#!/usr/bin/env python3
"""
Agent2Robot - HuggingFace Spaces Optimized
Designed specifically for HuggingFace Spaces deployment
"""

import os
import ssl
import json

# Multiple SSL fixes for Windows/conda environments
try:
    # Try to fix SSL certificate path
    import certifi
    os.environ['SSL_CERT_FILE'] = certifi.where()
    os.environ['REQUESTS_CA_BUNDLE'] = certifi.where()
    os.environ['CURL_CA_BUNDLE'] = certifi.where()
except ImportError:
    print("⚠️ Warning: certifi not available, using alternative SSL fix")

# Disable SSL verification if needed (for development only)
ssl._create_default_https_context = ssl._create_unverified_context

# Additional environment fixes for Windows
os.environ['PYTHONHTTPSVERIFY'] = '0'
os.environ['PYTHONPATH'] = os.environ.get('PYTHONPATH', '') + ';.'

import gradio as gr

def design_vehicle(vehicle_type, description):
    """
    Main design function optimized for HuggingFace Spaces
    Returns formatted results as strings to avoid schema issues
    """
    
    # Simulate design process
    design_specs = {
        "vehicle_type": vehicle_type,
        "description": description,
        "status": "Design Complete",
        "optimization_score": 95,
        "features": [
            "Advanced navigation system",
            "Obstacle avoidance capabilities", 
            "Energy-efficient design",
            "Modular architecture"
        ],
        "performance": {
            "speed": "Optimized for task",
            "efficiency": "95%",
            "reliability": "High",
            "maintainability": "Excellent"
        }
    }
    
    # Format as readable text for display
    result_text = f"""
🤖🚁 Agent2Robot Design Results
================================

Vehicle Type: {vehicle_type}
Description: {description}

🔧 Design Process:
✅ Requirements analyzed
✅ Design specifications generated  
✅ Parameters optimized
✅ Design validated

📋 Design Specifications:
- Vehicle Type: {vehicle_type}
- Primary Function: {description}
- Status: {design_specs['status']}
- Optimization Score: {design_specs['optimization_score']}%

🎯 Key Features:
{chr(10).join(f'- {feature}' for feature in design_specs['features'])}

📊 Performance Metrics:
- Speed: {design_specs['performance']['speed']}
- Efficiency: {design_specs['performance']['efficiency']}
- Reliability: {design_specs['performance']['reliability']}
- Maintainability: {design_specs['performance']['maintainability']}

🔗 Next Steps:
1. Review design specifications
2. Proceed to simulation phase
3. Generate manufacturing files
4. Deploy to production

Design completed successfully! ✅
"""
    
    # Return JSON as formatted string to avoid schema issues
    json_output = json.dumps(design_specs, indent=2)
    
    return result_text, json_output

# Create the Gradio interface using the most compatible approach
with gr.Blocks(
    title="🤖🚁 Agent2Robot",
    theme=gr.themes.Default(),
) as demo:
    
    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 and Optimization Platform</p>
        <p><strong>Built for MCP Hackathon</strong></p>
    </div>
    """)
    
    with gr.Row():
        with gr.Column():
            gr.Markdown("## 🎯 Design Input")
            
            vehicle_type = gr.Dropdown(
                choices=["Robot", "Drone", "Autonomous Vehicle", "Robotic Arm"],
                label="🚀 Vehicle Type",
                value="Robot"
            )
            
            description = gr.Textbox(
                label="📝 Design Requirements",
                lines=4,
                placeholder="Describe your vehicle requirements...",
                value="Design a robot for obstacle navigation and package delivery"
            )
            
            submit_btn = gr.Button("🚀 Generate Design", variant="primary")
        
        with gr.Column():
            gr.Markdown("## 📊 Results")
            
            design_output = gr.Textbox(
                label="🎯 Design Report",
                lines=20,
                interactive=False
            )
            
            json_output = gr.Textbox(
                label="📋 Design Specifications (JSON)",
                lines=10,
                interactive=False
            )
    
    # Connect the function
    submit_btn.click(
        fn=design_vehicle,
        inputs=[vehicle_type, description],
        outputs=[design_output, json_output]
    )
    
    gr.Markdown("""
    ---
    ### 🔧 About Agent2Robot
    
    Agent2Robot is an AI-powered design assistant for creating optimized vehicle designs:
    
    - **🤖 Robots**: Ground-based autonomous vehicles
    - **🚁 Drones**: Aerial vehicles for various applications  
    - **🚗 Autonomous Vehicles**: Self-driving transportation
    - **🦾 Robotic Arms**: Industrial and service manipulators
    
    **Features**: AI optimization • Performance analysis • Custom specifications • Export-ready designs
    
    **HuggingFace Spaces Optimized** | Powered by Gradio
    """)

# Launch configuration for HuggingFace Spaces
if __name__ == "__main__":
    demo.launch()