debug

app.py

@@ -1,280 +1,148 @@
 #!/usr/bin/env python3
 """
 Hugging Face Spaces deployment for Residential Architecture Assistant
-Multi-Agent LangGraph System for Architecture Consultation
+Simplified version to avoid schema issues
 """
 
 import os
 import gradio as gr
-import json
 import traceback
-from typing import List, Tuple, Dict, Any
-from datetime import datetime
+from typing import List, Tuple
 
-# Import the core system
-from graph import ArchitectureAssistant
-
-class HuggingFaceArchitectureApp:
-    """Hugging Face Spaces compatible wrapper for the Architecture Assistant"""
-    
-    def __init__(self):
-        self.assistant = None
-        self.conversation_history = []
-        
-    def initialize_assistant(self, api_key: str, user_id: str = None) -> Tuple[str, bool]:
-        """Initialize the assistant with API key"""
-        try:
-            if not api_key or api_key.strip() == "":
-                return "❌ Please provide your OpenAI API key to get started.", False
-            
-            # Initialize the assistant
-            self.assistant = ArchitectureAssistant(
-                openai_api_key=api_key.strip(),
-                user_id=user_id or f"hf_user_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
-            )
-            
-            return "✅ Architecture Assistant initialized! You can now start your consultation.", True
-            
-        except Exception as e:
-            error_msg = f"❌ Error initializing assistant: {str(e)}"
-            print(f"Initialization error: {traceback.format_exc()}")
-            return error_msg, False
+# Create a minimal interface without complex imports to avoid schema issues
+def create_simple_interface():
+    """Create a simple Gradio interface that works reliably in HF Spaces"""
     
-    def chat_with_assistant(self, message: str, history: List[List[str]], api_key: str) -> Tuple[List[List[str]], str]:
-        """Process chat message and return updated history"""
+    def handle_message(message: str, history: List[List[str]], api_key: str) -> Tuple[List[List[str]], str]:
+        """Simple message handler"""
         try:
-            # Check if assistant is initialized
-            if not self.assistant or not api_key:
-                error_response = "❌ Please provide your OpenAI API key first."
-                history.append([message, error_response])
+            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, ""
             
-            # Get response from assistant
-            response = self.assistant.chat(message)
-            
-            # Add to history
-            history.append([message, response])
-            
-            return history, ""
-            
-        except Exception as e:
-            error_response = f"❌ Error: {str(e)}\n\nPlease check your API key and try again."
-            print(f"Chat error: {traceback.format_exc()}")
-            history.append([message, error_response])
-            return history, ""
-    
-    def get_conversation_summary(self, api_key: str) -> str:
-        """Get current conversation summary"""
-        try:
-            if not self.assistant or not api_key:
-                return "❌ Assistant not initialized. Please provide your API key first."
-            
-            summary = self.assistant.get_conversation_summary()
-            
-            # Format summary nicely
-            formatted_summary = f"""📋 **CONVERSATION SUMMARY**
+            # Try to import and use the actual system
+            try:
+                from graph import ArchitectureAssistant
+                
+                # Create assistant instance
+                assistant = ArchitectureAssistant(
+                    openai_api_key=api_key.strip(),
+                    user_id=f"hf_user_{len(history)}"
+                )
+                
+                # Get response
+                response = assistant.chat(message)
+                history.append([message, response])
+                
+            except Exception as e:
+                # Fallback error handling
+                error_msg = f"""❌ **System Error**: {str(e)}
 
-👤 **User Requirements:**
-• Budget: ${summary['user_requirements'].get('budget', 0):,} CAD
-• Location: {summary['user_requirements'].get('location', 'Not specified')}
-• Family Size: {summary['user_requirements'].get('family_size', 'Not specified')}
-• Preferences: {', '.join(summary['user_requirements'].get('lifestyle_preferences', []) or ['None specified'])}
+**Possible Solutions:**
+1. **Check your OpenAI API key** - Make sure it's valid and has sufficient credits
+2. **Try again** - Sometimes there are temporary connection issues
+3. **Simpler questions** - Start with basic architecture questions
 
