diff --git "a/app.py" "b/app.py"
--- "a/app.py"
+++ "b/app.py"
@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 """
-Apex Biotical Veterinary WhatsApp Bot - Premium Edition
-The most effective and accurate veterinary chatbot in the market
+Apex Biotical Veterinary WhatsApp Assistant - Premium Edition
+The most effective and accurate veterinary Assistant in the market
 """
 
 import os
@@ -60,7 +60,11 @@ logger = logging.getLogger(__name__)
 load_dotenv()
 
 # Initialize FastAPI app
-app = FastAPI(title="Apex Biotical Veterinary Bot", version="2.0.0")
+app = FastAPI(title="Apex Biotical Veterinary Assistant", version="2.0.0")
+
+# Ensure static and uploads directories exist before mounting
+os.makedirs('static', exist_ok=True)
+os.makedirs('uploads', exist_ok=True)
 
 # Mount static files and templates
 app.mount("/static", StaticFiles(directory="static"), name="static")
@@ -256,7 +260,7 @@ async def download_voice_file(media_url: str, filename: str) -> str:
         return None
 
 async def transcribe_voice_with_openai(file_path: str) -> str:
-    """Transcribe voice file using OpenAI Whisper with improved error handling and language restriction"""
+    """Transcribe voice file using OpenAI Whisper with comprehensive veterinary domain system prompt"""
     try:
         # Check if file exists and has content
         if not os.path.exists(file_path):
@@ -270,13 +274,82 @@ async def transcribe_voice_with_openai(file_path: str) -> str:
         
         logger.info(f"[Transcribe] Transcribing file: {file_path} (size: {file_size} bytes)")
         
-        # First attempt with English-specific prompt and language restriction
+        # Comprehensive system prompt for veterinary WhatsApp assistant
+        system_prompt = """
+You are transcribing voice messages for Apex Biotical Veterinary WhatsApp Assistant. This is a professional veterinary products chatbot.
+
+CONTEXT: Users can speak product names, menu selections, numbers, and general queries in English or Urdu.
+
+PRODUCT NAMES (Veterinary Products):
+- Hydropex (electrolyte supplement)
+- Respira Aid Plus (respiratory support)
+- Heposel (liver tonic)
+- Bromacid (respiratory/mucolytic)
+- Hexatox (liver & kidney support)
+- APMA Fort (mycotoxin binder)
+- Para C.E (heat stress support)
+- Tribiotic (antibiotic)
+- PHYTO-SAL (phytogenic supplement)
+- Mycopex Super (mycotoxin binder)
+- Eflin KT-20 (antibiotic)
+- Salcozine ST-30 (anticoccidial)
+- Oftilex UA-10 (antibiotic)
+- Biscomin 10 (injectable antibiotic)
+- Apvita Plus (vitamin supplement)
+- B-G Aspro-C (aspirin + vitamin C)
+- EC-Immune (immune booster)
+- Liverpex (liver tonic)
+- Symodex (multivitamin)
+- Respira Aid (respiratory support)
+- Adek Gold (multivitamin)
+- Immuno DX (immune enhancer)
+
+MENU SELECTIONS:
+- Main menu options: 1, 2, 3, 4
+- Product numbers: 1-23
+- Category numbers: 1-10
+- Navigation: main, menu, back, home, start
+
+NUMBERS (English & Urdu):
+English: one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, eighteen, nineteen, twenty, twenty-one, twenty-two, twenty-three
+Urdu (Roman): aik, ek, do, teen, char, panch, che, sat, ath, nau, das, gyara, bara, tera, choda, pandra, sola, satara, athara, unnees, bees, ikkees, baees, tees
+Urdu (Script): ایک, دو, تین, چار, پانچ, چھ, سات, آٹھ, نو, دس, گیارہ, بارہ, تیرہ, چودہ, پندرہ, سولہ, سترہ, اٹھارہ, انیس, بیس, اکیس, بائیس, تئیس
+
+COMMON GREETINGS:
+English: hi, hello, hey, good morning, good afternoon, good evening, how are you
+Urdu: salam, assalamu alaikum, adaab, namaste, khuda hafiz
+
+MENU COMMANDS:
+English: search, browse, download, catalog, contact, availability, main menu, option, number, choice
+Urdu: تلاش, براؤز, ڈاؤن لوڈ, کیٹلاگ, رابطہ, دستیابی, مین مینو, آپشن, نمبر, اختیار
+
+TRANSCRIPTION RULES:
+1. Transcribe product names exactly as listed above
+2. Convert spoken numbers to digits (1, 2, 3, etc.)
+3. Handle both English and Urdu speech
+4. Preserve exact spelling for product names
+5. Convert menu selections to numbers
+6. Handle common transcription errors (opium->option, numara->number)
+7. Maintain context for veterinary domain
+
+EXAMPLES:
+- "hydropex" -> "hydropex"
+- "respira aid plus" -> "respira aid plus"
+- "option number one" -> "1"
+- "aik" -> "1"
+- "do" -> "2"
+- "main menu" -> "main"
+- "salam" -> "salam"
+- "search products" -> "search products"
+"""
+        
+        # First attempt with comprehensive system prompt
         with open(file_path, 'rb') as audio_file:
             transcript = openai.Audio.transcribe(
                 model="whisper-1",
                 file=audio_file,
-                language="en",  # Force English first
-                prompt="This is a voice message for a veterinary products bot. Language: English or Urdu only. Common greetings: hi, hello, hey, salam, assalamualaikum. Numbers: one, two, three, 1, 2, 3, aik, do, teen. Menu options: search, browse, download, catalog, products, categories, contact, availability. Products: hydropex, heposel, bromacid, tribiotic, symodex, adek gold. Please transcribe clearly and accurately."
+                language="en",  # Start with English
+                prompt=system_prompt
             )
             
         transcribed_text = transcript.text.strip()
@@ -286,12 +359,51 @@ async def transcribe_voice_with_openai(file_path: str) -> str:
         if not transcribed_text or len(transcribed_text.strip()) < 2:
             logger.warning(f"[Transcribe] First attempt failed, trying with Urdu-specific prompt")
             
+            urdu_system_prompt = """
+You are transcribing Urdu voice messages for Apex Biotical Veterinary WhatsApp Assistant.
+
+PRODUCT NAMES (Urdu/English):
+- ہائیڈروپیکس (Hydropex)
+- ریسپیرا ایڈ پلس (Respira Aid Plus)
+- ہیپوسیل (Heposel)
+- بروماسڈ (Bromacid)
+- ہیکساٹوکس (Hexatox)
+- اے پی ایم اے فورٹ (APMA Fort)
+- پیرا سی ای (Para C.E)
+- ٹرائی بیوٹک (Tribiotic)
+- فائٹو سال (PHYTO-SAL)
+- مائیکوپیکس سپر (Mycopex Super)
+
+URDU NUMBERS:
+- ایک (1), دو (2), تین (3), چار (4), پانچ (5)
+- چھ (6), سات (7), آٹھ (8), نو (9), دس (10)
+- گیارہ (11), بارہ (12), تیرہ (13), چودہ (14), پندرہ (15)
+- سولہ (16), سترہ (17), اٹھارہ (18), انیس (19), بیس (20)
+- اکیس (21), بائیس (22), تئیس (23)
+
+URDU GREETINGS:
+- سلام (salam), السلام علیکم (assalamu alaikum)
+- آداب (adaab), نمستے (namaste), خدا حافظ (khuda hafiz)
+
+URDU MENU COMMANDS:
+- مین مینو (main menu), آپشن (option), نمبر (number)
+- تلاش (search), براؤز (browse), ڈاؤن لوڈ (download)
+- کیٹلاگ (catalog), رابطہ (contact), دستیابی (availability)
+
+TRANSCRIPTION RULES:
+1. Transcribe Urdu words in Urdu script
+2. Convert Urdu numbers to digits
+3. Handle mixed Urdu-English speech
+4. Preserve product names exactly
+5. Convert menu selections to numbers
+"""
+            
             with open(file_path, 'rb') as audio_file:
                 transcript = openai.Audio.transcribe(
                     model="whisper-1",
                     file=audio_file,
                     language="ur",  # Force Urdu
-                    prompt="This is a voice message in Urdu for a veterinary products bot. Common Urdu greetings: سلام, ہیلو, ہائے, السلام علیکم, وعلیکم السلام. Numbers: ایک, دو, تین, چار, پانچ, 1, 2, 3, 4, 5. Menu options: تلاش, براؤز, ڈاؤن لوڈ, کیٹلاگ, پروڈکٹ, کیٹیگری, رابطہ, دستیابی. Products: ہائیڈروپیکس, ہیپوسیل, بروماسڈ, ٹرائیبیوٹک. Please transcribe clearly in Urdu or English."
+                    prompt=urdu_system_prompt
                 )
                 
             transcribed_text = transcript.text.strip()
@@ -301,11 +413,35 @@ async def transcribe_voice_with_openai(file_path: str) -> str:
             if not transcribed_text or len(transcribed_text.strip()) < 2:
                 logger.warning(f"[Transcribe] Second attempt failed, trying with mixed language prompt")
                 
+                mixed_system_prompt = """
+You are transcribing voice messages for a veterinary products WhatsApp assistant. The user may speak in English, Urdu, or a mix of both languages.
+
+PRODUCT NAMES (exact spelling required):
+Hydropex, Respira Aid Plus, Heposel, Bromacid, Hexatox, APMA Fort, Para C.E, Tribiotic, PHYTO-SAL, Mycopex Super, Eflin KT-20, Salcozine ST-30, Oftilex UA-10, Biscomin 10, Apvita Plus, B-G Aspro-C, EC-Immune, Liverpex, Symodex, Respira Aid, Adek Gold, Immuno DX
+
+NUMBERS (convert to digits):
+English: one->1, two->2, three->3, etc.
+Urdu: aik->1, ek->1, do->2, teen->3, etc.
+
+MENU COMMANDS:
+main, menu, back, home, start, option, number, search, browse, download, catalog, contact, availability
+
+GREETINGS:
+hi, hello, salam, assalamu alaikum, adaab, namaste
+
+TRANSCRIPTION RULES:
+1. Transcribe exactly what you hear
+2. Convert numbers to digits
+3. Preserve product names exactly
+4. Handle both languages
+5. Convert menu selections to numbers
+"""
+                
                 with open(file_path, 'rb') as audio_file:
                     transcript = openai.Audio.transcribe(
                         model="whisper-1",
                         file=audio_file,
-                        prompt="This is a voice message for a veterinary products bot. Language: English or Urdu only. Common words: hi, hello, salam, one, two, three, aik, do, teen, search, browse, download, catalog, products, categories, contact, availability, hydropex, heposel, bromacid, tribiotic, symodex, adek gold. Please transcribe any speech you can hear, even if unclear. Numbers and menu selections are important."
+                        prompt=mixed_system_prompt
                     )
                     
                 transcribed_text = transcript.text.strip()
@@ -324,7 +460,7 @@ async def transcribe_voice_with_openai(file_path: str) -> str:
         return None
 
 def process_voice_input(text: str) -> str:
-    """Process and clean voice input text with common transcription error correction"""
+    """Process and clean voice input text with veterinary domain-specific transcription error correction"""
     if not text:
         return ""
     
@@ -337,12 +473,9 @@ def process_voice_input(text: str) -> str:
     # Basic punctuation cleanup
     processed_text = processed_text.replace(' ,', ',').replace(' .', '.')
     
-    # Common transcription error corrections
+    # Veterinary domain-specific transcription error corrections
     transcription_fixes = {
-        'bye': 'hi',
-        'goodbye': 'hello',
-        'good bye': 'hello',
-        'good by': 'hello',
+        # Common menu selection errors
         'opium': 'option',
         'opium numara': 'option number',
         'opium number': 'option number',
@@ -361,6 +494,7 @@ def process_voice_input(text: str) -> str:
         'numbra 1': 'number 1',
         'numbra 2': 'number 2',
         'numbra 3': 'number 3',
+        
         # Number fixes - only when they appear as standalone numbers
         'aik': '1',
         'ek': '1',
@@ -378,6 +512,7 @@ def process_voice_input(text: str) -> str:
         'ath': '8',
         'nau': '9',
         'das': '10',
+        
         # Navigation command fixes
         'man': 'main',
         'men': 'main',
@@ -387,7 +522,34 @@ def process_voice_input(text: str) -> str:
         'menu': 'main',
         'home': 'main',
         'back': 'main',
-        'return': 'main'
+        'return': 'main',
+        
+        # Veterinary product name corrections
+        'hydro pex': 'hydropex',
+        'hydro pex': 'hydropex',
+        'respira aid': 'respira aid plus',
+        'respira aid plus': 'respira aid plus',
+        'hepo sel': 'heposel',
+        'brom acid': 'bromacid',
+        'hexa tox': 'hexatox',
+        'apma fort': 'apma fort',
+        'para c': 'para c.e',
+        'para ce': 'para c.e',
+        'tribiotic': 'tribiotic',
+        'phyto sal': 'phyto-sal',
+        'mycopex': 'mycopex super',
+        'mycopex super': 'mycopex super',
+        'eflin': 'eflin kt-20',
+        'salcozine': 'salcozine st-30',
+        'oftilex': 'oftilex ua-10',
+        'biscomin': 'biscomin 10',
+        'apvita': 'apvita plus',
+        'bg aspro': 'b-g aspro-c',
+        'ec immune': 'ec-immune',
+        'liverpex': 'liverpex',
+        'symodex': 'symodex',
+        'adek': 'adek gold',
+        'immuno': 'immuno dx'
     }
     
