掌握OpenAI Assistant函数调用：正确提交工具输出的Python指南

# 错误的尝试
message = client.beta.threads.messages.create(
    thread_id=thread.id,
    role="tool", # 错误：此角色不适用于创建新消息来提交工具输出
    content=ret,
)

run = client.beta.threads.runs.submit_tool_outputs(
  thread_id=thread.id,
  run_id=run.id,
  tool_outputs=[
      {
        "tool_call_id": tool_call_id,
        "output": "your_function_output_string_here",
      },
      # 如果有多个工具调用，可以在这里添加更多字典
    ]
)

from openai import OpenAI
import time
import os
import json # 导入json库，用于处理函数参数

# 初始化OpenAI客户端
client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY")) # 建议从环境变量获取API_KEY

# 假设你已经创建并配置了一个Assistant，其ID存储在环境变量中
# 并添加了名为 'funnyfunc' 的工具
# 例如：assistant = client.beta.assistants.create(
#     name="Function Caller Assistant",
#     instructions="You are a helpful assistant that can call the funnyfunc.",
#     model="gpt-4-turbo",
#     tools=[{"type": "function", "function": {"name": "funnyfunc", "description": "Returns a funny value."}}]
# )
# 然后将 assistant.id 存储到环境变量 ALEXA_ASSISTANT_ID_OPENAI 中

assistant_id = os.environ.get("ALEXA_ASSISTANT_ID_OPENAI")
if not assistant_id:
    raise ValueError("请设置环境变量 ALEXA_ASSISTANT_ID_OPENAI 为您的Assistant ID")

# 创建一个新的线程
thread = client.beta.threads.create()

# 辅助函数：等待Run完成
def wait_on_run(run_obj, thread_obj):
    """
    等待Run对象完成执行，并返回最新的Run状态。
    """
    while run_obj.status in ["queued", "in_progress", "cancelling"]:
        time.sleep(0.5) # 适当增加等待时间以减少API调用频率
        run_obj = client.beta.threads.runs.retrieve(
            thread_id=thread_obj.id,
            run_id=run_obj.id,
        )
    return run_obj

# 模拟自定义函数
def funnyfunc():
    """一个简单的模拟函数，返回一个字符串。"""
    print("Executing funnyfunc...")
    return "The funniest number is five!"

# 核心函数：向Assistant提问并处理函数调用
def ask_question_and_handle_tools(question_content):
    """
    向Assistant提问，并处理可能的函数调用。
    """
    # 1. 向线程添加用户消息
    client.beta.threads.messages.create(
        thread_id=thread.id,
        role="user",
        content=question_content,
    )

    # 2. 创建并运行Assistant
    run = client.beta.threads.runs.create(
        thread_id=thread.id,
        assistant_id=assistant_id,
    )

    # 3. 等待Run完成或需要动作
    run = wait_on_run(run, thread)

    # 4. 循环处理 'requires_action' 状态
    while run.status == 'requires_action':
        if run.required_action.type == 'submit_tool_outputs':
            tool_outputs_to_submit = []
            for tool_call in run.required_action.submit_tool_outputs.tool_calls:
                function_name = tool_call.function.name
                tool_call_id = tool_call.id

                # 假设我们只处理 'funnyfunc'
                if function_name == 'funnyfunc':
                    # 在实际应用中，这里会解析 tool_call.function.arguments 并传递给实际函数
                    # 例如：args = json.loads(tool_call.function.arguments)
                    # result = funnyfunc(**args)
                    result = funnyfunc() # 调用模拟函数
                    tool_outputs_to_submit.append({
                        "tool_call_id": tool_call_id,
                        "output": result,
                    })
                else:
                    # 对于未实现的函数，可以返回一个错误或默认值
                    print(f"Warning: Unimplemented function called: {function_name}")
                    tool_outputs_to_submit.append({
                        "tool_call_id": tool_call_id,
                        "output": f"Error: Function '{function_name}' not implemented.",
                    })

            # 提交工具输出
            run = client.beta.threads.runs.submit_tool_outputs(
                thread_id=thread.id,
                run_id=run.id,
                tool_outputs=tool_outputs_to_submit
            )

            # 提交后，需要再次等待Run完成
            run = wait_on_run(run, thread)
        else:
            raise NotImplementedError(f"Unhandled required action type: {run.required_action.type}")

    # 5. Run完成后，获取Assistant的响应
    if run.status == 'completed':
        messages = client.beta.threads.messages.list(
            thread_id=thread.id,
            order="desc", # 获取最新消息
            limit=1 # 只获取一条
        )
        # 查找最新的Assistant消息
        for message in messages.data:
            if message.role == "assistant":
                for content_block in message.content:
                    if content_block.type == "text":
                        return content_block.text.value
        return "No assistant response found."
    else:
        return f"Run finished with status: {run.status}"

# 提问并打印结果
response = ask_question_and_handle_tools("What is funnyfunc() equal to right now?")
print("\nAssistant's final response:")
print(response)