Update app.py

app.py

@@ -129,7 +129,7 @@ MENU_CONFIG = {
         'name': 'Main Menu',
         'valid_options': ['1', '2', '3', '4'],
         'option_descriptions': {
-            '1': 'Complete Products List',
+            '1': 'Search Products',
             '2': 'Browse Categories', 
             '3': 'Download Catalog',
             '4': 'Chat with Veterinary AI Assistant'
@@ -275,7 +275,7 @@ 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 intelligent English/Urdu focus"""
+    """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):
@@ -289,11 +289,19 @@ async def transcribe_voice_with_openai(file_path: str) -> str:
         
         logger.info(f"[Transcribe] Transcribing file: {file_path} (size: {file_size} bytes)")
         
-        # Intelligent English/Urdu focused system prompt
+        # Comprehensive system prompt for veterinary WhatsApp assistant
         system_prompt = """
-You are transcribing voice messages for Apex Biotical Veterinary WhatsApp Assistant.
+You are transcribing voice messages for Apex Biotical Veterinary WhatsApp Assistant. This is a professional veterinary products chatbot.
 
-FOCUS: The user will speak in English, Urdu, or a mix of both languages. Be intelligent and natural in understanding their speech.
+CRITICAL: TRANSCRIBE ONLY ENGLISH OR URDU SPEECH - NOTHING ELSE
+
+IMPORTANT RULES:
+1. ONLY transcribe English or Urdu speech
+2. If you hear unclear audio, transcribe as English
+3. If you hear mixed languages, transcribe as English
+4. Never transcribe gibberish or random characters
+5. If audio is unclear, transcribe as "unclear audio"
+6. Keep transcriptions simple and clean
 
 PRODUCT NAMES (exact spelling required):
 - Hydropex, Respira Aid Plus, Heposel, Bromacid, Hexatox
@@ -302,25 +310,22 @@ PRODUCT NAMES (exact spelling required):
 - Apvita Plus, B-G Aspro-C, EC-Immune, Liverpex, Symodex
 - Respira Aid, Adek Gold, Immuno DX
 
-ENGLISH NUMBERS: one->1, two->2, three->3, four->4, five->5, six->6, seven->7, eight->8, nine->9, ten->10
-
-URDU NUMBERS: aik->1, ek->1, do->2, teen->3, char->4, panch->5, cheh->6, saat->7, aath->8, nau->9, das->10
-
 MENU COMMANDS:
-- English: main, menu, back, home, start, option, number, search, browse, download, catalog, contact, availability
-- Urdu: main menu, option, number, search, browse, download, catalog, contact, availability
+- Numbers: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10
+- Navigation: main, menu, back, home, start
+- Options: option, number, choice, select
 
 GREETINGS:
 - English: hi, hello, hey, good morning, good afternoon, good evening
 - Urdu: salam, assalamu alaikum, adaab, namaste, khuda hafiz
 
 TRANSCRIPTION RULES:
-1. Intelligently transcribe English and Urdu speech
-2. Handle mixed English-Urdu speech naturally
-3. Convert numbers to digits
-4. Preserve product names exactly
-5. Only return "unclear audio" if the voice is genuinely unclear or inaudible
-6. Be natural and conversational in understanding
+1. Transcribe exactly what you hear in English or Urdu
+2. Convert numbers to digits (one->1, two->2, etc.)
+3. Preserve product names exactly
+4. If unclear, transcribe as "unclear audio"
+5. Keep it simple and clean
+6. No random characters or mixed languages
 
 EXAMPLES:
 - "hydropex" -> "hydropex"
@@ -329,12 +334,10 @@ EXAMPLES:
 - "main menu" -> "main"
 - "salam" -> "salam"
 - "search products" -> "search products"
-- "how many products" -> "how many products"
-- "kitne products hain" -> "kitne products hain"
-- Genuinely unclear audio -> "unclear audio"
+- Unclear audio -> "unclear audio"
 """
         
-        # First attempt with intelligent English/Urdu focus
+        # First attempt with comprehensive system prompt
         with open(file_path, 'rb') as audio_file:
             transcript = openai.Audio.transcribe(
                 model="whisper-1",
@@ -353,8 +356,6 @@ EXAMPLES:
             urdu_system_prompt = """
 You are transcribing Urdu voice messages for Apex Biotical Veterinary WhatsApp Assistant.
 
-FOCUS: The user will speak in Urdu, English, or a mix of both. Be intelligent and natural.
-
 PRODUCT NAMES (Urdu/English):
 - ہائیڈروپیکس (Hydropex)
 - ریسپیرا ایڈ پلس (Respira Aid Plus)
@@ -367,11 +368,12 @@ PRODUCT NAMES (Urdu/English):
 - فائٹو سال (PHYTO-SAL)
 - مائیکوپیکس سپر (Mycopex Super)
 
-URDU NUMBERS (convert to digits):
+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)
@@ -383,12 +385,11 @@ URDU MENU COMMANDS:
 - کیٹلاگ (catalog), رابطہ (contact), دستیابی (availability)
 
 TRANSCRIPTION RULES:
-1. Intelligently transcribe Urdu and English speech
-2. Handle mixed language naturally
-3. Convert Urdu numbers to digits
+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. Only return "unclear audio" if voice is genuinely unclear
-6. Be natural and conversational
+5. Convert menu selections to numbers
 """
             
             with open(file_path, 'rb') as audio_file:
@@ -401,16 +402,59 @@ TRANSCRIPTION RULES:
                 
             transcribed_text = transcript.text.strip()
             logger.info(f"[Transcribe] Second attempt transcribed (Urdu): '{transcribed_text}'")
+            
+            # Third attempt with mixed language prompt if still failing
+            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=mixed_system_prompt
+                    )
+                    
+                transcribed_text = transcript.text.strip()
+                logger.info(f"[Transcribe] Third attempt (mixed) transcribed: '{transcribed_text}'")
         
-        # Final check for genuinely unclear audio
+        # Final check for empty transcription or unclear audio
         if not transcribed_text or len(transcribed_text.strip()) < 2:
             logger.warning(f"[Transcribe] Very short or empty transcription: '{transcribed_text}'")
             return "unclear audio"
         
-        # Check for too many special characters (indicates unclear audio)
+        # Check for gibberish or mixed characters
+        if len(transcribed_text) > 10 and not re.search(r'[a-zA-Z\u0600-\u06FF]', transcribed_text):
+            logger.warning(f"[Transcribe] Gibberish detected: '{transcribed_text}'")
+            return "unclear audio"
+        
+        # Check for too many special characters
         special_char_ratio = len(re.findall(r'[^\w\s]', transcribed_text)) / len(transcribed_text)
-        if special_char_ratio > 0.5:  # More than 50% special characters
-            logger.warning(f"[Transcribe] Too many special characters, unclear audio: '{transcribed_text}'")
+        if special_char_ratio > 0.3:
+            logger.warning(f"[Transcribe] Too many special characters: '{transcribed_text}'")
             return "unclear audio"
         
         return transcribed_text
@@ -431,80 +475,6 @@ def process_voice_input(text: str) -> str:
     # Remove extra whitespace
     processed_text = re.sub(r'\s+', ' ', processed_text)
     
