Update model.py

model.py

@@ -57,18 +57,35 @@ tokenizer = transformers.AutoTokenizer.from_pretrained(
 
 
 
+# def get_prompt(message: str, chat_history: list[tuple[str, str]], system_prompt: str) -> str:
+#     texts = [f'{system_prompt}\n']
+
+#     for user_input, response in chat_history[:-1]:
+#         texts.append(f'{user_input} {response}\n')
+
+#     # Getting the user input and response from the last tuple in the chat history
+#     last_user_input, last_response = chat_history[-1]
+#     texts.append(f' input: {last_user_input} {last_response} {message} response: ')
+
+#     return ''.join(texts)
+
 def get_prompt(message: str, chat_history: list[tuple[str, str]], system_prompt: str) -> str:
     texts = [f'{system_prompt}\n']
 
-    for user_input, response in chat_history[:-1]:
-        texts.append(f'{user_input} {response}\n')
+    # If chat_history is not empty, process all but the last entry
+    if chat_history:
+        for user_input, response in chat_history[:-1]:
+            texts.append(f'{user_input} {response}\n')
 
-    # Getting the user input and response from the last tuple in the chat history
-    last_user_input, last_response = chat_history[-1]
-    texts.append(f' input: {last_user_input} {last_response} {message} response: ')
+        # Getting the user input and response from the last tuple in the chat history
+        last_user_input, last_response = chat_history[-1]
+        texts.append(f' input: {last_user_input} {last_response} {message} Response: ')
+    else:
+        # If chat_history is empty, just add the message with 'Response:' at the end
+        texts.append(f' input: {message} Response: ')
 
     return ''.join(texts)
-    
+
 
 def get_input_token_length(message: str, chat_history: list[tuple[str, str]], system_prompt: str) -> int:
     prompt = get_prompt(message, chat_history, system_prompt)