The OpenAI Agents SDK is a lightweight yet powerful framework for building multi-agent workflows. It is provider-agnostic, supporting the OpenAI Responses and Chat Completions APIs, as well as 100+ other LLMs.

1. Agents: LLMs configured with instructions, tools, guardrails, and handoffs
2. Agents as tools / Handoffs: Delegating to other agents for specific tasks
3. Tools: Various Tools let agents take actions (functions, MCP, hosted tools)
4. Guardrails: Configurable safety checks for input and output validation
5. Human in the loop: Built-in mechanisms for involving humans across agent runs
6. Sessions: Automatic conversation history management across agent runs
7. Tracing: Built-in tracking of agent runs, allowing you to view, debug and optimize your workflows
8. Realtime Agents: Build powerful voice agents with full features

Explore the examples directory to see the SDK in action, and read our documentation for more details.

To get started, set up your Python environment (Python 3.10 or newer required), and then install OpenAI Agents SDK package.

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate
pip install openai-agents

For voice support, install with the optional voice group: pip install 'openai-agents[voice]'. For Redis session support, install with the optional redis group: pip install 'openai-agents[redis]'.

If you're familiar with uv, installing the package would be even easier:

uv init
uv add openai-agents

For voice support, install with the optional voice group: uv add 'openai-agents[voice]'. For Redis session support, install with the optional redis group: uv add 'openai-agents[redis]'.

from agents import Agent, Runner

agent = Agent(name="Assistant", instructions="You are a helpful assistant")

result = Runner.run_sync(agent, "Write a haiku about recursion in programming.")
print(result.final_output)

# Code within the code,
# Functions calling themselves,
# Infinite loop's dance.

(If running this, ensure you set the OPENAI_API_KEY environment variable)

(For Jupyter notebook users, see hello_world_jupyter.ipynb)

Explore the examples directory to see the SDK in action, and read our documentation for more details.

We'd like to acknowledge the excellent work of the open-source community, especially:

• Pydantic (data validation) and PydanticAI (advanced agent framework)
• LiteLLM (unified interface for 100+ LLMs)
• MkDocs
• Griffe
• uv and ruff

We're committed to continuing to build the Agents SDK as an open source framework so others in the community can expand on our approach.