Update app.py

app.py

@@ -5,7 +5,6 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 import spaces
   
 tokenizer = AutoTokenizer.from_pretrained("Rorical/0-roleplay", trust_remote_code=True)
-tokenizer.chat_template = "{% for message in messages %}{{'<|im_start|>' + ((message['role'] + '\n') if message['role'] != '' else '') + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}"
 tokenizer.add_special_tokens({"bos_token": tokenizer.eos_token})
 tokenizer.bos_token_id = tokenizer.eos_token_id
 
@@ -14,19 +13,22 @@ tokenizer.bos_token_id = tokenizer.eos_token_id
 def respond(
     message,
     history: list[tuple[str, str]],
+    user_name,
+    bot_name,
     system_message,
     max_tokens,
     temperature,
     top_p,
 ):
     model = AutoModelForCausalLM.from_pretrained("Rorical/0-roleplay", return_dict=True, trust_remote_code=True)
-        
+    tokenizer.chat_template = "{% for message in messages %}{{'<|im_start|>' + ((message['role'] + '\n') if message['role'] != '' else '') + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>" + bot_name + "\n' }}{% endif %}" # Be careful that this model used custom chat template.
+    
     # Construct the messages for the chat
     messages = [{"role": "", "content": system_message}]
     for user_message, bot_response in history:
-        messages.append({"role": "老师", "content": user_message})  # Assuming the user is "老师"
-        messages.append({"role": "星野", "content": bot_response})  # Assuming the bot is "星野"
-    messages.append({"role": "老师", "content": message})  # Append the latest user message
+        messages.append({"role": user_name, "content": user_message})
+        messages.append({"role": bot_name, "content": bot_response})
+    messages.append({"role": user_name, "content": message})
     
     # Tokenize and prepare inputs
     inputs = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
@@ -75,7 +77,8 @@ prompt = """# 角色扮演
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox
+        gr.Textbox(value="老师", label="User name", lines=1),
+        gr.Textbox(value="星野", label="Bot name", lines=1),
         gr.Textbox(value=prompt, label="System message", lines=5),
         gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),