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如何在异步环境中使用回调

先决条件

本指南假定您熟悉以下概念：

如果您打算使用异步 API，建议使用和扩展AsyncCallbackHandler以避免阻塞事件。

警告

如果您使用同步CallbackHandler使用异步方法运行您的 LLM / Chain / Tool / Agent 时，它仍然可以工作。但是，在后台，它将使用run_in_executor这可能会导致问题，如果您的CallbackHandler不是线程安全的。

危险

如果您在python<=3.10，您需要记住传播config或callbacks调用其他runnable从RunnableLambda,RunnableGenerator或@tool.如果您不这样做， 回调不会传播到正在调用的子 Runnables。

import asyncio
from typing import Any, Dict, List

from langchain_anthropic import ChatAnthropic
from langchain_core.callbacks import AsyncCallbackHandler, BaseCallbackHandler
from langchain_core.messages import HumanMessage
from langchain_core.outputs import LLMResult


class MyCustomSyncHandler(BaseCallbackHandler):
    def on_llm_new_token(self, token: str, **kwargs) -> None:
        print(f"Sync handler being called in a `thread_pool_executor`: token: {token}")


class MyCustomAsyncHandler(AsyncCallbackHandler):
    """Async callback handler that can be used to handle callbacks from langchain."""

    async def on_llm_start(
        self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
    ) -> None:
        """Run when chain starts running."""
        print("zzzz....")
        await asyncio.sleep(0.3)
        class_name = serialized["name"]
        print("Hi! I just woke up. Your llm is starting")

    async def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
        """Run when chain ends running."""
        print("zzzz....")
        await asyncio.sleep(0.3)
        print("Hi! I just woke up. Your llm is ending")


# To enable streaming, we pass in `streaming=True` to the ChatModel constructor
# Additionally, we pass in a list with our custom handler
chat = ChatAnthropic(
    model="claude-3-sonnet-20240229",
    max_tokens=25,
    streaming=True,
    callbacks=[MyCustomSyncHandler(), MyCustomAsyncHandler()],
)

await chat.agenerate([[HumanMessage(content="Tell me a joke")]])
zzzz....
Hi! I just woke up. Your llm is starting
Sync handler being called in a `thread_pool_executor`: token: Here
Sync handler being called in a `thread_pool_executor`: token: 's
Sync handler being called in a `thread_pool_executor`: token:  a
Sync handler being called in a `thread_pool_executor`: token:  little
Sync handler being called in a `thread_pool_executor`: token:  joke
Sync handler being called in a `thread_pool_executor`: token:  for
Sync handler being called in a `thread_pool_executor`: token:  you
Sync handler being called in a `thread_pool_executor`: token: :
Sync handler being called in a `thread_pool_executor`: token: 

Why
Sync handler being called in a `thread_pool_executor`: token:  can
Sync handler being called in a `thread_pool_executor`: token: 't
Sync handler being called in a `thread_pool_executor`: token:  a
Sync handler being called in a `thread_pool_executor`: token:  bicycle
Sync handler being called in a `thread_pool_executor`: token:  stan
Sync handler being called in a `thread_pool_executor`: token: d up
Sync handler being called in a `thread_pool_executor`: token:  by
Sync handler being called in a `thread_pool_executor`: token:  itself
Sync handler being called in a `thread_pool_executor`: token: ?
Sync handler being called in a `thread_pool_executor`: token:  Because
Sync handler being called in a `thread_pool_executor`: token:  it
Sync handler being called in a `thread_pool_executor`: token: 's
Sync handler being called in a `thread_pool_executor`: token:  two
Sync handler being called in a `thread_pool_executor`: token: -
Sync handler being called in a `thread_pool_executor`: token: tire
zzzz....
Hi! I just woke up. Your llm is ending
LLMResult(generations=[[ChatGeneration(text="Here's a little joke for you:\n\nWhy can't a bicycle stand up by itself? Because it's two-tire", message=AIMessage(content="Here's a little joke for you:\n\nWhy can't a bicycle stand up by itself? Because it's two-tire", id='run-8afc89e8-02c0-4522-8480-d96977240bd4-0'))]], llm_output={}, run=[RunInfo(run_id=UUID('8afc89e8-02c0-4522-8480-d96977240bd4'))])

后续步骤

您现在已经学习了如何创建自己的自定义回调处理程序。

接下来，查看本节中的其他操作指南，例如如何将回调附加到 runnable。