Update app.py

app.py

@@ -600,6 +600,19 @@ 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
@@ -620,27 +633,29 @@ def get_veterinary_product_matches(query: str) -> List[Dict[str, Any]]:
         if category_key in normalized_query:
             expanded_queries.extend(categories)
     
-    # Common veterinary product variations
+    # Enhanced veterinary product variations with more variations
     veterinary_variations = {
-        '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'],
+        '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'],
         'tribiotic': ['tribiotic', 'antibiotic', 'respiratory infection'],
-        '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'],
+        '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'],
         'liverpex': ['liverpex', 'liver', 'metabolic'],
         'symodex': ['symodex', 'multivitamin', 'vitamin'],
-        'adek gold': ['adek gold', 'vitamin', 'multivitamin'],
-        'immuno dx': ['immuno dx', 'immune', 'antioxidant']
+        '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']
     }
     
     # Add veterinary variations
@@ -678,11 +693,11 @@ 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
+            # Fuzzy matching for close matches (improved threshold)
             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 > 70:
+                    if score > best_score and score > 75:  # Increased threshold for better accuracy
                         best_score = score
                         best_match_type = "fuzzy"
                         match_details = {"field": field_name, "query": expanded_query}
@@ -1955,37 +1970,9 @@ async def process_incoming_message(from_number: str, msg: dict):
                 return
 
         else:
-            # Enhanced "not found" response with veterinary suggestions
-            message = (
-                "❌ *Product Not Found*\n\n"
-                f"🔍 *We couldn't find '{message_body}' in our veterinary database.*\n\n"
-                "💡 *Try these alternatives:*\n"
-                "• Check spelling (e.g., 'Hydropex' not 'Hydro pex')\n"
-                "• Search by symptoms (e.g., 'respiratory', 'liver support')\n"
-                "• Search by category (e.g., 'antibiotic', 'vitamin')\n"
-                "• Search by species (e.g., 'poultry', 'livestock')\n\n"
-                "🏥 *Popular Veterinary Products:*\n"
-                "• Hydropex (Electrolyte supplement)\n"
-                "• Heposel (Liver tonic)\n"
-                "• Bromacid (Respiratory support)\n"
-                "• Tribiotic (Antibiotic)\n"
-                "• Symodex (Multivitamin)\n\n"
-                "💬 *Type 'main' to return to main menu or try another search.*"
-            )
-            
-            # 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)
-            
-        # 🎯 PRIORITY 5: Default: treat as general query with intelligent product inquiry
-        await handle_intelligent_product_inquiry(from_number, message_body, user_context, reply_language)
+            # Use intelligent product inquiry for all non-found queries
+            await handle_intelligent_product_inquiry(from_number, message_body, user_context, reply_language)
+            return
             
     except Exception as e:
         logger.error(f"Error in process_incoming_message: {e}")
@@ -2001,20 +1988,50 @@ async def handle_general_query_with_ai(from_number: str, query: str, user_contex
     logger.info(f"[AI General] Forcing reply_language to Urdu for Option 4.")
     
     try:
+        # 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)
+        
+        if is_company_query:
+            if reply_language == 'ur':
+                response = "🏥 *Apex Biotical Solutions*\n\nہم ایک پیشہ ور ویٹرنری پروڈکٹس کمپنی ہیں۔\n\n💬 *براہ کرم 'main' لکھ کر مین مینو پر جائیں*"
+            else:
+                response = "🏥 *Apex Biotical Solutions*\n\nWe are a professional veterinary products company.\n\n💬 *Please type 'main' to go to main menu*"
+            send_whatsjet_message(from_number, response)
+            return
+        
         if not OPENAI_API_KEY:
-            send_whatsjet_message(from_number, 
-                "❌ AI assistance is not available. Please try searching for a specific product or type 'main' for the menu.")
+            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.")
             return
         
         # Create context-aware prompt
         current_state = user_context.get('current_state', 'main_menu')
         current_product = user_context.get('current_product')
         
-        # --- SYSTEM PROMPT FOR GENERAL/OUT-OF-MENU QUERIES ---
-        # This prompt ensures the assistant answers professionally, accurately, and helpfully.
-        # If the query is about products, list all relevant products (not just one) with brief details.
-        # If the query is general, provide a concise, expert veterinary answer.
-        # Clarify when a query is outside the menu system and offer to return to the main menu if needed.
+        # 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"
+        
+        # Enhanced prompt for better responses
         prompt = f"""
 You are a professional veterinary product assistant for Apex Biotical, helping users on WhatsApp.
 Always answer in a clear, accurate, and helpful manner.
@@ -2023,21 +2040,40 @@ User Query: "{query}"
 Current State: {current_state}
 Current Product: {current_product.get('Product Name', 'None') if current_product else 'None'}
 
