Revert "Update app.py"

This reverts commit 280f5c97a7495a1ea0075593609f2cd2f29f4554.

app.py

@@ -1,148 +1,85 @@
-import torch
-from PIL import Image
 import gradio as gr
-import spaces
-from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
-import os
-from threading import Thread
-
-
-HF_TOKEN = os.environ.get("HF_TOKEN", None)
-MODELS = "Rorical/0-roleplay"
-MODEL_NAME = MODELS.split("/")[-1]
-
-TITLE = "<h1><center>Rorical/0-roleplay</center></h1>"
 
-DESCRIPTION = f"""
-<h3>MODEL: <a href="https://hf.co/{MODELS}">{MODEL_NAME}</a></h3>
-<center>
-<p>Qwen is the large language model built by Alibaba Cloud.
-<br>
-Feel free to test without log.
-</p>
-</center>
-"""
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import TextStreamer
 
-CSS = """
-.duplicate-button {
-margin: auto !important;
-color: white !important;
-background: black !important;
-border-radius: 100vh !important;
-}
-h3 {
-text-align: center;
-}
-"""
+import spaces
 
-model = AutoModelForCausalLM.from_pretrained(
-          MODELS,
-          torch_dtype=torch.float16,
-          device_map="auto",
-        )
-tokenizer = AutoTokenizer.from_pretrained(MODELS)
+# Load model and tokenizer
+model = AutoModelForCausalLM.from_pretrained("Rorical/0-roleplay", return_dict=True, trust_remote_code=True, device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("Rorical/0-roleplay", trust_remote_code=True)
 tokenizer.chat_template = "{% for message in messages %}{{'' + ((message['role'] + '\n') if message['role'] != '' else '') + message['content'] + '' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '星野\n' }}{% endif %}"
 
+# Define the response function
 @spaces.GPU
-def stream_chat(message: str, history: list, temperature: float, max_new_tokens: int, top_p: float, top_k: int, penalty: float):
-    print(f'message is - {message}')
-    print(f'history is - {history}')
-    conversation = []
-    for prompt, answer in history:
-        conversation.extend([{"role": "user", "content": prompt}, {"role": "assistant", "content": answer}])
-    conversation.append({"role": "user", "content": message})
-
-    print(f"Conversation is -\n{conversation}")
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    # 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
     
-    input_ids = tokenizer.apply_chat_template(conversation, tokenize=False, add_generation_prompt=True)
-    inputs = tokenizer(input_ids, return_tensors="pt").to(0)
+    # Tokenize and prepare inputs
+    inputs = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt")
+    inputs = inputs.to("cuda")
     
-    streamer = TextIteratorStreamer(tokenizer, timeout=10., skip_prompt=True, skip_special_tokens=True)
-
-    generate_kwargs = dict(
-        inputs, 
-        streamer=streamer,
-        top_k=top_k,
-        top_p=top_p,
-        repetition_penalty=penalty,
-        max_new_tokens=max_new_tokens, 
-        do_sample=True, 
+    # Generate response
+    streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+    generate_ids = model.generate(
+        inputs,
+        max_length=max_tokens,
         temperature=temperature,
-        eos_token_id = [151645, 151643],
+        top_p=top_p,
+        streamer=streamer
     )
     
-    thread = Thread(target=model.generate, kwargs=generate_kwargs)
-    thread.start()
-
-    buffer = ""
-    for new_text in streamer:
-        buffer += new_text
-        yield buffer
-
-
-
-chatbot = gr.Chatbot(height=450)
-
-with gr.Blocks(css=CSS) as demo:
-    gr.HTML(TITLE)
-    gr.HTML(DESCRIPTION)
-    gr.DuplicateButton(value="Duplicate Space for private use", elem_classes="duplicate-button")
-    gr.ChatInterface(
-        fn=stream_chat,
-        chatbot=chatbot,
-        fill_height=True,
-        additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
-        additional_inputs=[
-            gr.Slider(
-                minimum=0,
-                maximum=1,
-                step=0.1,
-                value=0.8,
-                label="Temperature",
-                render=False,
-            ),
-            gr.Slider(
-                minimum=128,
-                maximum=4096,
-                step=1,
-                value=1024,
-                label="Max new tokens",
-                render=False,
-            ),
-            gr.Slider(
-                minimum=0.0,
-                maximum=1.0,
-                step=0.1,
-                value=0.8,
-                label="top_p",
-                render=False,
-            ),
-            gr.Slider(
-                minimum=1,
-                maximum=20,
-                step=1,
-                value=20,
-                label="top_k",
-                render=False,
-            ),
-            gr.Slider(
-                minimum=0.0,
-                maximum=2.0,
-                step=0.1,
-                value=1.0,
-                label="Repetition penalty",
-                render=False,
-            ),
-        ],
-        examples=[
-            ["Help me study vocabulary: write a sentence for me to fill in the blank, and I'll try to pick the correct option."],
-            ["What are 5 creative things I could do with my kids' art? I don't want to throw them away, but it's also so much clutter."],
-            ["Tell me a random fun fact about the Roman Empire."],
-            ["Show me a code snippet of a website's sticky header in CSS and JavaScript."],
-        ],
-        cache_examples=False,
-    )
-
+    # Decode the generated response
+    response = tokenizer.decode(generate_ids[0], skip_special_tokens=True)
+    response = response.replace("星野\n", "", 1)  # Remove the "星野\n" prefix if it exists
+    response = response.split("老师\n")[0]  # Split on the next possible user input
+    
+    return response, history + [(message, response)]
+
+# Default prompt for the chatbot
+prompt = """以下是小鸟游星野的介绍
+星野是阿拜多斯高中对策委员会的委员长，同时也是学生会副主席。语气懒散，经常自称为大叔，实际上是自己默默承担一切的女生。
+比起工作，她更喜欢玩。 正因为如此，她经常被委员会的其他人骂。 但是，一旦任务开始，她就会在前线勇敢地战斗以保护她的战友。
+她在阿拜多斯上高中。与星野一起在对策委员会的成员有白子，茜香，野乃美，和绫音。
+星野的年龄是17岁，生日为1月2日。
+星野有一头粉红色的头发，头巾一直长到她的腿上。 
+星野有蓝色和橙色眼睛的异色症。
+星野其实更符合认真而默默努力的类型。她实际上不相信其它的学校和大人，是对策委员会中最谨慎保守的人。当然，这并不妨碍老师和星野增进关系，成为她唯一信任的大人。
+是萝莉、有呆毛、天然萌、早熟、学生会副会长、异色瞳、慵懒。
+星野对海洋动物很感兴趣，对鱼类的知识了解得不少。她在拿到附录中包含2000多种热带鱼图鉴的书后，迫不及待地找了家店坐下来阅读。
+在众多海洋动物中，星野最喜欢的当属鲸鱼，情人节时星野还在海洋馆买了鲸鱼的巧克力作为纪念。
+星野还对寻宝有着十分浓厚的兴趣，曾和老师探索了阿拜多斯多个角落。
+星野给人一种白天睡不醒的瞌睡虫形象。"""
+
+# Create the Gradio interface
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        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"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
+)
 
 if __name__ == "__main__":
     demo.launch()