AI Agents
openai-agents-js
OpenAI's lightweight TypeScript framework for multi-agent workflows and voice agents.
★ 3.9k starsMIT
View guide →Swarm is an open-source ai agents project by openai (openai/swarm on GitHub). It has 22,080 GitHub stars and 2,345 forks, is released under the MIT license, and was last updated on GitHub on 15 April 2026.
Swarm — OpenAI's experimental framework for lightweight multi-agent orchestration with agents and handoffs, MIT
Swarm needs Python 3.10+ and installs directly from the repository.
Create agents with instructions and tools, and let one agent's function return another agent to hand the conversation over.
Start a client, run with an agent and messages, and read the final response.
Agents and handoffs express rich multi-agent dynamics without a heavy framework to learn.
Coordination stays explicit and controllable, so agent behaviour is easy to test and debug.
Agents call Python functions directly, and returning another agent is how handoffs work.
Streaming runs and evaluation helpers come with the framework, plus worked examples.
The README install route (HTTPS form).
pip install git+https://github.com/openai/swarm.gitThe README example: agent A hands off to agent B.
from swarm import Swarm, Agent
client = Swarm()
def transfer_to_agent_b():
return agent_b
agent_a = Agent(name="Agent A", instructions="You are a helpful agent.", functions=[transfer_to_agent_b])
agent_b = Agent(name="Agent B", instructions="Only speak in Haikus.")The README run call for the handoff example.
response = client.run(agent=agent_a, messages=[{"role": "user", "content": "I want to talk to agent B."}])
print(response.messages[-1]["content"])OpenAI, as an experimental, educational multi-agent framework.
Yes — MIT licensed.
No — OpenAI labels it experimental and educational. Use it to learn and prototype multi-agent patterns, not as a supported production platform.
Agents (instructions plus tools) and handoffs (one agent returning another to take over the conversation).
pip install from GitHub on Python 3.10+, define two agents with a handoff function, and run a conversation with the client.
OpenAI's lightweight TypeScript framework for multi-agent workflows and voice agents.
A lightweight, powerful framework for multi-agent workflows
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
Enterprise-grade AI agent framework with multi-provider LLM management, secure knowledge bases and high-precision RAG, visual workflow orchestration, and mul…
The Enterprise-Grade Multi-Agent Orchestration Framework. Website: https://swarms.ai
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if Swarm is not the right fit.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Nearby AI Agents projects in the catalogue, closest in stars to Swarm — keep exploring the shelf either side of it.
Stanford's Generative Agents simulation - 25 AI characters living in a virtual town
Google's code-first toolkit for building real AI agents.
Yohei Nakajima's autonomous task agent - now a self-building agent framework in Python
A visual all-in-one platform for building, debugging, and deploying AI agents.
Open-source LLM observability: trace, evaluate and monitor apps and agents
A self-improving agent for coding workflows and long-running autonomous tasks
Free and open — grab the source, star the repo, and start creating.