-If the user asks about products (e.g., 'poultry products', 'respiratory medicine'), list ALL relevant products from the database with a short description for each. If there are many, summarize or group them.
-If the user asks a general veterinary question, provide a concise, expert answer.
-If the query is outside the menu system, politely clarify and offer to return to the main menu (type 'main').
-Always keep responses professional, concise, and user-friendly.
+Available Products:
+{products_context}
+
+IMPORTANT RULES:
+1. If the user asks about products, list relevant products with brief descriptions
+2. If the user asks general veterinary questions, provide concise, expert answers
+3. If the query is unclear or not related to veterinary products, politely redirect to main menu
+4. Keep responses professional, concise, and user-friendly
+5. Always end with instructions to type 'main' to return to main menu
+6. If the query seems like a test or unrelated question, provide a simple redirect response
+
+Response Guidelines:
+- Be professional and helpful
+- Keep responses concise (max 3-4 sentences)
+- Always include menu navigation instructions
+- If unsure, redirect to main menu
 """
         
         response = openai.ChatCompletion.create(
             model="gpt-4o",
             messages=[{"role": "user", "content": prompt}],
             temperature=0.7,
-            max_tokens=300
+            max_tokens=200  # Reduced for more concise 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
         if reply_language == 'ur':
             try:
@@ -2054,9 +2090,13 @@ Always keep responses professional, concise, and user-friendly.
         
     except Exception as e:
         logger.error(f"[AI] Error handling general query: {e}")
-        # Instead of sending a generic error, return to main menu
-        welcome_msg = generate_veterinary_welcome_message()
-        send_whatsjet_message(from_number, welcome_msg)
+        # 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)
         context_manager.update_context(
             from_number, 
             current_state='main_menu',
@@ -3714,9 +3754,96 @@ 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:
-        # First try direct product search
+        # Clean and normalize the query
+        clean_query = query.strip().lower()
+        
+        # Check for common misspellings and variations
+        misspelling_corrections = {
+            'aapex': 'apex',
+            'apex': 'apex biotical',
+            'ec immune': 'ec-immune',
+            'ecimmune': 'ec-immune',
+            'hydro pex': 'hydropex',
+            'hydropex': 'hydropex',
+            'respira aid': 'respira aid plus',
+            'respiraaid': 'respira aid plus',
+            'hepo sel': 'heposel',
+            'heposel': 'heposel',
+            'brom acid': 'bromacid',
+            'bromacid': 'bromacid',
+            'hexa tox': 'hexatox',
+            'hexatox': 'hexatox',
+            'apma fort': 'apma fort',
+            'apmafort': 'apma fort',
+            'para c': 'para c.e',
+            'para ce': 'para c.e',
+            'parace': 'para c.e',
+            'tribiotic': 'tribiotic',
+            'phyto sal': 'phyto-sal',
+            'phytosal': 'phyto-sal',
+            'mycopex': 'mycopex super',
+            'mycopexsuper': 'mycopex super',
+            'eflin': 'eflin kt-20',
+            'eflinkt20': 'eflin kt-20',
+            'salcozine': 'salcozine st-30',
+            'salcozinest30': 'salcozine st-30',
+            'oftilex': 'oftilex ua-10',
+            'oftilexua10': 'oftilex ua-10',
+            'biscomin': 'biscomin 10',
+            'biscomin10': 'biscomin 10',
+            'apvita': 'apvita plus',
+            'apvitaplus': 'apvita plus',
+            'bg aspro': 'b-g aspro-c',
+            'bgaspro': 'b-g aspro-c',
+            'liverpex': 'liverpex',
+            'symodex': 'symodex',
+            'adek': 'adek gold',
+            'adekgold': 'adek gold',
+            'immuno': 'immuno dx',
+            'immunodx': 'immuno dx',
+            'mood of action': 'mode of action',
+            'mode of action': 'mode of action',
+            'mechanism of action': 'mode of action',
+            'how does it work': 'mode of action',
+            'what does it do': 'mode of action',
+            'how it works': 'mode of action'
+        }
+        
+        # Apply misspelling corrections
+        corrected_query = clean_query
+        for misspelling, correction in misspelling_corrections.items():
+            if misspelling in clean_query:
+                corrected_query = clean_query.replace(misspelling, correction)
+                logger.info(f"[Query] Applied correction: '{misspelling}' -> '{correction}'")
+                break
+        
+        # Check if query is asking about mode of action or mechanism
+        mode_of_action_keywords = ['mode of action', 'mechanism', 'how does it work', 'what does it do', 'how it works']
+        is_mode_of_action_query = any(keyword in clean_query for keyword in mode_of_action_keywords)
+        
+        # First try direct product search with original query
         products = get_veterinary_product_matches(query)
         