-    # Remove all leading/trailing quotes and dots
-    processed_text = re.sub(r'^["\']*[. ]*', '', processed_text)
-    processed_text = re.sub(r'["\']*[. ]*$', '', processed_text)
-    
-    # Remove repeated phrases (if two sentences are very similar, keep only one)
-    # Split by sentence-ending punctuation
-    from rapidfuzz import fuzz
-    sentences = re.split(r'[.!?]+', processed_text)
-    unique_sentences = []
-    for s in sentences:
-        s = s.strip()
-        if not s:
-            continue
-        # Only add if not very similar to any already added
-        if not any(fuzz.ratio(s, us) > 85 for us in unique_sentences):
-            unique_sentences.append(s)
-    processed_text = '. '.join(unique_sentences)
-    
-    # Remove any remaining duplicate words/phrases
-    words = processed_text.split()
-    if len(words) > 5:
-        mid = len(words) // 2
-        first_half = ' '.join(words[:mid])
-        second_half = ' '.join(words[mid:])
-        if fuzz.ratio(first_half, second_half) > 85:
-            processed_text = first_half
-    
-    # Fix special characters and encoding issues
-    processed_text = clean_special_characters(processed_text)
-    
-    return processed_text
-
-def clean_special_characters(text: str) -> str:
-    """Clean special characters and fix encoding issues"""
-    if not text:
-        return text
-    
-    # Fix common encoding issues
-    replacements = {
-        'â€"': '–',  # Fix en dash
-        'â€"': '—',  # Fix em dash
-        '’': "'",   # Fix apostrophe
-        '“': '"',   # Fix opening quote
-        'â€': '"',    # Fix closing quote
-        '…': '...', # Fix ellipsis
-        '•': '•',   # Fix bullet
-        '‰': '°',   # Fix degree symbol
-        '′': '′',   # Fix prime
-        '″': '″',   # Fix double prime
-        '‼': '™',   # Fix trademark
-        '‮': '®',   # Fix registered
-        '
': '©',   # Fix copyright
-        'â€': '–',    # Generic fix for en dash
-        'â€"': '—',   # Generic fix for em dash
-        '’': "'",    # Generic fix for apostrophe
-        '“': '"',    # Generic fix for opening quote
-        'â€': '"',     # Generic fix for closing quote
-        '…': '...',  # Generic fix for ellipsis
-        '•': '•',    # Generic fix for bullet
-        '‰': '°',    # Generic fix for degree symbol
-    }
-    
-    # Apply replacements
-    for old_char, new_char in replacements.items():
-        text = text.replace(old_char, new_char)
-    
-    # Remove any remaining problematic characters
-    text = re.sub(r'â€[^"]*', '', text)  # Remove any remaining †patterns
-    
-    # Clean up multiple spaces
-    text = re.sub(r'\s+', ' ', text)
-    
-    return text.strip()
-    
     # Basic punctuation cleanup
     processed_text = processed_text.replace(' ,', ',').replace(' .', '.')
     
@@ -630,19 +600,6 @@ def get_veterinary_product_matches(query: str) -> List[Dict[str, Any]]:
         logger.info(f"[Veterinary Search] Skipping menu selection: '{normalized_query}'")
         return []
     
-    # Check if this is a mode of action query
-    mode_of_action_keywords = ['mode of action', 'mechanism', 'how does it work', 'what does it do', 'how it works', 'mood of action']
-    is_mode_of_action_query = any(keyword in normalized_query for keyword in mode_of_action_keywords)
-    
-    # Extract product name from mode of action query
-    if is_mode_of_action_query:
-        # Try to extract product name from the query
-        for _, row in products_df.iterrows():
-            product_name = str(row.get('Product Name', '')).lower()
-            if product_name in normalized_query:
-                logger.info(f"[Veterinary Search] Mode of action query for product: {product_name}")
-                return [row.to_dict()]
-    
     scored_matches = []
     
     # Veterinary-specific query expansion
@@ -663,29 +620,27 @@ def get_veterinary_product_matches(query: str) -> List[Dict[str, Any]]:
         if category_key in normalized_query:
             expanded_queries.extend(categories)
     
-    # Enhanced veterinary product variations with more variations
+    # Common veterinary product variations
     veterinary_variations = {
-        'hydropex': ['hydropex', 'hydro pex', 'hydropex', 'electrolyte', 'dehydration', 'heat stress'],
-        'heposel': ['heposel', 'hepo sel', 'heposel', 'liver tonic', 'hepatoprotective'],
-        'bromacid': ['bromacid', 'brom acid', 'bromacid', 'respiratory', 'mucolytic'],
-        'respira aid': ['respira aid', 'respira aid plus', 'respiraaid', 'respiratory support'],
-        'hexatox': ['hexatox', 'hexa tox', 'hexatox', 'liver support', 'kidney support'],
-        'apma fort': ['apma fort', 'apmafort', 'mycotoxin', 'liver support'],
-        'para c': ['para c', 'para c.e', 'parace', 'heat stress', 'paracetamol'],
+        'hydropex': ['hydropex', 'hydro pex', 'electrolyte', 'dehydration', 'heat stress'],
+        'heposel': ['heposel', 'hepo sel', 'liver tonic', 'hepatoprotective'],
+        'bromacid': ['bromacid', 'brom acid', 'respiratory', 'mucolytic'],
+        'respira aid': ['respira aid', 'respira aid plus', 'respiratory support'],
+        'hexatox': ['hexatox', 'hexa tox', 'liver support', 'kidney support'],
+        'apma fort': ['apma fort', 'mycotoxin', 'liver support'],
+        'para c': ['para c', 'para c.e', 'heat stress', 'paracetamol'],
         'tribiotic': ['tribiotic', 'antibiotic', 'respiratory infection'],
-        'phyto-sal': ['phyto-sal', 'phytosal', 'phytogenic', 'vitamin supplement'],
-        'mycopex': ['mycopex', 'mycopex super', 'mycotoxin binder', 'mold'],
-        'oftilex': ['oftilex', 'oftilex ua-10', 'ofloxacin', 'antibiotic'],
-        'biscomin': ['biscomin', 'biscomin 10', 'oxytetracycline', 'injectable'],
-        'apvita': ['apvita', 'apvita plus', 'vitamin b', 'amino acid'],
-        'bg aspro': ['bg aspro', 'b-g aspro-c', 'aspirin', 'vitamin c'],
-        'ec-immune': ['ec-immune', 'ec immune', 'ecimmune', 'immune', 'immunity'],
+        'phyto-sal': ['phyto-sal', 'phytogenic', 'vitamin supplement'],
+        'mycopex': ['mycopex', 'mycotoxin binder', 'mold'],
+        'oftilex': ['oftilex', 'ofloxacin', 'antibiotic'],
+        'biscomin': ['biscomin', 'oxytetracycline', 'injectable'],
+        'apvita': ['apvita', 'vitamin b', 'amino acid'],
+        'bg aspro': ['bg aspro', 'aspirin', 'vitamin c'],
+        'ec-immune': ['ec-immune', 'immune', 'immunity'],
         'liverpex': ['liverpex', 'liver', 'metabolic'],
         'symodex': ['symodex', 'multivitamin', 'vitamin'],
-        'adek gold': ['adek gold', 'adekgold', 'vitamin', 'multivitamin'],
-        'immuno dx': ['immuno dx', 'immunodx', 'immune', 'antioxidant'],
-        'apex': ['apex', 'aapex', 'apex biotical'],
-        'apex biotical': ['apex biotical', 'apex', 'aapex']
+        'adek gold': ['adek gold', 'vitamin', 'multivitamin'],
+        'immuno dx': ['immuno dx', 'immune', 'antioxidant']
     }
     
     # Add veterinary variations
@@ -723,11 +678,11 @@ def get_veterinary_product_matches(query: str) -> List[Dict[str, Any]]:
                         best_match_type = "exact"
                         match_details = {"field": field_name, "query": expanded_query}
             
-            # Fuzzy matching for close matches (improved threshold)
+            # Fuzzy matching for close matches
             for expanded_query in expanded_queries:
                 if len(expanded_query) > 3:  # Only fuzzy match longer queries
                     score = fuzz.partial_ratio(normalized_query, field_str) * weight
-                    if score > best_score and score > 75:  # Increased threshold for better accuracy
+                    if score > best_score and score > 70:
                         best_score = score
                         best_match_type = "fuzzy"
                         match_details = {"field": field_name, "query": expanded_query}
@@ -752,59 +707,20 @@ def get_veterinary_product_matches(query: str) -> List[Dict[str, Any]]:
     return unique_matches
 
 def normalize(text: str) -> str:
-    """Normalize text for better matching"""
-    return re.sub(r'[^\w\s\u0600-\u06FF]', '', text).lower().strip()
-
-def apply_intelligent_corrections(query: str) -> str:
-    """Apply intelligent corrections to common misspellings and variations"""
-    corrections = {
-        # Common misspellings
-        'hydropex': 'hydropex',
-        'respira': 'respira aid plus',
-        'bromacid': 'bromacid',
-        'heposel': 'heposel',
-        'tribiotic': 'tribiotic',
-        'para ce': 'para c.e',
-        'phytosal': 'phyto-sal',
-        'mycopex': 'mycopex super',
-        'eflin': 'eflin kt-20',
-        'salcozine': 'salcozine st-30',
-        'oftilex': 'oftilex ua-10',
-        'biscomin': 'biscomin 10',
-        'apvita': 'apvita plus',
-        'b gaspro': 'b-g aspro-c',
-        'ec immune': 'ec-immune',
-        'liverpex': 'liverpex',
-        'symodex': 'symodex',
-        'adek': 'adek gold',
-        'immuno dx': 'immuno dx',
-        
-        # Category corrections
-        'respiratory': 'respiratory',
-        'liver': 'liver health',
-        'antibiotic': 'antibiotics',
-        'vitamin': 'vitamins',
-        'supplement': 'supplements',
-        'immune': 'immune system',
-        
-        # Common variations
-        'apex': 'apex biotical',
-        'aapex': 'apex biotical',
-    }
+    """Normalize text for search"""
+    if not text:
+        return ""
     
