The OpenAI Agents SDK is a lightweight, production-oriented Python library for building agentic applications with handoffs, guardrails, sessions and tracing.
Evolved from OpenAI’s experimental Swarm, the Agents SDK keeps the core abstractions deliberately small: Agents, Tools, Handoffs, Sessions and Guardrails. This minimal surface makes it easy to reason about agent behavior while still supporting multi-agent systems where specialized agents hand work to each other.
The SDK integrates tightly with OpenAI models and the Responses API, includes built-in tracing for debugging runs, and works with any model that speaks the Chat Completions protocol. Streaming, structured outputs and human approval flows are supported, making it suitable for shipping agents rather than just prototyping them. Sessions keep conversation state without forcing you to design your own storage layer.
The Agents SDK is open source and free to use. You pay only for model usage through your API account, and the tracing dashboard has a free allowance with paid tiers for teams needing larger retention and collaboration features. Enterprise agreements can bundle model usage with hosted tooling at negotiated rates.
The SDK is aimed at Python developers who want to ship agentic products with OpenAI models and minimal framework overhead. It suits teams building support agents, coding assistants and workflow automations that need production reliability without a heavyweight orchestration layer.
Yes, the library is free and open source. Costs come from model inference, and OpenAI provides free usage credits for new accounts that are plenty for development.
The SDK runs inside your application, so you expose your own API endpoints around your agents. Tracing and evaluation features are hosted and accessible from the OpenAI dashboard.
The Agents SDK is intentionally smaller than LangGraph or AutoGen, favoring a few composable primitives over rich abstractions. Developers who want deep control of graph execution may prefer LangGraph; those who want to move fast on OpenAI models find the SDK refreshingly simple. For OpenAI-centric stacks it is the shortest path to production, while heavy custom control flows may still prefer a lower-level framework.