+        # If no products found, try with corrected query
+        if not products and corrected_query != clean_query:
+            products = get_veterinary_product_matches(corrected_query)
+            if products:
+                logger.info(f"[Query] Found products using corrected query: '{corrected_query}'")
+        
+        # If still no products, try fuzzy matching with product names
+        if not products:
+            if products_df is not None and not products_df.empty:
+                all_product_names = [str(name).lower() for name in products_df['Product Name'].dropna()]
+                
+                # Use fuzzy matching to find similar product names
+                for product_name in all_product_names:
+                    similarity = fuzz.ratio(clean_query, product_name)
+                    if similarity >= 80:  # 80% similarity threshold
+                        logger.info(f"[Query] Fuzzy match found: '{clean_query}' -> '{product_name}' (similarity: {similarity}%)")
+                        products = get_veterinary_product_matches(product_name)
+                        if products:
+                            break
+        
         if products:
             # Check if this is a broad/category query (multiple products found)
             if len(products) > 1:
@@ -3845,47 +3972,48 @@ Format your response professionally with emojis and clear structure. Keep it con
                     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)
+                # If it's a mode of action query, provide detailed mechanism information
+                if is_mode_of_action_query:
+                    product_name = selected_product.get('Product Name', 'Unknown')
+                    composition = selected_product.get('Composition', 'Not specified')
+                    indications = selected_product.get('Indications', 'Not specified')
+                    
+                    mode_of_action_response = (
+                        f"🧪 *{product_name} - Mode of Action*\n\n"
+                        f"📋 *Composition:* {composition}\n\n"
+                        f"💊 *Mechanism:* {indications}\n\n"
+                        f"💬 *For complete product details, select an option below:*\n"
+                        f"1️⃣ Talk to Veterinary Consultant\n"
+                        f"2️⃣ Inquire About Availability\n"
+                        f"3️⃣ Back to Main Menu"
+                    )
+                    
+                    send_whatsjet_message(from_number, mode_of_action_response)
+                else:
+                    # Send product image with caption using the new function
+                    await send_product_image_with_caption(from_number, selected_product, user_context)
                 
                 # Add to conversation history
                 context_manager.add_to_history(from_number, query, f"Product inquiry for {selected_product.get('Product Name', 'Unknown')}")
             
         else:
-            # Enhanced "not found" response with veterinary suggestions
-            message = (
-                "❌ *Product Not Found*\n\n"
-                f"🔍 *We couldn't find '{query}' in our veterinary database.*\n\n"
-                "💡 *Try these alternatives:*\n"
-                "• Check spelling (e.g., 'Hydropex' not 'Hydro pex')\n"
-                "• Search by symptoms (e.g., 'respiratory', 'liver support')\n"
-                "• Search by category (e.g., 'antibiotic', 'vitamin')\n"
-                "• Search by species (e.g., 'poultry', 'livestock')\n\n"
-                "🏥 *Popular Veterinary Products:*\n"
-                "• Hydropex (Electrolyte supplement)\n"
-                "• Heposel (Liver tonic)\n"
-                "• Bromacid (Respiratory support)\n"
-                "• Tribiotic (Antibiotic)\n"
-                "• Symodex (Multivitamin)\n\n"
-                "💬 *Type 'main' to return to main menu or try another search.*"
-            )
-            
-            # Translate response if needed
+            # Generic, professional "not found" response
             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)
+                message = "❌ *سوال درست نہیں ہے*\n\n💬 *براہ کرم اپنا سوال درست کریں یا 'main' لکھ کر مین مینو پر جائیں*"
             else:
-                send_whatsjet_message(from_number, message)
+                message = "❌ *Please correct your question*\n\n💬 *Type 'main' to go to main menu*"
+            
+            send_whatsjet_message(from_number, message)
             
     except Exception as e:
         logger.error(f"Error in product inquiry: {e}")
-        # Instead of sending a generic error, return to main menu
-        welcome_msg = generate_veterinary_welcome_message(from_number, user_context)
-        send_whatsjet_message(from_number, welcome_msg)
+        # 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)
         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):