-🏠 **Floorplan Requirements:**
-• Total Square Footage: {summary['floorplan_requirements'].get('total_sqft', 'Not specified')} sq ft
-• Number of Floors: {summary['floorplan_requirements'].get('num_floors', 'Not specified')}
-• Lot Dimensions: {summary['floorplan_requirements'].get('lot_dimensions', 'Not specified')}
-• Rooms: {len(summary['floorplan_requirements'].get('rooms', []))} room types specified
+**This is a multi-agent LangGraph system** that provides:
+- 🏛️ **Architecture design guidance**
+- 💰 **Montreal market cost analysis** 
+- 📐 **Professional floorplan generation**
+- 📋 **Building codes & permit requirements**
 
-📊 **Progress:**
-• Total Messages: {summary['total_messages']}
-• Current Topic: {summary['current_topic'] or 'General consultation'}
-"""
-            
-            return formatted_summary
+Please try your question again, or contact support if the issue persists."""
+                
+                history.append([message, error_msg])
+                
+            return history, ""
             
         except Exception as e:
-            return f"❌ Error getting summary: {str(e)}"
-    
-    def reset_conversation(self, api_key: str) -> Tuple[List, str, str]:
-        """Reset the conversation"""
-        try:
-            if self.assistant and api_key:
-                self.assistant.reset_conversation()
-                return [], "", "✅ Conversation reset. You can start a new consultation."
-            else:
-                return [], "", "❌ Please initialize with your API key first."
-        except Exception as e:
-            return [], "", f"❌ Error resetting: {str(e)}"
-
-# Create app instance
-app = HuggingFaceArchitectureApp()
-
-# Create Gradio interface
-def create_gradio_interface():
-    """Create the Gradio interface for Hugging Face Spaces"""
+            # Final fallback
+            error_msg = f"❌ Unexpected error: {str(e)}"
+            history.append([message, error_msg])
+            return history, ""
     
-    with gr.Blocks(
-        title="🏠 Residential Architecture Assistant",
-        theme=gr.themes.Soft(),
-        css="""
-        .container { max-width: 1200px; margin: auto; }
-        .header { text-align: center; padding: 20px; }
-        .chat-container { height: 500px; }
-        .summary-box { background-color: #f8f9fa; padding: 15px; border-radius: 10px; }
-        """
-    ) as demo:
+    # Create interface with minimal components
+    with gr.Blocks(title="🏠 Architecture Assistant") as demo:
         
-        # Header
         gr.HTML("""
-        <div class="header">
+        <div style="text-align: center; padding: 20px;">
             <h1>🏠 Residential Architecture Assistant</h1>
-            <p><em>Multi-Agent LangGraph System for Professional Architecture Consultation</em></p>
-            <p><strong>✨ 7 AI Specialists | 📐 Professional Floorplans | 💰 Montreal Market Analysis | 📋 Building Codes</strong></p>
+            <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 (persistent across the session)
-        with gr.Row():
-            api_key_input = gr.Textbox(
-                label="🔑 OpenAI API Key",
-                placeholder="Enter your OpenAI API key (sk-...)",
-                type="password",
-                info="Your API key is used securely and not stored. Required for AI agent functionality."
-            )
-            
-        with gr.Row():
-            init_btn = gr.Button("🚀 Initialize Assistant", variant="primary", size="sm")
-            reset_btn = gr.Button("🔄 Reset Conversation", variant="secondary", size="sm")
+        # API Key input
+        api_key = gr.Textbox(
+            label="🔑 OpenAI API Key",
+            placeholder="Enter your OpenAI API key (sk-...)",
+            type="password",
+            info="Required for AI functionality. Not stored or logged."
+        )
         
-        init_status = gr.HTML("")
+        # 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
+        )
         
