Update app.py

app.py

@@ -1996,25 +1996,15 @@ async def process_incoming_message(from_number: str, msg: dict):
 
 async def handle_general_query_with_ai(from_number: str, query: str, user_context: dict, reply_language: str = 'en'):
     """Handle general queries with OpenAI intelligence"""
-    # Force Urdu replies for Option 4
     reply_language = 'ur'
     logger.info(f"[AI General] Forcing reply_language to Urdu for Option 4.")
-    
     try:
-        if not OPENAI_API_KEY:
+        if not openai.api_key:
             send_whatsjet_message(from_number, 
                 "❌ AI assistance is not available. Please try searching for a specific product or type 'main' for the menu.")
             return
-        
-        # Create context-aware prompt
         current_state = user_context.get('current_state', 'main_menu')
         current_product = user_context.get('current_product')
-        
-        # --- SYSTEM PROMPT FOR GENERAL/OUT-OF-MENU QUERIES ---
-        # This prompt ensures the assistant answers professionally, accurately, and helpfully.
-        # If the query is about products, list all relevant products (not just one) with brief details.
-        # If the query is general, provide a concise, expert veterinary answer.
-        # Clarify when a query is outside the menu system and offer to return to the main menu if needed.
         prompt = f"""
 You are a professional veterinary product assistant for Apex Biotical, helping users on WhatsApp.
 Always answer in a clear, accurate, and helpful manner.
@@ -2028,17 +2018,13 @@ If the user asks a general veterinary question, provide a concise, expert answer
 If the query is outside the menu system, politely clarify and offer to return to the main menu (type 'main').
 Always keep responses professional, concise, and user-friendly.
 """
-        
         response = openai.ChatCompletion.create(
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}],
             temperature=0.7,
             max_tokens=300
         )
-        
         ai_response = response.choices[0].message.content.strip()
-        
-        # Translate response if needed
         if reply_language == 'ur':
             try:
                 translated_response = GoogleTranslator(source='auto', target='ur').translate(ai_response)
@@ -2048,21 +2034,11 @@ Always keep responses professional, concise, and user-friendly.
                 send_whatsjet_message(from_number, ai_response)
         else:
             send_whatsjet_message(from_number, ai_response)
-        
-        # Add to conversation history
-        context_manager.add_to_history(from_number, query, ai_response)
-        
+        if context_manager:
+            context_manager.add_to_history(from_number, query, ai_response)
     except Exception as e:
         logger.error(f"[AI] Error handling general query: {e}")
-        # Instead of sending a generic error, return to main menu
-        welcome_msg = generate_veterinary_welcome_message()
-        send_whatsjet_message(from_number, welcome_msg)
-        context_manager.update_context(
-            from_number, 
-            current_state='main_menu',
-            current_menu='main_menu',
-            current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values())
-        )
+        send_whatsjet_message(from_number, "❌ AI Assistant encountered an error. Please try again or type 'main' to return to main menu.")
 
 async def handle_contact_request(from_number: str):
     """Handle contact request"""
@@ -3712,181 +3688,51 @@ async def test_send_product_image(phone: str, product_name: str = "Bromacid"):
         return {"error": str(e)}
 
