OpenAI Swarm — AI Agent Review & Live Stats

Live GitHub stats, community sentiment, and trend data for OpenAI Swarm. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.

GitHub data synced: Mar 11, 2025 • Sentiment updated: Mar 17, 2026

GitHub Statistics

Community Sentiment

Community Buzz: The openai/swarm project has generated significant interest in the AI community, with developers actively contributing and discussing its features.

Why OpenAI Swarm Stands Out

Swarm is valuable because it provides a lightweight and controllable approach to multi-agent orchestration, making it easy to build scalable and customizable solutions. Its stateless design and focus on agent coordination enable developers to build complex systems without having to worry about state management. Additionally, Swarm's ability to chain agents and execute functions enables efficient data processing and personalized interactions. Unlike other frameworks, Swarm's educational focus and simple architecture make it an ideal choice for developers looking to learn about multi-agent systems.

Built With

Build a multi-agent customer service system — Swarm's lightweight and controllable architecture enables easy integration of multiple agents, Build an educational chatbot that teaches users about AI — Swarm's stateless design and focus on agent coordination make it ideal for educational projects, Build a scalable research agent that can handle large amounts of data — Swarm's ability to chain agents and execute functions enables efficient data processing, Build a personalized shopping assistant that can handle multiple user requests — Swarm's support for context variables and agent handoffs enables personalized interactions, Build a triage system that can route user requests to the right agent — Swarm's simple and flexible architecture makes it easy to set up and configure

Getting Started

  1. Install Swarm using pip: `pip install git+ssh://git@github.com/openai/swarm.git`
  2. Import the Swarm library: `from swarm import Swarm, Agent`
  3. Create a new Swarm client: `client = Swarm()`
  4. Define a new agent: `agent = Agent(name='My Agent', instructions='You are a helpful agent.')`
  5. Try running the client with a sample message to verify it works: `response = client.run(agent=agent, messages=[{'role': 'user', 'content': 'Hello'}])`

About

Educational framework exploring ergonomic, lightweight multi-agent orchestration. Managed by OpenAI Solution team.

Category & Tags

Category: multi-agent

Market Context

The project is part of OpenAI's efforts to advance AI research and development, with potential applications in various industries.