gradio创建openai前端对接deepseek等模型流式输出markdown格式文本

环境

gradio==3.50.2
openai==1.63.1

代码

import openai
import gradio as gr#导入gradio的包
 
api_key = "sk-**a8"
api_base = "https://api.deepseek.com/v1"

import gradio as gr
import openai
from typing import List, Any, Iterator


client = openai.OpenAI(api_key=api_key,base_url=api_base)

def chat_stream(
    message: str,
    history: List[List[str]],
    temperature: float = 0.7,
    top_k: int = 40,
    system_prompt: str = "You are a helpful assistant."
) -> Iterator[Any]:
    """流式输出OpenAI响应"""
    messages = [{"role": "system", "content": system_prompt}]
    
    # 添加历史记录
    for human_msg, ai_msg in history:
        messages.append({"role": "user", "content": human_msg})
        messages.append({"role": "assistant", "content": ai_msg})
    
    # 添加当前消息
    messages.append({"role": "user", "content": message})
    
    # 调用OpenAI API进行流式输出 (新版API)
    response = client.chat.completions.create(
        model="deepseek-chat",  # 可以更换为其他模型
        messages=messages,
        temperature=temperature,
        top_p=1 - (1.0 / top_k) if top_k > 1 else 1.0,  # 转换top_k为top_p
        stream=True
    )
    
    full_response = ""
    
    for chunk in response:
        if chunk.choices and len(chunk.choices) > 0:
            content = chunk.choices[0].delta.content
            if content is not None:
                full_response += content
                yield full_response

def clear_history():
    """清除聊天历史记录"""
    return []

# 创建Gradio界面
with gr.Blocks(css="footer {visibility: hidden}") as demo:
    gr.Markdown("# OpenAI Chat Interface")
    
    with gr.Row():
        with gr.Column(scale=4):
            chatbot = gr.Chatbot(height=500, label="对话记录", render_markdown=True)
            
            with gr.Row():
                message = gr.Textbox(
                    show_label=False,
                    placeholder="在这里输入您的消息...",
                    container=False,
                    scale=9
                )
                submit = gr.Button("发送", scale=1)
        
        with gr.Column(scale=1):
            system_prompt = gr.Textbox(
                label="系统提示",
                placeholder="设置AI的角色和行为...",
                value="You are a helpful assistant."
            )
            temperature = gr.Slider(
                minimum=0.0,
                maximum=1.0,
                value=0.7,
                step=0.1,
                label="Temperature",
                info="控制生成文本的随机性（值越高越随机）"
            )
            top_k = gr.Slider(
                minimum=1,
                maximum=100,
                value=40,
                step=1,
                label="Top K",
                info="从K个最可能的下一个词中选择（值越小结果越确定）"
            )
            clear = gr.Button("清除历史记录")
    
    # 处理提交操作
    def user(user_message, history):
        if user_message == "":
            return "", history
        return "", history + [[user_message, ""]]
    
    def bot(history, temperature, top_k, system_prompt):
        if not history:
            return history
        
        user_message = history[-1][0]
        bot_response = ""
        
        for response in chat_stream(user_message, history[:-1], temperature, top_k, system_prompt):
            bot_response = response
            history[-1][1] = bot_response
            yield history
    
    message.submit(user, [message, chatbot], [message, chatbot], queue=False).then(
        bot, [chatbot, temperature, top_k, system_prompt], chatbot
    )
    submit.click(user, [message, chatbot], [message, chatbot], queue=False).then(
        bot, [chatbot, temperature, top_k, system_prompt], chatbot
    )
    clear.click(clear_history, None, chatbot)

# 启动应用
if __name__ == "__main__":
    demo.queue()
    demo.launch(debug=True)

展示