 async def handle_intelligent_product_inquiry(from_number: str, query: str, user_context: dict, reply_language: str = 'en'):
-    """Handle product inquiry with OpenAI intelligence and media support"""
+    """Handle product inquiry with OpenAI intelligence and media support, matching WhatsApp screenshot logic"""
     try:
-        # First try direct product search
         products = get_veterinary_product_matches(query)
-        
         if products:
-            # Check if this is a broad/category query (multiple products found)
             if len(products) > 1:
-                # Use OpenAI to generate a professional summary and list all products
-                if OPENAI_API_KEY:
-                    try:
-                        # Create a comprehensive prompt for multiple products
-                        products_info = []
-                        for i, product in enumerate(products, 1):
-                            product_name = product.get('Product Name', 'N/A')
-                            category = product.get('Category', 'N/A')
-                            target_species = product.get('Target Species', 'N/A')
-                            products_info.append(f"{i}. {product_name} - {category} ({target_species})")
-                        
-                        products_text = "\n".join(products_info)
-                        
-                        prompt = f"""
-You are a professional veterinary product assistant for Apex Biotical. The user asked about "{query}" and we found {len(products)} relevant products.
-
-Available Products:
-{products_text}
-
-Please provide:
-1. A professional, welcoming response acknowledging their query
-2. A brief summary of what these products are for (if it's a category like "poultry products", explain the category)
-3. List all products with their numbers and brief descriptions
-4. Clear instructions on how to proceed
-
-Format your response professionally with emojis and clear structure. Keep it concise but informative.
-"""
-                        
-                        response = openai.ChatCompletion.create(
-                            model="gpt-4o",
-                            messages=[{"role": "user", "content": prompt}],
-                            temperature=0.7,
-                            max_tokens=400
-                        )
-                        
-                        ai_response = response.choices[0].message['content'].strip()
-                        
-                        # Add instructions for selection
-                        selection_instructions = (
-                            f"\n\n💬 *To view detailed information about any product, reply with its number (1-{len(products)})*\n"
-                            "💬 *Type 'main' to return to the main menu*"
-                        )
-                        
-                        full_response = ai_response + selection_instructions
-                        
-                        # Translate response if needed
-                        if reply_language == 'ur':
-                            try:
-                                translated_response = GoogleTranslator(source='auto', target='ur').translate(full_response)
-                                send_whatsjet_message(from_number, translated_response)
-                            except Exception as e:
-                                logger.error(f"[AI] Translation error: {e}")
-                                send_whatsjet_message(from_number, full_response)
-                        else:
-                            send_whatsjet_message(from_number, full_response)
-                        
-                        # Store the product list in context for selection handling
-                        context_manager.update_context(
-                            from_number, 
-                            current_state='intelligent_products_menu',
-                            current_menu='intelligent_products_menu',
-                            current_menu_options=[f"Product {i+1}" for i in range(len(products))],
-                            available_products=products,
-                            last_query=query
-                        )
-                        
-                        # Add to conversation history
-                        context_manager.add_to_history(from_number, query, full_response)
-                        return
-                        
-                    except Exception as e:
-                        logger.error(f"[AI] Error generating product summary: {e}")
-                        # Fall back to simple listing if AI fails
-                        pass
-                
-                # Fallback: Simple listing without AI
-                message = f"🔍 *Found {len(products)} products matching '{query}':*\n\n"
-                
+                message = f"Certainly, here are the relevant products for your query:\n\n"
                 for i, product in enumerate(products, 1):
-                    product_name = product.get('Product Name', 'N/A')
-                    category = product.get('Category', 'N/A')
-                    target_species = product.get('Target Species', 'N/A')
-                    message += f"{format_number_with_emoji(i)} {product_name}\n"
-                    message += f"   📦 {category} ({target_species})\n\n"
-                
-                message += (
-                    f"💬 *To view detailed information about any product, reply with its number (1-{len(products)})*\n"
-                    "💬 *Type 'main' to return to the main menu*"
-                )
-                
-                # Translate response if needed
-                if reply_language == 'ur':
-                    try:
-                        translated_message = GoogleTranslator(source='auto', target='ur').translate(message)
-                        send_whatsjet_message(from_number, translated_message)
-                    except Exception as e:
-                        logger.error(f"[AI] Translation error: {e}")
-                        send_whatsjet_message(from_number, message)
-                else:
-                    send_whatsjet_message(from_number, message)
-                
-                # Store the product list in context for selection handling
-                context_manager.update_context(
-                    from_number, 
-                    current_state='intelligent_products_menu',
-                    current_menu='intelligent_products_menu',
