Apr 20
Loading video player...
One AI agent writes code. A swarm of them builds entire systems — researcher gathers data, analyst processes it, writer drafts the report, reviewer checks quality, all coordinated automatically. Swarms is the production-grade framework that orchestrates teams of AI agents into real workflows. 5,800+ stars. 10+ pre-built multi-agent architectures: sequential chains, parallel processing, hierarchical delegation, mixture-of-experts, DAG workflows, debate-and-judge, council-of-judges, group chat, dynamic routing, and custom social algorithms. Any LLM provider: OpenAI, Anthropic, Google, open-source models. Any topology you can imagine. The AgentRearrange syntax is the killer feature — define complex multi-agent workflows in one string: "researcher → analyst, writer → editor." Einsum-inspired notation for agent orchestration. Backwards compatible with LangChain, AutoGen, and CrewAI. MCP for tool integration. A2A for agent-to-agent communication. Full Agent Orchestration Protocol for production deployment with health monitoring, queue management, and distributed services. Not a toy framework — production-grade. Scaling, monitoring, observability, enterprise tool library, agent registry, and structured outputs built in. The framework you need when a single agent isn't enough. 5,800+ stars | Python | Apache 2.0 | 10+ architectures | Model-agnostic 🔗 https://github.com/kyegomez/swarms 📖 https://docs.swarms.world 🔔 Subscribe to GithubTrends for daily open-source discoveries #Shorts #Swarms #MultiAgent #AIagents #Orchestration #OpenSource #GitHubTrends #LLM #CrewAI #AutoGen #Python #AgentFramework #AIautomation #Programming