Update app.py

app.py

@@ -2166,11 +2166,93 @@ async def process_incoming_message(from_number: str, msg: dict):
 
 async def handle_general_query_with_ai(from_number: str, query: str, user_context: dict, reply_language: str = 'en'):
     """Handle general queries with OpenAI intelligence"""
-    # Force Urdu replies for Option 4
-    reply_language = 'ur'
-    logger.info(f"[AI General] Forcing reply_language to Urdu for Option 4.")
+    logger.info(f"[AI General] Processing query: '{query}' with language: {reply_language}")
     
     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"
+                
+                # Enhanced AI prompt for intelligent query understanding
+                prompt = f"""
+You are a professional veterinary product assistant for Apex Biotical, helping users on WhatsApp.
+
+User Query: "{query}"
+
+Available Products Database:
+{products_context}
+
+IMPORTANT INSTRUCTIONS:
+1. FIRST, analyze if this is a COUNT query (asking for numbers, quantities, how many, etc.)
+2. If it's a COUNT query:
+   - Determine if asking for TOTAL products or SPECIFIC category/products
+   - If TOTAL: Provide total count of all products and categories
+   - If SPECIFIC: Search the database for matching products and provide count with breakdown
+   - Always provide accurate numbers from the database
+3. If it's NOT a count query:
+   - Handle as a general product inquiry
+   - List relevant products with descriptions
+   - Provide helpful veterinary advice
+
+RESPONSE FORMAT:
+- Be professional, concise, and helpful
+- Use emojis for better readability
+- Always include navigation instructions
+- If count query: Show numbers clearly with category breakdown
+- If product query: List products with brief descriptions
+
+IMPORTANT: Always respond in a way that shows you understand the user's intent and provide accurate information from the database.
+"""
+                
+                response = openai.ChatCompletion.create(
+                    model="gpt-4o",
+                    messages=[{"role": "user", "content": prompt}],
+                    temperature=0.7,
+                    max_tokens=500
+                )
+                
+                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)
@@ -2179,6 +2261,15 @@ async def handle_general_query_with_ai(from_number: str, query: str, user_contex
         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 = (
@@ -2266,6 +2357,7 @@ Response Guidelines:
 - Keep responses concise (max 3-4 sentences)
 - Always include menu navigation instructions
 - If unsure, redirect to main menu
+- Focus on veterinary products and services only
 """
         
         response = openai.ChatCompletion.create(
@@ -3495,80 +3587,111 @@ async def handle_category_selection(selection: str, from_number: str):
         send_helpful_guidance(from_number, 'category_selection_menu')
 
