import jsonimport osimport time
import requestsfrom openai import OpenAI
client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))# 一个发送邮件的函数工具def send_email(quote, recipient="霍格沃兹测试开发学社@email.com"):    # Print the quote and recipient for debugging purposes    print(f"生成消息:\n {quote}\n\n发送邮件给: {recipient}")    # Return a success message    return "发送邮件给" + recipient# 工具的提示词。为了让大模型更好理解工作的作用。tools = [{    "type": "function",    "function": {        "name": "send_email",        "description": "Sends a quote via email",        "parameters": {            "type": "object",            "properties": {                "quote": {                    "type": "string",                    "description": "A generated funny quote"                }            },            "required": [                "quote"            ]        }    }}]# 1. 创建助手assistant = client.beta.assistants.create(    name="Wise Guy",    instructions="你是一位聪明的哲学家，会产生有趣的引言。",    model="gpt-3.5-turbo-1106",    tools=tools)# 2. 创建线程thread = client.beta.threads.create()# 3. 传入 prompt 并执行线程message = client.beta.threads.messages.create(    thread_id=thread.id,    role="user",    content="创建一个笑话并且使用邮件发送",)# 4. 执行消息run_res = client.beta.threads.runs.create(    thread_id=thread.id,    assistant_id=assistant.id, )# 5. 等待回复def wait_on_run(run):    while run.status == "queued" or run.status == "in_progress":        run = client.beta.threads.runs.retrieve(            thread_id=thread.id,            run_id=run.id,        )        print(f"执行的状态为:{run.status}")        time.sleep(0.5)    return run# 6. 获取回复的结果run_res = wait_on_run(run_res)# 7. 如果回复的结果需要调用工具if run_res.status == "requires_action":    # 提交工具的返回信息    tool_call = run_res.required_action.submit_tool_outputs.tool_calls[0]    name = tool_call.function.name    arguments = json.loads(tool_call.function.arguments)    print("等待返回的参数:", name)    print(f"函数参数为:{arguments}")    # 调用发送邮件工具    task = send_email(**arguments)    # 提交工具执行后的结果信息。    run = client.beta.threads.runs.submit_tool_outputs(        thread_id=thread.id,        run_id=run_res.id,        tool_outputs=[            {                "tool_call_id": tool_call.id,                "output": "done",            }        ],    )    print("==========调用 chatgpt 执行内容")    run = wait_on_run(run)    print("==========获取返回信息")    print(client.beta.threads.messages.list(thread_id=thread.id, order="asc").model_dump_json(indent=2))