     # Apply transcription fixes - but be careful with Islamic greetings
@@ -646,18 +808,22 @@ context_manager = VeterinaryContextManager()
 # Enhanced product response with veterinary domain expertise
 def generate_veterinary_product_response(product_info: Dict[str, Any], user_context: Dict[str, Any]) -> str:
     """Generate comprehensive veterinary product response with intelligent information handling"""
+    
     def clean_text(text):
         if pd.isna(text) or text is None:
             return "Not specified"
         return str(text).strip()
+    
     # Extract product details
     product_name = clean_text(product_info.get('Product Name', ''))
     product_type = clean_text(product_info.get('Type', ''))
     category = clean_text(product_info.get('Category', ''))
     indications = clean_text(product_info.get('Indications', ''))
+    
     # Check for PDF link in the CSV data
     pdf_link = ""
     try:
+        # Load CSV data to check for PDF link
         csv_data = pd.read_csv('Veterinary.csv')
         product_row = csv_data[csv_data['Product Name'] == product_name]
         if not product_row.empty:
@@ -666,15 +832,27 @@ def generate_veterinary_product_response(product_info: Dict[str, Any], user_cont
                 pdf_link = brochure_link.strip()
     except Exception as e:
         logger.warning(f"Error checking PDF link for {product_name}: {e}")
-    response = f"""🧪 *Name:* {product_name}\n📦 *Type:* {product_type}\n🏥 *Category:* {category}\n💊 *Used For:* {indications}"""
+    
+    # Build the response
+    response = f"""🧪 *Name:* {product_name}
+📦 *Type:* {product_type}
+🏥 *Category:* {category}
+💊 *Used For:* {indications}"""
+    
+    # Add PDF link if available, in the requested format
     if pdf_link:
         response += f"\n\n📄 Product Brochure Available\n🔗 {product_name} PDF:\n{pdf_link}"
+    
+    # Add menu options
     response += f"""
-\n💬 *Available Actions:*
+
+💬 *Available Actions:*
 1️⃣ Talk to Veterinary Consultant
 2️⃣ Inquire About Availability
 3️⃣ Back to Main Menu
-\n💬 Select an option or ask about related products"""
+
+💬 Select an option or ask about related products"""
+    
     return response
 
 def clean_text_for_pdf(text: str) -> str:
@@ -808,10 +986,8 @@ def generate_veterinary_pdf(product: Dict[str, Any]) -> bytes:
 async def send_catalog_pdf(phone_number: str):
     """Send the complete product catalog as a link to the PDF"""
     try:
-        # Use the static file URL for Hugging Face Spaces
-        server_url = os.getenv("SERVER_URL", "https://your-huggingface-space-url.hf.space")
-        catalog_url = f"{server_url}/static/Hydropex.pdf"
-        
+        # Use the correct Google Drive link converted to direct download format
+        catalog_url = "https://drive.google.com/uc?export=download&id=1mxpkFf3DY-n3QHzZBe_CdksR-gHu2f_0"
         message = (
             "📋 *Apex Biotical Veterinary Products Catalog*\n\n"
             "📄 Here's your complete product catalog with all our veterinary products:\n"
@@ -838,16 +1014,16 @@ async def send_individual_product_pdf(phone_number: str, product: Dict[str, Any]
         filename = f"{safe_name}_{timestamp}.pdf"
         
         # Save PDF to uploads directory
-        uploads_dir = "uploads"
+        uploads_dir = "../uploads"
         os.makedirs(uploads_dir, exist_ok=True)
         pdf_path = os.path.join(uploads_dir, filename)
         
         with open(pdf_path, 'wb') as f:
             f.write(pdf_content)
         
-        # Generate download URL for Hugging Face Spaces
-        server_url = os.getenv("SERVER_URL", "https://your-huggingface-space-url.hf.space")
-        download_url = f"{server_url}/uploads/{filename}"
+        # Generate download URL
+        base_url = os.getenv("PUBLIC_BASE_URL", "http://localhost:8000")
+        download_url = f"{base_url}/uploads/{filename}"
         
         # Send PDF via WhatsApp media
         success = send_whatsjet_message(
@@ -862,7 +1038,7 @@ async def send_individual_product_pdf(phone_number: str, product: Dict[str, Any]
         if success:
             message = (
                 f"📄 *{product_name} - Product Information*\n\n"
-                f"📎 [Direct Download Link]({download_url})\n\n"
+                "📎 [Direct Download Link]({download_url})\n\n"
                 "💬 *If the PDF didn't download, use the link above*\n"
                 "Type 'main' to return to main menu."
             )
@@ -871,7 +1047,7 @@ async def send_individual_product_pdf(phone_number: str, product: Dict[str, Any]
             # If media send failed, send only the link
             message = (
                 f"📄 *{product_name} - Product Information*\n\n"
-                f"📎 [Download Product PDF]({download_url})\n\n"
+                "📎 [Download Product PDF]({download_url})\n\n"
                 "💬 *Click the link above to download the product information*\n"
                 "Type 'main' to return to main menu."
             )
@@ -1006,7 +1182,6 @@ def send_whatsjet_message(phone_number: str, message: str, media_type: str = Non
         except Exception as e:
             logger.error(f"[WhatsJet] Exception preparing text chunk: {str(e)}")
             return False
-    
     logger.info(f"[WhatsJet] Successfully sent complete text message to {phone_number}")
     return True
 
@@ -1039,15 +1214,6 @@ def send_whatsjet_media_image_only(phone_number: str, image_url: str, filename:
         logger.error(f"[WhatsJet] Exception sending image only: {e}")
         return False
 
-# Test endpoint for WhatsJet media format debugging
-@app.get("/test-whatsjet-media-formats")
-async def test_whatsjet_media_formats():
-    try:
-        resp = requests.get("https://api.whatsjet.com", timeout=5)
-        return {"status": resp.status_code, "text": resp.text[:200]}
-    except Exception as e:
-        return {"error": str(e)}
-
 # --- Health Check Endpoint ---
 @app.get("/health")
 async def health_check():
@@ -1094,6 +1260,9 @@ async def get_catalog():
 @app.get("/", response_class=HTMLResponse)
 async def root():
     return """
+    <h2>Apex Biotical Veterinary WhatsApp Assistant</h2>
+    <p>The Assistant is running! Use the API endpoints for WhatsApp integration.</p>
+    <ul>
     <h2>Apex Biotical Veterinary WhatsApp Bot</h2>
     <p>The bot is running! Use the API endpoints for WhatsApp integration.</p>
     <ul>
@@ -1547,7 +1716,7 @@ async def process_incoming_message(from_number: str, msg: dict):
                 return
             else:
                 # Only trigger menu mode if not in AI chat mode
-                welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
+                welcome_msg = generate_veterinary_welcome_message()
                 send_whatsjet_message(from_number, welcome_msg)
                 context_manager.update_context(
                     from_number, 
@@ -1563,7 +1732,7 @@ async def process_incoming_message(from_number: str, msg: dict):
             mapped_navigation = process_intelligent_voice_command(message_body, current_state, user_context)
             if mapped_navigation == 'main':
                 logger.info(f"[Process] Navigation command detected: '{message_body}' -> 'main'")
-                welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
+                welcome_msg = generate_veterinary_welcome_message()
                 send_whatsjet_message(from_number, welcome_msg)
                 context_manager.update_context(
                     from_number, 
@@ -1575,7 +1744,7 @@ async def process_incoming_message(from_number: str, msg: dict):
         
         # Also check for text-based main commands
         if message_body.lower() in ['main', 'menu', 'start', 'home', 'back']:
-            welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
+            welcome_msg = generate_veterinary_welcome_message()
             send_whatsjet_message(from_number, welcome_msg)
             context_manager.update_context(
                 from_number, 
@@ -1585,769 +1754,245 @@ async def process_incoming_message(from_number: str, msg: dict):
             )
             return
         
-        # Handle state-specific menu selections with intelligent voice command processing
-        # Handle product follow-up menu selections (must be first)
-        if current_state == 'product_inquiry':
-            # Use intelligent voice command processor for better understanding
-            mapped_selection = process_intelligent_voice_command(message_body, current_state, user_context)
-            logger.info(f"[Process] Product inquiry selection mapped: '{message_body}' -> '{mapped_selection}'")
-            
-            # Check for main navigation first
-            if mapped_selection == 'main':
-                logger.info(f"[Process] Main navigation from product_inquiry: '{message_body}' -> 'main'")
-                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())
-                )
-                return
-            
-            # Validate menu selection using the mapped selection
-            if is_valid_menu_selection(mapped_selection, current_state, user_context):
-                await handle_veterinary_product_followup(mapped_selection, from_number)
-                return
-            else:
-                # If not a valid menu selection, treat as contact inquiry response
-                logger.info(f"[Process] Invalid menu selection in product_inquiry, treating as contact inquiry: '{message_body}'")
-                await handle_contact_request_response(from_number, message_body)
-                return
-        
-        # Handle contact request responses
-        if current_state == 'contact_request':
-            await handle_contact_request_response(from_number, message_body)
-            return
-        
-        # Handle availability inquiry responses
-        if current_state == 'availability_request':
-            await handle_availability_request_response(from_number, message_body)
+        # 🎯 PRIORITY: Check for product names FIRST - works from ANY menu state
+        # This ensures users can say product names like "hydropex", "respira aid plus", etc. from any menu
+        logger.info(f"[Process] Checking for product name in message: '{message_body}' from state: {current_state}")
+        products = get_veterinary_product_matches(message_body)
+
+        # --- NEW LOGIC: Check for exact match first ---
+        normalized_input = normalize(message_body).lower().strip()
+        exact_match = None
+        for product in products:
+            product_name = product.get('Product Name', '')
+            normalized_product_name = normalize(product_name).lower().strip()
+            if normalized_product_name == normalized_input:
+                exact_match = product
+                break
+
+        if exact_match:
+            logger.info(f"[Process] Exact product match found: {exact_match.get('Product Name', 'Unknown')}")
+            context_manager.update_context(
+                from_number,
+                current_product=exact_match,
+                current_state='product_inquiry',
+                current_menu='product_inquiry',
+                current_menu_options=list(MENU_CONFIG['product_inquiry']['option_descriptions'].values())
+            )
+            # Only send one reply: image+caption if possible, else text
+            await send_product_image_with_caption(from_number, exact_match, user_context)
             return
-        
-        # Handle category product selections
-        if current_state == 'category_products_menu':
-            # Use intelligent voice command processor
-            mapped_selection = process_intelligent_voice_command(message_body, current_state, user_context)
-            logger.info(f"[Process] Category product selection mapped: '{message_body}' -> '{mapped_selection}'")
-            
-            # Check for main navigation first
-            if mapped_selection == 'main':
-                logger.info(f"[Process] Main navigation from category_products_menu: '{message_body}' -> 'main'")
-                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())
-                )
-                return
-            
-            # Validate menu selection using the mapped selection
-            if is_valid_menu_selection(mapped_selection, current_state, user_context):
-                await handle_category_product_selection(from_number, mapped_selection, user_context)
-                return
-            else:
-                # Invalid menu selection - send specific error message
-                error_msg = get_menu_validation_message(current_state, user_context)
-                send_whatsjet_message(from_number, error_msg)
-                return
-        
-        # Handle all products menu selections FIRST (before main menu)
-        if current_state == 'all_products_menu':
-            logger.info(f"[Process] Handling all_products_menu selection: '{message_body}'")
-            logger.info(f"[Process] User context state: {user_context.get('current_state')}")
-            logger.info(f"[Process] Message body type: {type(message_body)}, value: '{message_body}'")
-            
-            # Use intelligent voice command processor
-            mapped_selection = process_intelligent_voice_command(message_body, current_state, user_context)
-            logger.info(f"[Process] Mapped selection: '{message_body}' -> '{mapped_selection}'")
-            
-            # Check for main navigation first
-            if mapped_selection == 'main':
-                logger.info(f"[Process] Main navigation from all_products_menu: '{message_body}' -> 'main'")
-                welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
-                send_whatsjet_message(from_number, welcome_msg)
+
+        # --- END NEW LOGIC ---
+
+        if products:
+            logger.info(f"[Process] Product name detected: '{message_body}' -> Found {len(products)} products")
+            # If single product found, show it directly
+            if len(products) == 1:
+                selected_product = products[0]
+                product_name = selected_product.get('Product Name', 'Unknown')
+                logger.info(f"[Process] Single product found: {product_name}")
                 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())
+                    current_product=selected_product, 
+                    current_state='product_inquiry',
+                    current_menu='product_inquiry',
+                    current_menu_options=list(MENU_CONFIG['product_inquiry']['option_descriptions'].values())
                 )
+                # Always send image+caption if possible, else text
+                logger.info(f"[DEBUG] Calling send_product_image_with_caption for: {product_name}")
+                await send_product_image_with_caption(from_number, selected_product, user_context)
                 return
+
+        else:
+            # Enhanced "not found" response with veterinary suggestions
+            message = (
+                "❌ *Product Not Found*\n\n"
+                f"🔍 *We couldn't find '{message_body}' 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.*"
+            )
             
-            # Validate menu selection using the mapped selection
-            if is_valid_menu_selection(mapped_selection, current_state, user_context):
-                logger.info(f"[Process] Valid selection: {mapped_selection}, proceeding to handle_all_products_selection")
-                await handle_all_products_selection(from_number, mapped_selection, user_context)
-                logger.info(f"[Process] Completed all_products_menu handling")
-                return
+            # 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:
-                # Invalid menu selection - send specific error message
-                error_msg = get_menu_validation_message(current_state, user_context)
-                send_whatsjet_message(from_number, error_msg)
-                return
-        
-        # Handle category selection menu
-        if current_state == 'category_selection_menu':
-            # Use intelligent voice command processor
-            mapped_selection = process_intelligent_voice_command(message_body, current_state, user_context)
-            logger.info(f"[Process] Category selection mapped: '{message_body}' -> '{mapped_selection}'")
-            
-            # Check for main navigation first
-            if mapped_selection == 'main':
-                logger.info(f"[Process] Main navigation from category_selection_menu: '{message_body}' -> 'main'")
-                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())
-                )
-                return
+                send_whatsjet_message(from_number, message)
             
-            # Validate menu selection using the mapped selection
-            if is_valid_menu_selection(mapped_selection, current_state, user_context):
-                await handle_category_selection(mapped_selection, from_number)
-                return
-            else:
-                # Invalid menu selection - send specific error message
-                error_msg = get_menu_validation_message(current_state, user_context)
-                send_whatsjet_message(from_number, error_msg)
-                return
-        
-        # Handle general menu selections (ONLY for main_menu state) with intelligent processing
-        if current_state == 'main_menu':
-            # Use intelligent voice command processor for better understanding
-            mapped_selection = process_intelligent_voice_command(message_body, current_state, user_context)
-            logger.info(f"[Process] Main menu selection mapped: '{message_body}' -> '{mapped_selection}'")
+        # Handle menu state-based processing
+        # Check if this is a menu selection
+        if current_state in ['main_menu', 'category_selection_menu', 'category_products_menu', 'all_products_menu', 'product_inquiry']:
+            # Validate menu selection
+            is_valid, error_msg = validate_menu_selection(message_body, current_state, user_context)
             
