app.py

import gradio as gr
from huggingface_hub import InferenceClient
import os

api_key = os.environ.get('qwen_API_KEY')
"""
For more information on huggingface_hub Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
client = InferenceClient("Qwen/Qwen2.5-72B-Instruct", token=api_key)

def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p
):
    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

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

    response = ""

    for message in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p
    ):
        token = message.choices[0].delta.content

        response += token
        yield response
    
example_prompts = [
    ["How to cook Kung Pao chicken the tastiest?", ""],
    ["你是谁开发的？", ""],
    ["写一篇关于青春的五言绝句", ""],
    ["你是谁?", ""]
]
latex_delimiters = [
    {"left": "$$", "right": "$$", "display": True},
    {"left": "\\[", "right": "\\]", "display": True},
    {"left": "$", "right": "$", "display": False},
    {"left": "\\(", "right": "\\)", "display": False}
]

demo = gr.ChatInterface(
    fn=respond,
    examples=example_prompts,
    cache_examples=False,
    title="千问2.5-72B",
    description="千问2.5-72B聊天机器人",
    additional_inputs=[
        gr.Textbox(value="You are Qwen, created by Alibaba Cloud. You are a helpful assistant.", label="System message"),
        gr.Slider(minimum=1, maximum=8888, value=2048, 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)"),
    ],
    chatbot=gr.Chatbot(show_label=True, latex_delimiters=latex_delimiters, show_copy_button=True)
)

if __name__ == "__main__":
    demo.queue(default_concurrency_limit=40)
    demo.launch(max_threads=40)