Update app.py

app.py

@@ -12,17 +12,14 @@ tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-7B-Chat", trust_remote_code
 model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-7B-Chat", device_map="auto", trust_remote_code=True).eval()
 model.generation_config = GenerationConfig.from_pretrained("Qwen/Qwen-7B-Chat", trust_remote_code=True) # Different generation length, top_p and other related super parameters can be specified.
 
-
 def predict(input, history=[]):
-    # tokenize the new input sentence
-    new_user_input_ids = tokenizer.encode(
+    # Check if input is not None and eos_token is not None
     if input is not None and tokenizer.eos_token is not None:
         combined_input = input + tokenizer.eos_token
         # Rest of your code using combined_input
     else:
         # Handle the case where input or tokenizer.eos_token is None
-    print("Input or eos_token is None. Cannot concatenate.")
-    )
+        print("Input or eos_token is None. Cannot concatenate.")
 
     # append the new user input tokens to the chat history
     bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)