCP", variant="primary", size="lg")
            
            # Output Section  
            with gr.Column(scale=2):
                gr.Markdown("## 📊 MCP Design Results")
                
                design_report = gr.Textbox(
                    label="🎯 Complete Design Report",
                    lines=25,
                    interactive=False,
                    show_copy_button=True
                )
                
                design_json = gr.Textbox(
                    label="📋 Technical Specifications (JSON)",
                    lines=12,
                    interactive=False,
                    show_copy_button=True
                )
        
        # Simulation Video Section
        with gr.Row():
            with gr.Column():
                gr.Markdown("## 🎬 MCP Simulation Video")
                simulation_output = gr.Textbox(
                    label="🎥 Simulation Generated via MCP Server",
                    lines=15,
                    interactive=False,
                    show_copy_button=True,
                    placeholder="Simulation video information will appear here after design generation..."
                )
        
        # Connect functionality
        generate_btn.click(
            fn=design_vehicle_interface,
            inputs=[vehicle_type, description],
            outputs=[design_report, design_json, simulation_output]
        )
        
        # Additional MCP Info Section
        with gr.Row():
            with gr.Column():
                gr.Markdown("""
                ### 🔧 MCP Integration Features
                
                **Model Context Protocol (MCP) Integration:**
                - **🔗 Server Communication**: Direct integration with MCP servers for design generation
                - **📊 Real-time Validation**: Live design validation through MCP protocols
                - **🎯 Context Awareness**: Maintains design context across sessions
                - **🎬 Simulation Generation**: MCP-powered video simulation creation
                - **🚀 Scalable Architecture**: Modular design supporting multiple MCP servers
                """)
            
            with gr.Column():
                gr.Markdown("""
                ### 🏆 MCP Hackathon 2024 - Technical Stack
                
                **Core Components:**
                - **MCP Client**: `mcp_client.py` - Handles server communication
                - **Design Tools**: `design_tools.py` - Core vehicle design logic
                - **Gradio Interface**: `app.py` - User interaction layer
                - **Simulation Engine**: MCP-integrated video generation
                - **Modular Architecture**: Clean separation of concerns
                """)
        
        # Footer
        gr.Markdown("""
        ---
        ### 🏆 Agent2Robot - MCP Hackathon 2024
        
        **AI-Powered Vehicle Design Assistant** with **Model Context Protocol Integration**
        
        Create optimized designs for robots, drones, autonomous vehicles, and robotic arms using advanced AI algorithms and MCP server communication.
        
        **MCP Features**: Server integration • Real-time validation • Context preservation • Simulation generation • Modular architecture
        
        Built with ❤️ for the MCP Hackathon 2024 | Powered by Gradio + MCP
        """)
    
    return app

# Launch the application
if __name__ == "__main__":
    app = create_app()
    app.launch()