Switch to GPT-2 model for better API reliability

app.py

@@ -333,7 +333,7 @@ class TextilindoAI:
     def __init__(self):
         self.api_key = os.getenv('HUGGINGFAC_API_KEY_2')
         # Use available model with your API key
-        self.model = os.getenv('DEFAULT_MODEL', 'microsoft/DialoGPT-medium')
+        self.model = os.getenv('DEFAULT_MODEL', 'gpt2')
         self.system_prompt = self.load_system_prompt()
         self.data_loader = TrainingDataLoader()
         
@@ -491,11 +491,13 @@ Minimum purchase is 1 roll (67-70 yards)."""
             return self.get_fallback_response(user_message)
         
         try:
-            # Use DialoGPT conversation format with context
+            # Use appropriate conversation format
             if "dialogpt" in self.model.lower():
                 prompt = f"User: {user_message}\nAssistant:"
+            elif "gpt2" in self.model.lower():
+                prompt = f"User: {user_message}\nAssistant:"
             else:
-                # Fallback to GPT-2 format for other models
+                # Fallback format for other models
                 prompt = f"User: {user_message}\nAssistant:"
             
             logger.info(f"Using model: {self.model}")
@@ -531,8 +533,8 @@ Minimum purchase is 1 roll (67-70 yards)."""
             logger.info(f"Raw AI response: {response[:200]}...")
             
             # Clean up the response based on model type
-            if "dialogpt" in self.model.lower():
-                # Clean up DialoGPT response
+            if "dialogpt" in self.model.lower() or "gpt2" in self.model.lower():
+                # Clean up DialoGPT/GPT-2 response
                 if "Assistant:" in response:
                     assistant_response = response.split("Assistant:")[-1].strip()
                 else:
@@ -541,7 +543,7 @@ Minimum purchase is 1 roll (67-70 yards)."""
                 # Remove any remaining conversation markers
                 assistant_response = assistant_response.replace("User:", "").replace("Assistant:", "").strip()
             else:
-                # Clean up GPT-2 response
+                # Clean up other model responses
                 if "Assistant:" in response:
                     assistant_response = response.split("Assistant:")[-1].strip()
                 else: