[Python] How do i use agents in langgraph workflow

tools = [check_user_promotion, get_local_data, get_kpi_info, list_all_kpis]
llm_with_tools = model.bind_tools(tools)

def reasoner(state: MessagesState):
message_history = [
msg for msg in state["messages"][:-1]
if isinstance(msg, (HumanMessage, AIMessage))
and not hasattr(msg, 'tool_calls')
and not hasattr(msg, 'tool_call_id')
]

if len(message_history) >= 4:
last_human_message = state["messages"][-1]
summary_prompt = (
"Summarize the conversation between the human and AI, "
"focusing only on the key points of their dialogue. "
"Ignore any tool interactions or technical details."
)
summary_message = model.invoke(
message_history + [HumanMessage(content=summary_prompt)]
)

delete_messages = [RemoveMessage(id=m.id) for m in state["messages"]]
human_message = HumanMessage(content=last_human_message.content)
response = llm_with_tools.invoke([sys_msg, summary_message, human_message])
message_updates = [summary_message, human_message, response] + delete_messages
else:
message_updates = llm_with_tools.invoke([sys_msg] + state["messages"])
return {"messages": message_updates}

builder = StateGraph(MessagesState)
builder.add_node("reasoner", reasoner)
builder.add_node("tools", ToolNode(tools))
builder.add_edge(START, "reasoner")
builder.add_conditional_edges("reasoner", tools_condition)
builder.add_edge("tools", "reasoner")
memory = MemorySaver()
react_graph = builder.compile(checkpointer=memory)


i am developing a chatbot, its working fine but i wanted to convert some of the tools into a separate agent, why? because it will have its own workflow, and more tools ,for example if the question is related to a 'kpi' the agent will process the output where there will be several tools + human in the loop, i have searched and looked into the documentation , its just that every section is explained separately and i am struggling to put it all to work within the current implementation with memory and routing.

So if anyone could guide me to the correct path please.

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