-    normalized_query = query.lower().strip()
+    # Convert to lowercase and remove extra whitespace
+    normalized = text.lower().strip()
     
-    # Check for exact matches first
-    if normalized_query in corrections:
-        return corrections[normalized_query]
+    # Remove special characters but keep spaces
+    normalized = re.sub(r'[^\w\s]', '', normalized)
     
-    # Check for partial matches
-    for wrong, correct in corrections.items():
-        if wrong in normalized_query:
-            return normalized_query.replace(wrong, correct)
+    # Replace multiple spaces with single space
+    normalized = re.sub(r'\s+', ' ', normalized)
     
-    # If no corrections found, return original
-    return query
+    return normalized
 
 # Enhanced context management with veterinary domain awareness
 class VeterinaryContextManager:
@@ -895,16 +811,13 @@ class VeterinaryContextManager:
 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], reply_language: str = 'en') -> str:
+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"
-        cleaned = str(text).strip()
-        # Apply special character cleaning
-        cleaned = clean_special_characters(cleaned)
-        return cleaned
+        return str(text).strip()
     
     # Extract product details
     product_name = clean_text(product_info.get('Product Name', ''))
@@ -925,38 +838,18 @@ def generate_veterinary_product_response(product_info: Dict[str, Any], user_cont
     except Exception as e:
         logger.warning(f"Error checking PDF link for {product_name}: {e}")
     
-    # Build the response based on language
-    if reply_language == 'ur':
-        response = f"""🧪 *نام:* {product_name}
-📦 *قسم:* {product_type}
-🏥 *زمرہ:* {category}
-💊 *استعمال:* {indications}"""
-        
-        # Add PDF link if available, in the requested format
-        if pdf_link:
-            response += f"\n\n📄 پروڈکٹ بروشر دستیاب ہے\n🔗 {product_name} پی ڈی ایف:\n{pdf_link}"
-        
-        # Add menu options in Urdu
-        response += f"""
-
-💬 *دستیاب اختیارات:*
-1️⃣ ویٹرنری کنسلٹنٹ سے بات کریں
-2️⃣ دستیابی کے بارے میں پوچھیں
-3️⃣ مین مینو پر واپس جائیں
-
-💬 ایک اختیار منتخب کریں یا متعلقہ مصنوعات کے بارے میں پوچھیں"""
-    else:
-        response = f"""🧪 *Name:* {product_name}
+    # 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"""
+    
+    # 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"""
 
 💬 *Available Actions:*
 1️⃣ Talk to Veterinary Consultant
@@ -973,8 +866,6 @@ def clean_text_for_pdf(text: str) -> str:
         return "N/A"
     
     cleaned = str(text)
-    # Apply special character cleaning first
-    cleaned = clean_special_characters(cleaned)
     # Remove or replace problematic characters for PDF
     cleaned = cleaned.replace('â€"', '-').replace('â€"', '"').replace('’', "'")
     cleaned = cleaned.replace('“', '"').replace('â€', '"').replace('…', '...')
@@ -1803,36 +1694,7 @@ async def process_incoming_message(from_number: str, msg: dict):
         # Handle voice messages FIRST - before checking message_body
         if message_type in ['audio', 'voice'] or media_type == 'audio':
             logger.info(f"[Process] Processing voice message from {from_number}")
-            # Extract transcription (simulate as if already transcribed for this logic)
-            transcribed_text = msg.get('transcribed_text') or ''
-            # Only use menu navigation logic for strict commands
-            menu_commands = ['main', 'menu', 'start', 'home', 'back', '1', '2', '3', '4', '5']
-            if transcribed_text.lower().strip() in menu_commands:
-                # Existing menu navigation logic (unchanged)
-                if reply_language == 'ur':
-                    welcome_msg = (
-                        "🤖 ویٹرنری ورچوئل اسسٹنٹ\n\n"
-                        "آپ مجھ سے پوچھ سکتے ہیں:\n"
-                        "* ویٹرنری سوالات\n"
-                        "* پروڈکٹ کی سفارشات\n"
-                        "* علاج کے مشورے\n"
-                        "* عمومی معلومات\n\n"
-                        "💬 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                    )
-                else:
-                    welcome_msg = generate_veterinary_welcome_message()
-                send_whatsjet_message(from_number, welcome_msg)
-                context_manager.update_context(
-                    from_number, 
-                    current_state='main_menu', 
-                    current_menu='main_menu', 
-                    current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values()),
-                    reply_language=reply_language
-                )
-                return
-            # All other voice queries go to OpenAI/gpt-4o
-            user_context = context_manager.get_context(from_number)
-            await handle_general_query_with_ai(from_number, transcribed_text, user_context, reply_language)
+            await handle_voice_message_complete(from_number, msg)
             return
 
         # For text messages, check if body exists
@@ -1841,41 +1703,23 @@ async def process_incoming_message(from_number: str, msg: dict):
             return
 
         message_body = message_body.strip()
+
         logger.info(f"[Process] Processing {message_type} message from {from_number}: {message_body}")
 
