打造垂直领域内容的问答机器人

import timefrom openai import OpenAIimport osclient = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))# 1. 绑定课程文件file = client.files.create(    file=open("课程数据.md", "rb"),    purpose='assistants')# 2. 创建课程处理机器人assistant = client.beta.assistants.create(    instructions="你是一个课程维护者，你需要清楚的知道课程名称以及其对应的url地址。",    model="gpt-4-turbo-preview",    tools=[{"type": "retrieval"}],    file_ids=[file.id])# 3. 创建一个线程thread = client.beta.threads.create()# 4. 创建一条消息message = client.beta.threads.messages.create(    thread_id=thread.id,    role="user",    content="请告诉我超时处理对应的视频地址")# 5. 提问run = client.beta.threads.runs.create(    thread_id=thread.id,    assistant_id=assistant.id,    instructions="你是一个课程维护者，你需要清楚的知道课程名称以及其对应的url地址。",)# 6. 循环查询问题是否已经解决完成def wait_on_run(run, thread):    while run.status == "queued" or run.status == "in_progress":        run = client.beta.threads.runs.retrieve(            thread_id=thread.id,            run_id=run.id,        )        time.sleep(0.5)    return runwait_on_run(run, thread)# 6. 获取历史消息messages = client.beta.threads.messages.list(thread_id=thread.id).model_dump_json(indent=2)print(messages)