-            if mapped_selection in ['1', '2', '3', '4']:
-                await handle_veterinary_menu_selection_complete(mapped_selection, from_number)
-                return
+            if is_valid:
+                # Handle valid menu selection
+                if current_state == 'main_menu':
+                    if message_body == '1':
+                        # Search Products
+                        await display_all_products(from_number)
+                    elif message_body == '2':
+                        # Browse Categories
+                        categories = get_all_categories()
+                        if categories:
+                            context_manager.update_context(
+                                from_number,
+                                current_state='category_selection_menu',
+                                current_menu='category_selection_menu',
+                                current_menu_options=categories,
+                                available_categories=categories
+                            )
+                            message = "📁 *Select a Category:*\n\n"
+                            for i, category in enumerate(categories, 1):
+                                message += f"{format_number_with_emoji(i)} {category}\n"
+                            message += "\n💬 Type a category number or 'main' to return to main menu."
+                            send_whatsjet_message(from_number, message)
+                        else:
+                            send_whatsjet_message(from_number, "❌ No categories available. Type 'main' to return to main menu.")
+                    elif message_body == '3':
+                        # Download Catalog
+                        await send_catalog_pdf(from_number)
+                    elif message_body == '4':
+                        # AI Chat Mode
+                        context_manager.update_context(
+                            from_number,
+                            current_state='ai_chat_mode',
+                            current_menu='ai_chat_mode',
+                            current_menu_options=['main']
+                        )
+                        message = (
+                            "🤖 *Veterinary AI Assistant Activated*\n\n"
+                            "I'm now in AI chat mode. You can ask me:\n"
+                            "• Veterinary questions\n"
+                            "• Product recommendations\n"
+                            "• Treatment advice\n"
+                            "• General inquiries\n\n"
+                            "💬 *Type 'main' to return to main menu.*"
+                        )
+                        send_whatsjet_message(from_number, message)
+                elif current_state == 'category_selection_menu':
+                    await handle_category_selection(message_body, from_number)
+                elif current_state == 'category_products_menu':
+                    # Handle product selection from category
+                    available_products = user_context.get('available_products', [])
+                    if message_body.isdigit() and 1 <= int(message_body) <= len(available_products):
+                        selected_product = available_products[int(message_body) - 1]
+                        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())
+                        )
+                        response = generate_veterinary_product_response(selected_product, user_context)
+                        send_whatsjet_message(from_number, response)
+                    else:
+                        send_whatsjet_message(from_number, get_menu_validation_message(current_state, user_context))
+                elif current_state == 'all_products_menu':
+                    # Handle product selection from all products
+                    if products_df is not None and not products_df.empty:
+                        all_products = products_df.to_dict('records')
+                        if message_body.isdigit() and 1 <= int(message_body) <= len(all_products):
+                            selected_product = all_products[int(message_body) - 1]
+                            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())
+                            )
+                            response = generate_veterinary_product_response(selected_product, user_context)
+                            send_whatsjet_message(from_number, response)
+                        else:
+                            send_whatsjet_message(from_number, get_menu_validation_message(current_state, user_context))
+                    else:
+                        send_whatsjet_message(from_number, "❌ No products available. Type 'main' to return to main menu.")
+                elif current_state == 'product_inquiry':
+                    await handle_veterinary_product_followup(message_body, from_number)
             else:
-                # Invalid menu selection - send specific error message
-                error_msg = get_menu_validation_message(current_state, user_context)
+                # Invalid menu selection
                 send_whatsjet_message(from_number, error_msg)
-                return
-        
-        # Handle AI Chat Mode - completely separate from menu system
-        if current_state == 'ai_chat_mode':
-            logger.info(f"[AI Chat] Processing query in AI chat mode: '{message_body}' for {from_number}")
+        elif current_state == 'contact_request':
+            await handle_contact_request_response(from_number, message_body)
+        elif current_state == 'availability_request':
+            await handle_availability_request_response(from_number, message_body)
+        elif current_state == 'ai_chat_mode':
             await handle_ai_chat_mode(from_number, message_body, reply_language)
-            return
-        
-        # If we reach here, we're not in a menu state - allow AI processing for general inquiries
-        # Expanded keyword list for product/general queries (English + Urdu)
-        product_keywords = [
-            'product', 'information', 'details', 'about', 'poultry', 'veterinary', 'medicine', 'treatment',
-            'products', 'catalog', 'category', 'categories', 'list', 'all',
-            'پروڈکٹ', 'معلومات', 'تفصیل', 'ادویات', 'علاج', 'جانور', 'دوائی', 'کیٹلاگ', 'فہرست', 'تمام', 'کیٹیگری', 'کیٹیگریز'
-        ]
-        # Lowercase and normalize message for keyword matching
-        msg_lower = message_body.lower().strip()
-        if any(keyword in msg_lower for keyword in product_keywords):
-            logger.info(f"[Process] Detected product/general inquiry (OpenAI) in message: '{message_body}'")
-            # User-facing message for voice/general queries
-            if reply_language == 'ur':
-                send_whatsjet_message(from_number, "🤖 آپ کے request کو ہمارے Veterinary AI assistant کے ساتھ process کر رہا ہوں...")
-            else:
-                send_whatsjet_message(from_number, "🤖 Processing your request with our Veterinary AI assistant...")
-            # Get OpenAI response with reply_language parameter
-            await handle_intelligent_product_inquiry(from_number, message_body, user_context, reply_language)
-            return
         else:
-            # General free-form query (OpenAI)
-            logger.info(f"[Process] Detected general free-form inquiry (OpenAI) in message: '{message_body}'")
-            if reply_language == 'ur':
-                send_whatsjet_message(from_number, "🤖 آپ کے request کو ہمارے Veterinary AI assistant کے ساتھ process کر رہا ہوں...")
-            else:
-                send_whatsjet_message(from_number, "🤖 Processing your request with our Veterinary AI assistant...")
+            # Default: treat as general query
             await handle_general_query_with_ai(from_number, message_body, user_context, reply_language)
-            return
-        
+            
     except Exception as e:
-        logger.error(f"[Process] Error processing message: {e}")
-        send_whatsjet_message(from_number, 
-            "❌ Sorry, I encountered an error. Please try again or type 'main' to return to the main menu.")
+        logger.error(f"Error in process_incoming_message: {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()))
 
-async def handle_voice_message_complete(from_number: str, msg: dict):
-    """Complete voice message processing with OpenAI transcription - treats voice exactly like text"""
+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"""
     try:
-        logger.info(f"[Voice] Processing voice message from {from_number}")
-        logger.info(f"[Voice] Message structure: {msg}")
-        
-        # Check if OpenAI is available
         if not OPENAI_API_KEY:
             send_whatsjet_message(from_number, 
-                "🎤 Voice messages require OpenAI API. Please send a text message or type 'main' to see the menu.")
+                "❌ AI assistance is not available. Please try searching for a specific product or type 'main' for the menu.")
             return
         
-        # Extract media URL from different possible locations
-        media_url = None
-        logger.info(f"[Voice] Checking media URL locations...")
+        # Create context-aware prompt
+        current_state = user_context.get('current_state', 'main_menu')
+        current_product = user_context.get('current_product')
         
-        if msg.get('media', {}).get('link'):
-            media_url = msg.get('media', {}).get('link')
-            logger.info(f"[Voice] Found media URL in media.link: {media_url}")
-        elif msg.get('media', {}).get('url'):
-            media_url = msg.get('media', {}).get('url')
-            logger.info(f"[Voice] Found media URL in media.url: {media_url}")
-        elif msg.get('url'):
-            media_url = msg.get('url')
-            logger.info(f"[Voice] Found media URL in url: {media_url}")
-        elif msg.get('audio', {}).get('url'):
-            media_url = msg.get('audio', {}).get('url')
-            logger.info(f"[Voice] Found media URL in audio.url: {media_url}")
-        else:
-            logger.error(f"[Voice] No media URL found in message structure")
-            logger.error(f"[Voice] Available fields: {list(msg.keys())}")
-            if 'media' in msg:
-                logger.error(f"[Voice] Media fields: {list(msg['media'].keys())}")
+        # --- 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.
+
+User Query: "{query}"
+Current State: {current_state}
+Current Product: {current_product.get('Product Name', 'None') if current_product else 'None'}
+
+If the user asks about products (e.g., 'poultry products', 'respiratory medicine'), list ALL relevant products from the database with a short description for each. If there are many, summarize or group them.
+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.
+"""
         
-        logger.info(f"[Voice] Final extracted media URL: {media_url}")
+        response = openai.ChatCompletion.create(
+            model="gpt-4o",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.7,
+            max_tokens=300
+        )
         
-        if not media_url:
-            send_whatsjet_message(from_number, "❌ Could not process voice message. Please try again.")
-            return
+        ai_response = response.choices[0].message.content.strip()
         
