如何將回呼函數附加到可執行物件

先決條件

本指南假設您熟悉以下概念

• 回呼函數
• 自訂回呼處理器
• 鏈接可執行物件
• 將執行階段參數附加到可執行物件

如果您要組合可執行物件鏈，並希望在多次執行中重複使用回呼函數，您可以使用 .with_config() 方法附加回呼函數。這樣可以省去每次調用鏈時都傳遞回呼函數的麻煩。

重要事項

with_config() 綁定一個配置，該配置將被解釋為執行階段配置。因此，這些回呼函數將傳播到所有子組件。

以下是一個範例

from typing import Any, Dict, List

from langchain_anthropic import ChatAnthropic
from langchain_core.callbacks import BaseCallbackHandler
from langchain_core.messages import BaseMessage
from langchain_core.outputs import LLMResult
from langchain_core.prompts import ChatPromptTemplate


class LoggingHandler(BaseCallbackHandler):
    def on_chat_model_start(
        self, serialized: Dict[str, Any], messages: List[List[BaseMessage]], **kwargs
    ) -> None:
        print("Chat model started")

    def on_llm_end(self, response: LLMResult, **kwargs) -> None:
        print(f"Chat model ended, response: {response}")

    def on_chain_start(
        self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs
    ) -> None:
        print(f"Chain {serialized.get('name')} started")

    def on_chain_end(self, outputs: Dict[str, Any], **kwargs) -> None:
        print(f"Chain ended, outputs: {outputs}")


callbacks = [LoggingHandler()]
llm = ChatAnthropic(model="claude-3-sonnet-20240229")
prompt = ChatPromptTemplate.from_template("What is 1 + {number}?")

chain = prompt | llm

chain_with_callbacks = chain.with_config(callbacks=callbacks)

chain_with_callbacks.invoke({"number": "2"})

API 參考：ChatAnthropic | BaseCallbackHandler | BaseMessage | LLMResult | ChatPromptTemplate

Chain RunnableSequence started
Chain ChatPromptTemplate started
Chain ended, outputs: messages=[HumanMessage(content='What is 1 + 2?')]
Chat model started
Chat model ended, response: generations=[[ChatGeneration(text='1 + 2 = 3', message=AIMessage(content='1 + 2 = 3', response_metadata={'id': 'msg_01NTYMsH9YxkoWsiPYs4Lemn', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}}, id='run-d6bcfd72-9c94-466d-bac0-f39e456ad6e3-0'))]] llm_output={'id': 'msg_01NTYMsH9YxkoWsiPYs4Lemn', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}} run=None
Chain ended, outputs: content='1 + 2 = 3' response_metadata={'id': 'msg_01NTYMsH9YxkoWsiPYs4Lemn', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}} id='run-d6bcfd72-9c94-466d-bac0-f39e456ad6e3-0'

AIMessage(content='1 + 2 = 3', response_metadata={'id': 'msg_01NTYMsH9YxkoWsiPYs4Lemn', 'model': 'claude-3-sonnet-20240229', 'stop_reason': 'end_turn', 'stop_sequence': None, 'usage': {'input_tokens': 16, 'output_tokens': 13}}, id='run-d6bcfd72-9c94-466d-bac0-f39e456ad6e3-0')

綁定的回呼函數將為所有巢狀模組執行運行。

後續步驟

您現在已了解如何將回呼函數附加到鏈。

接下來，查看本節中的其他操作指南，例如如何在執行階段傳遞回呼函數。