-                    current_menu_options=[f"Product {i+1}" for i in range(len(products))],
-                    available_products=products,
-                    last_query=query
-                )
-                
-                # Add to conversation history
-                context_manager.add_to_history(from_number, query, message)
-                
+                    product_name = product.get('Product Name', 'Unknown')
+                    category = product.get('Category', '')
+                    short_desc = product.get('Type', '') or product.get('Indications', '')
+                    message += f"{i}. {product_name}"
+                    if category:
+                        message += f" - {category}"
+                    if short_desc:
+                        message += f" / {short_desc}"
+                    message += "\n"
+                message += (f"\nTo view detailed information about any product, reply with its number (1-{len(products)})\n"
+                            "Type 'main' to return to the main menu")
+                send_whatsjet_message(from_number, message)
+                if context_manager:
+                    context_manager.update_context(
+                        from_number,
+                        current_state='intelligent_products_menu',
+                        current_menu='intelligent_products_menu',
+                        current_menu_options=[str(i) for i in range(1, len(products)+1)],
+                        available_products=products
+                    )
+                return
             else:
-                # Single product found - show detailed information with media support
                 selected_product = products[0]
-                context_manager.update_context(
-                    from_number, 
-                    current_product=selected_product, 
-                    current_state='product_inquiry',
-                    current_menu='product_inquiry',
-                    current_menu_options=list(MENU_CONFIG['product_inquiry']['option_descriptions'].values())
-                )
-                
-                # Send product image with caption using the new function
-                await send_product_image_with_caption(from_number, selected_product, user_context)
-                
-                # Add to conversation history
-                context_manager.add_to_history(from_number, query, f"Product inquiry for {selected_product.get('Product Name', 'Unknown')}")
-            
+                if context_manager:
+                    context_manager.update_context(
+                        from_number,
+                        current_product=selected_product,
+                        current_state='product_inquiry',
+                        current_menu='product_inquiry',
+                        current_menu_options=list(MENU_CONFIG['product_inquiry']['option_descriptions'].values())
+                    )
+                # The actual sending of product details should be handled by the caller
+                return selected_product
         else:
-            # Enhanced "not found" response with veterinary suggestions
-            message = (
-                "❌ *Product Not Found*\n\n"
-                f"🔍 *We couldn't find '{query}' in our veterinary database.*\n\n"
-                "💡 *Try these alternatives:*\n"
-                "• Check spelling (e.g., 'Hydropex' not 'Hydro pex')\n"
-                "• Search by symptoms (e.g., 'respiratory', 'liver support')\n"
-                "• Search by category (e.g., 'antibiotic', 'vitamin')\n"
-                "• Search by species (e.g., 'poultry', 'livestock')\n\n"
-                "🏥 *Popular Veterinary Products:*\n"
-                "• Hydropex (Electrolyte supplement)\n"
-                "• Heposel (Liver tonic)\n"
-                "• Bromacid (Respiratory support)\n"
-                "• Tribiotic (Antibiotic)\n"
-                "• Symodex (Multivitamin)\n\n"
-                "💬 *Type 'main' to return to main menu or try another search.*"
-            )
-            
-            # Translate response if needed
-            if reply_language == 'ur':
-                try:
-                    translated_message = GoogleTranslator(source='auto', target='ur').translate(message)
-                    send_whatsjet_message(from_number, translated_message)
-                except Exception as e:
-                    logger.error(f"[AI] Translation error: {e}")
-                    send_whatsjet_message(from_number, message)
-            else:
-                send_whatsjet_message(from_number, message)
-            
+            send_whatsjet_message(from_number, "❌ No products found matching your query.\nType 'main' to return to the main menu.")
     except Exception as e:
-        logger.error(f"Error in product inquiry: {e}")
-        # Instead of sending a generic error, return to main menu
-        welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
-        send_whatsjet_message(from_number, welcome_msg)
-        context_manager.update_context(from_number, current_state='main_menu', current_menu='main_menu', current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values()))
+        logger.error(f"Error in handle_intelligent_product_inquiry: {e}")
+        send_whatsjet_message(from_number, "❌ Error processing your request. Type 'main' to return to the main menu.")
 
 async def handle_contact_request(from_number: str):
     """Handle contact request"""
@@ -3920,17 +3766,11 @@ async def handle_contact_request(from_number: str):
             current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values())
         )
 
-# Add this helper function near the top of the file:
+# Helper for restoring English terms in translations
 def restore_english_terms(translated_text, original_text, product_names, category_names):
-    """
-    Replace Urdu-translated product/category names in translated_text with their original English from original_text.
-    """
     for name in product_names + category_names:
         if name and name.lower() in translated_text.lower() and name.lower() not in original_text.lower():
-            # If the English name is not in the original, skip
             continue
-        # Replace Urdu translation with English name
-        # (This is a simple approach; for more accuracy, use regex or fuzzy matching)
         translated_text = translated_text.replace(name, name)
     return translated_text