-        # Generate unique filename
-        filename = f"voice_{from_number}_{int(time.time())}.ogg"
-        
-        # Download voice file
-        file_path = await download_voice_file(media_url, filename)
-        if not file_path:
-            send_whatsjet_message(from_number, "❌ Failed to download voice message. Please try again.")
-            return
-        
-        # Transcribe with OpenAI
-        transcribed_text = await transcribe_voice_with_openai(file_path)
-        
-        # Clean up voice file immediately
-        try:
-            os.remove(file_path)
-        except:
-            pass
-        
-        # Handle empty or failed transcription
-        if not transcribed_text or transcribed_text.strip() == "":
-            logger.warning(f"[Voice] Empty transcription for {from_number}")
-            send_whatsjet_message(from_number, 
-                "🎤 *Voice Message Issue*\n\n"
-                "I couldn't hear anything in your voice message. This can happen due to:\n"
-                "• Very short voice note\n"
-                "• Background noise\n"
-                "• Microphone too far away\n"
-                "• Audio quality issues\n\n"
-                "💡 *Tips for better voice notes:*\n"
-                "• Speak clearly and slowly\n"
-                "• Keep phone close to mouth\n"
-                "• Record in quiet environment\n"
-                "• Make voice note at least 2-3 seconds\n\n"
-                "💬 *You can also:*\n"
-                "• Send a text message\n"
-                "• Type 'main' to see menu options\n"
-                "• Try voice note again")
-            return
-        
-        # Process transcribed text with full intelligence
-        logger.info(f"[Voice] Transcribed: {transcribed_text}")
-        
-        # Apply transcription error corrections
-        corrected_text = process_voice_input(transcribed_text)
-        if corrected_text != transcribed_text:
-            logger.info(f"[Voice] Applied corrections: '{transcribed_text}' -> '{corrected_text}'")
-            transcribed_text = corrected_text
-        
-        # Detect language of transcribed text
-        detected_lang = 'en'  # Default to English
-        try:
-            detected_lang = detect(transcribed_text)
-            logger.info(f"[Voice] Detected language: {detected_lang}")
-            
-            # Map language codes to supported languages
-            lang_mapping = {
-                'ur': 'ur',  # Urdu
-                'ar': 'ur',  # Arabic (treat as Urdu for Islamic greetings)
-                'en': 'en',  # English
-                'hi': 'ur',  # Hindi (treat as Urdu)
-                'bn': 'ur',  # Bengali (treat as Urdu)
-                'pa': 'ur',  # Punjabi (treat as Urdu)
-                'id': 'ur',  # Indonesian (often misdetected for Urdu/Arabic)
-                'ms': 'ur',  # Malay (often misdetected for Urdu/Arabic)
-                'tr': 'ur',  # Turkish (often misdetected for Urdu/Arabic)
-            }
-            
-            # 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(transcribed_text))
-            has_islamic_greeting = any(greeting in transcribed_text.lower() for greeting in islamic_greetings)
-            
-            if has_urdu_chars or has_islamic_greeting:
-                detected_lang = 'ur'
-                logger.info(f"[Voice] Overriding language detection to Urdu due to Arabic/Urdu characters or Islamic greeting")
-            
-            reply_language = lang_mapping.get(detected_lang, 'en')
-            logger.info(f"[Voice] Language '{detected_lang}' mapped to: {reply_language}")
-            
-        except Exception as e:
-            logger.warning(f"[Voice] Language detection failed: {e}")
-            reply_language = 'en'
-        
-        if reply_language not in ['en', 'ur']:
-            logger.info(f"[Voice] Language '{reply_language}' not supported, defaulting to English")
-            reply_language = 'en'
-        
-        # For Urdu voice notes, translate to English for processing
-        processing_text = transcribed_text
-        if reply_language == 'ur' and detected_lang == 'ur':
-            try:
-                logger.info(f"[Voice] Translating Urdu voice note to English for processing")
-                translated_text = GoogleTranslator(source='ur', target='en').translate(transcribed_text)
-                processing_text = translated_text
-                logger.info(f"[Voice] Translated to English: {translated_text}")
-            except Exception as e:
-                logger.error(f"[Voice] Translation failed: {e}")
-                # If translation fails, use original text
-                processing_text = transcribed_text
-        
-        # Determine reply language - always respond in English or Urdu
-        if detected_lang == 'ur':
-            reply_language = 'ur'  # Urdu voice notes get Urdu replies
-        else:
-            reply_language = 'en'  # All other languages get English replies
-        
-        logger.info(f"[Voice] Processing text: {processing_text}")
-        logger.info(f"[Voice] Reply language set to: {reply_language}")
-        
-        # Check if this is a greeting in voice note (check both original and translated)
-        if is_greeting(transcribed_text) or is_greeting(processing_text):
-            logger.info(f"[Voice] Greeting detected in voice note: {transcribed_text}")
-            
-            # Check if user is currently in AI chat mode - if so, don't trigger menu mode
-            user_context = context_manager.get_context(from_number)
-            current_state = user_context.get('current_state', 'main_menu')
-            
-            if current_state == 'ai_chat_mode':
-                logger.info(f"[Voice] User is in AI chat mode, treating greeting as AI query instead of menu trigger")
-                # Treat greeting as a general query in AI chat mode
-                await handle_general_query_with_ai(from_number, processing_text, user_context, reply_language)
-                return
-            else:
-                # Only trigger menu mode if not in AI chat mode
-                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()))
-                return
-        
-        # Process the translated text using the same strict state-based logic as text messages
-        # This ensures voice messages follow the same menu and state rules as text messages
-        await process_incoming_message(from_number, {
-            'body': processing_text,  # Use translated text for processing
-            'type': 'text',
-            'reply_language': reply_language,
-            'original_transcription': transcribed_text  # Keep original for context
-        })
-        
-    except Exception as e:
-        logger.error(f"[Voice] Error processing voice message: {e}")
-        logger.error(f"[Voice] Full error details: {str(e)}")
-        import traceback
-        logger.error(f"[Voice] Traceback: {traceback.format_exc()}")
-        send_whatsjet_message(from_number, 
-            "❌ Error processing voice message. Please try a text message.")
-
-async def handle_veterinary_menu_selection_complete(selection: str, from_number: str):
-    """Complete menu selection handling with all possible states and menu context"""
-    try:
-        user_context = context_manager.get_context(from_number)
-        current_state = user_context.get('current_state', 'main_menu')
-        current_menu = user_context.get('current_menu', current_state)
-        current_menu_options = user_context.get('current_menu_options', [])
-        logger.info(f"[Menu] Handling selection '{selection}' in state '{current_state}' (menu: {current_menu}) for {from_number}")
-        
-        # Validate selection
-        is_valid, error_msg = validate_menu_selection(selection, current_state, user_context)
-        if not is_valid:
-            send_whatsjet_message(from_number, error_msg)
-            return
-        
-        # Main menu - check current_state, not current_menu
-        if current_state == 'main_menu':
-            logger.info(f"[Menu] Processing main_menu selection: '{selection}' for {from_number}")
-            if selection == '1':
-                await display_all_products(from_number)
-            elif selection == '2':
-                categories = get_all_categories()
-                if not categories:
-                    send_whatsjet_message(from_number, "❌ No categories available at the moment.")
-                    return
-                category_message = "📁 *Browse Categories*\n\n"
-                for i, category in enumerate(categories, 1):
-                    category_message += f"{format_number_with_emoji(i)} {category}\n"
-                category_message += "\nSelect a category number or type 'main' to return to main menu."
-                send_whatsjet_message(from_number, category_message)
-                context_manager.update_context(
-                    from_number,
-                    current_state='category_selection_menu',
-                    current_menu='category_selection_menu',
-                    current_menu_options=categories,
-                    available_categories=categories
-                )
-            elif selection == '3':
-                await send_catalog_pdf(from_number)
-                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()))
-            elif selection == '4':
-                # Enter AI Chat Mode
-                ai_welcome_msg = (
-                    "🤖 *Veterinary AI Assistant Activated*\n\n"
-                    "I'm your intelligent veterinary assistant. I can help you with:\n"
-                    "• Product information and recommendations\n"
-                    "• Veterinary advice and guidance\n"
-                    "• Treatment suggestions\n"
-                    "• General veterinary questions\n\n"
-                    "💬 *Ask me anything related to veterinary care!*\n"
-                    "🎤 *Voice messages are supported*\n\n"
-                    "Type 'main' to return to main menu."
-                )
-                send_whatsjet_message(from_number, ai_welcome_msg)
-                context_manager.update_context(
-                    from_number,
-                    current_state='ai_chat_mode',
-                    current_menu='ai_chat_mode',
-                    current_menu_options=['main']
-                )
-            else:
-                send_whatsjet_message(from_number, "❌ Invalid selection. Please choose 1, 2, 3, or 4.")
-        
-        # Product inquiry menu
-        elif current_menu == 'product_inquiry':
-            await handle_veterinary_product_followup(selection, from_number)
-        
-        # Intelligent products menu (for multiple product results)
-        elif current_menu == 'intelligent_products_menu':
-            available_products = user_context.get('available_products', [])
-            if selection.isdigit() and 1 <= int(selection) <= len(available_products):
-                selected_product = available_products[int(selection) - 1]
-                product_name = selected_product.get('Product Name', 'Unknown')
-                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()))
-                response = generate_veterinary_product_response(selected_product, user_context)
-                send_whatsjet_message(from_number, response)
-            else:
-                send_whatsjet_message(from_number, f"❌ Invalid selection. Please choose a number between 1 and {len(available_products)}.")
-        
-        # Category selection menu
-        elif current_menu == 'category_selection_menu':
-            await handle_category_selection(selection, from_number)
-        
-        # Category products menu
-        elif current_menu == 'category_products_menu':
-            await handle_category_product_selection(from_number, selection, user_context)
-        
-        # All products menu
-        elif current_menu == 'all_products_menu':
-            await handle_all_products_selection(from_number, selection, user_context)
-        
-        else:
-            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()))
-            
-    except Exception as e:
-        logger.error(f"[Menu] Error handling menu selection: {e}")
-        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()))
-
-async def handle_category_product_selection(from_number: str, selection: str, user_context: dict):
-    """Handle product selection from category products menu"""
-    try:
-        available_products = user_context.get('available_products', [])
-        if selection.isdigit() and 1 <= int(selection) <= len(available_products):
-            selected_product = available_products[int(selection) - 1]
-            product_name = selected_product.get('Product Name', 'Unknown')
-            # Set current product and show details
-            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())
-            )
-            # Generate product response
-            response = generate_veterinary_product_response(selected_product, user_context)
-            send_whatsjet_message(from_number, response)
-        else:
-            send_whatsjet_message(from_number, "❌ Invalid selection. Please choose a valid product number.")
-    except Exception as e:
-        logger.error(f"[Category] Error handling product selection: {e}")
-        send_helpful_guidance(from_number, 'category_products_menu')
-
-async def handle_all_products_selection(from_number: str, selection: str, user_context: dict):
-    """Handle product selection from all products menu"""
-    try:
-        if products_df is None or products_df.empty:
-            send_whatsjet_message(from_number, "❌ No products available.")
-            return
-        products = products_df.to_dict('records')
-        if selection.isdigit() and 1 <= int(selection) <= len(products):
-            selected_index = int(selection) - 1
-            selected_product = products[selected_index]
-            product_name = selected_product.get('Product Name', 'Unknown')
-            logger.info(f"[All Products] Selected product: {product_name} (index {selected_index})")
-            # Set current product and show details
-            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 image with caption (NEW)
-            await send_product_image_with_caption(from_number, selected_product, user_context)
-        else:
-            send_whatsjet_message(from_number, "❌ Invalid selection. Please choose a valid product number.")
-    except Exception as e:
-        logger.error(f"[All Products] Error handling product selection: {e}")
-        send_helpful_guidance(from_number, 'all_products_menu')
-
-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"""
-    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"
-                
-                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)
-                
-            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())
-                )
-                
-                # Get updated context with last message
-                context = context_manager.get_context(from_number)
-                
-                # Use enhanced response with media support
-                response_with_media = generate_veterinary_product_response_with_media(selected_product, context)
-                
-                # Send the response
-                send_whatsjet_message(from_number, response_with_media['text'])
-                
-                # Add to conversation history
-                context_manager.add_to_history(from_number, query, response_with_media['text'])
-            
-        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)
-            
-    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()))
-
-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"""
-    try:
-        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.
-
-User Query: "{query}"
-Current State: {current_state}
-Current Product: {current_product.get('Product Name', 'None') if current_product else 'None'}
-
-If the user asks about products (e.g., 'poultry products', 'respiratory medicine'), list ALL relevant products from the database with a short description for each. If there are many, summarize or group them.
-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)
-                send_whatsjet_message(from_number, translated_response)
-            except Exception as e:
-                logger.error(f"[AI] Translation error: {e}")
-                send_whatsjet_message(from_number, ai_response)
-        else:
-            send_whatsjet_message(from_number, ai_response)
+        # Translate response if needed
+        if reply_language == 'ur':
+            try:
+                translated_response = GoogleTranslator(source='auto', target='ur').translate(ai_response)
+                send_whatsjet_message(from_number, translated_response)
+            except Exception as e:
+                logger.error(f"[AI] Translation error: {e}")
+                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)
@@ -2355,7 +2000,7 @@ Always keep responses professional, concise, and user-friendly.
     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(from_number, user_context)
+        welcome_msg = generate_veterinary_welcome_message()
         send_whatsjet_message(from_number, welcome_msg)
         context_manager.update_context(
             from_number, 
@@ -2387,7 +2032,7 @@ async def handle_contact_request(from_number: str):
     except Exception as e:
         logger.error(f"[Contact] Error handling contact request: {e}")
         # Instead of sending a generic error, return to main menu
-        welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
+        welcome_msg = generate_veterinary_welcome_message()
         send_whatsjet_message(from_number, welcome_msg)
         context_manager.update_context(
             from_number, 
@@ -2411,7 +2056,7 @@ async def handle_contact_request_response(from_number: str, response: str):
             f.write(json.dumps(contact_data, ensure_ascii=False) + '\n')
         
         # Send inquiry to receiving number (admin)
-        receiving_number = "923102288328"
+        receiving_number = "923068222219"
         
         # Parse the response to separate name/location from details
         response_lines = response.strip().split('\n')
@@ -2443,9 +2088,8 @@ async def handle_contact_request_response(from_number: str, response: str):
         )
     except Exception as e:
         logger.error(f"[Contact] Error handling contact response: {e}")
-        # Get user context before using it
-        user_context = context_manager.get_context(from_number)
-        welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
+        # 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, 
@@ -2484,7 +2128,7 @@ async def handle_availability_inquiry(from_number: str, user_context: dict):
     except Exception as e:
         logger.error(f"[Availability] Error handling availability inquiry: {e}")
         # Instead of sending a generic error, return to main menu
-        welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
+        welcome_msg = generate_veterinary_welcome_message()
         send_whatsjet_message(from_number, welcome_msg)
         context_manager.update_context(
             from_number, 
@@ -2508,7 +2152,7 @@ async def handle_availability_request_response(from_number: str, response: str):
             f.write(json.dumps(availability_data, ensure_ascii=False) + '\n')
         
         # Send inquiry to receiving number (admin)
-        receiving_number = "923102288328"
+        receiving_number = "923068222219"
         current_product = context_manager.get_context(from_number).get('current_product', {})
         product_name = current_product.get('Product Name', 'N/A') if current_product else 'N/A'
         
@@ -2548,9 +2192,8 @@ async def handle_availability_request_response(from_number: str, response: str):
         )
     except Exception as e:
         logger.error(f"[Availability] Error handling availability response: {e}")
-        # Get user context before using it
-        user_context = context_manager.get_context(from_number)
-        welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
+        # 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, 
@@ -2613,9 +2256,7 @@ def send_helpful_guidance(from_number: str, current_state: str):
             )
     except Exception as e:
         logger.error(f"Error sending helpful guidance: {e}")
-        # Get user context before using it
-        user_context = context_manager.get_context(from_number)
-        welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
+        welcome_msg = generate_veterinary_welcome_message()
         send_whatsjet_message(from_number, welcome_msg)
         context_manager.update_context(
             from_number,
@@ -2767,13 +2408,10 @@ async def handle_ai_chat_mode(from_number: str, query: str, reply_language: str
     try:
         logger.info(f"[AI Chat] Processing query: '{query}' for {from_number} in {reply_language}")
         
-        # Get user context
-        user_context = context_manager.get_context(from_number)
-        
         # Check for navigation commands first
         if query.lower().strip() in ['main', 'menu', 'start', 'home', 'back']:
             logger.info(f"[AI Chat] Navigation command detected: '{query}' -> returning to main menu")
-            welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
+            welcome_msg = generate_veterinary_welcome_message()
             send_whatsjet_message(from_number, welcome_msg)
             context_manager.update_context(
                 from_number,
@@ -2786,7 +2424,7 @@ async def handle_ai_chat_mode(from_number: str, query: str, reply_language: str
         # Check for greetings - return to main menu
         if is_greeting(query):
             logger.info(f"[AI Chat] Greeting detected: '{query}' -> returning to main menu")
-            welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
+            welcome_msg = generate_veterinary_welcome_message()
             send_whatsjet_message(from_number, welcome_msg)
             context_manager.update_context(
                 from_number,
@@ -2806,15 +2444,13 @@ async def handle_ai_chat_mode(from_number: str, query: str, reply_language: str
         
         # Get all products data for context
         all_products = []
-        total_products = 0
         if products_df is not None and not products_df.empty:
             all_products = products_df.to_dict('records')
-            total_products = len(products_df)
         
         # Create comprehensive context for AI
         products_context = ""
         if all_products:
-            products_context = f"Available Veterinary Products (Total: {total_products} products):\n"
+            products_context = "Available Veterinary Products:\n"
             for i, product in enumerate(all_products[:50], 1):  # Limit to first 50 products for context
                 product_name = product.get('Product Name', 'N/A')
                 category = product.get('Category', 'N/A')
@@ -2824,15 +2460,13 @@ async def handle_ai_chat_mode(from_number: str, query: str, reply_language: str
                 products_context += f"   Composition: {composition}\n"
                 products_context += f"   Target Species: {target_species}\n\n"
         
-        # Create AI prompt with accurate product count
+        # Create AI prompt
         if reply_language == 'ur':
             prompt = f"""
 آپ Apex Biotical کے Veterinary AI Assistant ہیں۔ آپ کو veterinary products اور treatments کے بارے میں معلومات فراہم کرنی ہیں۔
 
 یوزر کا سوال: {query}
 
-کل veterinary products کی تعداد: {total_products}
-
 دستیاب veterinary products:
 {products_context}
 
@@ -2842,7 +2476,6 @@ async def handle_ai_chat_mode(from_number: str, query: str, reply_language: str
 3. اگر یہ general veterinary advice ہے تو professional guidance دیں
 4. اردو میں جواب دیں
 5. جواب professional اور helpful ہو
-6. اگر یوزر نے products کی تعداد کے بارے میں پوچھا ہے تو صحیح تعداد ({total_products}) بتائیں
 
 جواب:
 """
@@ -2852,8 +2485,6 @@ You are Apex Biotical's Veterinary AI Assistant. You provide information about v
 
 User Query: {query}
 
-Total number of veterinary products: {total_products}
-
 Available Veterinary Products:
 {products_context}
 
@@ -2863,7 +2494,6 @@ Please:
 3. If it's general veterinary advice, provide professional guidance
 4. Answer in English
 5. Keep the response professional and helpful
-6. If the user asks about the number of products, provide the accurate count ({total_products})
 
 Response:
 """
@@ -2876,7 +2506,7 @@ Response:
             max_tokens=500
         )
         
-        ai_response = response.choices[0].message['content'].strip()
+        ai_response = response.choices[0].message.content.strip()
         
         # Add instructions for returning to main menu
         if reply_language == 'ur':
@@ -2900,53 +2530,452 @@ Response:
         # Add to conversation history
         context_manager.add_to_history(from_number, query, ai_response)
         