 def get_menu_validation_message(current_state: str, user_context: dict) -> str:
-    """Get appropriate validation message for current menu state"""
+    """Get professional validation message for current menu state"""
     if current_state == 'main_menu':
         return (
-            "❌ *Invalid Selection*\n\n"
-            "Please choose from the main menu:\n"
+            "⚠️ *Invalid Selection*\n\n"
+            "Please select a valid option from the main menu:\n\n"
+            "📋 *Available Options:*\n"
             "1️⃣ Search Veterinary Products\n"
             "2️⃣ Browse Categories\n"
             "3️⃣ Download Catalog\n"
             "4️⃣ Chat with Veterinary AI Assistant\n\n"
-            "💬 *You can also:*\n"
+            "💡 *Quick Actions:*\n"
             "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
-            "• Type 'main' to refresh the menu"
+            "• Type 'main' to refresh the menu\n"
+            "• Ask about symptoms or categories"
         )
     elif current_state == 'all_products_menu':
         if products_df is not None and not products_df.empty:
             total_products = len(products_df)
             return (
-                f"❌ *Invalid Product Selection*\n\n"
+                f"⚠️ *Invalid Product Selection*\n\n"
                 f"Please choose a product number between 1 and {total_products}.\n\n"
-                "💬 *You can also:*\n"
-                "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
-                "• Type 'main' to return to main menu"
+                "💡 *Alternative Options:*\n"
+                "• Type a specific product name (e.g., 'hydropex')\n"
+                "• Type 'main' to return to main menu\n"
+                "• Ask about product categories"
             )
         else:
-            return "❌ No products available. Type 'main' to return to main menu."
+            return (
+                "⚠️ *No Products Available*\n\n"
+                "Currently no products are loaded in the system.\n\n"
+                "💡 *Please:*\n"
+                "• Type 'main' to return to main menu\n"
+                "• Contact support if this issue persists"
+            )
     elif current_state == 'category_products_menu':
         available_products = user_context.get('available_products', [])
         if available_products:
             return (
-                f"❌ *Invalid Product Selection*\n\n"
+                f"⚠️ *Invalid Product Selection*\n\n"
                 f"Please choose a product number between 1 and {len(available_products)}.\n\n"
-                "💬 *You can also:*\n"
-                "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
-                "• Type 'main' to return to main menu"
+                "💡 *Alternative Options:*\n"
+                "• Type a specific product name\n"
+                "• Type 'main' to return to main menu\n"
+                "• Browse other categories"
             )
         else:
-            return "❌ No products available in this category. Type 'main' to return to main menu."
+            return (
+                "⚠️ *No Products in Category*\n\n"
+                "This category currently has no available products.\n\n"
+                "💡 *Please:*\n"
+                "• Type 'main' to return to main menu\n"
+                "• Browse other categories\n"
+                "• Ask about specific products"
+            )
     elif current_state == 'category_selection_menu':
         available_categories = user_context.get('available_categories', [])
         if available_categories:
             return (
-                f"❌ *Invalid Category Selection*\n\n"
+                f"⚠️ *Invalid Category Selection*\n\n"
                 f"Please choose a category number between 1 and {len(available_categories)}.\n\n"
-                "💬 *You can also:*\n"
-                "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
-                "• Type 'main' to return to main menu"
+                "💡 *Alternative Options:*\n"
+                "• Type a specific product name\n"
+                "• Type 'main' to return to main menu\n"
+                "• Ask about product types"
             )
         else:
-            return "❌ No categories available. Type 'main' to return to main menu."
+            return (
+                "⚠️ *No Categories Available*\n\n"
+                "Currently no product categories are available.\n\n"
+                "💡 *Please:*\n"
+                "• Type 'main' to return to main menu\n"
+                "• Ask about specific products\n"
+                "• Contact support if needed"
+            )
     elif current_state == 'product_inquiry':
         return (
-            "❌ *Invalid Selection*\n\n"
-            "Please choose an option:\n"
+            "⚠️ *Invalid Selection*\n\n"
+            "Please choose a valid option for this product:\n\n"
+            "📋 *Available Actions:*\n"
             "1️⃣ Talk to Veterinary Consultant\n"
             "2️⃣ Inquire About Availability\n"
             "3️⃣ Back to Main Menu\n\n"
-            "💬 *You can also:*\n"
-            "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
-            "• Type 'main' to return to main menu"
+            "💡 *Alternative Options:*\n"
+            "• Type another product name\n"
+            "• Type 'main' to return to main menu\n"
+            "• Ask about related products"
         )
     elif current_state == 'intelligent_products_menu':
+        available_products = user_context.get('available_products', [])
         return (
-            "❌ *Invalid Selection*\n\n"
-            "Please choose a product number between 1 and {len(available_products)}.\n\n"
-            "💬 *You can also:*\n"
-            "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
-            "• Type 'main' to return to main menu"
+            f"⚠️ *Invalid Product Selection*\n\n"
+            f"Please choose a product number between 1 and {len(available_products)}.\n\n"
+            "💡 *Alternative Options:*\n"
+            "• Type a specific product name\n"
+            "• Type 'main' to return to main menu\n"
+            "• Ask about different categories"
         )
     else:
         return (
-            "❌ *Invalid Selection*\n\n"
+            "⚠️ *Invalid Selection*\n\n"
             "Please choose a valid option or type 'main' to return to main menu.\n\n"
-            "💬 *You can also:*\n"
-            "• Type a product name (e.g., 'hydropex', 'respira aid plus')"
+            "💡 *Helpful Options:*\n"
+            "• Type a product name (e.g., 'hydropex', 'respira aid plus')\n"
+            "• Type 'main' to return to main menu\n"
+            "• Ask about veterinary products or categories"
         )
 
 def is_valid_menu_selection(selection: str, current_state: str, user_context: dict) -> bool:
@@ -3576,6 +3699,39 @@ def is_valid_menu_selection(selection: str, current_state: str, user_context: di
     is_valid, _ = validate_menu_selection(selection, current_state, user_context)
     return is_valid
 
