#!/usr/bin/env python3
"""
Hugging Face Spaces deployment for Residential Architecture Assistant
Standalone version that avoids all LangGraph imports at startup
"""

import os
import gradio as gr

def create_interface():
    """Create interface that works reliably in HF Spaces"""
    
    def handle_chat(message, history, api_key, user_id=""):
        if not api_key or not api_key.strip():
            error_msg = "❌ Please provide your OpenAI API key to start using the Architecture Assistant."
            history.append([message, error_msg])
            return history, ""
        
        if not message.strip():
            return history, ""
        
        try:
            # Only import when actually needed to avoid schema issues
            from graph import ArchitectureAssistant
            
            # Create assistant instance
            assistant = ArchitectureAssistant(
                openai_api_key=api_key.strip(),
                user_id=user_id.strip() if user_id.strip() else f"hf_user_{len(history)}"
            )
            
            # Get response
            response = assistant.chat(message)
            history.append([message, response])
            
        except ImportError as e:
            error_msg = f"""❌ **System modules not available**: {str(e)}

**This should be the Residential Architecture Assistant** with:
- 🏛️ Architecture design guidance  
- 💰 Montreal market cost analysis
- 📐 Professional floorplan generation
- 📋 Building codes & permit requirements

The system modules couldn't be loaded in this environment. Please try again or contact support."""
            
            history.append([message, error_msg])
            
        except Exception as e:
            error_msg = f"""❌ **Error**: {str(e)}

**Troubleshooting:**
1. **Check your OpenAI API key** - Ensure it's valid and has credits
2. **Try a simpler question** - Start with basic architecture questions
3. **Wait and retry** - There might be temporary connectivity issues

**Expected functionality:**
- Multi-agent architecture consultation
- Montreal-specific building analysis
- Professional floorplan generation
- Building code guidance

Please try again or contact support if issues persist."""
            
            history.append([message, error_msg])
        
        return history, ""
    
    with gr.Blocks(title="🏠 Architecture Assistant") as interface:
        gr.HTML("""
        <div style="text-align: center; padding: 20px;">
            <h1>🏠 Residential Architecture Assistant</h1>
            <p><strong>Multi-Agent LangGraph System for Professional Architecture Consultation</strong></p>
            <p>✨ 7 AI Specialists | 📐 Professional Floorplans | 💰 Montreal Market Analysis | 📋 Building Codes</p>
        </div>
        """)
        
        # API Key input
        api_key = gr.Textbox(
            label="🔑 OpenAI API Key", 
            type="password",
            placeholder="Enter your OpenAI API key (sk-...)",
            info="Required for AI functionality. Not stored or logged."
        )
        
        # Optional User ID
        user_id = gr.Textbox(
            label="👤 User ID (Optional)",
            placeholder="Enter a unique ID to save your conversation (e.g., 'john_house_project')",
            info="Leave blank for anonymous session"
        )
        
        # Chat interface  
        chatbot = gr.Chatbot(
            label="💬 Architecture Consultation",
            height=400
        )
        
        msg = gr.Textbox(
            label="Your Message",
            placeholder="Ask about home design, budgets, floorplans, Montreal building codes...",
            lines=2
        )
        
        with gr.Row():
            send_btn = gr.Button("📤 Send", variant="primary")
            clear_btn = gr.Button("🔄 Clear", variant="secondary")
        
        gr.HTML("""
        <div style="background: #f8f9fa; padding: 15px; margin: 20px 0; border-radius: 8px;">
            <h4>💡 Example Questions:</h4>
            <ul style="margin: 10px 0;">
                <li>"I want to design a home but don't know where to start"</li>
                <li>"I have a $800,000 budget for Montreal - is that realistic?"</li>
                <li>"We're a family of 4, what size house do we need?"</li>
                <li>"Can you generate a floorplan for a 2500 sq ft house?"</li>
                <li>"What building permits do I need in Montreal?"</li>
            </ul>
            
            <h4>🤖 Our AI Specialists:</h4>
            <ul style="margin: 10px 0;">
                <li><strong>RouterAgent:</strong> Intelligent conversation routing</li>
                <li><strong>GeneralDesignAgent:</strong> Architecture principles & design guidance</li>
                <li><strong>BudgetAnalysisAgent:</strong> Montreal market cost analysis</li>
                <li><strong>FloorplanAgent:</strong> Spatial planning & requirements</li>
                <li><strong>FloorplanGeneratorAgent:</strong> Detailed architectural specifications</li>
                <li><strong>DetailedBudgetAgent:</strong> Comprehensive cost breakdowns</li>
                <li><strong>RegulationAgent:</strong> Montreal building codes & permits</li>
            </ul>
        </div>
        """)
        
        # Event handlers
        msg.submit(handle_chat, [msg, chatbot, api_key, user_id], [chatbot, msg])
        send_btn.click(handle_chat, [msg, chatbot, api_key, user_id], [chatbot, msg])
        clear_btn.click(lambda: ([], ""), outputs=[chatbot, msg])
        
        gr.HTML("""
        <div style="text-align: center; padding: 20px; border-top: 1px solid #ddd; margin-top: 20px;">
            <p><strong>🏠 Residential Architecture Assistant v3.0</strong></p>
            <p>Built with <a href="https://langchain.ai/langgraph">LangGraph</a> • 
               Powered by <a href="https://openai.com">OpenAI</a> • 
               Interface by <a href="https://gradio.app">Gradio</a></p>
            <p><em>Professional architecture consultation from concept to construction</em></p>
        </div>
        """)
    
    return interface

if __name__ == "__main__":
    demo = create_interface()
    demo.launch()