Langgraph Swarm Py

🤖 LangGraph Multi-Agent Swarm

A Python library for creating swarm-style multi-agent systems using [LangGraph](https://github.com/langchain-ai/langgraph). A swarm is a type of [multi-agent](https://langchain-ai.github.io/langgraph/concepts/multi_agent) architecture where 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.


Features

• 🤖 Multi-agent collaboration - Enable specialized agents to work together and hand off context to each other
• 🛠️ Customizable handoff tools - Built-in tools for communication between agents

This library is built on top of [LangGraph](https://github.com/langchain-ai/langgraph), a powerful framework for building agent applications, and comes with out-of-box support for [streaming](https://langchain-ai.github.io/langgraph/how-tos/#streaming), [short-term and long-term memory](https://langchain-ai.github.io/langgraph/concepts/memory/) and [human-in-the-loop](https://langchain-ai.github.io/langgraph/concepts/human_in_the_loop/)

Installation

pip install langgraph-swarm

Quickstart

pip install langgraph-swarm langchain-openai

export OPENAI_API_KEY=

from langchain_openai import ChatOpenAI

from langgraph.checkpoint.memory import InMemorySaver
from langchain.agents import create_agent
from langgraph_swarm import create_handoff_tool, create_swarm

model = ChatOpenAI(model="gpt-4o")

def add(a: int, b: int) -> int:
    """Add two numbers"""
    return a + b

alice = create_agent(
    model,
    tools=[
        add,
        create_handoff_tool(
            agent_name="Bob",
            description="Transfer to Bob",
        ),
    ],
    system_prompt="You are Alice, an addition expert.",
    name="Alice",
)

bob = create_agent(
    model,
    tools=[
        create_handoff_tool(