Sync handler being called in a `thread_pool_executor`: token:  don
Sync handler being called in a `thread_pool_executor`: token: 't
Sync handler being called in a `thread_pool_executor`: token:  scientists
Sync handler being called in a `thread_pool_executor`: token:  trust
Sync handler being called in a `thread_pool_executor`: token:  atoms
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:  they
Sync handler being called in a `thread_pool_executor`: token:  make
Sync handler being called in a `thread_pool_executor`: token:  up
Sync handler being called in a `thread_pool_executor`: token:  everything
Sync handler being called in a `thread_pool_executor`: token: !
Sync handler being called in a `thread_pool_executor`: token: 
zzzz....
Hi! I just woke up. Your llm is ending
LLMResult(generations=[[ChatGeneration(text="Why don't scientists trust atoms?\n\nBecause they make up everything!", generation_info=None, message=AIMessage(content="Why don't scientists trust atoms?\n\nBecause they make up everything!", additional_kwargs={}))]], llm_output={'token_usage': {}, 'model_name': 'gpt-3.5-turbo'})
Using multiple handlers, passing in handlers#
In the previous examples, we passed in callback handlers upon creation of an object by using callbacks=. In this case, the callbacks will be scoped to that particular object.
rtdocs_stable/api.python.langchain.com/en/stable/modules/callbacks/getting_started.html