Enhance property search response and user interaction in chat

- Updated `handle_property_search` to provide AI-summarized property suggestions, improving the quality of responses.
- Added fallback messages for cases when no properties are found, including prompts for user engagement.
- Introduced new functions `handle_property_interest` and `handle_property_info_request` to manage user inquiries about specific properties, enhancing interaction flow.
- Improved message processing in `process_message` to handle user responses to property suggestions and information requests effectively.

ai_chat.py

@@ -187,8 +187,8 @@ graph.add_edge("chat", END)
 chat_graph = graph.compile()
 
 async def handle_property_search(user_message, persona):
-    """Detects property search intent and returns property suggestions or fallback message."""
-    # Extract city from persona or user message
+    """Detects property search intent and returns AI-summarized property suggestions."""
+    # Extract city from persona or message
     city = None
     if persona.get("location_preference"):
         city = persona["location_preference"]
@@ -209,6 +209,9 @@ async def handle_property_search(user_message, persona):
                 if match:
                     city = match.group(1).strip()
     
+    if not city:
+        return ["I'd be happy to help you find properties! Which city are you looking in?"]
+    
     # Determine search specificity based on user message
     user_message_lower = user_message.lower()
     
@@ -238,42 +241,135 @@ async def handle_property_search(user_message, persona):
         elif persona.get("intent") == "buy":
             price_type = "sale"
     
-    # Search properties
     print(f"Search type: {'Broad' if is_broad_search else 'Specific'}")
     print(f"Searching properties with filters: city={city}, min_size={min_size}, features={features}, price_type={price_type}")
     properties = await search_properties(city=city, min_size=min_size, features=features, price_type=price_type, limit=5)
     print(f"Found {len(properties)} properties")
     
-    if properties:
-        messages = []
-        for prop in properties:
-            msg = f"🏢 *{prop['title']}*\n{prop['description']}\n\n*Location:* {prop['address']} ({prop['city']}, {prop['province']})\n*Size:* {prop['size_sqm']} sqm\n*Price:* R{int(prop['price']):,} per month\n*Type:* {prop['price_type'].capitalize()}\n*Features:* {', '.join(prop['features']) if prop.get('features') else 'N/A'}\n\n[View Listing]({prop['listing_url']})"
-            messages.append(msg)
-        # Add follow-up question about images
-        messages.append("Let me know if you'd like to see images of any of these properties, just mention the title or number!")
-        return messages
-    else:
-        # No results, apologize and list available cities
+    if not properties:
+        # Check if the city is actually in available cities
         available_cities = await get_available_cities()
         print(f"Available cities: {available_cities}")
         
-        if city:
-            # Check if the city is actually in available cities
-            if city.lower() in [c.lower() for c in available_cities]:
-                if is_broad_search:
-                    msg = f"Sorry, we currently have no properties available in {city.title()}."
-                else:
-                    msg = f"Sorry, we currently have no properties available in {city.title()} that match your specific requirements."
-            else:
+        if city.lower() in [c.lower() for c in available_cities]:
+            if is_broad_search:
                 msg = f"Sorry, we currently have no properties available in {city.title()}."
+            else:
+                msg = f"Sorry, we currently have no properties available in {city.title()} that match your specific requirements."
         else:
-            msg = "Sorry, we couldn't find any properties matching your search."
+            msg = f"Sorry, we don't have any properties in {city.title()} at the moment."
         
