Update main.py

main.py

@@ -1179,43 +1179,84 @@ def get_price_trends():
 
 # --- AI Chat Endpoint & History ---
 def _get_price_trend_analysis_for_chat(crop_type=None, location=None):
-    if not gemini_client: return "AI service for trend analysis is currently unavailable.", []
-    if not FIREBASE_INITIALIZED: return "Firebase not ready for trend analysis.", []
+    if not gemini_client: 
+        return "AI service for trend analysis is currently unavailable.", []
+    if not FIREBASE_INITIALIZED: 
+        return "Firebase not ready for trend analysis.", []
+    
     try:
         all_deals = db.reference('deals', app=db_app).order_by_child('status').equal_to('completed').get() or {}
         price_data_points = []
+        
         if all_deals:
             for deal_id, deal in all_deals.items():
-                if not deal: continue # Skip if deal data is malformed or None
+                if not deal or not isinstance(deal, dict): 
+                    continue # Skip if deal data is malformed or None
+                
                 listing_id = deal.get('listing_id')
-                listing_details = db.reference(f'listings/{listing_id}', app=db_app).get() if listing_id else None
-                if listing_details:
-                    deal_crop_type = listing_details.get('crop_type')
-                    deal_location = listing_details.get('location')
+                if not listing_id:
+                    continue
                     
-                    match_crop = not crop_type or (deal_crop_type and crop_type.lower() in deal_crop_type.lower())
-                    match_location = not location or (deal_location and location.lower() in deal_location.lower())
-
-                    if match_crop and match_location:
+                listing_details = db.reference(f'listings/{listing_id}', app=db_app).get()
+                if not listing_details or not isinstance(listing_details, dict):
+                    continue
+                    
+                deal_crop_type = listing_details.get('crop_type')
+                deal_location = listing_details.get('location')
+                
+                match_crop = not crop_type or (deal_crop_type and crop_type.lower() in deal_crop_type.lower())
+                match_location = not location or (deal_location and location.lower() in deal_location.lower())
+
+                if match_crop and match_location:
+                    price = deal.get('agreed_price') or deal.get('proposed_price')
+                    if price:  # Only include if we have a valid price
+                        date_str = deal.get('admin_approved_at') or deal.get('created_at', '')
+                        # Extract date portion safely
+                        date_only = date_str[:10] if isinstance(date_str, str) and len(date_str) >= 10 else ''
+                        
                         price_data_points.append({
-                            'price': deal.get('agreed_price') or deal.get('proposed_price'),
-                            'date': (deal.get('admin_approved_at') or deal.get('created_at', ''))[:10], # Date only, ensure created_at exists
-                            'crop': deal_crop_type
+                            'price': price,
+                            'date': date_only,
+                            'crop': deal_crop_type or 'Unknown'
                         })
-        if not price_data_points: return f"Not enough historical data for trends for {crop_type or 'crops'} in {location or 'all locations'}.", []
+        
+        if not price_data_points: 
+            return f"Not enough historical data for trends for {crop_type or 'crops'} in {location or 'all locations'}.", []
+        
+        # Sort by date (newest first) and limit data points
+        price_data_points.sort(key=lambda x: x.get('date', ''), reverse=True)
+        limited_data = price_data_points[:15]
         
         data_summary_for_gemini = f"Historical transaction data for {crop_type or 'various crops'} in {location or 'various locations'}:\n"
-        for point in price_data_points[:15]: # Limit data points for chat context
+        for point in limited_data:
             data_summary_for_gemini += f"- Crop: {point.get('crop')}, Price: {point.get('price')}, Date: {point.get('date')}\n"
 
         prompt = f"""
         Analyze transaction data from Tunasonga Agri. Provide a brief price trend analysis for {crop_type if crop_type else 'the general market'}{f' in {location}' if location else ''}.
-        Is price increasing, decreasing, or stable? Note patterns. Concise. State if data is sparse.
+        Is price increasing, decreasing, or stable? Note patterns. Keep response concise (2-3 sentences). State if data is sparse.
+        
         Data: {data_summary_for_gemini}
+        
         Analysis:
         """
-        response = gemini_client.generate_content(model='gemini-2.0-flash', contents=[{'parts': [{'text': prompt}]}])
-        return response.text.strip(), price_data_points
+        
+        # Use proper Gemini API call structure
+        response = gemini_client.generate_content(prompt)
+        response_text = ""
+        
+        # Handle different response structures safely
+        if hasattr(response, 'text') and response.text:
+            response_text = response.text.strip()
+        elif hasattr(response, 'candidates') and response.candidates:
+            if hasattr(response.candidates[0], 'content'):
+                if hasattr(response.candidates[0].content, 'parts') and response.candidates[0].content.parts:
+                    response_text = response.candidates[0].content.parts[0].text.strip()
+        
+        if not response_text:
+            response_text = "Unable to generate trend analysis at this time."
+            
+        return response_text, price_data_points
+        
     except firebase_exceptions.FirebaseError as fe:
         logger.error(f"Chat (Trend Helper): Firebase Error: {fe}")
         return "Database error occurred while fetching trend data.", []
@@ -1223,59 +1264,102 @@ def _get_price_trend_analysis_for_chat(crop_type=None, location=None):
         logger.error(f"Chat (Trend Helper): Gemini Trend Error or other: {e}")
         return "Could not generate price trend analysis at this time.", []
 
