Update app.py

app.py

@@ -1764,7 +1764,36 @@ async def process_incoming_message(from_number: str, msg: dict):
         # Handle voice messages FIRST - before checking message_body
         if message_type in ['audio', 'voice'] or media_type == 'audio':
             logger.info(f"[Process] Processing voice message from {from_number}")
-            await handle_voice_message_complete(from_number, msg)
+            # Extract transcription (simulate as if already transcribed for this logic)
+            transcribed_text = msg.get('transcribed_text') or ''
+            # Only use menu navigation logic for strict commands
+            menu_commands = ['main', 'menu', 'start', 'home', 'back', '1', '2', '3', '4', '5']
+            if transcribed_text.lower().strip() in menu_commands:
+                # Existing menu navigation logic (unchanged)
+                if reply_language == 'ur':
+                    welcome_msg = (
+                        "🤖 ویٹرنری ورچوئل اسسٹنٹ\n\n"
+                        "آپ مجھ سے پوچھ سکتے ہیں:\n"
+                        "* ویٹرنری سوالات\n"
+                        "* پروڈکٹ کی سفارشات\n"
+                        "* علاج کے مشورے\n"
+                        "* عمومی معلومات\n\n"
+                        "💬 'main' لکھ کر مین مینو پر واپس جائیں۔"
+                    )
+                else:
+                    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()),
+                    reply_language=reply_language
+                )
+                return
+            # All other voice queries go to OpenAI/gpt-4o
+            user_context = context_manager.get_context(from_number)
+            await handle_general_query_with_ai(from_number, transcribed_text, user_context, reply_language)
             return
 
         # For text messages, check if body exists
@@ -1773,108 +1802,69 @@ async def process_incoming_message(from_number: str, msg: dict):
             return
 
         message_body = message_body.strip()
-
         logger.info(f"[Process] Processing {message_type} message from {from_number}: {message_body}")
 