         # Get user context
         user_context = context_manager.get_context(from_number)
         current_state = user_context.get('current_state', 'main_menu')
+        
+        # Update context with last message for intelligent responses
         context_manager.update_context(from_number, last_message=message_body)
+        
+        # Debug logging
         logger.info(f"[Process] Current state: {current_state}, Message: '{message_body}' from {from_number}")
-
+        
+        # Handle text messages
         if not message_body:
             return
-
-        # LANGUAGE DETECTION FOR TEXT MESSAGES - STRICTLY ENGLISH OR URDU ONLY
-        reply_language = 'en'  # Default to English
-        try:
-            detected_lang = detect(message_body)
-            logger.info(f"[Process] Raw detected language: {detected_lang}")
-            if detected_lang in ['en', 'ur']:
-                reply_language = detected_lang
-                logger.info(f"[Process] Valid language detected: {detected_lang}")
-            else:
-                reply_language = 'en'
-                logger.warning(f"[Process] Invalid language '{detected_lang}' detected - forcing to English")
-            urdu_arabic_pattern = re.compile(r'[\u0600-\u06FF\u0750-\u077F\u08A0-\u08FF\uFB50-\uFDFF\uFE70-\uFEFF]')
-            islamic_greetings = ['assalamu', 'assalam', 'salam', 'salaam', 'adaab', 'namaste', 'khuda', 'allah']
-            has_urdu_chars = bool(urdu_arabic_pattern.search(message_body))
-            has_islamic_greeting = any(greeting in message_body.lower() for greeting in islamic_greetings)
-            if has_urdu_chars or has_islamic_greeting:
-                detected_lang = 'ur'
-                reply_language = 'ur'
-                logger.info(f"[Process] Overriding language detection to Urdu due to Arabic/Urdu characters or Islamic greeting")
-            logger.info(f"[Process] Final language set to: {reply_language}")
-        except Exception as e:
-            logger.warning(f"[Process] Language detection failed: {e}, defaulting to English")
-            reply_language = 'en'
-
+        
         # Check for greetings with multilingual support
         if is_greeting(message_body):
             # Check if user is currently in AI chat mode - if so, don't trigger menu mode
@@ -1886,337 +1730,45 @@ async def process_incoming_message(from_number: str, msg: dict):
                 return
             else:
                 # Only trigger menu mode if not in AI chat mode
-                # Generate welcome message in detected language
-                if reply_language == 'ur':
-                    welcome_msg = (
-                        "🤖 ویٹرنری ورچوئل اسسٹنٹ\n\n"
-                        "آپ مجھ سے پوچھ سکتے ہیں:\n"
-                        "* ویٹرنری سوالات\n"
-                        "* پروڈکٹ کی سفارشات\n"
-                        "* علاج کے مشورے\n"
-                        "* عمومی معلومات\n\n"
-                        "💬 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                    )
-                else:
-                    welcome_msg = generate_veterinary_welcome_message()
-                
-                send_whatsjet_message(from_number, welcome_msg)
-                context_manager.update_context(
-                    from_number, 
-                    current_state='main_menu', 
-                    current_menu='main_menu', 
-                    current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values()),
-                    reply_language=reply_language
-                )
-                return
-
-        # 🎯 PRIORITY 1: Navigation commands - work from ANY state
-        # Check for "main" command - now works for both text and voice
-        if current_state != 'main_menu' and current_state != 'ai_chat_mode':  # Only check for main if not already in main menu and not in AI chat mode
-            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'")
-                # Generate welcome message in detected language
-                if reply_language == 'ur':
-                    welcome_msg = (
-                        "🤖 ویٹرنری ورچوئل اسسٹنٹ\n\n"
-                        "آپ مجھ سے پوچھ سکتے ہیں:\n"
-                        "* ویٹرنری سوالات\n"
-                        "* پروڈکٹ کی سفارشات\n"
-                        "* علاج کے مشورے\n"
-                        "* عمومی معلومات\n\n"
-                        "💬 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                    )
-                else:
-                    welcome_msg = generate_veterinary_welcome_message()
-                
+                welcome_msg = generate_veterinary_welcome_message()
                 send_whatsjet_message(from_number, welcome_msg)
                 context_manager.update_context(
                     from_number, 
                     current_state='main_menu', 
                     current_menu='main_menu', 
-                    current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values()),
-                    reply_language=reply_language
-                )
-                return
-        
-        # Also check for text-based navigation commands
-        if message_body.lower() in ['main', 'menu', 'start', 'home', 'back']:
-            # Generate welcome message in detected language
-            if reply_language == 'ur':
-                welcome_msg = (
-                    "🤖 ویٹرنری ورچوئل اسسٹنٹ\n\n"
-                    "آپ مجھ سے پوچھ سکتے ہیں:\n"
-                    "* ویٹرنری سوالات\n"
-                    "* پروڈکٹ کی سفارشات\n"
-                    "* علاج کے مشورے\n"
-                    "* عمومی معلومات\n\n"
-                    "💬 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                )
-            else:
-                welcome_msg = generate_veterinary_welcome_message()
-            
-            send_whatsjet_message(from_number, welcome_msg)
-            context_manager.update_context(
-                from_number, 
-                current_state='main_menu', 
-                current_menu='main_menu', 
-                current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values()),
-                reply_language=reply_language
-            )
-            return
-        
-        # 🎯 PRIORITY 2: State-specific handling (contact_request, availability_request, ai_chat_mode, clarification)
-        if current_state == 'contact_request':
-            await handle_contact_request_response(from_number, message_body)
-            return
-        elif current_state == 'availability_request':
-            await handle_availability_request_response(from_number, message_body)
-            return
-        elif current_state == 'ai_chat_mode':
-            await handle_ai_chat_mode(from_number, message_body, reply_language)
-            return
-        elif user_context.get('awaiting_clarification', False):
-            # Handle clarification responses
-            await handle_clarification_response(from_number, message_body, user_context)
-            return
-        
-        # 🎯 PRIORITY 3: Menu selection validation and handling
-        if current_state == 'main_menu':
-            # Validate menu selection
-            is_valid, validation_message = validate_menu_selection(message_body, current_state, user_context)
-            
-            if not is_valid:
-                send_whatsjet_message(from_number, validation_message)
-                return
-            
-            # Handle valid menu selection
-            if message_body == '1':
-                # Complete Products List - Display all 23 products
-                await display_all_products(from_number)
-                return
-                
-            elif message_body == '2':
-                # Category Browse - Show all categories
-                categories = get_all_categories()
-                if reply_language == 'ur':
-                    message = "📂 *زمرے براؤز کریں:*\n\n"
-                    for i, category in enumerate(categories, 1):
-                        message += f"{format_number_with_emoji(i)} {category}\n"
-                    message += "\n💬 اپنا انتخاب لکھیں یا 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                else:
-                    message = "📂 *Browse Categories:*\n\n"
-                    for i, category in enumerate(categories, 1):
-                        message += f"{format_number_with_emoji(i)} {category}\n"
-                    message += "\n💬 Type your choice or 'main' to return to main menu"
-                
-                send_whatsjet_message(from_number, message)
-                context_manager.update_context(
-                    from_number,
-                    current_state='category_selection',
-                    current_menu='category_selection',
-                    current_menu_options=categories,
-                    available_categories=categories,
-                    reply_language=reply_language
-                )
-                return
-                
-            elif message_body == '3':
-                # Catalog Download
-                await send_catalog_pdf(from_number)
-                return
-                
-            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'],
-                    reply_language=reply_language
+                    current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values())
                 )
-                if reply_language == 'ur':
-                    message = (
-                        "🤖 ویٹرنری ورچوئل اسسٹنٹ\n\n"
-                        "آپ مجھ سے پوچھ سکتے ہیں:\n"
-                        "* ویٹرنری سوالات\n"
-                        "* پروڈکٹ کی سفارشات\n"
-                        "* علاج کے مشورے\n"
-                        "* عمومی معلومات\n\n"
-                        "💬 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                    )
-                else:
-                    message = (
-                        "🤖 Veterinary Virtual Assistant\n\n"
-                        "You can ask me about:\n"
-                        "* Veterinary questions\n"
-                        "* Product recommendations\n"
-                        "* Treatment advice\n"
-                        "* General information\n\n"
-                        "💬 Type 'main' to return to main menu"
-                    )
-                send_whatsjet_message(from_number, message)
                 return
         
