import openai
import gradio as gr
import time

# 设置OpenAI API密钥
openai.api_key = 'sk-proj-yhAZYjSv6CBPOuOKV0iYT3BlbkFJg5k1dOwWdh7WZxNstGIt'

# 初始化OpenAI客户端
client = openai.OpenAI(api_key=openai.api_key)

# 创建助手
assistant = client.beta.assistants.create(
    name="医疗问诊",
    instructions="You are a personal math tutor. Write and run code to answer math questions.",
    tools=[{"type": "code_interpreter"}],
    model="gpt-4o",
)

# 定义与助手进行交互的函数
def chat_with_gpt4o(input_text):
    # 创建对话线程和用户消息
    thread = client.beta.threads.create()
    message = client.beta.threads.messages.create(
        thread_id=thread.id,
        role="user",
        content=input_text
    )

    # 开始运行助手
    run = client.beta.threads.runs.create(
        thread_id=thread.id,
        assistant_id=assistant.id,
        instructions="Please address the user as Jane Doe. The user has a premium account."
    )

    # 等待助手运行完成
    while True:
        run = client.beta.threads.runs.retrieve(run.id, thread_id=thread.id)
        if run.status == 'completed':
            break
        time.sleep(1)

    # 获取对话线程中的消息
    messages = client.beta.threads.messages.list(thread_id=thread.id)

    # 提取最后一条助手消息的内容
    assistant_message = None
    for msg in messages:
        if msg.role == 'assistant':
            assistant_message = msg.content[0].text.value

    if assistant_message:
        return assistant_message
    else:
        return "未找到助手的响应。"

# 创建Gradio接口
iface = gr.Interface(
    fn=chat_with_gpt4o,
    inputs="text",
    outputs="text",
    title="GPT-4o 医疗模型",
    description="与GPT-4o进行对话并获取响应。"
)

# 启动接口
iface.launch()