+def get_irrelevant_query_response(query: str, current_state: str, reply_language: str = 'en') -> str:
+    """Get professional response for irrelevant or unclear queries"""
+    if reply_language == 'ur':
+        return (
+            "🤖 *Apex Biotical Veterinary Assistant*\n\n"
+            "آپ کا سوال واضح نہیں ہے یا یہ ویٹرنری مصنوعات سے متعلق نہیں ہے۔\n\n"
+            "💡 *میں آپ کی مدد کر سکتا ہوں:*\n"
+            "• ویٹرنری مصنوعات کے بارے میں معلومات\n"
+            "• مصنوعات کی تلاش اور براؤز\n"
+            "• ویٹرنری مشورے اور رہنمائی\n"
+            "• مصنوعات کی دستیابی کے بارے میں پوچھنا\n\n"
+            "📋 *مثال کے طور پر:*\n"
+            "• 'hydropex کے بارے میں بتائیں'\n"
+            "• 'سانس کی مصنوعات کون سی ہیں؟'\n"
+            "• 'main' لکھ کر مین مینو پر جائیں"
+        )
+    else:
+        return (
+            "🤖 *Apex Biotical Veterinary Assistant*\n\n"
+            "I'm here to help you with veterinary products and information. "
+            "Your query doesn't seem to be related to our veterinary services.\n\n"
+            "💡 *I can help you with:*\n"
+            "• Information about veterinary products\n"
+            "• Product search and browsing\n"
+            "• Veterinary advice and guidance\n"
+            "• Product availability inquiries\n\n"
+            "📋 *Examples of what you can ask:*\n"
+            "• 'Tell me about hydropex'\n"
+            "• 'What respiratory products do you have?'\n"
+            "• 'Show me all antibiotics'\n"
+            "• Type 'main' to return to main menu"
+        )
+
 def generate_veterinary_welcome_message(phone_number=None, user_context=None):
     """Generate veterinary welcome message"""
     return (
@@ -4037,6 +4193,196 @@ async def test_send_product_image(phone: str, product_name: str = "Bromacid"):
 async def handle_intelligent_product_inquiry(from_number: str, query: str, user_context: dict, reply_language: str = 'en'):
     """Handle product inquiry with OpenAI intelligence and media support"""
     try:
+        # Check for intelligent product count queries
+        count_keywords = ['how many', 'count', 'number of', 'total', 'quantity', 'amount']
+        is_count_query = any(keyword in query.lower() for keyword in count_keywords)
+        
+        if is_count_query and products_df is not None and not products_df.empty:
+            # Intelligent count analysis
+            query_lower = query.lower()
+            
+            # Check if it's asking for total products
+            total_indicators = ['total products', 'all products', 'products you have', 'products in total', 'total medicines', 'all medicines']
+            is_total_query = any(indicator in query_lower for indicator in total_indicators)
+            
+            if is_total_query:
+                # Total products count
+                total_products = len(products_df)
+                categories = products_df['Category'].dropna().unique()
+                total_categories = len(categories)
+                
+                if reply_language == 'ur':
+                    response = (
+                        f"📊 *کل مصنوعات کی تعداد*\n\n"
+                        f"ہمارے پاس کل **{total_products}** ویٹرنری مصنوعات ہیں۔\n\n"
+                        f"📂 *زمرے:* {total_categories}\n"
+                        f"📦 *مصنوعات:* {total_products}\n\n"
+                        "💡 *مثال کے طور پر:*\n"
+                        "• 'سانس کی مصنوعات دکھائیں'\n"
+                        "• 'hydropex کے بارے میں بتائیں'\n"
+                        "• 'main' لکھ کر مین مینو پر جائیں"
+                    )
+                else:
+                    response = (
+                        f"📊 *Total Product Count*\n\n"
+                        f"We have a total of **{total_products}** veterinary products.\n\n"
+                        f"📂 *Categories:* {total_categories}\n"
+                        f"📦 *Products:* {total_products}\n\n"
+                        "💡 *Examples:*\n"
+                        "• 'Show me respiratory products'\n"
+                        "• 'Tell me about hydropex'\n"
+                        "• Type 'main' to return to main menu"
+                    )
+                
+                send_whatsjet_message(from_number, response)
+                return
+            else:
+                # Specific category/product type count
+                # Extract search terms from the query
+                search_terms = []
+                
+                # Common veterinary categories and terms
+                category_mappings = {
+                    'respiratory': ['respiratory', 'breathing', 'lung', 'bronchi', 'respira'],
+                    'liver': ['liver', 'hepatic', 'hepat', 'hepo'],
+                    'antibiotic': ['antibiotic', 'anti-biotic', 'biotic', 'tribiotic'],
+                    'vitamin': ['vitamin', 'vit', 'multivitamin', 'symodex', 'adek'],
+                    'electrolyte': ['electrolyte', 'hydropex', 'rehydration'],
+                    'poultry': ['poultry', 'chicken', 'bird', 'avian'],
+                    'livestock': ['livestock', 'cattle', 'cow', 'buffalo', 'animal'],
+                    'immune': ['immune', 'immunity', 'immuno', 'ec-immune'],
+                    'parasite': ['parasite', 'parasitic', 'para'],
+                    'antifungal': ['antifungal', 'fungal', 'myco'],
+                    'pain': ['pain', 'analgesic', 'painkiller'],
+                    'fever': ['fever', 'pyrexia', 'temperature']
+                }
+                
+                # Find matching categories
+                matched_categories = []
+                for category, terms in category_mappings.items():
+                    if any(term in query_lower for term in terms):
+                        matched_categories.append(category)
+                
+                # Search in CSV for matching products
+                matching_products = []
+                if matched_categories:
+                    for category in matched_categories:
+                        # Search by category name