-        # 🎯 PRIORITY 4: Category selection handling
-        elif current_state == 'category_selection':
-            await handle_category_selection(message_body, from_number)
-            return
-        
-
-        
-        # 🎯 PRIORITY 5: Product inquiry handling (for direct product searches)
-        elif current_state == 'product_inquiry':
-            # Check for voice commands first
-            mapped_command = process_intelligent_voice_command(message_body, current_state, user_context)
-            if mapped_command != message_body:
-                logger.info(f"[Voice Command] Processing: '{message_body}' in state: {current_state}")
-                message_body = mapped_command
-                logger.info(f"[Voice Command] Mapped to: '{message_body}'")
-            
-            # Search for products
-            matches = get_veterinary_product_matches(message_body)
-            
-            if matches:
-                logger.info(f"[Process] Product query detected from menu state '{current_state}': '{message_body}' -> Found {len(matches)} products")
-                
-                # Apply intelligent corrections
-                corrected_query = apply_intelligent_corrections(message_body)
-                if corrected_query != message_body:
-                    logger.info(f"[Query] Applied correction: '{message_body}' -> '{corrected_query}'")
-                    matches = get_veterinary_product_matches(corrected_query)
-                
-                # Handle product matches
-                if len(matches) == 1:
-                    # Single product match - show detailed info
-                    product = matches[0]
-                    context_manager.update_context(from_number, current_product=product)
-                    await send_product_with_image(from_number, product, user_context)
-                    
-                    # Send follow-up options
-                    await handle_veterinary_product_followup(message_body, from_number)
-                    
-                elif len(matches) <= 5:
-                    # Multiple products - show list
-                    if reply_language == 'ur':
-                        response = f"🔍 *{len(matches)} پروڈکٹ ملے:*\n\n"
-                    else:
-                        response = f"🔍 *Found {len(matches)} products:*\n\n"
-                    
-                    for i, product in enumerate(matches, 1):
-                        product_name = product.get('Product Name', 'N/A')
-                        category = product.get('Category', 'N/A')
-                        if reply_language == 'ur':
-                            response += f"{format_number_with_emoji(i)} {product_name} ({category})\n"
-                        else:
-                            response += f"{format_number_with_emoji(i)} {product_name} ({category})\n"
-                    
-                    if reply_language == 'ur':
-                        response += "\n💬 اپنا انتخاب لکھیں یا 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                    else:
-                        response += "\n💬 Type your choice or 'main' to return to main menu"
-                    
-                    send_whatsjet_message(from_number, response)
-                    context_manager.update_context(
-                        from_number,
-                        current_state='product_selection',
-                        current_menu='product_selection',
-                        current_menu_options=[p.get('Product Name', 'N/A') for p in matches],
-                        reply_language=reply_language
-                    )
-                    
-                else:
-                    # Too many matches - ask for clarification
-                    if reply_language == 'ur':
-                        response = f"🔍 *{len(matches)} سے زیادہ پروڈکٹ ملے۔ براہ کرم مزید تفصیل دیں:*\n\n"
-                    else:
-                        response = f"🔍 *Found {len(matches)}+ products. Please be more specific:*\n\n"
-                    
-                    # Show first 10 matches as examples
-                    for i, product in enumerate(matches[:10], 1):
-                        product_name = product.get('Product Name', 'N/A')
-                        category = product.get('Category', 'N/A')
-                        if reply_language == 'ur':
-                            response += f"{format_number_with_emoji(i)} {product_name} ({category})\n"
-                        else:
-                            response += f"{format_number_with_emoji(i)} {product_name} ({category})\n"
-                    
-                    if reply_language == 'ur':
-                        response += "\n💬 براہ کرم مزید تفصیل دیں یا 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                    else:
-                        response += "\n💬 Please provide more details or type 'main' to return to main menu"
-                    
-                    send_whatsjet_message(from_number, response)
-                    context_manager.update_context(from_number, awaiting_clarification=True)
-                    
-            else:
-                # No matches found - use OpenAI for intelligent response
-                await handle_general_query_with_ai(from_number, message_body, user_context, reply_language)
-                return
-        
-        # 🎯 PRIORITY 6: All other queries - use OpenAI for intelligent response
-        await handle_general_query_with_ai(from_number, message_body, user_context, reply_language)
-        return
-
         # 🎯 PRIORITY 1: Navigation commands - work from ANY state
         # Check for "main" command - now works for both text and voice
         if current_state != 'main_menu' and current_state != 'ai_chat_mode':  # Only check for main if not already in main menu and not in AI chat mode
             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'")
-                # Generate welcome message in detected language
-                if reply_language == 'ur':
-                    welcome_msg = (
-                        "🩺 *اپیکس بائیوٹیکل ویٹرنری اسسٹنٹ*\n\n"
-                        "آپ کا خیر مقدم ہے! میں آپ کی ویٹرنری مصنوعات کے بارے میں مدد کر سکتا ہوں۔\n\n"
-                        "📋 *مین مینو:*\n"
-                        "1️⃣ مصنوعات تلاش کریں\n"
-                        "2️⃣ زمرے براؤز کریں\n"
-                        "3️⃣ کیٹلاگ ڈاؤن لوڈ کریں\n"
-                        "4️⃣ اے آئی چیٹ موڈ\n\n"
-                        "💬 اپنا انتخاب لکھیں یا 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                    )
-                else:
-                    welcome_msg = generate_veterinary_welcome_message()
-                
+                welcome_msg = generate_veterinary_welcome_message()
                 send_whatsjet_message(from_number, welcome_msg)
                 context_manager.update_context(
                     from_number, 
                     current_state='main_menu', 
                     current_menu='main_menu', 
-                    current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values()),
-                    reply_language=reply_language
+                    current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values())
                 )
                 return
         
         # Also check for text-based navigation commands
         if message_body.lower() in ['main', 'menu', 'start', 'home', 'back']:
-            # Generate welcome message in detected language
-            if reply_language == 'ur':
-                welcome_msg = (
-                    "🩺 *اپیکس بائیوٹیکل ویٹرنری اسسٹنٹ*\n\n"
-                    "آپ کا خیر مقدم ہے! میں آپ کی ویٹرنری مصنوعات کے بارے میں مدد کر سکتا ہوں۔\n\n"
-                    "📋 *مین مینو:*\n"
-                    "1️⃣ مصنوعات تلاش کریں\n"
-                    "2️⃣ زمرے براؤز کریں\n"
-                    "3️⃣ کیٹلاگ ڈاؤن لوڈ کریں\n"
-                    "4️⃣ اے آئی چیٹ موڈ\n\n"
-                    "💬 اپنا انتخاب لکھیں یا 'main' لکھ کر مین مینو پر واپس جائیں۔"
-                )
-            else:
-                welcome_msg = generate_veterinary_welcome_message()
-            
+            welcome_msg = generate_veterinary_welcome_message()
             send_whatsjet_message(from_number, welcome_msg)
             context_manager.update_context(
                 from_number, 
                 current_state='main_menu', 
                 current_menu='main_menu', 
-                current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values()),
-                reply_language=reply_language
+                current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values())
             )
             return
         
-        # 🎯 PRIORITY 2: State-specific handling (contact_request, availability_request, ai_chat_mode, clarification)
+        # 🎯 PRIORITY 2: State-specific handling (contact_request, availability_request, ai_chat_mode)
         if current_state == 'contact_request':
             await handle_contact_request_response(from_number, message_body)
             return
@@ -2226,29 +1778,8 @@ async def process_incoming_message(from_number: str, msg: dict):
         elif current_state == 'ai_chat_mode':
             await handle_ai_chat_mode(from_number, message_body, reply_language)
             return
-        elif user_context.get('awaiting_clarification', False):
-            # Handle clarification responses
-            await handle_clarification_response(from_number, message_body, user_context)
-            return
-        
-        # 🎯 PRIORITY 3: Intelligent product queries from any menu state
-        # Check if the message is about a product from CSV, regardless of current menu
-        products = get_veterinary_product_matches(message_body)
-        
-        if products:
-            logger.info(f"[Process] Product query detected from menu state '{current_state}': '{message_body}' -> Found {len(products)} products")
-            
-            # If user is in a specific menu but asks about a product, handle it intelligently
-            if current_state in ['main_menu', 'category_selection_menu', 'category_products_menu', 'all_products_menu', 'product_inquiry', 'intelligent_products_menu']:
-                # Use intelligent product inquiry to handle the product query
-                await handle_intelligent_product_inquiry(from_number, message_body, user_context, reply_language)
-                return
-            else:
-                # For other menu states, still handle product queries but remind about menu context
-                await handle_intelligent_product_inquiry(from_number, message_body, user_context, reply_language)
-                return
         
-        # 🎯 PRIORITY 4: Menu selections - check if this is a valid menu selection for current state
+        # 🎯 PRIORITY 3: Menu selections - check if this is a valid menu selection for current state
         if current_state in ['main_menu', 'category_selection_menu', 'category_products_menu', 'all_products_menu', 'product_inquiry', 'intelligent_products_menu']:
             # Validate menu selection
             is_valid, error_msg = validate_menu_selection(message_body, current_state, user_context)
@@ -2290,12 +1821,12 @@ async def process_incoming_message(from_number: str, msg: dict):
                             reply_language='ur'
                         )
                         message = (
-                            "🤖 ویٹرنری ورچوئل اسسٹنٹ\n\n"
+                            "🤖 ویٹرنری اے آئی اسسٹنٹ\n\n"
                             "آپ مجھ سے پوچھ سکتے ہیں:\n"
-                            "* ویٹرنری سوالات\n"
-                            "* پروڈکٹ کی سفارشات\n"
-                            "* علاج کے مشورے\n"
-                            "* عمومی معلومات\n\n"
+                            "• ویٹرنری سوالات\n"
+                            "• پروڈکٹ کی سفارشات\n"
+                            "• علاج کے مشورے\n"
+                            "• عمومی معلومات\n\n"
                             "💬 'main' لکھ کر مین مینو پر واپس جائیں۔"
                         )
                         send_whatsjet_message(from_number, message)
@@ -2318,24 +1849,26 @@ async def process_incoming_message(from_number: str, msg: dict):
                         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
-                    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())
-                        )
-                        await send_product_image_with_caption(from_number, selected_product, user_context)
-                        return
+                    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())
+                            )
+                            await send_product_image_with_caption(from_number, selected_product, user_context)
+                        else:
+                            send_whatsjet_message(from_number, get_menu_validation_message(current_state, user_context))
                     else:
-                        send_whatsjet_message(from_number, get_menu_validation_message(current_state, user_context))
-                        return
+                        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)
                 elif current_state == 'intelligent_products_menu':
+                    # Handle product selection from intelligent products menu
                     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]
@@ -2353,7 +1886,7 @@ async def process_incoming_message(from_number: str, msg: dict):
                         return
                 return  # Exit after handling menu selection
         