-        # Main chat interface
+        # Buttons
         with gr.Row():
-            with gr.Column(scale=2):
-                chatbot = gr.Chatbot(
-                    label="💬 Architecture Consultation",
-                    height=500,
-                    show_label=True
-                )
-                
-                with gr.Row():
-                    msg_input = gr.Textbox(
-                        label="Your Message",
-                        placeholder="Ask about home design, budgets, floorplans, building codes...",
-                        lines=2,
-                        scale=4
-                    )
-                    send_btn = gr.Button("📤 Send", variant="primary", scale=1)
-            
-            with gr.Column(scale=1):
-                gr.HTML("<h3>📊 Project Status</h3>")
-                summary_display = gr.HTML(
-                    value="<div class='summary-box'>Initialize the assistant to see your project summary.</div>",
-                    label="Conversation Summary"
-                )
-                
-                summary_btn = gr.Button("🔄 Update Summary", variant="secondary", size="sm")
+            send_btn = gr.Button("📤 Send", variant="primary")
+            clear_btn = gr.Button("🔄 Clear", variant="secondary")
         
-        # Usage instructions
-        with gr.Accordion("📖 How to Use", open=False):
-            gr.HTML("""
-            <div style="padding: 15px;">
-                <h4>🚀 Getting Started:</h4>
-                <ol>
-                    <li>Enter your OpenAI API key above</li>
-                    <li>Click "Initialize Assistant"</li>
-                    <li>Start your consultation with questions like:</li>
-                </ol>
-                
-                <h4>💡 Example Questions:</h4>
-                <ul>
-                    <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>
-                    <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>
-            """)
+        # Examples
+        gr.HTML("""
+        <div style="margin: 20px; padding: 15px; background: #f0f0f0; border-radius: 10px;">
+            <h4>💡 Try these example questions:</h4>
+            <ul>
+                <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>"Can you generate a floorplan for a 2500 sq ft house?"</li>
+                <li>"What permits do I need in Montreal?"</li>
+            </ul>
+        </div>
+        """)
         
         # Event handlers
-        def handle_init(api_key):
-            status_msg, success = app.initialize_assistant(api_key)
-            if success:
-                return gr.HTML(f"<div style='color: green; padding: 10px;'>{status_msg}</div>")
-            else:
-                return gr.HTML(f"<div style='color: red; padding: 10px;'>{status_msg}</div>")
-        
-        def handle_chat(message, history, api_key):
-            return app.chat_with_assistant(message, history, api_key)
-        
-        def handle_summary(api_key):
-            summary = app.get_conversation_summary(api_key)
-            return f"<div class='summary-box'>{summary}</div>"
-        
-        def handle_reset(api_key):
-            history, msg, status = app.reset_conversation(api_key)
-            return history, msg, gr.HTML(f"<div style='color: green; padding: 10px;'>{status}</div>")
-        
-        # Wire up events
-        init_btn.click(
-            handle_init,
-            inputs=[api_key_input],
-            outputs=[init_status]
-        )
-        
-        msg_input.submit(
-            handle_chat,
-            inputs=[msg_input, chatbot, api_key_input],
-            outputs=[chatbot, msg_input]
+        msg.submit(
+            handle_message,
+            inputs=[msg, chatbot, api_key],
+            outputs=[chatbot, msg]
         )
         
         send_btn.click(
-            handle_chat,
-            inputs=[msg_input, chatbot, api_key_input],
-            outputs=[chatbot, msg_input]
+            handle_message,
+            inputs=[msg, chatbot, api_key],
+            outputs=[chatbot, msg]
         )
         
-        summary_btn.click(
-            handle_summary,
-            inputs=[api_key_input],
-            outputs=[summary_display]
-        )
-        
-        reset_btn.click(
-            handle_reset,
-            inputs=[api_key_input],
-            outputs=[chatbot, msg_input, init_status]
+        clear_btn.click(
+            lambda: ([], ""),
+            outputs=[chatbot, msg]
         )
         
         # Footer
         gr.HTML("""
         <div style="text-align: center; padding: 20px; margin-top: 30px; border-top: 1px solid #ddd;">
-            <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>
+            <p><strong>🏠 Residential Architecture Assistant</strong></p>
+            <p>Multi-Agent LangGraph System • Built with Gradio</p>
         </div>
         """)
     
     return demo
 
-# Create and launch the interface
+# Launch the interface
 if __name__ == "__main__":
-    demo = create_gradio_interface()
-    
-    # Launch configuration for Hugging Face Spaces
+    demo = create_simple_interface()
     demo.launch()