added formatted prompt to model fns

app.py

@@ -56,22 +56,22 @@ def gpt_respond(tab_name, message, chat_history, max_convo_length = 10):
     return "", chat_history
 
 def vicuna_respond(tab_name, message, chat_history):
-    # formatted_prompt = f'''Generate the output only for the assistant. Please output any <{tab_name}> in the following sentence one per line without any additional text: <{message}>'''
-    input_ids = vicuna_tokenizer.encode(message, return_tensors="pt")
+    formatted_prompt = f'''Generate the output only for the assistant. Please output any <{tab_name}> in the following sentence one per line without any additional text: <{message}>'''
+    input_ids = vicuna_tokenizer.encode(formatted_prompt, return_tensors="pt")
     output_ids = vicuna_model.generate(input_ids, max_length=50, num_beams=5, no_repeat_ngram_size=2)
     bot_message = vicuna_tokenizer.decode(output_ids[0], skip_special_tokens=True)
         
-    chat_history.append((message, bot_message))
+    chat_history.append((formatted_prompt, bot_message))
     time.sleep(2)
     return "", chat_history
 
 def llama_respond(tab_name, message, chat_history):
-    # formatted_prompt = f'''Generate the output only for the assistant. Please output any <{tab_name}> in the following sentence one per line without any additional text: <{message}>'''
-    input_ids = llama_tokenizer.encode(message, return_tensors="pt")
+    formatted_prompt = f'''Generate the output only for the assistant. Please output any <{tab_name}> in the following sentence one per line without any additional text: <{message}>'''
+    input_ids = llama_tokenizer.encode(formatted_prompt, return_tensors="pt")
     output_ids = llama_model.generate(input_ids, max_length=50, num_beams=5, no_repeat_ngram_size=2)
     bot_message = llama_tokenizer.decode(output_ids[0], skip_special_tokens=True)
         
-    chat_history.append((message, bot_message))
+    chat_history.append((formatted_prompt, bot_message))
     time.sleep(2)
     return "", chat_history