-        # 🎯 PRIORITY 6: Product names - works from ANY menu state
+        # 🎯 PRIORITY 4: Product names - 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)
@@ -2463,254 +1996,52 @@ async def process_incoming_message(from_number: str, msg: dict):
 
 async def handle_general_query_with_ai(from_number: str, query: str, user_context: dict, reply_language: str = 'en'):
     """Handle general queries with OpenAI intelligence"""
-    logger.info(f"[AI General] Processing query: '{query}' with language: {reply_language}")
+    # Force Urdu replies for Option 4
+    reply_language = 'ur'
+    logger.info(f"[AI General] Forcing reply_language to Urdu for Option 4.")
     
     try:
-        # Let OpenAI handle all queries intelligently first
-        if OPENAI_API_KEY and products_df is not None and not products_df.empty:
-            try:
-                # Get all products data for context
-                all_products = products_df.to_dict('records')
-                
-                # Create comprehensive context for AI
-                products_context = ""
-                if all_products:
-                    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')
-                        target_species = product.get('Target Species', 'N/A')
-                        products_context += f"{i}. {product_name} - {category} ({target_species})\n"
-                
-                # Expert-level AI prompt for comprehensive veterinary assistance
-                prompt = f"""
-You are an EXPERT veterinary pharmaceutical assistant for Apex Biotical, with deep knowledge of veterinary medicine, animal health, and pharmaceutical products. You help users on WhatsApp with professional, accurate, and context-aware responses.
-
-USER QUERY: "{query}"
-
-AVAILABLE PRODUCTS DATABASE:
-{products_context}
-
-EXPERT ANALYSIS FRAMEWORK:
-
-1. **QUERY TYPE DETECTION:**
-   - COUNT/QUANTITY queries: "how many", "count", "total", "number of"
-   - PRODUCT INQUIRIES: specific product names, categories, or therapeutic areas
-   - COMPANY INQUIRIES: "apex", "company", "about", "who are you"
-   - VETERINARY ADVICE: medical questions, treatment recommendations, dosage
-   - GENERAL QUESTIONS: greetings, navigation, help requests
-
-2. **CONTEXT-AWARE RESPONSE STRATEGY:**
-   - For COUNT queries: Provide exact numbers with category breakdowns
-   - For PRODUCT queries: List relevant products with therapeutic benefits, target species, and key features
-   - For COMPANY queries: Professional company overview with expertise areas
-   - For VETERINARY ADVICE: Evidence-based recommendations with product suggestions
-   - For GENERAL queries: Helpful guidance with menu navigation
-
-3. **EXPERT KNOWLEDGE INTEGRATION:**
-   - Veterinary pharmacology and therapeutics
-   - Animal health and disease management
-   - Pharmaceutical product applications
-   - Professional veterinary communication
-   - Regulatory and safety considerations
-
-RESPONSE GUIDELINES:
-- Be PROFESSIONAL, EXPERT, and HELPFUL
-- Use appropriate veterinary terminology
-- Include relevant emojis for clarity
-- Provide accurate, evidence-based information
-- Always include navigation instructions
-- Show understanding of user's intent and context
-- Be concise but comprehensive
-- Maintain professional veterinary standards
-
-IMPORTANT: Demonstrate expert-level veterinary knowledge while being accessible and helpful. Always provide accurate information from the database and professional veterinary guidance.
-"""
-                
-                response = openai.ChatCompletion.create(
-                    model="gpt-4o",
-                    messages=[{"role": "user", "content": prompt}],
-                    temperature=0.3,  # Lower temperature for more consistent, expert responses
-                    max_tokens=600   # Increased for more comprehensive expert responses
-                )
-                
-                ai_response = response.choices[0].message.content.strip()
-                
-                # Ensure the response includes navigation instructions
-                if 'main' not in ai_response.lower():
-                    if reply_language == 'ur':
-                        ai_response += "\n\n💬 *براہ کرم 'main' لکھ کر مین مینو پر جائیں*"
-                    else:
-                        ai_response += "\n\n💬 *Please type 'main' to go to main menu*"
-                
-                # Translate response if needed (ENGLISH/URDU ONLY)
-                if reply_language == 'ur':
-                    try:
-                        # Only translate from English to Urdu - no other languages
-                        translated_response = GoogleTranslator(source='en', 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)
-                return
-                
-            except Exception as e:
-                logger.error(f"[AI] Error handling query with OpenAI: {e}")
-                # Fall back to existing logic if OpenAI fails
-                pass
-        
-        # Check if this is a non-product query that should get a simple response
-        non_product_keywords = ['what is', 'who are', 'where is', 'when', 'why', 'how to', 'can you', 'do you', 'is this', 'are you']
-        is_simple_query = any(keyword in query.lower() for keyword in non_product_keywords)
-        
-        # Check for company-related queries
-        company_queries = ['apex', 'aapex', 'apex biotical', 'company', 'about', 'who are you', 'what are you']
-        is_company_query = any(keyword in query.lower() for keyword in company_queries)
-        
-        # Check for irrelevant or unclear queries
-        irrelevant_keywords = ['weather', 'football', 'cricket', 'movie', 'music', 'food', 'restaurant', 'hotel', 'travel', 'shopping', 'fashion', 'beauty', 'sports', 'game', 'entertainment']
-        is_irrelevant_query = any(keyword in query.lower() for keyword in irrelevant_keywords)
-        
-        if is_irrelevant_query:
-            response = get_irrelevant_query_response(query, user_context.get('current_state', 'main_menu'), reply_language)
-            send_whatsjet_message(from_number, response)
-            return
-        
-        if is_company_query:
-            if reply_language == 'ur':
-                response = (
-                    "🏥 *Apex Biotical Solutions*\n\n"
-                    "ہم ایک پیشہ ور ویٹرنری فارماسیوٹیکل کمپنی ہیں جو مندرجہ ذیل میں مہارت رکھتے ہیں:\n\n"
-                    "📦 *ہماری مصنوعات:*\n"
-                    "• سانس کی مدد (Respira Aid Plus, Bromacid)\n"
-                    "• جگر کی صحت (Heposel, Liverpex)\n"
-                    "• مدافعتی نظام (EC-Immune)\n"
-                    "• اینٹی بائیوٹکس (Tribiotic, Para C.E)\n"
-                    "• وٹامنز اور سپلیمنٹس (Symodex, Adek Gold)\n\n"
-                    "💬 *مصنوعات دیکھنے کے لیے:*\n"
-                    "• 'main' لکھ کر مین مینو پر جائیں"
-                )
-            else:
-                response = (
-                    "🏥 *Apex Biotical Solutions*\n\n"
-                    "We are a leading veterinary pharmaceutical company specializing in:\n\n"
-                    "📦 *Our Products:*\n"
-                    "• Respiratory support (Respira Aid Plus, Bromacid)\n"
-                    "• Liver health (Heposel, Liverpex)\n"
-                    "• Immune system (EC-Immune)\n"
-                    "• Antibiotics (Tribiotic, Para C.E)\n"
-                    "• Vitamins & supplements (Symodex, Adek Gold)\n\n"
-                    "🌍 *Our Focus:*\n"
-                    "• Professional veterinary solutions\n"
-                    "• Quality pharmaceutical products\n"
-                    "• Comprehensive animal healthcare\n\n"
-                    "💬 *To explore our products:*\n"
-                    "• Type 'main' to see the main menu\n"
-                    "• Type a product name (e.g., 'hydropex', 'respira aid plus')"
-                )
-            send_whatsjet_message(from_number, response)
-            return
-        
         if not OPENAI_API_KEY:
-            if reply_language == 'ur':
-                send_whatsjet_message(from_number, 
-                    "❌ *AI assistance دستیاب نہیں ہے*\n\n💬 *براہ کرم 'main' لکھ کر مین مینو پر جائیں*")
-            else:
-                send_whatsjet_message(from_number, 
-                    "❌ AI assistance is not available. Please type 'main' for the menu.")
+            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')
         
