The OpenAI Agents SDK is a Python package for building agentic applications with very few abstractions. It is the production-ready successor to the earlier experimental project Swarm and rests on a small set of primitives: agents, which are language models equipped with instructions and tools, handoffs that let one agent delegate to another, and guardrails that validate inputs and outputs. A built-in loop keeps an agent working until its task is complete. Installation is a single pip command, and built-in tracing lets developers visualize and debug each run.
It targets Python developers and engineering teams who want a managed runtime for multi-step agents without learning a heavy framework. Backend engineers can wrap existing functions as tools with automatic schema generation, while teams building voice products can use the realtime and voice agent modules. Developers who prefer to own the loop can call the Responses API directly, and the documentation spells out when each approach fits. Platform teams concerned with safety can run guardrails in parallel and fail fast, and those needing audit trails can rely on tracing.
Typical projects include a triage agent that hands conversations to specialist agents, a research workflow that calls tools and returns a structured result, and a voice assistant that chains speech-to-text, an agent and text-to-speech. Sandbox agents run work inside isolated workspaces with resumable sessions, which suits tasks that produce files or run code. Sessions provide persistent memory backed by stores such as SQLite, Redis, MongoDB or SQLAlchemy, and human-in-the-loop controls pause runs for approval. Remote MCP servers can expose extra tools alongside Python function tools, and traces feed evaluation, fine-tuning and distillation work.