+
 def _fetch_platform_data_for_chat(user_message):
-    if not FIREBASE_INITIALIZED: return "Firebase not ready for platform data.", []
+    if not FIREBASE_INITIALIZED: 
+        return "Firebase not ready for platform data.", []
+    
     try:
         keywords = user_message.lower().split()
         extracted_entities = {'crop_type': None, 'location': None, 'listing_type': None}
+        
         # Consider making these lists configurable or fetched from DB if they grow large
-        common_crops = ["maize", "beans", "tomatoes", "potatoes", "cabbage", "onions", "sorghum", "millet", "groundnuts", "wheat", "soybeans", "sunflower"]
-        common_locations = ["harare", "bulawayo", "mutare", "gweru", "masvingo", "chinhoyi", "bindura", "marondera", # Zimbabwe
-                            "lusaka", "ndola", "kitwe", "livingstone", "chipata", # Zambia
-                            "maputo", "beira", "nampula", "tete"] # Mozambique
-
+        common_crops = ["maize", "beans", "tomatoes", "potatoes", "cabbage", "onions", "sorghum", 
+                       "millet", "groundnuts", "wheat", "soybeans", "sunflower"]
+        common_locations = ["harare", "bulawayo", "mutare", "gweru", "masvingo", "chinhoyi", 
+                           "bindura", "marondera",  # Zimbabwe
+                           "lusaka", "ndola", "kitwe", "livingstone", "chipata",  # Zambia
+                           "maputo", "beira", "nampula", "tete"]  # Mozambique
+
+        # Extract entities from keywords
         for word in keywords:
-            if word in common_crops and not extracted_entities['crop_type']: extracted_entities['crop_type'] = word
-            if word in common_locations and not extracted_entities['location']: extracted_entities['location'] = word
+            if word in common_crops and not extracted_entities['crop_type']: 
+                extracted_entities['crop_type'] = word
+            if word in common_locations and not extracted_entities['location']: 
+                extracted_entities['location'] = word
+        
+        # Determine listing type
+        produce_keywords = ["listings", "produce", "selling", "for sale", "offerings"]
+        demand_keywords = ["demands", "requests", "buying", "looking for", "needs"]
         
-        if any(k in keywords for k in ["listings", "produce", "selling", "for sale", "offerings"]): extracted_entities['listing_type'] = 'produce'
-        elif any(k in keywords for k in ["demands", "requests", "buying", "looking for", "needs"]): extracted_entities['listing_type'] = 'demand'
+        if any(k in user_message.lower() for k in produce_keywords): 
+            extracted_entities['listing_type'] = 'produce'
+        elif any(k in user_message.lower() for k in demand_keywords): 
+            extracted_entities['listing_type'] = 'demand'
         
         if not extracted_entities['listing_type'] and not extracted_entities['crop_type']:
             return "To search platform data, please specify if you're looking for produce for sale or buyer demands, and optionally a crop type or location.", []
         
+        # Fetch active listings
         listings_ref = db.reference('listings', app=db_app).order_by_child('status').equal_to('active')
         all_active_listings = listings_ref.get() or {}
         found_items = []
 
         for lid, ldata in all_active_listings.items():
-            if not isinstance(ldata, dict): continue # Skip malformed entries
+            if not isinstance(ldata, dict): 
+                continue  # Skip malformed entries
 
             match = True
+            
+            # Check listing type match
             if extracted_entities['listing_type'] and ldata.get('listing_type') != extracted_entities['listing_type']:
                 match = False
-            # Use 'in' for partial matches on crop type and location if desired, or exact match
-            if extracted_entities['crop_type'] and not (extracted_entities['crop_type'] in ldata.get('crop_type', '').lower()):
-                match = False
-            if extracted_entities['location'] and not (extracted_entities['location'] in ldata.get('location', '').lower()):
-                match = False
+            
+            # Check crop type match (partial match)
+            if extracted_entities['crop_type']:
+                crop_type_data = ldata.get('crop_type', '').lower()
+                if not crop_type_data or extracted_entities['crop_type'] not in crop_type_data:
+                    match = False
+            
+            # Check location match (partial match)
+            if extracted_entities['location']:
+                location_data = ldata.get('location', '').lower()
+                if not location_data or extracted_entities['location'] not in location_data:
+                    match = False
             