-        # Get all products data for context
-        all_products = []
-        if products_df is not None and not products_df.empty:
-            all_products = products_df.to_dict('records')
-        
-        # Create comprehensive context for AI
-        products_context = ""
-        if all_products:
-            products_context = "Available Veterinary Products:\n"
-            for i, product in enumerate(all_products[:30], 1):  # Limit to first 30 products for context
-                product_name = product.get('Product Name', 'N/A')
-                category = product.get('Category', 'N/A')
-                products_context += f"{i}. {product_name} - {category}\n"
-        
-        # Expert-level prompt for comprehensive veterinary assistance
+        # --- 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 an EXPERT veterinary pharmaceutical assistant for Apex Biotical, with deep knowledge of veterinary medicine, animal health, and pharmaceutical products. You help users on WhatsApp with professional, accurate, and context-aware responses.
-
-USER QUERY: "{query}"
-CURRENT STATE: {current_state}
-CURRENT PRODUCT: {current_product.get('Product Name', 'None') if current_product else 'None'}
+You are a professional veterinary product assistant for Apex Biotical, helping users on WhatsApp.
+Always answer in a clear, accurate, and helpful manner.
 
-AVAILABLE PRODUCTS:
-{products_context}
+User Query: "{query}"
+Current State: {current_state}
+Current Product: {current_product.get('Product Name', 'None') if current_product else 'None'}
 
-EXPERT ANALYSIS FRAMEWORK:
-
-1. **QUERY TYPE DETECTION:**
-   - COUNT/QUANTITY queries: "how many", "count", "total", "number of"
-   - PRODUCT INQUIRIES: specific product names, categories, or therapeutic areas
-   - COMPANY INQUIRIES: "apex", "company", "about", "who are you"
-   - VETERINARY ADVICE: medical questions, treatment recommendations, dosage
-   - GENERAL QUESTIONS: greetings, navigation, help requests
-
-2. **CONTEXT-AWARE RESPONSE STRATEGY:**
-   - For COUNT queries: Provide exact numbers with category breakdowns
-   - For PRODUCT queries: List relevant products with therapeutic benefits, target species, and key features
-   - For COMPANY queries: Professional company overview with expertise areas
-   - For VETERINARY ADVICE: Evidence-based recommendations with product suggestions
-   - For GENERAL queries: Helpful guidance with menu navigation
-
-3. **EXPERT KNOWLEDGE INTEGRATION:**
-   - Veterinary pharmacology and therapeutics
-   - Animal health and disease management
-   - Pharmaceutical product applications
-   - Professional veterinary communication
-   - Regulatory and safety considerations
-
-RESPONSE GUIDELINES:
-- Be PROFESSIONAL, EXPERT, and HELPFUL
-- Use appropriate veterinary terminology
-- Include relevant emojis for clarity
-- Provide accurate, evidence-based information
-- Always include navigation instructions
-- Show understanding of user's intent and context
-- Be concise but comprehensive
-- Maintain professional veterinary standards
-
-IMPORTANT: Demonstrate expert-level veterinary knowledge while being accessible and helpful. Always provide accurate information from the database and professional veterinary guidance.
+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=0.3,  # Lower temperature for more consistent, expert responses
-            max_tokens=400   # Increased for more comprehensive expert responses
+            temperature=0.7,
+            max_tokens=300
         )
         
         ai_response = response.choices[0].message.content.strip()
         
-        # Ensure the response includes navigation instructions
-        if 'main' not in ai_response.lower():
-            if reply_language == 'ur':
-                ai_response += "\n\n💬 *براہ کرم 'main' لکھ کر مین مینو پر جائیں*"
-            else:
-                ai_response += "\n\n💬 *Please type 'main' to go to main menu*"
-        
-        # Translate response if needed (ENGLISH/URDU ONLY)
+        # Translate response if needed
         if reply_language == 'ur':
             try:
-                # Only translate from English to Urdu - no other languages
-                translated_response = GoogleTranslator(source='en', target='ur').translate(ai_response)
+                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}")
@@ -2723,13 +2054,9 @@ IMPORTANT: Demonstrate expert-level veterinary knowledge while being accessible
         
     except Exception as e:
         logger.error(f"[AI] Error handling general query: {e}")
-        # Professional error response
-        if reply_language == 'ur':
-            error_msg = "❌ *خطا آ گئی ہے*\n\n💬 *براہ کرم 'main' لکھ کر مین مینو پر جائیں*"
-        else:
-            error_msg = "❌ *An error occurred*\n\n💬 *Please type 'main' to go to main menu*"
-        
-        send_whatsjet_message(from_number, error_msg)
+        # 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',
@@ -2737,58 +2064,6 @@ IMPORTANT: Demonstrate expert-level veterinary knowledge while being accessible
             current_menu_options=list(MENU_CONFIG['main_menu']['option_descriptions'].values())
         )
 
-async def handle_clarification_response(from_number: str, response: str, user_context: dict):
-    """Handle user response to clarification questions"""
-    try:
-        clean_response = response.strip().lower()
-        
-        if clean_response in ['yes', 'y', 'apex', 'apex biotical', 'apex biotical solution']:
-            # User confirmed they want Apex Biotical - provide company information
-            company_info = (
-                "🏥 *Apex Biotical Solutions*\n\n"
-                "We are a leading veterinary pharmaceutical company specializing in:\n\n"
-                "📦 *Our Products:*\n"
-                "• Respiratory support (Respira Aid Plus, Bromacid)\n"
-                "• Liver health (Heposel, Liverpex)\n"
-                "• Immune system (EC-Immune)\n"
-                "• Antibiotics (Tribiotic, Para C.E)\n"
-                "• Vitamins & supplements (Symodex, Adek Gold)\n\n"
-                "🌍 *Our Focus:*\n"
-                "• Professional veterinary solutions\n"
-                "• Quality pharmaceutical products\n"
-                "• Comprehensive animal healthcare\n\n"
-                "💬 *To explore our products:*\n"
-                "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
-                "• Type 'main' to see the main menu\n"
-                "• Ask about specific symptoms or conditions"
-            )
-            
-            send_whatsjet_message(from_number, company_info)
-            
-            # Update context
-            user_context['awaiting_clarification'] = False
-            user_context.pop('clarification_product', None)
-            context_manager.update_context(from_number, **user_context)
-            
-        else:
-            # User didn't confirm - use OpenAI for intelligent response
-            if OPENAI_API_KEY:
-                await handle_ai_chat_mode(from_number, response, 'en')
-            else:
-                send_whatsjet_message(from_number, "💬 *Type 'main' to go to main menu or ask another question.*")
-            
-            # Clear clarification context
-            user_context['awaiting_clarification'] = False
-            user_context.pop('clarification_product', None)
-            context_manager.update_context(from_number, **user_context)
-            
-    except Exception as e:
-        logger.error(f"[Clarification] Error: {str(e)}")
-        send_whatsjet_message(from_number, "❌ *An error occurred. Please type 'main' to go to main menu.*")
-        user_context['awaiting_clarification'] = False
-        user_context.pop('clarification_product', None)
-        context_manager.update_context(from_number, **user_context)
-
 async def handle_contact_request(from_number: str):
     """Handle contact request"""
     try:
@@ -3298,14 +2573,13 @@ Response:
         else:
             ai_response += "\n\n💬 *Type 'main' to return to main menu*"
         
