Enhance property request handling and conversation context in AI chat

- Updated the `extract_and_search_properties` function to utilize existing properties in the state for specific classification requests, improving efficiency in handling user inquiries.
- Enhanced the `handle_image_request` function to analyze recent conversation history for property mentions, allowing for more contextually relevant property selections when multiple options are available.
- Added debug statements to track property mentions and selections, improving traceability and user experience during property inquiries.
- These changes aim to streamline user interactions by leveraging existing data and conversation context, ensuring more accurate and responsive AI behavior.

ai_chat.py

@@ -371,6 +371,17 @@ async def extract_and_search_properties(state):
     classification = state.get("classification")
     print(f"DEBUG - Property search classification check: '{classification}'")
     
+    # Check if this is a detail request for existing properties in state
+    existing_properties = state.get("properties", [])
+    if (classification.startswith("request_images") or 
+        classification == "request_address" or 
+        classification == "request_details") and existing_properties:
+        print(f"DEBUG - Using existing properties from state, count: {len(existing_properties)}")
+        return {
+            "properties": existing_properties,
+            "classification": classification
+        }
+    
     # Check if classification matches our search categories
     is_search_request = (
         classification == "search_listings" or
@@ -575,7 +586,45 @@ async def handle_image_request(state):
                     best_match_score = score
                     selected_property = prop
     
-    # Fallback: use first property if no specific identifier
+    # Fallback: Use conversation context to find which property user was discussing
+    if not selected_property and len(props) > 1:
+        # Check conversation history for property context
+        session_messages = state.get("session_messages", [])
+        print(f"DEBUG - Checking {len(session_messages)} session messages for property context")
+        
+        # Look for property mentions in recent conversation
+        recent_messages = session_messages[-10:]  # Last 10 messages
+        property_mentions = {}
+        
+        for msg in recent_messages:
+            if msg.get("role") == "assistant":
+                content = msg.get("content", "").lower()
+                for i, prop in enumerate(props):
+                    title = prop.get("title", "").lower()
+                    location = prop.get("location", "").lower()
+                    # Check if this property was mentioned in AI response
+                    title_words = title.split()
+                    if len(title_words) >= 2:  # Use first 2 words for matching
+                        key_phrase = " ".join(title_words[:2])
+                        if key_phrase in content or location in content:
+                            property_mentions[i] = property_mentions.get(i, 0) + 1
+                            print(f"DEBUG - Found mention of property {i}: {title}")
+        
+        # Use most mentioned property from conversation
+        if property_mentions:
+            most_mentioned = max(property_mentions.items(), key=lambda x: x[1])
+            selected_property = props[most_mentioned[0]]
+            print(f"DEBUG - Selected property from conversation context: {selected_property.get('title')}")
+        else:
+            # Multiple properties available - ask user to specify
+            prop_options = []
+            for i, prop in enumerate(props[:3], 1):  # Show first 3 options
+                prop_options.append(f"Option {i}: {prop.get('title')}")
+            
+            options_text = "\n".join(prop_options)
+            return [f"I have multiple properties available. Which one would you like to see images of?\n\n{options_text}\n\nPlease let me know which option you'd like images for."]
+    
+    # Final fallback: use first property if only one or no context found
     if not selected_property:
         selected_property = props[0]
     

database.py

@@ -329,8 +329,8 @@ async def search_properties(filters: dict) -> list:
         # Note: Must-have features are removed from database search
         # They will be handled by the LLM in the chat response
         
-        # e. Order & limit
-        query = query.order("is_featured", desc=True).order("price").limit(5)
+        # e. Order & limit - prioritize recent activity, then featured, then price
+        query = query.order("updated_at", desc=True).order("is_featured", desc=True).order("price").limit(5)
         
         # f. Execute and return
         resp = query.execute()