| 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( 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, | |
| model="Qwen/Qwen2.5-72B-Instruct", | |
| max_tokens=max_tokens, | |
| stream=True, | |
| temperature=temperature, | |
| top_p=top_p | |
| ): | |
| token = message.choices[0].delta.content | |
| response += token | |
| yield response | |
| example_prompts = [ | |
| ["泰语的起源?", "你是一个歌词助手"], | |
| ["你是谁开发的?", "你是一个歌词助手"], | |
| ["写一篇关于青春的五言绝句", "你是一个歌词助手"], | |
| ["你是谁?", "你是一个歌词助手"] | |
| ] | |
| 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="Qwen2.5-72B-Instruct", | |
| description="千问2.5-72B聊天机器人", | |
| additional_inputs=[ | |
| gr.Textbox(value="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=60) | |
| demo.launch(max_threads=60) |