Bug: `AgentExecutor` doesn't use its local callbacks during planning about langchain

[jamesbraza]

Here is a workaround:

from typing import cast
from unittest.mock import patch

from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.callbacks import BaseCallbackHandler, BaseCallbackManager, Callbacks

orig_plan = OpenAIFunctionsAgent.plan

...

def plan_with_injected_callbacks(
    self,
    intermediate_steps: list[tuple[AgentAction, str]],
    callbacks: Callbacks = None,
    **kwargs
) -> AgentAction | AgentFinish:
    if self == agent_instance.agent:
        # Work around https://github.com/langchain-ai/langchain/issues/22703
        for callback in cast(list[BaseCallbackHandler], agent_instance.callbacks):
            cast(BaseCallbackManager, callbacks).add_handler(callback, inherit=False)
    return orig_plan(self, intermediate_steps, callbacks, **kwargs)


# NOTE: intentionally, I am not specifying the callback to invoke, as that
# would make the cost_callback be considered "inheritable" (which I don't want)
with patch.object(OpenAIFunctionsAgent, "plan", plan_with_injected_callbacks):
    outputs = agent_instance.invoke(
        input={"input": "Sleep a few times for 100-ms."},
        # config=RunnableConfig(callbacks=[cost_callback]),  # "Inheritable" callbacks
    )