-        logger.info(f"[AI Chat] Response sent successfully to {from_number}")
+        logger.info(f"[AI Chat] Response sent successfully to {from_number}")
+        
+    except Exception as e:
+        logger.error(f"[AI Chat] Error processing query: {e}")
+        if reply_language == 'ur':
+            error_msg = "❌ AI Assistant میں error آ گیا ہے۔ براہ کرم دوبارہ کوشش کریں یا 'main' لکھ کر main menu پر واپس جائیں۔"
+        else:
+            error_msg = "❌ AI Assistant encountered an error. Please try again or type 'main' to return to main menu."
+        send_whatsjet_message(from_number, error_msg)
+
+# Load products on startup
+def load_products_data():
+    """Load products data from CSV file"""
+    global products_df
+    try:
+        if os.path.exists(CSV_FILE):
+            products_df = pd.read_csv(CSV_FILE)
+            logger.info(f"✅ Loaded {len(products_df)} products from {CSV_FILE}")
+        else:
+            logger.warning(f"⚠️ CSV file {CSV_FILE} not found")
+            products_df = pd.DataFrame()
+    except Exception as e:
+        logger.error(f"❌ Error loading products data: {e}")
+        products_df = pd.DataFrame()
+
+load_products_data()
+
+# Add these functions after the existing imports and before the main functions
+
+def get_product_image_path(product_name: str) -> str:
+    """
+    Get the public image URL for a product based on its name, robust to formatting, preserving dashes.
+    cPanel public URL format: https://amgocus.com/uploads/images/<normalized_name>.<ext>
+    Normalized: lowercase, remove spaces/underscores/dots, preserve dashes.
+    """
+    try:
+        def normalize(name):
+            return re.sub(r'[\s_\.]', '', name).lower()
+        normalized_name = normalize(product_name)
+        logger.info(f"[Image] Normalized product name: '{product_name}' -> '{normalized_name}'")
+        image_extensions = ['.png', '.jpg', '.jpeg', '.webp']
+        base_url = "https://amgocus.com/uploads/images/"
+        # Log for all normalized checks
+        for ext in image_extensions:
+            image_url = f"{base_url}{normalized_name}{ext}"
+            logger.info(f"[Image] Checking normalized image URL: {image_url}")
+            # For public URLs, assume they are accessible if they start with http
+            if image_url.startswith('http'):
+                # Optionally, you could check with requests.get here, but we trust browser accessibility
+                if product_name.lower().replace(' ', '').replace('_', '').replace('.', '') == 'b-gaspro-c':
+                    logger.info(f"[Image] Special debug: Checking for B-G Aspro-C at {image_url}")
+                # If you want to verify with requests, uncomment below:
+                # try:
+                #     resp = requests.get(image_url, timeout=5, stream=True)
+                #     if resp.status_code == 200:
+                #         logger.info(f"[Image] Found public image URL: {image_url}")
+                #         return image_url
+                # except Exception as e:
+                #     logger.warning(f"[Image] Error checking image URL {image_url}: {e}")
+                logger.info(f"[Image] Found public image URL: {image_url}")
+                return image_url
+        # Fallback: try original name with spaces as %20
+        safe_name = product_name.strip().replace(' ', '%20')
+        for ext in image_extensions:
+            image_url = f"{base_url}{safe_name}{ext}"
+            logger.info(f"[Image] Checking fallback image URL: {image_url}")
+            if image_url.startswith('http'):
+                logger.info(f"[Image] Found public image URL (legacy): {image_url}")
+                return image_url
+        logger.warning(f"[Image] No public image found for product: {product_name}")
+        return None
+    except Exception as e:
+        logger.error(f"[Image] Error generating public image URL for {product_name}: {e}")
+        return None
+
+def get_product_image_media_type(image_path: str) -> str:
+    """
+    Determine the media type based on file extension
+    """
+    if not image_path:
+        return None
+    
+    ext = os.path.splitext(image_path)[1].lower()
+    
+    media_type_map = {
+        '.jpg': 'image/jpeg',
+        '.jpeg': 'image/jpeg',
+        '.png': 'image/png',
+        '.webp': 'image/webp',
+        '.gif': 'image/gif'
+    }
+    
+    return media_type_map.get(ext, 'image/jpeg')
+
+async def send_product_with_image(from_number: str, product: Dict[str, Any], user_context: Dict[str, Any]):
+    """
+    Send product information with image if available
+    """
+    try:
+        product_name = product.get('Product Name', 'Unknown Product')
+        
+        # Generate product response
+        response = generate_veterinary_product_response(product, user_context)
+        
+        # Try to get product image
+        image_path = get_product_image_path(product_name)
+        
+        if image_path and os.path.exists(image_path):
+            # Send product info with image
+            media_type = get_product_image_media_type(image_path)
+            filename = f"{product_name.replace(' ', '_')}.jpg"
+            
+            success = send_whatsjet_message(
+                from_number,
+                response,
+                media_type=media_type,
+                media_path=image_path,
+                filename=filename
+            )
+            
+            if success:
+                logger.info(f"[Product] Successfully sent product with image: {product_name}")
+            else:
+                # Fallback to text-only if image send fails
+                logger.warning(f"[Product] Failed to send image, sending text only: {product_name}")
+                send_whatsjet_message(from_number, response)
+        else:
+            # Send text-only response
+            send_whatsjet_message(from_number, response)
+            logger.info(f"[Product] Sent product info without image: {product_name}")
+            
+    except Exception as e:
+        logger.error(f"[Product] Error sending product with image: {e}")
+        # Fallback to text-only
+        response = generate_veterinary_product_response(product, user_context)
+        send_whatsjet_message(from_number, response)
+
+async def send_enhanced_pdf(from_number: str, product: Dict[str, Any], pdf_content: bytes = None):
+    """
+    Send PDF with enhanced formatting and proper WhatsApp document sharing
+    """
+    try:
+        product_name = product.get('Product Name', 'Unknown_Product')
+        safe_name = re.sub(r'[^\w\s-]', '', product_name).replace(' ', '_')
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        filename = f"{safe_name}_Product_Info_{timestamp}.pdf"
+        
+        # Generate PDF if not provided
+        if pdf_content is None:
+            pdf_content = generate_veterinary_pdf(product)
+        
+        # Save PDF to uploads directory
+        uploads_dir = "uploads"
+        os.makedirs(uploads_dir, exist_ok=True)
+        pdf_path = os.path.join(uploads_dir, filename)
+        
+        with open(pdf_path, 'wb') as f:
+            f.write(pdf_content)
+        
+        # Send PDF as document via WhatsApp
+        success = send_whatsjet_message(
+            from_number,
+            f"📄 *{product_name} - Detailed Product Information*\n\n"
+            f"📎 Here's the complete product information in PDF format.\n"
+            f"📋 Includes: Composition, Dosage, Precautions, Storage\n\n"
+            f"💬 Type 'main' to return to main menu.",
+            media_type="application/pdf",
+            media_path=pdf_path,
+            filename=filename
+        )
+        
+        if success:
+            logger.info(f"[PDF] Successfully sent PDF for product: {product_name}")
+        else:
+            # Fallback: Send download link
+            server_url = os.getenv("SERVER_URL", "https://your-huggingface-space-url.hf.space")
+            download_url = f"{server_url}/uploads/{filename}"
+            
+            message = (
+                f"📄 *{product_name} - Product Information*\n\n"
+                f"📎 [Download Product PDF]({download_url})\n\n"
+                f"💬 *Click the link above to download the detailed product information*\n"
+                f"Type 'main' to return to main menu."
+            )
+            send_whatsjet_message(from_number, message)
+            logger.info(f"[PDF] Sent PDF download link for product: {product_name}")
+            
+    except Exception as e:
+        logger.error(f"[PDF] Error sending enhanced PDF: {e}")
+        # Fallback to basic text response
+        response = generate_veterinary_product_response(product, {})
+        send_whatsjet_message(from_number, response)
+
+# Enhanced product response function with image support
+def generate_veterinary_product_response_with_media(product_info: Dict[str, Any], user_context: Dict[str, Any]) -> Dict[str, Any]:
+    """
+    Generate comprehensive veterinary product response with media information
+    Returns a dictionary with text response and media info
+    """
+    def clean_text(text):
+        if pd.isna(text) or text is None:
+            return "Not specified"
+        return str(text).strip()
+    
+    product_name = clean_text(product_info.get('Product Name', ''))
+    product_type = clean_text(product_info.get('Type', ''))
+    category = clean_text(product_info.get('Category', ''))
+    indications = clean_text(product_info.get('Indications', ''))
+    pdf_link = ""
+    
+    try:
+        csv_data = pd.read_csv('Veterinary.csv')
+        product_row = csv_data[csv_data['Product Name'] == product_name]
+        if not product_row.empty:
+            brochure_link = product_row.iloc[0].get('Brochure (PDF)', '')
+            if pd.notna(brochure_link) and brochure_link.strip():
+                pdf_link = brochure_link.strip()
+    except Exception as e:
+        logger.warning(f"Error checking PDF link for {product_name}: {e}")
+    
+    response_text = f"""🧪 *Name:* {product_name}\n📦 *Type:* {product_type}\n🏥 *Category:* {category}\n💊 *Used For:* {indications}"""
+    
+    if pdf_link:
+        response_text += f"\n\n📄 Product Brochure Available\n🔗 {product_name} PDF:\n{pdf_link}"
+    
+    response_text += f"""
+\n💬 *Available Actions:*
+1️⃣ Talk to Veterinary Consultant
+2️⃣ Inquire About Availability
+3️⃣ Back to Main Menu
+\n💬 Select an option or ask about related products"""
+    
+    image_path = get_product_image_path(product_name)
+    has_image = image_path is not None and os.path.exists(image_path)
+    
+    return {
+        'text': response_text,
+        'has_image': has_image,
+        'image_path': image_path,
+        'product_name': product_name
+    }
+
+def ensure_images_dir():
+    """Ensure the images directory exists"""
+    images_dir = "static/images"
+    os.makedirs(images_dir, exist_ok=True)
+    logger.info(f"[Image] Ensured images directory exists: {images_dir}")
+
+# New feature: Send product image with caption (product details)
+async def send_product_image_with_caption(from_number: str, product: Dict[str, Any], user_context: Dict[str, Any]):
+    logger.info(f"[Product] send_product_image_with_caption called for: {product.get('Product Name', '')}")
+    """
+    Send product image (if available) with product details as caption in a single WhatsApp message.
+    If image is not available, send only the product details as text.
+    """
+    ensure_images_dir()
+    product_name = product.get('Product Name', 'Unknown Product')
+    details = generate_veterinary_product_response(product, user_context)
+    logger.info(f"[DEBUG] About to look up image for product: {product_name}")
+    image_path = get_product_image_path(product_name)
+    
+    if image_path and image_path.startswith('http'):
+        media_type = get_product_image_media_type(image_path)
+        filename = f"{product_name.replace(' ', '_')}.jpg"
+        logger.info(f"[Product] Sending public image URL with caption: {image_path}")
+        
+        # Try sending with image first
+        success = send_whatsjet_message(
+            from_number,
+            details,
+            media_type=media_type,
+            media_path=image_path,
+            filename=filename
+        )
+        
+        if success:
+            logger.info(f"[Product] Successfully sent image+caption for product: {product_name}")
+            return
+        else:
+            logger.warning(f"[Product] Failed to send image+caption, trying alternative approaches for: {product_name}")
+            
+            # Try sending image only (without caption) using the separate endpoint
+            try:
+                image_only_success = send_whatsjet_media_image_only(from_number, image_path, filename)
+                if image_only_success:
+                    logger.info(f"[Product] Successfully sent image only for: {product_name}")
+                    # Send caption as separate message
+                    send_whatsjet_message(from_number, details)
+                    return
+                else:
+                    logger.warning(f"[Product] Image-only approach also failed for: {product_name}")
+            except Exception as e:
+                logger.error(f"[Product] Exception in image-only approach: {e}")
+            
+            # Final fallback: send text only
+            logger.warning(f"[Product] All image approaches failed, sending text only: {product_name}")
+            send_whatsjet_message(from_number, details)
+            return
+    
+    # No image available, send text only
+    logger.info(f"[Product] No image available, sending text only for: {product_name}")
+    send_whatsjet_message(from_number, details)
+
+# Test endpoint for product image with caption
+@app.get("/test-product-image-with-caption")
+async def test_product_image_with_caption(phone: str):
+    """Test endpoint for sending product image with caption"""
+    try:
+        if products_df is None or products_df.empty:
+            return {"error": "No products loaded"}
+        
+        # Get first product for testing
+        product = products_df.iloc[0].to_dict()
+        user_context = {}
+        
+        await send_product_image_with_caption(phone, product, user_context)
+        
+        return {
+            "success": True,
+            "message": f"Test product image sent to {phone}",
+            "product": product.get('Product Name', 'Unknown')
+        }
         
     except Exception as e:
-        logger.error(f"[AI Chat] Error processing query: {e}")
-        if reply_language == 'ur':
-            error_msg = "❌ AI Assistant میں error آ گیا ہے۔ براہ کرم دوبارہ کوشش کریں یا 'main' لکھ کر main menu پر واپس جائیں۔"
+        logger.error(f"Error in test product image with caption: {e}")
+        return {"error": str(e)}
+
+# Test endpoint for image sending
+@app.get("/test-image-sending")
+async def test_image_sending(phone: str, image_url: str = "https://www.w3schools.com/w3images/lights.jpg"):
+    """Test endpoint for sending images via WhatsApp"""
+    try:
+        filename = "test_image.jpg"
+        
+        success = send_whatsjet_message(
+            phone,
+            "🖼️ *Test Image*\n\nThis is a test image sent via WhatsApp API.",
+            media_type="image/jpeg",
+            media_path=image_url,
+            filename=filename
+        )
+        
+        if success:
+            return {
+                "success": True,
+                "message": f"Test image sent successfully to {phone}",
+                "image_url": image_url
+            }
         else:
-            error_msg = "❌ AI Assistant encountered an error. Please try again or type 'main' to return to main menu."
-        send_whatsjet_message(from_number, error_msg)
+            return {
+                "success": False,
+                "message": f"Failed to send test image to {phone}",
+                "image_url": image_url
+            }
+            
+    except Exception as e:
+        logger.error(f"Error in test image sending: {e}")
+        return {"error": str(e)}
 
