极简代码使用gradio openai 搭建chatbot

主要用来方便测试接口。
gr.ChatInterface() 是比 gr.Chatbot() 更高一级的封装，
如果只是需要一个纯文字聊天的窗口（见下图），完全满足需求。
如果需要更多定制化的功能，比如定义prompt，显示图片等，那么就要使用gr.Chatbot() 开发。
修改为自己的接口，只需要修改predict_stream 或者predict函数，输入参数不变，输出为返回对话结果，str格式。
ps: 花费了几个小时研究gr.Chatbot()，其实gr.ChatInterface() 一行代码就够了。
更多需求请参考：creating-a-chatbot-fast

import os
import gradio as gr
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),  # 如果您没有配置环境变量，请在此处用您的API Key进行替换
    base_url="https://dashscope.aliyuncs.com/compatible-mode/v1",  # 填写DashScope SDK的base_url
)

MODEL = "qwen-max"

#输入参数必须是 “用户输入”和“历史记录”，输出为字符串，变量名随便。
def predict_stream(message, history):
    history_openai_format = []
    for human, assistant in history:
        history_openai_format.append({"role": "user", "content": human})
        history_openai_format.append({"role": "assistant", "content": assistant})
    history_openai_format.append({"role": "user", "content": message})

    response = client.chat.completions.create(
        model=MODEL, messages=history_openai_format, temperature=1.0, stream=True
    )

    partial_message = ""
    for chunk in response:
        if chunk.choices[0].delta.content is not None:
            partial_message = partial_message + chunk.choices[0].delta.content
            yield partial_message


def predict(message, history):
    history_openai_format = []
    for human, assistant in history:
        history_openai_format.append({"role": "user", "content": human})
        history_openai_format.append({"role": "assistant", "content": assistant})
    history_openai_format.append({"role": "user", "content": message})

    response = client.chat.completions.create(
        model=MODEL, messages=history_openai_format, temperature=1.0, stream=False
    )
    return response.choices[0].message.content


gr.ChatInterface(predict).launch(server_name="127.0.0.1", server_port=8000, inbrowser=True)