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# OpenAI Agents SDK [![PyPI](https://img.shields.io/pypi/v/openai-agents?label=pypi%20package)](https://pypi.org/project/openai-agents/)
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.
<img src="https://cdn.openai.com/API/docs/images/orchestration.png" alt="Image of the Agents Tracing UI" style="max-height: 803px;">
> [!NOTE]
> Looking for the JavaScript/TypeScript version? Check out [Agents SDK JS/TS](https://github.com/openai/openai-agents-js).
### Core concepts:
1. [**Agents**](https://openai.github.io/openai-agents-python/agents): LLMs configured with instructions, tools, guardrails, and handoffs
1. [**Sandbox Agents**](https://openai.github.io/openai-agents-python/sandbox_agents): Agents preconfigured to work with a container to perform work over long time horizons.
1. **[Agents as tools](https://openai.github.io/openai-agents-python/tools/#agents-as-tools) / [Handoffs](https://openai.github.io/openai-agents-python/handoffs/)**: Delegating to other agents for specific tasks
1. [**Tools**](https://openai.github.io/openai-agents-python/tools/): Various Tools let agents take actions (functions, MCP, hosted tools)
1. [**Guardrails**](https://openai.github.io/openai-agents-python/guardrails/): Configurable safety checks for input and output validation
1. [**Human in the loop**](https://openai.github.io/openai-agents-python/human_in_the_loop/): Built-in mechanisms for involving humans across agent runs
1. [**Sessions**](https://openai.github.io/openai-agents-python/sessions/): Automatic conversation history management across agent runs
1. [**Tracing**](https://openai.github.io/openai-agents-python/tracing/): Built-in tracking of agent runs, allowing you to view, debug and optimize your workflows
1. [**Realtime Agents**](https://openai.github.io/openai-agents-python/realtime/quickstart/): Build powerful voice agents with `gpt-realtime-2.1` and full agent features
Explore the [examples](https://github.com/openai/openai-agents-python/tree/main/examples) directory to see the SDK in action, and read our [documentation](https://openai.github.io/openai-agents-python/) for more details.
## Get started
To get started, set up your Python environment (Python 3.10 or newer required), and then install OpenAI Agents SDK package.
### venv
```bash
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]'`.
### uv
If you're familiar with [uv](https://docs.astral.sh/uv/), installing the package would be even easier:
```bash
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]'`.
## Run your first agents
The SDK supports three primary ways to run agents. Set the `OPENAI_API_KEY` environment variable before running any of these examples.
### Run a sandbox agent
Use a [`SandboxAgent`](https://openai.github.io/openai-agents-python/sandbox_agents) when the agent needs to inspect files, run commands, apply patches, or preserve workspace state across longer tasks.
```python
from agents import Runner
from agents.run import RunConfig
from agents.sandbox import Manifest, SandboxAgent, SandboxRunConfig
from agents.sandbox.entries import GitRepo
from agents.sandbox.sandboxes import UnixLocalSandboxClient
agent = SandboxAgent(
name="Workspace Assistant",
instructions="Inspect the sandbox workspace before answering.",
default_manifest=Manifest(entries={"repo": GitRepo(repo="openai/openai-agents-python", ref="main")}),
)
result = Runner.run_sync(
agent,
"Inspect the repo README and summarize what this project does.",
run_config=RunConfig(sandbox=SandboxRunConfig(client=UnixLocalSandboxClient())),
)
print(result.final_output)
```
### Run a text agent
Use a text `Agent` for workflows that do not need a persistent realtime connection or a sandbox workspace.
```python
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.
```
(_For Jupyter notebook users, see [hello_world_jupyter.ipynb](https://github.com/openai/openai-agents-python/blob/main/examples/basic/hello_world_jupyter.ipynb)_)
### Run a realtime agent
Use a [`RealtimeAgent`](https://openai.github.io/openai-agents-python/realtime/quickstart/) for low-latency, server-side voice and multimodal experiences over WebSocket.
```python
import asyncio
from agents.realtime import RealtimeAgent, RealtimeRunner
async def main() -> None:
agent = RealtimeAgent(name="Assistant", instructions="You are a helpful voice assistant. Keep responses short.")
runner = RealtimeRunner(starting_agent=agent)
session = await runner.run()
async with session:
await session.send_message("Say hello in one short sentence.")
async for event in session:
if event.type == "audio":
# Forward or play event.audio.data.
pass
elif event.type == "history_added":
print(event.item)
elif event.type == "agent_end":
break
if __name__ == "__main__":
asyncio.run(main())
```
Explore the [examples](https://github.com/openai/openai-agents-python/tree/main/examples) directory to see the SDK in action, and read our [documentation](https://openai.github.io/openai-agents-python/) for more details.
## Acknowledgements
We'd like to acknowledge the excellent work of the open-source community, especially:
- [Pydantic](https://docs.pydantic.dev/latest/)
- [Requests](https://github.com/psf/requests)
- [MCP Python SDK](https://github.com/modelcontextprotocol/python-sdk)
- [Griffe](https://github.com/mkdocstrings/griffe)
This library has these optional dependencies:
- [websockets](https://github.com/python-websockets/websockets)
- [SQLAlchemy](https://github.com/sqlalchemy/sqlalchemy)
- [any-llm](https://github.com/mozilla-ai/any-llm) and [LiteLLM](https://github.com/BerriAI/litellm)
We also rely on the following tools to manage the project:
- [uv](https://github.com/astral-sh/uv) and [ruff](https://github.com/astral-sh/ruff)
- [mypy](https://github.com/python/mypy) and [Pyright](https://github.com/microsoft/pyright)
- [pytest](https://github.com/pytest-dev/pytest) and [Coverage.py](https://github.com/coveragepy/coveragepy)
- [MkDocs](https://github.com/squidfunk/mkdocs-material)
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.