             if match:
                 item_summary = f"- {ldata.get('listing_type', 'Item').capitalize()}: {ldata.get('crop_type', 'N/A')} in {ldata.get('location', 'N/A')}"
+                
                 if ldata.get('listing_type') == 'produce':
-                    item_summary += f", Price: {ldata.get('asking_price', 'N/A')}"
+                    asking_price = ldata.get('asking_price', 'N/A')
+                    item_summary += f", Price: {asking_price}"
                 elif ldata.get('listing_type') == 'demand':
-                     item_summary += f", Price Range: {ldata.get('price_range', 'N/A')}"
-                item_summary += f" (Qty: {ldata.get('quantity', 'N/A')})"
+                    price_range = ldata.get('price_range', 'N/A')
+                    item_summary += f", Price Range: {price_range}"
+                
+                quantity = ldata.get('quantity', 'N/A')
+                item_summary += f" (Qty: {quantity})"
                 found_items.append(item_summary)
 
         if not found_items:
-            return f"No active {extracted_entities['listing_type'] or 'items'} currently found on the platform matching your criteria ({extracted_entities['crop_type'] or 'any crop'}, {extracted_entities['location'] or 'any location'}). You can browse all items in the marketplace section.", []
+            search_criteria = []
+            if extracted_entities['crop_type']:
+                search_criteria.append(extracted_entities['crop_type'])
+            if extracted_entities['location']:
+                search_criteria.append(extracted_entities['location'])
+            if extracted_entities['listing_type']:
+                search_criteria.append(extracted_entities['listing_type'])
+            
+            criteria_str = ', '.join(search_criteria) if search_criteria else 'your criteria'
+            return f"No active {extracted_entities['listing_type'] or 'items'} currently found on the platform matching {criteria_str}. You can browse all items in the marketplace section.", []
 
-        summary = f"Here's what I found on the Tunasonga Agri platform based on your query:\n" + "\n".join(found_items[:5]) # Show top 5
+        # Prepare summary response
+        summary = f"Here's what I found on the Tunasonga Agri platform based on your query:\n" + "\n".join(found_items[:5])
         if len(found_items) > 5:
             summary += f"\n...and {len(found_items) - 5} more. For a full list, please visit the marketplace section or refine your search terms."
+        
         return summary, found_items
+        
     except firebase_exceptions.FirebaseError as fe:
         logger.error(f"Chat (Platform Data Helper): Firebase Error: {fe}")
         return "Database error occurred while fetching platform data.", []
@@ -1283,21 +1367,27 @@ def _fetch_platform_data_for_chat(user_message):
         logger.error(f"Chat (Platform Data Helper): Error: {e}")
         return "Could not fetch platform data at this time.", []
 
+
 # --- AI Chat Endpoint ---
 @app.route("/api/ai/chat", methods=["POST"])
 def ai_chat():
-    auth_header = request.headers.get("Authorization", "");
+    auth_header = request.headers.get("Authorization", "")
     uid = None
-    response_obj_gemini = None # For logging Gemini response object in case of AttributeError
+    response_obj_gemini = None  # For logging Gemini response object in case of AttributeError
+    intent = "unknown"  # Initialize intent
+    
     try:
         if not FIREBASE_INITIALIZED or not gemini_client:
             return jsonify({'error': 'Server or AI service not ready.'}), 503
         
         uid = verify_token(auth_header)
-        if not uid: # verify_token now raises, so this is a fallback if it somehow returns None without raising
+        if not uid:  # verify_token now raises, so this is a fallback if it somehow returns None without raising
             return jsonify({"error": "Authentication required.", "login_required": True}), 401
 
         data = request.get_json()
+        if not data:
+            return jsonify({"error": "Invalid request data."}), 400
+            
         user_message = data.get("message", "").strip()
         if not user_message:
             return jsonify({"error": "Message cannot be empty."}), 400
@@ -1314,9 +1404,20 @@ def ai_chat():
 
