Update app.py

app.py

@@ -35,8 +35,6 @@ data = {
 }
 table = pd.DataFrame.from_dict(data)
 
-step = 0
-
 def chatbot_response(user_message):
     # Generate chatbot response using the chatbot model
     #inputs = chatbot_tokenizer.encode("User: " + user_message, return_tensors="pt")
@@ -47,7 +45,10 @@ def chatbot_response(user_message):
     new_user_input_ids = chatbot_tokenizer.encode(user_message + tokenizer.eos_token, return_tensors='pt')
 
     # append the new user input tokens to the chat history
-    bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if step > 0 else new_user_input_ids
+    if bot_input_ids is None:
+        bot_input_ids = new_user_input_ids
+    else:
+        bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1)
 
     # generated a response while limiting the total chat history to 1000 tokens, 
     chat_history_ids = chatbot_model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)
@@ -55,7 +56,6 @@ def chatbot_response(user_message):
     # pretty print last ouput tokens from bot
     response = "DialoGPT: {}".format(chatbot_tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True))
 
-    step += 1
     return response
 
 def sql_response(user_query):