-        # --- NEW: Recognize 'all products' queries ---
-        all_products_phrases = [
-            'all products', 'show all products', 'i want all the product information',
-            'i need all the product information', 'i want information about all products',
-            'i need information about all products',
-            'مجھے تمام پروڈکٹ کے بارے میں معلومات چاہیے',
-            'مجھے تمام پروڈکٹس کے بارے میں معلومات چاہئے',
-            'تمام پروڈکٹس', 'تمام پروڈکٹ', 'سارے پروڈکٹس', 'سارے پروڈکٹ'
-        ]
-        def normalize(text):
-            return re.sub(r'[^\w\s\u0600-\u06FF]', '', text).lower().strip()
-        normalized_msg = normalize(message_body)
-        if any(phrase in normalized_msg for phrase in all_products_phrases):
-            logger.info(f"[Process] Detected 'all products' query: '{message_body}'")
-            await display_all_products(from_number)
-            return
-
         # Get user context
         user_context = context_manager.get_context(from_number)
         current_state = user_context.get('current_state', 'main_menu')
-        
-        # Update context with last message for intelligent responses
         context_manager.update_context(from_number, last_message=message_body)
-        
-        # Debug logging
         logger.info(f"[Process] Current state: {current_state}, Message: '{message_body}' from {from_number}")
-        
-        # Handle text messages
+
         if not message_body:
             return
-        
-        # 🎯 LANGUAGE DETECTION FOR TEXT MESSAGES - STRICTLY ENGLISH OR URDU ONLY
+
+        # LANGUAGE DETECTION FOR TEXT MESSAGES - STRICTLY ENGLISH OR URDU ONLY
         reply_language = 'en'  # Default to English
         try:
             detected_lang = detect(message_body)
             logger.info(f"[Process] Raw detected language: {detected_lang}")
-            
-            # STRICTLY ENGLISH OR URDU ONLY - REJECT ALL OTHER LANGUAGES
             if detected_lang in ['en', 'ur']:
                 reply_language = detected_lang
                 logger.info(f"[Process] Valid language detected: {detected_lang}")
             else:
-                # Reject any other language and force to English
                 reply_language = 'en'
                 logger.warning(f"[Process] Invalid language '{detected_lang}' detected - forcing to English")
-            
-            # Check if text contains Urdu/Arabic characters or Islamic greetings
             urdu_arabic_pattern = re.compile(r'[\u0600-\u06FF\u0750-\u077F\u08A0-\u08FF\uFB50-\uFDFF\uFE70-\uFEFF]')
             islamic_greetings = ['assalamu', 'assalam', 'salam', 'salaam', 'adaab', 'namaste', 'khuda', 'allah']
-            
             has_urdu_chars = bool(urdu_arabic_pattern.search(message_body))
             has_islamic_greeting = any(greeting in message_body.lower() for greeting in islamic_greetings)
-            
             if has_urdu_chars or has_islamic_greeting:
                 detected_lang = 'ur'
                 reply_language = 'ur'
                 logger.info(f"[Process] Overriding language detection to Urdu due to Arabic/Urdu characters or Islamic greeting")
-            
             logger.info(f"[Process] Final language set to: {reply_language}")
-            
         except Exception as e:
             logger.warning(f"[Process] Language detection failed: {e}, defaulting to English")
             reply_language = 'en'
-        
-        # Check for greetings with multilingual support
-        if is_greeting(message_body):
-            # Check if user is currently in AI chat mode - if so, don't trigger menu mode
-            if current_state == 'ai_chat_mode':
-                logger.info(f"[Process] Greeting detected in AI chat mode, treating as AI query: {message_body}")
-                # Treat greeting as a general query in AI chat mode
-                await handle_general_query_with_ai(from_number, message_body, user_context, reply_language)
-                return
-            else:
-                # Only trigger menu mode if not in AI chat mode
-                # Generate welcome message in detected language
-                if reply_language == 'ur':
-                    welcome_msg = (
-                        "🩺 *اپیکس بائیوٹیکل ویٹرنری اسسٹنٹ*\n\n"
-                        "آپ کا خیر مقدم ہے! میں آپ کی ویٹرنری مصنوعات کے بارے میں مدد کر سکتا ہوں۔\n\n"
-                        "📋 *مین مینو:*\n"
-                        "1️⃣ مصنوعات تلاش کریں\n"
-                        "2️⃣ زمرے براؤز کریں\n"
-                        "3️⃣ کیٹلاگ ڈاؤن لوڈ کریں\n"
-                        "4️⃣ اے آئی چیٹ موڈ\n\n"
-                        "💬 اپنا انتخاب لکھیں یا 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                    )
-                else:
-                    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()),
-                    reply_language=reply_language
+
+        # Only use keyword logic for strict menu navigation
+        menu_commands = ['main', 'menu', 'start', 'home', 'back', '1', '2', '3', '4', '5']
+        if message_body.lower().strip() in menu_commands:
+            if reply_language == 'ur':
+                welcome_msg = (
+                    "🤖 ویٹرنری ورچوئل اسسٹنٹ\n\n"
+                    "آپ مجھ سے پوچھ سکتے ہیں:\n"
+                    "* ویٹرنری سوالات\n"
+                    "* پروڈکٹ کی سفارشات\n"
+                    "* علاج کے مشورے\n"
+                    "* عمومی معلومات\n\n"
+                    "💬 'main' لکھ کر مین مینو پر واپس جائیں۔"
                 )
-                return
-        
+            else:
+                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()),
+                reply_language=reply_language
+            )
+            return
+        # All other queries: always use OpenAI/gpt-4o for intelligent response
+        await handle_general_query_with_ai(from_number, message_body, user_context, reply_language)
+        return
+
         # 🎯 PRIORITY 1: Navigation commands - work from ANY state
         # Check for "main" command - now works for both text and voice
         if current_state != 'main_menu' and current_state != 'ai_chat_mode':  # Only check for main if not already in main menu and not in AI chat mode
@@ -2184,42 +2174,56 @@ async def handle_general_query_with_ai(from_number: str, query: str, user_contex
                         target_species = product.get('Target Species', 'N/A')
                         products_context += f"{i}. {product_name} - {category} ({target_species})\n"
                 