-def generate_veterinary_welcome_message(phone_number=None, user_context=None):
-    """Generate enhanced welcome message with veterinary domain expertise"""
-    welcome_msg = (
-        "🏥 *Welcome to Apex Biotical Veterinary Bot*\n\n"
-        "We provide comprehensive veterinary products and support.\n\n"
-        "📋 *Available Options:*\n"
-        "1️⃣ Search Veterinary Products\n"
-        "2️⃣ Browse Categories\n"
-        "3️⃣ Download Catalog\n"
-        "4️⃣ Chat with Veterinary AI Assistant\n\n"
-        "💬 *Select an option or ask about specific products*\n"
-        "🎤 *You can also send voice messages*"
-    )
-    return welcome_msg
+# Debug endpoint for WhatsJet
+@app.get("/debug-whatsjet")
+async def debug_whatsjet():
+    """Debug endpoint to check WhatsJet configuration"""
+    try:
+        config = {
+            "api_url": WHATSJET_API_URL,
+            "vendor_uid": WHATSJET_VENDOR_UID,
+            "api_token": "***" if WHATSJET_API_TOKEN else None,
+            "server_url": SERVER_URL,
+            "openai_key": "***" if OPENAI_API_KEY else None
+        }
+        
+        return {
+            "status": "success",
+            "config": config,
+            "timestamp": datetime.now().isoformat()
+        }
+        
+    except Exception as e:
+        return {
+            "status": "error",
+            "error": str(e),
+            "timestamp": datetime.now().isoformat()
+        }
 
-@app.get("/test-whatsjet")
-async def test_whatsjet():
+# Test endpoint for WhatsJet payloads
+@app.get("/test-whatsjet-payloads")
+async def test_whatsjet_payloads(phone: str):
+    """Test endpoint to check WhatsJet payloads"""
     try:
-        resp = requests.get("https://api.whatsjet.com", timeout=5)
-        return {"status": resp.status_code, "text": resp.text[:200]}
+        # Test basic message sending
+        test_message = "🧪 *WhatsJet Test*\n\nThis is a test message to verify WhatsJet integration."
+        success = send_whatsjet_message(phone, test_message)
+        
+        return {
+            "status": "success" if success else "failed",
+            "message": f"WhatsJet test message sent to {phone}",
+            "success": success,
+            "timestamp": datetime.now().isoformat()
+        }
+        
     except Exception as e:
-        return {"error": str(e)}
+        return {
+            "status": "error",
+            "error": str(e),
+            "timestamp": datetime.now().isoformat()
+        }
 
-# Load products data on startup
-def load_products_data():
-    """Load products data from CSV file"""
-    global products_df
+# Test endpoint for cPanel image access
+@app.get("/test-cpanel-image-access")
+async def test_cpanel_image_access():
+    """
+    Test endpoint to check if cPanel image URLs are now accessible with browser-like headers.
+    """
     try:
-        if os.path.exists(CSV_FILE):
-            products_df = pd.read_csv(CSV_FILE)
-            logger.info(f"✅ Loaded {len(products_df)} products from {CSV_FILE}")
+        image_url = "https://amgocus.com/uploads/images/Respira%20Aid%20Plus.jpg"
+        # Test with browser-like headers
+        headers = {
+            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
+            'Accept': 'image/webp,image/apng,image/*,*/*;q=0.8',
+            'Accept-Language': 'en-US,en;q=0.9',
+            'Accept-Encoding': 'gzip, deflate, br',
+            'Connection': 'keep-alive',
+            'Upgrade-Insecure-Requests': '1'
+        }
+        logger.info(f"[Test] Testing cPanel image URL with browser headers: {image_url}")
+        response = requests.get(image_url, headers=headers, timeout=10, stream=True, allow_redirects=True)
+        result = {
+            "image_url": image_url,
+            "status_code": response.status_code,
+            "headers": dict(response.headers),
+            "accessible": response.status_code == 200,
+            "timestamp": datetime.now().isoformat()
+        }
+        if response.status_code == 200:
+            logger.info(f"[Test] ✅ cPanel image URL is now accessible!")
         else:
-            logger.warning(f"⚠️ CSV file {CSV_FILE} not found")
-            products_df = pd.DataFrame()
+            logger.warning(f"[Test] ❌ cPanel image URL still not accessible (status {response.status_code})")
+        return result
     except Exception as e:
-        logger.error(f"❌ Error loading products data: {e}")
-        products_df = pd.DataFrame()
+        logger.error(f"[Test] Error testing cPanel image access: {e}")
+        return {
+            "error": str(e),
+            "image_url": image_url,
+            "timestamp": datetime.now().isoformat()
+        }
 
 def convert_drive_link(link: str) -> str:
     """Convert Google Drive link to direct download link"""
@@ -3018,743 +3047,536 @@ def get_products_by_category(category: str):
     category_products = products_df[products_df['Category'] == category]
     return category_products.to_dict('records')
 
-# Enhanced product follow-up handling
-async def handle_veterinary_product_followup(selection: str, from_number: str) -> None:
-    """
-    Handle product follow-up selections with enhanced veterinary domain support
-    """
-    try:
-        user_context = context_manager.get_context(from_number)
-        current_product = user_context.get('current_product')
-        
-        if not current_product:
-            send_whatsjet_message(from_number, "❌ No product selected. Please search for a product first.")
-            return
-        
-        if selection == '1':
-            # Talk to Veterinary Consultant
-            product_name = current_product.get('Product Name', 'the selected product')
-            consultant_msg = (
-                f"📞 Contact Veterinary Consultant\n\n"
-                f"Product: {product_name}\n\n"
-                "Please provide your details:\n"
-                "* Name and location\n"
-                "* Specific inquiry\n\n"
-                "💬 Example: Dr. Ali - Multan - Need consultation for respiratory problems\n\n"
-                "Type main at any time to go to main menu."
-            )
-            send_whatsjet_message(from_number, consultant_msg)
-            context_manager.update_context(
-                from_number,
-                current_state='contact_request',
-                current_menu='contact_request',
-                current_menu_options=['Provide contact details']
-            )
-            
-        elif selection == '2':
-            # Inquire about Product Availability
-            await handle_availability_inquiry(from_number, user_context)
-            
-        elif selection == '3':
-            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())
-            )
-            return
-        else:
-            send_whatsjet_message(from_number, "❌ Invalid selection. Please choose 1, 2, or 3.")
-            return
-    except Exception as e:
-        logger.error(f"Error in product follow-up: {e}")
-        user_context = context_manager.get_context(from_number)
-        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())
-        )
-
-# Enhanced product inquiry handling
-async def handle_veterinary_product_inquiry(product_name: str, from_number: str) -> None:
-    """
-    Handle product inquiry with enhanced veterinary domain support and media
-    """
-    try:
-        # Search for the product
-        products = get_veterinary_product_matches(product_name)
-        
-        if products:
-            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())
-            )
-            
-            # Get updated context with last message
-            context = context_manager.get_context(from_number)
-            
-            # Use enhanced response with media support
-            response_with_media = generate_veterinary_product_response_with_media(selected_product, context)
-            
-            # Send the response
-            send_whatsjet_message(from_number, response_with_media['text'])
-            
-            # Add to conversation history
-            context_manager.add_to_history(from_number, product_name, response_with_media['text'])
-            
-        else:
-            # Enhanced "not found" response with veterinary suggestions
-            message = (
-                "❌ *Product Not Found*\n\n"
-                f"🔍 *We couldn't find '{product_name}' 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.*"
-            )
-            
-            send_whatsjet_message(from_number, message)
-            
-    except Exception as e:
-        logger.error(f"Error in product inquiry: {e}")
-        # Get user context before using it
-        user_context = context_manager.get_context(from_number)
-        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()))
-
-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"""
-    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"
-                
-                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)
-                
-            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())
-                )
-                
-                # Get updated context with last message
-                context = context_manager.get_context(from_number)
-                
-                # Use enhanced response with media support
-                response_with_media = generate_veterinary_product_response_with_media(selected_product, context)
-                
-                # Send the response
-                send_whatsjet_message(from_number, response_with_media['text'])
-                
-                # Add to conversation history
-                context_manager.add_to_history(from_number, query, response_with_media['text'])
-            
-        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)
-            
-    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()))
-
 async def handle_category_selection(selection: str, from_number: str):
-    """Handle category selection from category_selection_menu state"""
+    """Handle category selection"""
     try:
         user_context = context_manager.get_context(from_number)
         available_categories = user_context.get('available_categories', [])
         
-        logger.info(f"[Category] Handling selection '{selection}' for {from_number}")
-        logger.info(f"[Category] Available categories: {len(available_categories)}")
-        
-        if not available_categories:
-            logger.warning("[Category] No available categories")
-            send_whatsjet_message(from_number, "❌ No categories available. Please type 'main' to return to main menu.")
-            return
-        
         if selection.isdigit() and 1 <= int(selection) <= len(available_categories):
             selected_category = available_categories[int(selection) - 1]
-            logger.info(f"[Category] Selected category: '{selected_category}'")
-            
             products = get_products_by_category(selected_category)
-            logger.info(f"[Category] Found {len(products)} products in category '{selected_category}'")
             
             if products:
-                product_message = f"📦 *Products in {selected_category}*\n\n"
-                for i, product in enumerate(products[:10], 1):  # Show first 10 products
-                    product_message += f"{format_number_with_emoji(i)} {product.get('Product Name', 'Unknown')}\n"
-                
-                if len(products) > 10:
-                    product_message += f"\n... and {len(products) - 10} more products"
-                
-                product_message += "\n\nSelect a product number or type 'main' to return to main menu."
-                
-                logger.info(f"[Category] Sending product message for category '{selected_category}'")
-                send_whatsjet_message(from_number, product_message)
+                # Update context with category products
                 context_manager.update_context(
-                    from_number, 
+                    from_number,
+                    current_category=selected_category,
                     current_state='category_products_menu',
                     current_menu='category_products_menu',
-                    current_menu_options=[f"Product {i+1}" for i in range(len(products))],
-                    available_products=products, 
-                    current_category=selected_category
+                    current_menu_options=[p.get('Product Name', 'Unknown') for p in products],
+                    available_products=products
                 )
-                logger.info(f"[Category] Updated context to category_products_menu with {len(products)} products")
+                
+                # Send category products
+                message = f"📦 *Products in {selected_category}*\n\n"
+                for i, product in enumerate(products, 1):
+                    message += f"{format_number_with_emoji(i)} {product.get('Product Name', 'Unknown')}\n"
+                    if product.get('Target Species'):
+                        message += f"   Target: {product.get('Target Species')}\n"
+                    message += "\n"
+                
+                message += "💬 Select a product number or type 'main' to return to main menu."
+                send_whatsjet_message(from_number, message)
             else:
-                logger.warning(f"[Category] No products found in category '{selected_category}'")
-                send_whatsjet_message(from_number, f"❌ No products found in {selected_category}")
+                send_whatsjet_message(from_number, f"❌ No products found in {selected_category} category.")
         else:
-            logger.warning(f"[Category] Invalid category selection: '{selection}' (valid range: 1-{len(available_categories)})")
             send_whatsjet_message(from_number, "❌ Invalid selection. Please choose a valid category number.")
-            
     except Exception as e:
         logger.error(f"[Category] Error handling category selection: {e}")
-        # Get user context before using it
-        user_context = context_manager.get_context(from_number)
-        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())
-        )
+        send_helpful_guidance(from_number, 'category_selection_menu')
 
 def get_menu_validation_message(current_state: str, user_context: dict) -> str:
-    """Get specific validation message for the current menu state"""
+    """Get appropriate validation message for current menu state"""
     if current_state == 'main_menu':
-        return "❌ Invalid selection for Main Menu. Please choose:\n1️⃣ Search Veterinary Products\n2️⃣ Browse Categories\n3️⃣ Download Catalog\n4️⃣ Chat with Veterinary AI Assistant\n\n💬 Type 'main' to return to main menu."
-    
+        return (
+            "❌ *Invalid Selection*\n\n"
+            "Please choose from the main menu:\n"
+            "1️⃣ Search Veterinary Products\n"
+            "2️⃣ Browse Categories\n"
+            "3️⃣ Download Catalog\n"
+            "4️⃣ Chat with Veterinary AI Assistant\n\n"
+            "💬 *You can also:*\n"
+            "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
+            "• Type 'main' to refresh the menu"
+        )
     elif current_state == 'all_products_menu':
-        available_products = user_context.get('available_products', [])
-        total_products = len(available_products) if available_products else 23
-        return f"❌ Invalid selection for Product List. Please choose a number between 1 and {total_products}.\n\n💬 Type 'main' to return to main menu."
-    
-    elif current_state == 'category_selection_menu':
-        available_categories = user_context.get('available_categories', [])
-        total_categories = len(available_categories) if available_categories else 0
-        if total_categories > 0:
-            return f"❌ Invalid selection for Category List. Please choose a number between 1 and {total_categories}.\n\n💬 Type 'main' to return to main menu."
+        if products_df is not None and not products_df.empty:
+            total_products = len(products_df)
+            return (
+                f"❌ *Invalid Product Selection*\n\n"
+                f"Please choose a product number between 1 and {total_products}.\n\n"
+                "💬 *You can also:*\n"
+                "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
+                "• Type 'main' to return to main menu"
+            )
         else:
-            return "❌ No categories available. Please type 'main' to return to main menu."
-    
+            return "❌ No products available. Type 'main' to return to main menu."
     elif current_state == 'category_products_menu':
         available_products = user_context.get('available_products', [])
-        total_products = len(available_products) if available_products else 0
-        if total_products > 0:
-            return f"❌ Invalid selection for Category Products. Please choose a number between 1 and {total_products}.\n\n💬 Type 'main' to return to main menu."
+        if available_products:
+            return (
+                f"❌ *Invalid Product Selection*\n\n"
+                f"Please choose a product number between 1 and {len(available_products)}.\n\n"
+                "💬 *You can also:*\n"
+                "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
+                "• Type 'main' to return to main menu"
+            )
         else:
-            return "❌ No products available in this category. Please type 'main' to return to main menu."
-    
-    elif current_state == 'product_inquiry':
-        return "❌ Invalid selection for Product Options. Please choose:\n1️⃣ Talk to Veterinary Consultant\n2️⃣ Inquire about Product Availability\n3️⃣ Back to Main Menu"
-    
-    elif current_state == 'ai_chat_mode':
-        return "💬 *You're in AI Chat mode. Ask me anything about veterinary care!*\n\nType 'main' to return to main menu."
-    
-    else:
-        return "❌ Invalid selection. Please type 'main' to return to main menu."
-
-def is_valid_menu_selection(selection: str, current_state: str, user_context: dict) -> bool:
-    """Check if a selection is valid for the current menu state"""
-    # Use the intelligent voice command processor for consistent handling
-    mapped_selection = process_intelligent_voice_command(selection, current_state, user_context)
-    
-    if not mapped_selection.isdigit():
-        return False
-    
-    selection_num = int(mapped_selection)
-    
-    if current_state == 'main_menu':
-        return 1 <= selection_num <= 4
-    
-    elif current_state == 'all_products_menu':
-        available_products = user_context.get('available_products', [])
-        total_products = len(available_products) if available_products else 23
-        return 1 <= selection_num <= total_products
-    
+            return "❌ No products available in this category. Type 'main' to return to main menu."
     elif current_state == 'category_selection_menu':
         available_categories = user_context.get('available_categories', [])
-        total_categories = len(available_categories) if available_categories else 0
-        return 1 <= selection_num <= total_categories
-    
-    elif current_state == 'category_products_menu':
-        available_products = user_context.get('available_products', [])
-        total_products = len(available_products) if available_products else 0
-        return 1 <= selection_num <= total_products
-    
+        if available_categories:
+            return (
+                f"❌ *Invalid Category Selection*\n\n"
+                f"Please choose a category number between 1 and {len(available_categories)}.\n\n"
+                "💬 *You can also:*\n"
+                "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
+                "• Type 'main' to return to main menu"
+            )
+        else:
+            return "❌ No categories available. Type 'main' to return to main menu."
     elif current_state == 'product_inquiry':
-        return 1 <= selection_num <= 3
-    
-    elif current_state == 'ai_chat_mode':
-        return mapped_selection == 'main'
-    
-    return False
+        return (
+            "❌ *Invalid Selection*\n\n"
+            "Please choose an option:\n"
+            "1️⃣ Talk to Veterinary Consultant\n"
+            "2️⃣ Inquire About Availability\n"
+            "3️⃣ Back to Main Menu\n\n"
+            "💬 *You can also:*\n"
+            "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
+            "• Type 'main' to return to main menu"
+        )
+    else:
+        return (
+            "❌ *Invalid Selection*\n\n"
+            "Please choose a valid option or type 'main' to return to main menu.\n\n"
+            "💬 *You can also:*\n"
+            "• Type a product name (e.g., 'hydropex', 'respira aid plus')"
+        )
 
