Update app.py

app.py

@@ -1893,7 +1893,14 @@ async def process_incoming_message(from_number: str, msg: dict):
             await handle_general_query_with_ai(from_number, message_body, user_context, reply_language)
             return
         
-        # 🎯 PRIORITY 5: Product names - works from ANY menu state
+        # 🎯 PRIORITY 5: Check for product-specific questions (mode of action, dosage, etc.)
+        product_question_keywords = ['mode of action', 'dosage', 'administration', 'composition', 'indications', 'precautions', 'storage', 'how to use', 'side effects']
+        if any(keyword in query_lower for keyword in product_question_keywords):
+            # Use OpenAI for product-specific questions
+            await handle_general_query_with_ai(from_number, message_body, user_context, reply_language)
+            return
+        
+        # 🎯 PRIORITY 6: 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)
@@ -1988,7 +1995,7 @@ async def process_incoming_message(from_number: str, msg: dict):
             # Simple one-liner for wrong queries
             send_whatsjet_message(from_number, "❌ Please correct your question or type 'main' to go to main menu.")
             
-        # 🎯 PRIORITY 6: Default: treat as general query with intelligent product inquiry
+        # 🎯 PRIORITY 7: Default: treat as general query with intelligent product inquiry
         await handle_intelligent_product_inquiry(from_number, message_body, user_context, reply_language)
             
     except Exception as e:
@@ -2030,6 +2037,12 @@ IMPORTANT INSTRUCTIONS:
 6. Use emojis and bullet points for better readability.
 7. If you don't have specific information, say so clearly and suggest alternatives.
 
+CRITICAL NAMING RULES:
+- ALWAYS keep company name "Apex Biotical Solutions" in English, even in Urdu responses
+- ALWAYS keep product names in English (e.g., "EC-Immune", "Hydropex", "Heposel")
+- ALWAYS keep technical terms in English when possible
+- Only translate descriptive text, not proper nouns or brand names
+
 Available Products Database: {products_df.to_dict('records') if products_df is not None else 'No products loaded'}
 
 RESPONSE FORMAT:
@@ -2037,6 +2050,7 @@ RESPONSE FORMAT:
 - Use emojis sparingly but effectively
 - Avoid long titles or headers
 - Focus on providing accurate, helpful information
+- Preserve English company names and product names
 """
         response = openai.ChatCompletion.create(
             model="gpt-4o",
@@ -2047,7 +2061,21 @@ RESPONSE FORMAT:
         ai_response = response.choices[0].message.content.strip()
         if reply_language == 'ur':
             try:
+                # Get all product and category names for restoration
+                product_names = []
+                category_names = []
+                if products_df is not None and not products_df.empty:
+                    product_names = [str(p.get('Product Name', '')) for p in products_df.to_dict('records') if p.get('Product Name')]
+                    category_names = list(set([str(p.get('Category', '')) for p in products_df.to_dict('records') if p.get('Category')]))
+                
+                # Add company names to preserve in English
+                company_names = ['Apex Biotical Solutions', 'Apex Biotical', 'Apex']
+                
                 translated_response = GoogleTranslator(source='auto', target='ur').translate(ai_response)
+                
+                # Restore English terms including company names
+                translated_response = restore_english_terms(translated_response, ai_response, product_names + company_names, category_names)
+                
                 send_whatsjet_message(from_number, translated_response)
             except Exception as e:
                 logger.error(f"[AI] Translation error: {e}")
@@ -2575,9 +2603,15 @@ Response:
                 # 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')]))
+                
+                # Add company names to preserve in English
+                company_names = ['Apex Biotical Solutions', 'Apex Biotical', 'Apex']
+                
                 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)
+                
+                # Restore English terms including company names
+                translated_response = restore_english_terms(translated_response, ai_response, product_names + company_names, category_names)
+                
                 send_whatsjet_message(from_number, translated_response)
             except Exception as e:
                 logger.error(f"[AI] Translation error: {e}")
@@ -3749,29 +3783,6 @@ async def handle_intelligent_product_inquiry(from_number: str, query: str, user_
                 # The actual sending of product details should be handled by the caller
                 return selected_product
         else:
-            # Check for specific query types before falling back to generic response
-            query_lower = query.lower().strip()
-            
-            # Check for company/about queries
-            if any(keyword in query_lower for keyword in ['apex', 'company', 'about', 'who', 'what is']):
-                # Use OpenAI for company information
-                await handle_general_query_with_ai(from_number, query, user_context, reply_language)
-                return
-            
-            # Check for product-specific questions (mode of action, dosage, etc.)
-            product_question_keywords = ['mode of action', 'dosage', 'administration', 'composition', 'indications', 'precautions', 'storage', 'how to use', 'side effects']
-            if any(keyword in query_lower for keyword in product_question_keywords):
-                # Use OpenAI for product-specific questions
-                await handle_general_query_with_ai(from_number, query, user_context, reply_language)
-                return
-            
-            # Check for general veterinary questions
-            veterinary_keywords = ['weather', 'temperature', 'disease', 'symptoms', 'treatment', 'prevention', 'vaccination', 'nutrition', 'health']
-            if any(keyword in query_lower for keyword in veterinary_keywords):
-                # Simple redirect for non-veterinary topics
-                send_whatsjet_message(from_number, "❌ Please ask the correct question related to Apex Biotical Solutions or type 'main' to go to main menu.")
-                return
-            
             # Simple one-liner for wrong queries
             send_whatsjet_message(from_number, "❌ Please correct your question or type 'main' to go to main menu.")
     except Exception as e:
@@ -3812,10 +3823,34 @@ async def handle_contact_request(from_number: str):
 
 # Helper for restoring English terms in translations
 def restore_english_terms(translated_text, original_text, product_names, category_names):
-    for name in product_names + category_names:
-        if name and name.lower() in translated_text.lower() and name.lower() not in original_text.lower():
-            continue
-        translated_text = translated_text.replace(name, name)
+    """
+    Restore English terms (company names, product names, technical terms) in translated text.
+    This ensures that proper nouns and brand names remain in English even in Urdu responses.
+    """
+    # Add common technical terms that should remain in English
+    technical_terms = [
+        'EC-Immune', 'Hydropex', 'Heposel', 'Respira Aid Plus', 'Bromacid',
+        'mode of action', 'dosage', 'administration', 'composition',
+        'veterinary', 'pharmaceutical', 'supplement', 'antibiotic'
+    ]
+    
+    # Combine all terms that should remain in English
+    all_english_terms = product_names + category_names + technical_terms
+    
+    # Process each term
+    for term in all_english_terms:
+        if term and term.strip():
+            # Handle case variations
+            term_lower = term.lower()
+            translated_lower = translated_text.lower()
+            
+            # If the term exists in translated text but not in original, restore it
+            if term_lower in translated_lower:
+                # Find the actual case in the translated text and replace with original
+                import re
+                pattern = re.compile(re.escape(term), re.IGNORECASE)
+                translated_text = pattern.sub(term, translated_text)
+    
     return translated_text
 
 if __name__ == "__main__":