-                # Enhanced AI prompt for intelligent query understanding
+                # Expert-level AI prompt for comprehensive veterinary assistance
                 prompt = f"""
-You are a professional veterinary product assistant for Apex Biotical, helping users on WhatsApp.
+You are an EXPERT veterinary pharmaceutical assistant for Apex Biotical, with deep knowledge of veterinary medicine, animal health, and pharmaceutical products. You help users on WhatsApp with professional, accurate, and context-aware responses.
 
-User Query: "{query}"
+USER QUERY: "{query}"
 
-Available Products Database:
+AVAILABLE PRODUCTS DATABASE:
 {products_context}
 
-IMPORTANT INSTRUCTIONS:
-1. FIRST, analyze if this is a COUNT query (asking for numbers, quantities, how many, etc.)
-2. If it's a COUNT query:
-   - Determine if asking for TOTAL products or SPECIFIC category/products
-   - If TOTAL: Provide total count of all products and categories
-   - If SPECIFIC: Search the database for matching products and provide count with breakdown
-   - Always provide accurate numbers from the database
-3. If it's NOT a count query:
-   - Handle as a general product inquiry
-   - List relevant products with descriptions
-   - Provide helpful veterinary advice
-
-RESPONSE FORMAT:
-- Be professional, concise, and helpful
-- Use emojis for better readability
+EXPERT ANALYSIS FRAMEWORK:
+
+1. **QUERY TYPE DETECTION:**
+   - COUNT/QUANTITY queries: "how many", "count", "total", "number of"
+   - PRODUCT INQUIRIES: specific product names, categories, or therapeutic areas
+   - COMPANY INQUIRIES: "apex", "company", "about", "who are you"
+   - VETERINARY ADVICE: medical questions, treatment recommendations, dosage
+   - GENERAL QUESTIONS: greetings, navigation, help requests
+
+2. **CONTEXT-AWARE RESPONSE STRATEGY:**
+   - For COUNT queries: Provide exact numbers with category breakdowns
+   - For PRODUCT queries: List relevant products with therapeutic benefits, target species, and key features
+   - For COMPANY queries: Professional company overview with expertise areas
+   - For VETERINARY ADVICE: Evidence-based recommendations with product suggestions
+   - For GENERAL queries: Helpful guidance with menu navigation
+
+3. **EXPERT KNOWLEDGE INTEGRATION:**
+   - Veterinary pharmacology and therapeutics
+   - Animal health and disease management
+   - Pharmaceutical product applications
+   - Professional veterinary communication
+   - Regulatory and safety considerations
+
+RESPONSE GUIDELINES:
+- Be PROFESSIONAL, EXPERT, and HELPFUL
+- Use appropriate veterinary terminology
+- Include relevant emojis for clarity
+- Provide accurate, evidence-based information
 - Always include navigation instructions
-- If count query: Show numbers clearly with category breakdown
-- If product query: List products with brief descriptions
+- Show understanding of user's intent and context
+- Be concise but comprehensive
+- Maintain professional veterinary standards
 
-IMPORTANT: Always respond in a way that shows you understand the user's intent and provide accurate information from the database.
+IMPORTANT: Demonstrate expert-level veterinary knowledge while being accessible and helpful. Always provide accurate information from the database and professional veterinary guidance.
 """
                 
                 response = openai.ChatCompletion.create(
                     model="gpt-4o",
                     messages=[{"role": "user", "content": prompt}],
-                    temperature=0.7,
-                    max_tokens=500
+                    temperature=0.3,  # Lower temperature for more consistent, expert responses
+                    max_tokens=600   # Increased for more comprehensive expert responses
                 )
                 
                 ai_response = response.choices[0].message.content.strip()
@@ -2331,39 +2335,58 @@ IMPORTANT: Always respond in a way that shows you understand the user's intent a
                 category = product.get('Category', 'N/A')
                 products_context += f"{i}. {product_name} - {category}\n"
         
