app.py

import gradio as gr
from gradio_client import Client

# 初始化 Hugging Face Space 的 Client
client = Client("Qwen/Qwen2.5-72B-Instruct")
history = []

def respond(prompt, fhistory):
    global history  

    messages = [{"role": "system", "content": "You are a helpful assistant."}]
    
    for user_text, assistant_text in history:
        messages.append({"role": "user", "content": user_text})
        messages.append({"role": "assistant", "content": assistant_text})

    messages.append({"role": "user", "content": prompt})

    result = client.predict(
        query=messages,  
        history=history, 
        system="You are a helpful assistant.",
        api_name="/model_chat"
    )

    print(result)

    response = result[1][-1][1]  # 獲取最新的 AI 回應

    history.append((prompt, response))  

    # **回傳符合 ChatInterface 格式**
    #return [{"role": "user", "content": prompt}, {"role": "assistant", "content": response}]
    return [{"role": "assistant", "content": response}]



# 設定 Gradio 的聊天界面
demo = gr.ChatInterface(
    fn=respond,
    title="Qwen2.5-72B-Instruct Demo",
    description="透過 Hugging Face Space API 與 Qwen 2.5 Max 模型互動。",
    type='messages'
)

if __name__ == "__main__":
    demo.launch()