         Return ONLY the category string (e.g., "platform_data_query").
         """
-        response_obj_gemini = gemini_client.generate_content(model='gemini-2.0-flash', contents=[{'parts': [{'text': classify_prompt}]}])
-        intent = response_obj_gemini.text.strip().replace('"', '')
-        if intent not in ["platform_data_query", "price_trend_query", "general_agri_info", "other"]:
+        
+        response_obj_gemini = gemini_client.generate_content(classify_prompt)
+        
+        # Safely extract intent
+        if hasattr(response_obj_gemini, 'text') and response_obj_gemini.text:
+            intent = response_obj_gemini.text.strip().replace('"', '')
+        elif hasattr(response_obj_gemini, 'candidates') and response_obj_gemini.candidates:
+            if hasattr(response_obj_gemini.candidates[0], 'content'):
+                if hasattr(response_obj_gemini.candidates[0].content, 'parts') and response_obj_gemini.candidates[0].content.parts:
+                    intent = response_obj_gemini.candidates[0].content.parts[0].text.strip().replace('"', '')
+        
+        # Validate intent
+        valid_intents = ["platform_data_query", "price_trend_query", "general_agri_info", "other"]
+        if intent not in valid_intents:
             logger.warning(f"AI Chat: Unexpected intent: '{intent}' for query '{user_message}'. Defaulting to general_agri_info.")
             intent = "general_agri_info"
         
@@ -1332,7 +1433,7 @@ def ai_chat():
         
         elif intent == "price_trend_query":
             # Basic entity extraction for trend query (crop, location)
-            crop_match = re.search(r"(?:trend for|prices of|price of|trend of)\s+([\w\s]+?)(?:\s+in\s+([\w\s]+))?$", user_message.lower())
+            crop_match = re.search(r"(?:trend for|prices of|price of|trend of)\s+([\w\s]+?)(?:\s+in\s+([\w\s]+?))?(?:\s|$)", user_message.lower())
             trend_crop, trend_location = (None, None)
             if crop_match:
                 trend_crop = crop_match.group(1).strip()
@@ -1362,27 +1463,40 @@ Specific Instructions based on intent:
 Keep your answers clear and easy to understand. Avoid overly technical jargon unless necessary and explain it.
 Answer:
 """
-        response_obj_gemini = gemini_client.generate_content(model='gemini-2.0-flash', contents=[{'parts': [{'text': main_prompt}]}])
-        ai_response_text = response_obj_gemini.text.strip()
+        
+        response_obj_gemini = gemini_client.generate_content(main_prompt)
+        ai_response_text = ""
+        
+        # Safely extract response text
+        if hasattr(response_obj_gemini, 'text') and response_obj_gemini.text:
+            ai_response_text = response_obj_gemini.text.strip()
+        elif hasattr(response_obj_gemini, 'candidates') and response_obj_gemini.candidates:
+            if hasattr(response_obj_gemini.candidates[0], 'content'):
+                if hasattr(response_obj_gemini.candidates[0].content, 'parts') and response_obj_gemini.candidates[0].content.parts:
+                    ai_response_text = response_obj_gemini.candidates[0].content.parts[0].text.strip()
+        
+        if not ai_response_text:
+            ai_response_text = "I'm having trouble generating a response right now. Please try again."
         
         # 4. Store Chat History
-        db.reference(f'ai_chat_history/{uid}/{str(uuid.uuid4())}', app=db_app).set({
-            'user_message': user_message,
-            'ai_response': ai_response_text,
-            'intent_classified': intent,
-            'timestamp': datetime.now(timezone.utc).isoformat()
-        })
+        try:
+            db.reference(f'ai_chat_history/{uid}/{str(uuid.uuid4())}', app=db_app).set({
+                'user_message': user_message,
+                'ai_response': ai_response_text,
+                'intent_classified': intent,
+                'timestamp': datetime.now(timezone.utc).isoformat()
+            })
+        except Exception as chat_history_error:
+            logger.error(f"Failed to store chat history for UID {uid}: {chat_history_error}")
+            # Don't fail the request if chat history storage fails
+        
         return jsonify({"response": ai_response_text, "intent": intent})
 
-    except AttributeError as ae: # Gemini response structure issue
+    except AttributeError as ae:  # Gemini response structure issue
         logger.error(f"Gemini Response Attribute Error in ai_chat (UID: {uid}): {ae}. Response object: {response_obj_gemini}")
         ai_response_text = "I'm having a little trouble understanding that. Could you try rephrasing?"
-        try: # Attempt to get text if it's a common alternative structure
-            if response_obj_gemini and response_obj_gemini.candidates:
-                ai_response_text = response_obj_gemini.candidates[0].content.parts[0].text
-        except Exception: pass # Stick to default error message
-        return jsonify({"response": ai_response_text, "intent": intent or "unknown", "error_detail": "AI_RESPONSE_FORMAT_ISSUE"}), 200 # Return 200 with a user-friendly error
-    except Exception as e: # Catches errors from verify_token, Firebase, or other unexpected issues
+        return jsonify({"response": ai_response_text, "intent": intent, "error_detail": "AI_RESPONSE_FORMAT_ISSUE"}), 200
+    except Exception as e:  # Catches errors from verify_token, Firebase, or other unexpected issues
         return handle_route_errors(e, uid_context=uid)
 
 @app.route('/api/user/ai-chat-history', methods=['GET'])