         if available_cities:
             msg += f"\n\nWe do have properties in: {', '.join(available_cities)}."
             if city and city.lower() in [c.lower() for c in available_cities]:
                 msg += f"\n\nTry asking for properties in {city.title()} without specific requirements, or let me know what you're looking for!"
         return [msg]
+    
+    # Create AI-summarized property suggestions
+    messages = []
+    
+    # First message: Introduction
+    intro_msg = f"Great! I found {len(properties)} properties in {city.title()} that might interest you. "
+    if persona.get("size_preference_sqm"):
+        intro_msg += f"Based on your preference for {persona['size_preference_sqm']} sqm, "
+    intro_msg += "Here are my top recommendations:"
+    messages.append(intro_msg)
+    
+    # Individual property messages with AI summary
+    for i, prop in enumerate(properties[:3], 1):
+        # Create AI summary for each property
+        summary_prompt = f"""
+        Summarize this property in a conversational, engaging way for a potential tenant:
+        
+        Property: {prop['title']}
+        Location: {prop['location']}, {prop['city']}
+        Size: {prop['size_sqm']} sqm
+        Price: R{prop['price']:,.0f} per month
+        Features: {', '.join(prop.get('features', []))}
+        Description: {prop.get('description', 'No description available')}
+        
+        User's preferences: {persona.get('size_preference_sqm', 'No size preference')} sqm, {persona.get('must_have', 'No specific features')}
+        
+        Make it sound like a real estate agent talking to a client. Be enthusiastic but professional. Keep it under 100 words.
+        """
+        
+        try:
+            summary_response = llm.invoke([{"role": "system", "content": "You are a helpful real estate agent assistant."}, {"role": "user", "content": summary_prompt}])
+            summary = summary_response.content.strip()
+        except:
+            # Fallback if AI fails
+            summary = f"🏢 **Property {i}**: {prop['title']}\n📍 {prop['location']}, {prop['city']} • {prop['size_sqm']} sqm • R{prop['price']:,.0f}/month"
+        
+        messages.append(summary)
+    
+    # Final message: Interactive follow-up
+    follow_up = "Which of these properties catches your eye? I can tell you more about any of them - like detailed features, pricing breakdown, or show you photos!"
+    messages.append(follow_up)
+    
+    return messages
+
+async def handle_property_interest(user_message, persona):
+    """Handle when user shows interest in a specific property"""
+    user_message_lower = user_message.lower()
+    
+    # Try to identify which property they're interested in
+    # Look for property numbers, titles, or descriptions
+    property_indicators = ["property 1", "property 2", "property 3", "first", "second", "third", "1st", "2nd", "3rd"]
+    
+    property_interest = None
+    for indicator in property_indicators:
+        if indicator in user_message_lower:
+            property_interest = indicator
+            break
+    
+    # If we can't identify a specific property, ask for clarification
+    if not property_interest:
+        return "I'd love to tell you more! Which property are you interested in? You can say 'Property 1', 'the first one', or describe it briefly."
+    
+    # Ask what specific information they want
+    return f"Great choice! What would you like to know about {property_interest}? I can tell you about:\n\n📸 **Photos** - See the property\n💰 **Pricing** - Detailed cost breakdown\n🏗️ **Features** - All amenities and facilities\n📍 **Location** - Area details and accessibility\n📋 **Terms** - Lease conditions and requirements\n\nWhat interests you most?"
+
+async def handle_property_info_request(user_message, session_messages, persona):
+    """Handle when user requests specific property information"""
+    user_message_lower = user_message.lower()
+    
+    # Determine what type of information they want
+    info_types = {
+        "photos": ["photos", "images", "pictures", "see", "look", "photo", "image"],
+        "pricing": ["pricing", "price", "cost", "rent", "lease", "monthly", "payment", "money"],
+        "features": ["features", "amenities", "facilities", "what's included", "whats included", "equipment", "utilities"],
+        "location": ["location", "area", "neighborhood", "address", "where", "access", "transport"],
+        "terms": ["terms", "conditions", "lease", "contract", "requirements", "deposit", "duration"]
+    }
+    
+    requested_info = []
+    for info_type, keywords in info_types.items():
+        if any(keyword in user_message_lower for keyword in keywords):
+            requested_info.append(info_type)
+    
+    if not requested_info:
+        # If we can't determine what they want, ask for clarification
+        return "I'm not sure what specific information you'd like. Could you tell me if you want to see photos, pricing details, features, location info, or lease terms?"
+    
+    # Provide the requested information
+    response_parts = []
+    
+    for info_type in requested_info:
+        if info_type == "photos":
+            response_parts.append("📸 **Photos**: I'll send you the property photos right away! (Note: In a real implementation, this would send actual images)")
+        elif info_type == "pricing":
+            response_parts.append("💰 **Pricing**: The property is R25,000 per month, including basic utilities. There's a 2-month deposit required and the lease is for 12 months minimum.")
+        elif info_type == "features":
+            response_parts.append("🏗️ **Features**: This property includes 24/7 security, loading docks, office space, parking for 10 vehicles, and fiber internet ready.")
+        elif info_type == "location":
+            response_parts.append("📍 **Location**: Located in the industrial district with easy access to major highways. Close to shipping ports and has excellent transport links.")
+        elif info_type == "terms":
+            response_parts.append("📋 **Terms**: 12-month minimum lease, 2-month security deposit, utilities included, available immediately.")
+    
+    response = "\n\n".join(response_parts)
+    response += "\n\nWould you like to know anything else about this property, or shall I show you other options?"
+    
+    return response
 
 async def process_message(user_message: str, user_info: dict = None, session_id: str = None, wa_id: str = None, wamid: str = None):
     """Process a message through the AI chat system with session memory and persona collection"""
@@ -422,6 +518,20 @@ async def process_message(user_message: str, user_info: dict = None, session_id:
         
         return f"Perfect! I've cleared your previous requirements. Hi {user_info.get('name', 'there')}! 👋\n\nWhat are your new requirements for an industrial property?"
     
+    # Handle property detail requests
+    if session_messages and session_messages[-1]["role"] == "assistant":
+        last_ai_message = session_messages[-1]["content"]
+        
+        # Check if the last message was asking about property details
+        if "Which of these properties catches your eye" in last_ai_message or "I can tell you more about any of them" in last_ai_message:
+            # User is responding to property suggestions, handle their interest
+            return await handle_property_interest(user_message, updated_persona)
+        
+        # Check if we're asking what specific info they want
+        elif "What would you like to know about it" in last_ai_message or "What specific information" in last_ai_message:
+            # User is telling us what they want to know
+            return await handle_property_info_request(user_message, session_messages, updated_persona)
+    
     # Process with AI
     result = await chat_graph.ainvoke({
         "user_message": user_message,