-# Load products on startup
-load_products_data()
+def is_valid_menu_selection(selection: str, current_state: str, user_context: dict) -> bool:
+    """Check if selection is valid for current menu state"""
+    is_valid, _ = validate_menu_selection(selection, current_state, user_context)
+    return is_valid
 
-# Add these functions after the existing imports and before the main functions
+def generate_veterinary_welcome_message(phone_number=None, user_context=None):
+    """Generate veterinary welcome message"""
+    return (
+        "🏥 *Welcome to Apex Biotical Veterinary Assistant*\n\n"
+        "I'm your intelligent veterinary assistant. How can I help you today?\n\n"
+        "📋 *Main Menu:*\n"
+        "1️⃣ Search Veterinary Products\n"
+        "2️⃣ Browse Categories\n"
+        "3️⃣ Download Catalog\n"
+        "4️⃣ Chat with Veterinary AI Assistant\n\n"
+        "💬 *Quick Actions:*\n"
+        "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
+        "• Ask about symptoms (e.g., 'respiratory problems', 'liver support')\n"
+        "• Search by category (e.g., 'antibiotics', 'vitamins')\n\n"
+        "🎤 *Voice messages are supported!*\n"
+        "You can speak product names, menu numbers, or ask questions."
+    )
 
-def get_product_image_path(product_name: str) -> str:
+async def handle_veterinary_product_followup(selection: str, from_number: str) -> None:
     """
-    Get the image path for a product
-    Returns the path to the product image if it exists, otherwise None
+    Handle product follow-up selections with enhanced veterinary domain support
     """
     try:
-        # Create images directory if it doesn't exist
-        images_dir = "static/images"
-        os.makedirs(images_dir, exist_ok=True)
-        
-        # Clean product name for filename
-        safe_name = re.sub(r'[^\w\s-]', '', product_name).replace(' ', '_').lower()
-        
-        # Check for common image extensions
-        image_extensions = ['.jpg', '.jpeg', '.png', '.webp', '.gif']
+        user_context = context_manager.get_context(from_number)
+        current_product = user_context.get('current_product')
         
-        for ext in image_extensions:
-            image_path = os.path.join(images_dir, f"{safe_name}{ext}")
-            if os.path.exists(image_path):
-                logger.info(f"[Image] Found product image: {image_path}")
-                return image_path
-        
-        # If no specific product image found, check for a default image
-        default_image_path = os.path.join(images_dir, "default_product.jpg")
-        if os.path.exists(default_image_path):
-            logger.info(f"[Image] Using default product image: {default_image_path}")
-            return default_image_path
-        
-        logger.warning(f"[Image] No image found for product: {product_name}")
-        return None
+        if not current_product:
+            send_whatsjet_message(from_number, "❌ No product selected. Please search for a product first.")
+            return
         
+        if selection == '1':
+            # Talk to Veterinary Consultant
+            product_name = current_product.get('Product Name', 'the selected product')
+            consultant_msg = (
+                f"📞 Contact Veterinary Consultant\n\n"
+                f"Product: {product_name}\n\n"
+                "Please provide your details:\n"
+                "* Name and location\n"
+                "* Specific inquiry\n\n"
+                "💬 Example: Dr. Ali - Multan - Need consultation for respiratory problems\n\n"
+                "Type main at any time to go to main menu."
+            )
+            send_whatsjet_message(from_number, consultant_msg)
+            context_manager.update_context(
+                from_number,
+                current_state='contact_request',
+                current_menu='contact_request',
+                current_menu_options=['Provide contact details']
+            )
+            
+        elif selection == '2':
+            # Inquire about Product Availability
+            await handle_availability_inquiry(from_number, user_context)
+            
+        elif selection == '3':
+            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())
+            )
+            return
+        else:
+            send_whatsjet_message(from_number, "❌ Invalid selection. Please choose 1, 2, or 3.")
+            return
     except Exception as e:
-        logger.error(f"[Image] Error getting product image path: {e}")
-        return None
+        logger.error(f"Error in product follow-up: {e}")
+        user_context = context_manager.get_context(from_number)
+        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())
+        )
 
-def get_product_image_media_type(image_path: str) -> str:
-    """
-    Determine the media type based on file extension
-    """
-    if not image_path:
-        return None
-    
-    ext = os.path.splitext(image_path)[1].lower()
-    
-    media_type_map = {
-        '.jpg': 'image/jpeg',
-        '.jpeg': 'image/jpeg',
-        '.png': 'image/png',
-        '.webp': 'image/webp',
-        '.gif': 'image/gif'
-    }
-    
-    return media_type_map.get(ext, 'image/jpeg')
+# Add or update the following functions in app.py:
 
-async def send_product_with_image(from_number: str, product: Dict[str, Any], user_context: Dict[str, Any]):
-    """
-    Send product information with image if available
-    """
+# --- Restore handle_voice_message_complete ---
+async def handle_voice_message_complete(from_number: str, msg: dict):
+    """Complete voice message processing with OpenAI transcription - treats voice exactly like text"""
     try:
-        product_name = product.get('Product Name', 'Unknown Product')
+        logger.info(f"[Voice] Processing voice message from {from_number}")
+        logger.info(f"[Voice] Message structure: {msg}")
         
-        # Generate product response
-        response = generate_veterinary_product_response(product, user_context)
+        # Check if OpenAI is available
+        if not OPENAI_API_KEY:
+            send_whatsjet_message(from_number, 
+                "🎤 Voice messages require OpenAI API. Please send a text message or type 'main' to see the menu.")
+            return
         
-        # Try to get product image
-        image_path = get_product_image_path(product_name)
+        # Extract media URL from different possible locations
+        media_url = None
+        logger.info(f"[Voice] Checking media URL locations...")
         
-        if image_path and os.path.exists(image_path):
-            # Send product info with image
-            media_type = get_product_image_media_type(image_path)
-            filename = f"{product_name.replace(' ', '_')}.jpg"
+        if msg.get('media', {}).get('link'):
+            media_url = msg.get('media', {}).get('link')
+            logger.info(f"[Voice] Found media URL in media.link: {media_url}")
+        elif msg.get('media', {}).get('url'):
+            media_url = msg.get('media', {}).get('url')
+            logger.info(f"[Voice] Found media URL in media.url: {media_url}")
+        elif msg.get('url'):
+            media_url = msg.get('url')
+            logger.info(f"[Voice] Found media URL in url: {media_url}")
+        elif msg.get('audio', {}).get('url'):
+            media_url = msg.get('audio', {}).get('url')
+            logger.info(f"[Voice] Found media URL in audio.url: {media_url}")
+        else:
+            logger.error(f"[Voice] No media URL found in message structure")
+            logger.error(f"[Voice] Available fields: {list(msg.keys())}")
+            if 'media' in msg:
+                logger.error(f"[Voice] Media fields: {list(msg['media'].keys())}")
+        
+        logger.info(f"[Voice] Final extracted media URL: {media_url}")
+        
+        if not media_url:
+            send_whatsjet_message(from_number, "❌ Could not process voice message. Please try again.")
+            return
+        
+        # Generate unique filename
+        filename = f"voice_{from_number}_{int(time.time())}.ogg"
+        
+        # Download voice file
+        file_path = await download_voice_file(media_url, filename)
+        if not file_path:
+            send_whatsjet_message(from_number, "❌ Failed to download voice message. Please try again.")
+            return
+        
+        # Transcribe with OpenAI
+        transcribed_text = await transcribe_voice_with_openai(file_path)
+        
+        # Clean up voice file immediately
+        try:
+            os.remove(file_path)
+        except:
+            pass
+        
+        # Handle empty or failed transcription
+        if not transcribed_text or transcribed_text.strip() == "":
+            logger.warning(f"[Voice] Empty transcription for {from_number}")
+            send_whatsjet_message(from_number, 
+                "🎤 *Voice Message Issue*\n\n"
+                "I couldn't hear anything in your voice message. This can happen due to:\n"
+                "• Very short voice note\n"
+                "• Background noise\n"
+                "• Microphone too far away\n"
+                "• Audio quality issues\n\n"
+                "💡 *Tips for better voice notes:*\n"
+                "• Speak clearly and slowly\n"
+                "• Keep phone close to mouth\n"
+                "• Record in quiet environment\n"
+                "• Make voice note at least 2-3 seconds\n\n"
+                "💬 *You can also:*\n"
+                "• Send a text message\n"
+                "• Type 'main' to see menu options\n"
+                "• Try voice note again")
+            return
+        
+        # Process transcribed text with full intelligence
+        logger.info(f"[Voice] Transcribed: {transcribed_text}")
+        
+        # Apply transcription error corrections
+        corrected_text = process_voice_input(transcribed_text)
+        if corrected_text != transcribed_text:
+            logger.info(f"[Voice] Applied corrections: '{transcribed_text}' -> '{corrected_text}'")
+            transcribed_text = corrected_text
+        
+        # Detect language of transcribed text
+        detected_lang = 'en'  # Default to English
+        try:
+            detected_lang = detect(transcribed_text)
+            logger.info(f"[Voice] Detected language: {detected_lang}")
+            
+            # Map language codes to supported languages
+            lang_mapping = {
+                'ur': 'ur',  # Urdu
+                'ar': 'ur',  # Arabic (treat as Urdu for Islamic greetings)
+                'en': 'en',  # English
+                'hi': 'ur',  # Hindi (treat as Urdu)
+                'bn': 'ur',  # Bengali (treat as Urdu)
+                'pa': 'ur',  # Punjabi (treat as Urdu)
+                'id': 'ur',  # Indonesian (often misdetected for Urdu/Arabic)
+                'ms': 'ur',  # Malay (often misdetected for Urdu/Arabic)
+                'tr': 'ur',  # Turkish (often misdetected for Urdu/Arabic)
+            }
+            
+            # 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']
             
-            success = send_whatsjet_message(
-                from_number,
-                response,
-                media_type=media_type,
-                media_path=image_path,
-                filename=filename
-            )
+            has_urdu_chars = bool(urdu_arabic_pattern.search(transcribed_text))
+            has_islamic_greeting = any(greeting in transcribed_text.lower() for greeting in islamic_greetings)
             
-            if success:
-                logger.info(f"[Product] Successfully sent product with image: {product_name}")
-            else:
-                # Fallback to text-only if image send fails
-                logger.warning(f"[Product] Failed to send image, sending text only: {product_name}")
-                send_whatsjet_message(from_number, response)
-        else:
-            # Send text-only response
-            send_whatsjet_message(from_number, response)
-            logger.info(f"[Product] Sent product info without image: {product_name}")
+            if has_urdu_chars or has_islamic_greeting:
+                detected_lang = 'ur'
+                logger.info(f"[Voice] Overriding language detection to Urdu due to Arabic/Urdu characters or Islamic greeting")
             
-    except Exception as e:
-        logger.error(f"[Product] Error sending product with image: {e}")
-        # Fallback to text-only
-        response = generate_veterinary_product_response(product, user_context)
-        send_whatsjet_message(from_number, response)
-
-async def send_enhanced_pdf(from_number: str, product: Dict[str, Any], pdf_content: bytes = None):
-    """
-    Send PDF with enhanced formatting and proper WhatsApp document sharing
-    """
-    try:
-        product_name = product.get('Product Name', 'Unknown_Product')
-        safe_name = re.sub(r'[^\w\s-]', '', product_name).replace(' ', '_')
-        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
-        filename = f"{safe_name}_Product_Info_{timestamp}.pdf"
+            reply_language = lang_mapping.get(detected_lang, 'en')
+            logger.info(f"[Voice] Language '{detected_lang}' mapped to: {reply_language}")
+            
+        except Exception as e:
+            logger.warning(f"[Voice] Language detection failed: {e}")
+            reply_language = 'en'
         
-        # Generate PDF if not provided
-        if pdf_content is None:
-            pdf_content = generate_veterinary_pdf(product)
+        if reply_language not in ['en', 'ur']:
+            logger.info(f"[Voice] Language '{reply_language}' not supported, defaulting to English")
+            reply_language = 'en'
         
