How to attach callbacks to a runnable
Prerequisites
This guide assumes familiarity with the following concepts:
If you are composing a chain of runnables and want to reuse callbacks across multiple executions, you can attach callbacks with the.with_config() method. This saves you the need to pass callbacks in each time you invoke the chain.
important
with_config() binds a configuration which will be interpreted asruntime configuration. So these callbacks will propagate to all child components.
Here's an example:
from typingimport Any, Dict, List
from langchain_anthropicimport ChatAnthropic
from langchain_core.callbacksimport BaseCallbackHandler
from langchain_core.messagesimport BaseMessage
from langchain_core.outputsimport LLMResult
from langchain_core.promptsimport ChatPromptTemplate
classLoggingHandler(BaseCallbackHandler):
defon_chat_model_start(
self, serialized: Dict[str, Any], messages: List[List[BaseMessage]],**kwargs
)->None:
print("Chat model started")
defon_llm_end(self, response: LLMResult,**kwargs)->None:
print(f"Chat model ended, response:{response}")
defon_chain_start(
self, serialized: Dict[str, Any], inputs: Dict[str, Any],**kwargs
)->None:
print(f"Chain{serialized.get('name')} started")
defon_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"})
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')
The bound callbacks will run for all nested module runs.
Next steps
You've now learned how to attach callbacks to a chain.
Next, check out the other how-to guides in this section, such as how topass callbacks in at runtime.