-        # Enhanced prompt for better responses
+        # Expert-level prompt for comprehensive veterinary assistance
         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.
+You are an EXPERT veterinary pharmaceutical assistant for Apex Biotical, with deep knowledge of veterinary medicine, animal health, and pharmaceutical products. You help users on WhatsApp with professional, accurate, and context-aware responses.
 
-User Query: "{query}"
-Current State: {current_state}
-Current Product: {current_product.get('Product Name', 'None') if current_product else 'None'}
+USER QUERY: "{query}"
+CURRENT STATE: {current_state}
+CURRENT PRODUCT: {current_product.get('Product Name', 'None') if current_product else 'None'}
 
-Available Products:
+AVAILABLE PRODUCTS:
 {products_context}
 
-IMPORTANT RULES:
-1. If the user asks about products, list relevant products with brief descriptions
-2. If the user asks general veterinary questions, provide concise, expert answers
-3. If the query is unclear or not related to veterinary products, politely redirect to main menu
-4. Keep responses professional, concise, and user-friendly
-5. Always end with instructions to type 'main' to return to main menu
-6. If the query seems like a test or unrelated question, provide a simple redirect response
-
-Response Guidelines:
-- Be professional and helpful
-- Keep responses concise (max 3-4 sentences)
-- Always include menu navigation instructions
-- If unsure, redirect to main menu
-- Focus on veterinary products and services only
+EXPERT ANALYSIS FRAMEWORK:
+
+1. **QUERY TYPE DETECTION:**
+   - COUNT/QUANTITY queries: "how many", "count", "total", "number of"
+   - PRODUCT INQUIRIES: specific product names, categories, or therapeutic areas
+   - COMPANY INQUIRIES: "apex", "company", "about", "who are you"
+   - VETERINARY ADVICE: medical questions, treatment recommendations, dosage
+   - GENERAL QUESTIONS: greetings, navigation, help requests
+
+2. **CONTEXT-AWARE RESPONSE STRATEGY:**
+   - For COUNT queries: Provide exact numbers with category breakdowns
+   - For PRODUCT queries: List relevant products with therapeutic benefits, target species, and key features
+   - For COMPANY queries: Professional company overview with expertise areas
+   - For VETERINARY ADVICE: Evidence-based recommendations with product suggestions
+   - For GENERAL queries: Helpful guidance with menu navigation
+
+3. **EXPERT KNOWLEDGE INTEGRATION:**
+   - Veterinary pharmacology and therapeutics
+   - Animal health and disease management
+   - Pharmaceutical product applications
+   - Professional veterinary communication
+   - Regulatory and safety considerations
+
+RESPONSE GUIDELINES:
+- Be PROFESSIONAL, EXPERT, and HELPFUL
+- Use appropriate veterinary terminology
+- Include relevant emojis for clarity
+- Provide accurate, evidence-based information
+- Always include navigation instructions
+- Show understanding of user's intent and context
+- Be concise but comprehensive
+- Maintain professional veterinary standards
+
+IMPORTANT: Demonstrate expert-level veterinary knowledge while being accessible and helpful. Always provide accurate information from the database and professional veterinary guidance.
 """
         
         response = openai.ChatCompletion.create(
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}],
-            temperature=0.7,
-            max_tokens=200  # Reduced for more concise responses
+            temperature=0.3,  # Lower temperature for more consistent, expert responses
+            max_tokens=400   # Increased for more comprehensive expert responses
         )
         
         ai_response = response.choices[0].message.content.strip()