Enhance classification handling in intent extraction and property search

- Updated the return structure of `extract_and_update_intent` and `extract_and_search_properties` to include the classification information, improving the context provided for subsequent processing.
- Added debug print statements in `receive_message` to log the classification being processed, enhancing traceability during image request handling.
- These changes aim to improve the clarity and responsiveness of the AI chat system by ensuring that classification data is consistently available and logged throughout the interaction flow.

ai_chat.py

@@ -295,7 +295,10 @@ async def extract_and_update_intent(state):
         if skip_preferences:
             # User is asking for properties, images, or address - don't interrupt with preference questions
             print(f"DEBUG - User asking for {classification}, skipping preference questions")
-            return {"response": None}
+            return {
+                "response": None,
+                "classification": classification
+            }
         
         # User is setting preferences, ask for missing fields
         questions = {
@@ -309,7 +312,10 @@ async def extract_and_update_intent(state):
         return state
 
     print("DEBUG - Intent update returning None")
-    return {"response": None}
+    return {
+        "response": None,
+        "classification": state.get("classification")
+    }
 
 async def classify_user_intent(state):
     """
@@ -389,7 +395,10 @@ async def extract_and_search_properties(state):
     
     if properties:
         print("DEBUG - Properties found, returning properties to continue to chat")
-        return {"properties": properties}
+        return {
+            "properties": properties,
+            "classification": state.get("classification")
+        }
 
     # No properties found with any filters
     state["response"] = (

main.py

@@ -74,9 +74,13 @@ async def receive_message(req: Request):
             
             # Check if this is an image request
             classification = ai_result.get("classification", "")
+            print(f"DEBUG - main.py classification: '{classification}'")
             image_messages = None
             
             if classification.startswith("request_images") or "image" in user_message.lower() or "photo" in user_message.lower():
+                print(f"DEBUG - Calling handle_image_request with classification: '{classification}'")
+                # Ensure classification is passed to handle_image_request
+                state["classification"] = classification
                 image_messages = await handle_image_request(state)
             
             if image_messages: