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2025-08-22 13:27:08 +00:00
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docs/docs/how-tos/multi_agent.md
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@@ -183,7 +183,6 @@ You can use the @[`Send()`][Send] primitive to directly send data to the worker
from typing import Annotated
from langchain_core.tools import tool, InjectedToolCallId
from langgraph.prebuilt import InjectedState
from langgraph.graph import StateGraph, START, MessagesState
# highlight-next-line
from langgraph.types import Command, Send
@@ -1251,3 +1250,4 @@ LangGraph comes with prebuilt implementations of two of the most popular multi-a
- [supervisor](../agents/multi-agent.md#supervisor) — individual agents are coordinated by a central supervisor agent. The supervisor controls all communication flow and task delegation, making decisions about which agent to invoke based on the current context and task requirements. You can use [`langgraph-supervisor`](https://github.com/langchain-ai/langgraph-supervisor-js) library to create a supervisor multi-agent systems.
- [swarm](../agents/multi-agent.md#supervisor) — agents dynamically hand off control to one another based on their specializations. The system remembers which agent was last active, ensuring that on subsequent interactions, the conversation resumes with that agent. You can use [`langgraph-swarm`](https://github.com/langchain-ai/langgraph-swarm-js) library to create a swarm multi-agent systems.
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