+                        category_products = products_df[
+                            products_df['Category'].str.lower().str.contains(category, na=False) |
+                            products_df['Product Name'].str.lower().str.contains(category, na=False) |
+                            products_df['Target Species'].str.lower().str.contains(category, na=False) |
+                            products_df['Mode of Action'].str.lower().str.contains(category, na=False)
+                        ]
+                        matching_products.extend(category_products.to_dict('records'))
+                    
+                    # Remove duplicates
+                    seen_names = set()
+                    unique_products = []
+                    for product in matching_products:
+                        name = product.get('Product Name', '')
+                        if name not in seen_names:
+                            seen_names.add(name)
+                            unique_products.append(product)
+                    
+                    matching_products = unique_products
+                else:
+                    # If no specific category found, search for any terms in the query
+                    query_words = query_lower.split()
+                    for word in query_words:
+                        if len(word) > 3:  # Only search for meaningful words
+                            word_products = products_df[
+                                products_df['Category'].str.lower().str.contains(word, na=False) |
+                                products_df['Product Name'].str.lower().str.contains(word, na=False) |
+                                products_df['Target Species'].str.lower().str.contains(word, na=False) |
+                                products_df['Mode of Action'].str.lower().str.contains(word, na=False)
+                            ]
+                            matching_products.extend(word_products.to_dict('records'))
+                    
+                    # Remove duplicates
+                    seen_names = set()
+                    unique_products = []
+                    for product in matching_products:
+                        name = product.get('Product Name', '')
+                        if name not in seen_names:
+                            seen_names.add(name)
+                            unique_products.append(product)
+                    
+                    matching_products = unique_products
+                
+                # Generate response based on results
+                if matching_products:
+                    count = len(matching_products)
+                    
+                    # Get category breakdown
+                    categories_found = {}
+                    for product in matching_products:
+                        category = product.get('Category', 'Unknown')
+                        categories_found[category] = categories_found.get(category, 0) + 1
+                    
+                    if reply_language == 'ur':
+                        response = (
+                            f"📊 *{query}*\n\n"
+                            f"ہمارے پاس **{count}** مصنوعات ملی ہیں۔\n\n"
+                        )
+                        
+                        if len(categories_found) > 1:
+                            response += "📂 *زمرے کے مطابق:*\n"
+                            for category, cat_count in categories_found.items():
+                                response += f"• {category}: {cat_count}\n"
+                            response += "\n"
+                        
+                        response += (
+                            "💡 *مثال کے طور پر:*\n"
+                            "• 'سانس کی مصنوعات دکھائیں'\n"
+                            "• 'hydropex کے بارے میں بتائیں'\n"
+                            "• 'main' لکھ کر مین مینو پر جائیں"
+                        )
+                    else:
+                        response = (
+                            f"📊 *{query}*\n\n"
+                            f"We found **{count}** products.\n\n"
+                        )
+                        
+                        if len(categories_found) > 1:
+                            response += "📂 *By Category:*\n"
+                            for category, cat_count in categories_found.items():
+                                response += f"• {category}: {cat_count}\n"
+                            response += "\n"
+                        
+                        response += (
+                            "💡 *Examples:*\n"
+                            "• 'Show me respiratory products'\n"
+                            "• 'Tell me about hydropex'\n"
+                            "• Type 'main' to return to main menu"
+                        )
+                    
+                    send_whatsjet_message(from_number, response)
+                    return
+                else:
+                    # No matching products found
+                    if reply_language == 'ur':
+                        response = (
+                            f"❌ *{query}*\n\n"
+                            "ہمیں کوئی مصنوعات نہیں ملی۔\n\n"
+                            "💡 *مثال کے طور پر:*\n"
+                            "• 'سانس کی مصنوعات'\n"
+                            "• 'جگر کی مصنوعات'\n"
+                            "• 'main' لکھ کر مین مینو پر جائیں"
+                        )
+                    else:
+                        response = (
+                            f"❌ *{query}*\n\n"
+                            "No products found matching your query.\n\n"
+                            "💡 *Try:*\n"
+                            "• 'respiratory products'\n"
+                            "• 'liver products'\n"
+                            "• Type 'main' to return to main menu"
+                        )
+                    
+                    send_whatsjet_message(from_number, response)
+                    return
+        
         # Clean and normalize the query
         clean_query = query.strip().lower()