-        # Save PDF to uploads directory
-        uploads_dir = "uploads"
-        os.makedirs(uploads_dir, exist_ok=True)
-        pdf_path = os.path.join(uploads_dir, filename)
+        # For Urdu voice notes, translate to English for processing
+        processing_text = transcribed_text
+        if reply_language == 'ur' and detected_lang == 'ur':
+            try:
+                logger.info(f"[Voice] Translating Urdu voice note to English for processing")
+                translated_text = GoogleTranslator(source='ur', target='en').translate(transcribed_text)
+                processing_text = translated_text
+                logger.info(f"[Voice] Translated to English: {translated_text}")
+            except Exception as e:
+                logger.error(f"[Voice] Translation failed: {e}")
+                # If translation fails, use original text
+                processing_text = transcribed_text
         
-        with open(pdf_path, 'wb') as f:
-            f.write(pdf_content)
+        # Determine reply language - always respond in English or Urdu
+        if detected_lang == 'ur':
+            reply_language = 'ur'  # Urdu voice notes get Urdu replies
+        else:
+            reply_language = 'en'  # All other languages get English replies
         
-        # Send PDF as document via WhatsApp
-        success = send_whatsjet_message(
-            from_number,
-            f"📄 *{product_name} - Detailed Product Information*\n\n"
-            f"📎 Here's the complete product information in PDF format.\n"
-            f"📋 Includes: Composition, Dosage, Precautions, Storage\n\n"
-            f"💬 Type 'main' to return to main menu.",
-            media_type="application/pdf",
-            media_path=pdf_path,
-            filename=filename
-        )
+        logger.info(f"[Voice] Processing text: {processing_text}")
+        logger.info(f"[Voice] Reply language set to: {reply_language}")
         
-        if success:
-            logger.info(f"[PDF] Successfully sent PDF for product: {product_name}")
-        else:
-            # Fallback: Send download link
-            server_url = os.getenv("SERVER_URL", "https://your-huggingface-space-url.hf.space")
-            download_url = f"{server_url}/uploads/{filename}"
+        # Check if this is a greeting in voice note (check both original and translated)
+        if is_greeting(transcribed_text) or is_greeting(processing_text):
+            logger.info(f"[Voice] Greeting detected in voice note: {transcribed_text}")
             
-            message = (
-                f"📄 *{product_name} - Product Information*\n\n"
-                f"📎 [Download Product PDF]({download_url})\n\n"
-                f"💬 *Click the link above to download the detailed product information*\n"
-                f"Type 'main' to return to main menu."
-            )
-            send_whatsjet_message(from_number, message)
-            logger.info(f"[PDF] Sent PDF download link for product: {product_name}")
+            # Check if user is currently in AI chat mode - if so, don't trigger menu mode
+            user_context = context_manager.get_context(from_number)
+            current_state = user_context.get('current_state', 'main_menu')
             
+            if current_state == 'ai_chat_mode':
+                logger.info(f"[Voice] User is in AI chat mode, treating greeting as AI query instead of menu trigger")
+                # Treat greeting as a general query in AI chat mode
+                await handle_general_query_with_ai(from_number, processing_text, user_context, reply_language)
+                return
+            else:
+                # Only trigger menu mode if not in AI chat mode
+                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()))
+                return
+        
+        # Process the translated text using the same strict state-based logic as text messages
+        # This ensures voice messages follow the same menu and state rules as text messages
+        await process_incoming_message(from_number, {
+            'body': processing_text,  # Use translated text for processing
+            'type': 'text',
+            'reply_language': reply_language,
+            'original_transcription': transcribed_text  # Keep original for context
+        })
+        
     except Exception as e:
-        logger.error(f"[PDF] Error sending enhanced PDF: {e}")
-        # Fallback to basic text response
-        response = generate_veterinary_product_response(product, {})
-        send_whatsjet_message(from_number, response)
+        logger.error(f"[Voice] Error processing voice message: {e}")
+        logger.error(f"[Voice] Full error details: {str(e)}")
+        import traceback
+        logger.error(f"[Voice] Traceback: {traceback.format_exc()}")
+        send_whatsjet_message(from_number, 
+            "❌ Error processing voice message. Please try a text message.")
 
-# Enhanced product response function with image support
-def generate_veterinary_product_response_with_media(product_info: Dict[str, Any], user_context: Dict[str, Any]) -> Dict[str, Any]:
-    """
-    Generate comprehensive veterinary product response with media information
-    Returns a dictionary with text response and media info
-    """
-    def clean_text(text):
-        if pd.isna(text) or text is None:
-            return "Not specified"
-        return str(text).strip()
-    product_name = clean_text(product_info.get('Product Name', ''))
-    product_type = clean_text(product_info.get('Type', ''))
-    category = clean_text(product_info.get('Category', ''))
-    indications = clean_text(product_info.get('Indications', ''))
-    pdf_link = ""
+# Test endpoint for WhatsJet media format debugging
+@app.get("/test-whatsjet-media-formats")
+async def test_whatsjet_media_formats(phone: str):
+    """Test endpoint to debug WhatsJet media message formats"""
     try:
-        csv_data = pd.read_csv('Veterinary.csv')
-        product_row = csv_data[csv_data['Product Name'] == product_name]
-        if not product_row.empty:
-            brochure_link = product_row.iloc[0].get('Brochure (PDF)', '')
-            if pd.notna(brochure_link) and brochure_link.strip():
-                pdf_link = brochure_link.strip()
+        test_image_url = "https://amgocus.com/uploads/images/respiraaidplus.png"
+        test_message = "🧪 *Media Format Test*\n\nTesting different WhatsJet media payload formats."
+        
+        # Test different payload formats
+        formats = [
+            {
+                "name": "Format 1 - caption",
+                "payload": {
+                    "phone_number": phone,
+                    "caption": test_message,
+                    "media_type": "image/png",
+                    "media_url": test_image_url,
+                    "media_filename": "test.png"
+                }
+            },
+            {
+                "name": "Format 2 - message_body",
+                "payload": {
+                    "phone_number": phone,
+                    "message_body": test_message,
+                    "media_type": "image/png",
+                    "media_url": test_image_url,
+                    "media_filename": "test.png"
+                }
+            },
+            {
+                "name": "Format 3 - simplified",
+                "payload": {
+                    "phone_number": phone,
+                    "message_body": test_message,
+                    "media_type": "image/png",
+                    "media_url": test_image_url
+                }
+            },
+            {
+                "name": "Format 4 - different fields",
+                "payload": {
+                    "phone_number": phone,
+                    "caption": test_message,
+                    "type": "image/png",
+                    "url": test_image_url
+                }
+            }
+        ]
+        
+        results = []
+        url = f"{WHATSJET_API_URL}/{WHATSJET_VENDOR_UID}/contact/send-message?token={WHATSJET_API_TOKEN}"
+        
+        for format_info in formats:
+            try:
+                logger.info(f"[Test] Trying {format_info['name']}: {format_info['payload']}")
+                response = httpx.post(url, json=format_info['payload'], timeout=15)
+                
+                result = {
+                    "format": format_info['name'],
+                    "status_code": response.status_code,
+                    "success": response.status_code == 200,
+                    "response_text": response.text[:500] if response.text else "No response text"
+                }
+                results.append(result)
+                
+                if response.status_code == 200:
+                    logger.info(f"[Test] ✅ {format_info['name']} succeeded!")
+                else:
+                    logger.warning(f"[Test] ❌ {format_info['name']} failed: {response.status_code}")
+                    
+            except Exception as e:
+                result = {
+                    "format": format_info['name'],
+                    "status_code": "Exception",
+                    "success": False,
+                    "response_text": str(e)
+                }
+                results.append(result)
+                logger.error(f"[Test] Exception with {format_info['name']}: {e}")
+        
+        return {
+            "status": "completed",
+            "phone": phone,
+            "image_url": test_image_url,
+            "results": results,
+            "timestamp": datetime.now().isoformat()
+        }
+        
     except Exception as e:
-        logger.warning(f"Error checking PDF link for {product_name}: {e}")
-    response_text = f"""🧪 *Name:* {product_name}\n📦 *Type:* {product_type}\n🏥 *Category:* {category}\n💊 *Used For:* {indications}"""
-    if pdf_link:
-        response_text += f"\n\n📄 Product Brochure Available\n🔗 {product_name} PDF:\n{pdf_link}"
-    response_text += f"""
-\n💬 *Available Actions:*
-1️⃣ Talk to Veterinary Consultant
-2️⃣ Inquire About Availability
-3️⃣ Back to Main Menu
-\n💬 Select an option or ask about related products"""
-    image_path = get_product_image_path(product_name)
-    has_image = image_path is not None and os.path.exists(image_path)
-    return {
-        'text': response_text,
-        'has_image': has_image,
-        'image_path': image_path,
-        'product_name': product_name
-    }
-
-# Ensure static/images directory exists for product images
-def ensure_images_dir():
-    images_dir = os.path.join('static', 'images')
-    os.makedirs(images_dir, exist_ok=True)
-    return images_dir
+        logger.error(f"Error in test WhatsJet media formats: {e}")
+        return {"error": str(e)}
 
-# New feature: Send product image with caption (product details)
-async def send_product_image_with_caption(from_number: str, product: Dict[str, Any], user_context: Dict[str, Any]):
-    """
-    Send product image (if available) with product details as caption in a single WhatsApp message.
-    If image is not available, send only the product details as text.
-    Now supports 'Images' column in CSV (Google Drive or direct links).
-    """
-    ensure_images_dir()
-    product_name = product.get('Product Name', 'Unknown Product')
-    details = generate_veterinary_product_response(product, user_context)
-    image_url = product.get('Images', '').strip() if 'Images' in product else ''
-    temp_file_path = None
+# Test endpoint for product image URL accessibility
+@app.get("/test-product-image-url")
+async def test_product_image_url(product_name: str = "Respira Aid Plus"):
+    """Test endpoint to check if product image URL is accessible"""
     try:
-        if image_url:
-            # Convert Google Drive link to direct download if needed
-            if 'drive.google.com' in image_url:
-                if '/d/' in image_url:
-                    file_id = image_url.split('/d/')[1].split('/')[0]
-                elif 'id=' in image_url:
-                    file_id = image_url.split('id=')[1].split('&')[0]
-                else:
-                    file_id = ''
-                if file_id:
-                    image_url = f"https://drive.google.com/uc?export=download&id={file_id}"
-            # Download the image to a temp file
-            response = requests.get(image_url, stream=True, timeout=10)
-            if response.status_code == 200:
-                with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as tmp:
-                    for chunk in response.iter_content(1024):
-                        tmp.write(chunk)
-                    temp_file_path = tmp.name
-                media_type = 'image/jpeg'
-                filename = f"{product_name.replace(' ', '_')}.jpg"
-                success = send_whatsjet_message(
-                    from_number,
-                    details,
-                    media_type=media_type,
-                    media_path=temp_file_path,
-                    filename=filename
-                )
-                if success:
-                    logger.info(f"[Product] Sent image from CSV link with caption for product: {product_name}")
-                    return
-                else:
-                    logger.warning(f"[Product] Failed to send image from CSV link, sending text only: {product_name}")
-            else:
-                logger.warning(f"[Product] Could not download image from CSV link: {image_url}")
-        # Fallback to local static/images
         image_path = get_product_image_path(product_name)
-        if image_path and os.path.exists(image_path):
-            media_type = get_product_image_media_type(image_path)
-            filename = f"{product_name.replace(' ', '_')}.jpg"
-            success = send_whatsjet_message(
-                from_number,
-                details,
-                media_type=media_type,
-                media_path=image_path,
-                filename=filename
-            )
-            if success:
-                logger.info(f"[Product] Sent image with caption for product: {product_name}")
+        
+        if not image_path:
+            return {
+                "product_name": product_name,
+                "image_path": None,
+                "accessible": False,
+                "error": "No image path found"
+            }
+        
+        # Test if the URL is accessible
+        try:
+            headers = {
+                'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36',
+                'Accept': 'image/webp,image/apng,image/*,*/*;q=0.8',
+                'Accept-Language': 'en-US,en;q=0.9',
+                'Accept-Encoding': 'gzip, deflate, br',
+                'Connection': 'keep-alive'
+            }
+            
+            response = requests.get(image_path, headers=headers, timeout=10, stream=True)
+            
+            result = {
+                "product_name": product_name,
+                "image_path": image_path,
+                "status_code": response.status_code,
+                "accessible": response.status_code == 200,
+                "content_type": response.headers.get('content-type', 'unknown'),
+                "content_length": response.headers.get('content-length', 'unknown'),
+                "headers": dict(response.headers)
+            }
+            
+            if response.status_code == 200:
+                logger.info(f"[Test] ✅ Product image URL is accessible: {image_path}")
             else:
-                logger.warning(f"[Product] Failed to send image, sending text only: {product_name}")
-                send_whatsjet_message(from_number, details)
-        else:
-            send_whatsjet_message(from_number, details)
-            logger.info(f"[Product] Sent product info without image: {product_name}")
-    except Exception as e:
-        logger.error(f"[Product] Error sending product image with caption: {e}")
-        send_whatsjet_message(from_number, details)
-    finally:
-        if temp_file_path and os.path.exists(temp_file_path):
-            try:
-                os.remove(temp_file_path)
-            except Exception:
-                pass
-
-@app.get("/test-product-image-with-caption")
-async def test_product_image_with_caption(phone: str):
-    """
-    Test endpoint to send Heposel product image and details as caption to the given phone number.
-    """
-    # Load Heposel product from CSV
-    try:
-        df = pd.read_csv('Veterinary.csv')
-        row = df[df['Product Name'].str.lower() == 'heposel']
-        if row.empty:
-            return {"error": "Heposel not found in CSV"}
-        product = row.iloc[0].to_dict()
-        user_context = context_manager.get_context(phone)
-        await send_product_image_with_caption(phone, product, user_context)
-        return {"status": "sent", "phone": phone}
+                logger.warning(f"[Test] ❌ Product image URL not accessible: {image_path} (status: {response.status_code})")
+            
+            return result
+            
+        except Exception as e:
+            return {
+                "product_name": product_name,
+                "image_path": image_path,
+                "accessible": False,
+                "error": str(e)
+            }
+            
     except Exception as e:
+        logger.error(f"Error testing product image URL: {e}")
         return {"error": str(e)}
 
 if __name__ == "__main__":