-        # Translate response if needed (ENGLISH/URDU ONLY)
+        # Translate response if needed
         if reply_language == 'ur':
             try:
                 # Get all product and category names
                 product_names = [str(p.get('Product Name', '')) for p in all_products if p.get('Product Name')]
                 category_names = list(set([str(p.get('Category', '')) for p in all_products if p.get('Category')]))
-                # Only translate from English to Urdu - no other languages
-                translated_response = GoogleTranslator(source='en', target='ur').translate(ai_response)
+                translated_response = GoogleTranslator(source='auto', target='ur').translate(ai_response)
                 # Restore English terms
                 translated_response = restore_english_terms(translated_response, ai_response, product_names, category_names)
                 send_whatsjet_message(from_number, translated_response)
@@ -3522,10 +2796,7 @@ def generate_veterinary_product_response_with_media(product_info: Dict[str, Any]
     def clean_text(text):
         if pd.isna(text) or text is None:
             return "Not specified"
-        cleaned = str(text).strip()
-        # Apply special character cleaning
-        cleaned = clean_special_characters(cleaned)
-        return cleaned
+        return str(text).strip()
     
     product_name = clean_text(product_info.get('Product Name', ''))
     product_type = clean_text(product_info.get('Type', ''))
@@ -3572,7 +2843,7 @@ def ensure_images_dir():
     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], reply_language: str = 'en'):
+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.
     Only uses cPanel images from https://amgocus.com/uploads/images/
@@ -3580,7 +2851,7 @@ async def send_product_image_with_caption(from_number: str, product: Dict[str, A
     """
     ensure_images_dir()
     product_name = product.get('Product Name', 'Unknown Product')
-    details = generate_veterinary_product_response(product, user_context, reply_language)
+    details = generate_veterinary_product_response(product, user_context)
     
     logger.info(f"[Product] Processing cPanel image for product: {product_name}")
     
@@ -3682,7 +2953,7 @@ async def test_product_image_with_caption(phone: str):
         product = products_df.iloc[0].to_dict()
         user_context = {}
         
-        await send_product_image_with_caption(phone, product, user_context, 'en')
+        await send_product_image_with_caption(phone, product, user_context)
         
         return {
             "success": True,
@@ -4047,9 +3318,11 @@ async def handle_veterinary_product_followup(selection: str, from_number: str) -
                 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)
@@ -4174,17 +3447,14 @@ async def handle_voice_message_complete(from_number: str, msg: dict):
             detected_lang = detect(transcribed_text)
             logger.info(f"[Voice] Raw detected language: {detected_lang}")
             
-            # STRICTLY ENGLISH OR URDU ONLY - REJECT ALL OTHER LANGUAGES
+            # STRICTLY ENGLISH OR URDU ONLY - NO OTHER LANGUAGES
+            # Only allow English and Urdu, reject everything else
             if detected_lang in ['en', 'ur']:
                 reply_language = detected_lang
-                logger.info(f"[Voice] Valid language detected: {detected_lang}")
             else:
-                # Reject any other language and force to English
+                # Force any other language to English
                 reply_language = 'en'
-                logger.warning(f"[Voice] Invalid language '{detected_lang}' detected - forcing to English")
-                # If it's clearly not English/Urdu, mark as unclear
-                if detected_lang not in ['en', 'ur', 'unknown']:
-                    logger.warning(f"[Voice] Non-English/Urdu language detected: {detected_lang}")
+                logger.warning(f"[Voice] Detected language '{detected_lang}' is not English or Urdu, forcing to English")
             
             # Check if text contains Urdu/Arabic characters or Islamic greetings
             urdu_arabic_pattern = re.compile(r'[\u0600-\u06FF\u0750-\u077F\u08A0-\u08FF\uFB50-\uFDFF\uFE70-\uFEFF]')
@@ -4204,12 +3474,11 @@ async def handle_voice_message_complete(from_number: str, msg: dict):
             logger.warning(f"[Voice] Language detection failed: {e}, defaulting to English")
             reply_language = 'en'
         
-        # For Urdu voice notes, translate to English for processing (ENGLISH/URDU ONLY)
+        # 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")
-                # Only translate from Urdu to English - no other languages
                 translated_text = GoogleTranslator(source='ur', target='en').translate(transcribed_text)
                 processing_text = translated_text
                 logger.info(f"[Voice] Translated to English: {translated_text}")
@@ -4217,17 +3486,6 @@ async def handle_voice_message_complete(from_number: str, msg: dict):
                 logger.error(f"[Voice] Translation failed: {e}")
                 # If translation fails, use original text
                 processing_text = transcribed_text
-        elif detected_lang not in ['en', 'ur']:
-            # If language is not English or Urdu, reject it
-            logger.warning(f"[Voice] Non-English/Urdu language detected: {detected_lang}")
-            send_whatsjet_message(from_number, 
-                "🎤 *Voice Message Issue*\n\n"
-                "I can only process voice messages in English or Urdu.\n\n"
-                "💡 *Please:*\n"
-                "• Speak in English or Urdu only\n"
-                "• Send a text message instead\n"
-                "• Type 'main' to see menu options")
-            return
         
         # Determine reply language - always respond in English or Urdu
         if detected_lang == 'ur':
@@ -4239,22 +3497,33 @@ async def handle_voice_message_complete(from_number: str, msg: dict):
         logger.info(f"[Voice] Reply language set to: {reply_language}")
         
         # Check if this is a greeting in voice note (check both original and translated)
-        user_context = context_manager.get_context(from_number)
-        current_state = user_context.get('current_state', 'main_menu')
         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
-        # For all other cases, always pass to OpenAI for intelligent response
-        await handle_general_query_with_ai(from_number, processing_text, user_context, reply_language)
-        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}")
@@ -4430,7 +3699,7 @@ async def test_send_product_image(phone: str, product_name: str = "Bromacid"):
         user_context = context_manager.get_context(phone)
         
         logger.info(f"[Test] Testing send_product_image_with_caption for product: {product_name}")
-        await send_product_image_with_caption(phone, product, user_context, 'en')
+        await send_product_image_with_caption(phone, product, user_context)
         
         return {
             "status": "sent", 
@@ -4443,53 +3712,181 @@ async def test_send_product_image(phone: str, product_name: str = "Bromacid"):
         return {"error": str(e)}
 
 async def handle_intelligent_product_inquiry(from_number: str, query: str, user_context: dict, reply_language: str = 'en'):
-    """Handle product inquiry with OpenAI intelligence and media support, matching WhatsApp screenshot logic"""
+    """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:
-                # Numbered list with short descriptions
-                message = f"Certainly, here are the relevant products for your query:\n\n"
+                # 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', 'Unknown')
-                    category = product.get('Category', '')
-                    short_desc = product.get('Type', '') or product.get('Indications', '')
-                    message += f"{i}. {product_name}"
-                    if category:
-                        message += f" - {category}"
-                    if short_desc:
-                        message += f" / {short_desc}"
-                    message += "\n"
-                message += (f"\nTo view detailed information about any product, reply with its number (1-{len(products)})\n"
-                            "Type 'main' to return to the main menu")
-                send_whatsjet_message(from_number, message)
-                # Store product list in context for selection
+                    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,
+                    from_number, 
                     current_state='intelligent_products_menu',
                     current_menu='intelligent_products_menu',
-                    current_menu_options=[str(i) for i in range(1, len(products)+1)],
-                    available_products=products
+                    current_menu_options=[f"Product {i+1}" for i in range(len(products))],
+                    available_products=products,
+                    last_query=query
                 )
-                return
+                
+                # Add to conversation history
+                context_manager.add_to_history(from_number, query, message)
+                
             else:
-                # Single product found - show details
+                # Single product found - show detailed information with media support
                 selected_product = products[0]
                 context_manager.update_context(
-                    from_number,
-                    current_product=selected_product,
+                    from_number, 
+                    current_product=selected_product, 
                     current_state='product_inquiry',
                     current_menu='product_inquiry',
                     current_menu_options=list(MENU_CONFIG['product_inquiry']['option_descriptions'].values())
                 )
+                
+                # Send product image with caption using the new function
                 await send_product_image_with_caption(from_number, selected_product, user_context)
-                return
+                
+                # Add to conversation history
+                context_manager.add_to_history(from_number, query, f"Product inquiry for {selected_product.get('Product Name', 'Unknown')}")
+            
         else:
-            # No products found
-            send_whatsjet_message(from_number, "❌ No products found matching your query.\nType 'main' to return to the main menu.")
+            # 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 handle_intelligent_product_inquiry: {e}")
-        send_whatsjet_message(from_number, "❌ Error processing your request. Type 'main' to return to the main menu.")
+        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_contact_request(from_number: str):
     """Handle contact request"""
@@ -4543,4 +3940,4 @@ if __name__ == "__main__":
     
     # Launch FastAPI app
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=7860)
+    uvicorn.run(app, host="0.0.0.0", port=7860)