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<!-- WEHUB_ZH_README -->
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> [!NOTE]
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> 本文档由 WeHub 基于上游 README 翻译整理,属于社区翻译,非官方中文文档。
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> [English](./README.en.md) · [原始项目](https://github.com/openai/openai-agents-python) · [上游 README](https://github.com/openai/openai-agents-python/blob/HEAD/README.md)
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> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
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# OpenAI Agents SDK [](https://pypi.org/project/openai-agents/)
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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.
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OpenAI Agents SDK 是一款轻量而强大的框架,用于构建多智能体工作流。它与提供商无关(provider-agnostic),支持 OpenAI Responses 和 Chat Completions API,以及 100 多种其他 LLM。
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<img src="https://cdn.openai.com/API/docs/images/orchestration.png" alt="Image of the Agents Tracing UI" style="max-height: 803px;">
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<img src="https://cdn.openai.com/API/docs/images/orchestration.png" alt="Agents Tracing UI 图像" style="max-height: 803px;">
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> [!NOTE]
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> Looking for the JavaScript/TypeScript version? Check out [Agents SDK JS/TS](https://github.com/openai/openai-agents-js).
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> 在找 JavaScript/TypeScript 版本?请查看 [Agents SDK JS/TS](https://github.com/openai/openai-agents-js).
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### Core concepts:
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### 核心概念:
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1. [**Agents**](https://openai.github.io/openai-agents-python/agents): LLMs configured with instructions, tools, guardrails, and handoffs
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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.
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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
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1. [**Tools**](https://openai.github.io/openai-agents-python/tools/): Various Tools let agents take actions (functions, MCP, hosted tools)
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1. [**Guardrails**](https://openai.github.io/openai-agents-python/guardrails/): Configurable safety checks for input and output validation
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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
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1. [**Sessions**](https://openai.github.io/openai-agents-python/sessions/): Automatic conversation history management across agent runs
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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
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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
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1. [**Agents**](https://openai.github.io/openai-agents-python/agents): 配置了指令、工具、防护栏(guardrails)和交接(handoffs)的 LLM
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1. [**Sandbox Agents**](https://openai.github.io/openai-agents-python/sandbox_agents): 预配置为与容器协同工作的智能体,可在较长的时间跨度内执行任务。
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1. **[Agents as tools](https://openai.github.io/openai-agents-python/tools/#agents-as-tools) / [Handoffs](https://openai.github.io/openai-agents-python/handoffs/)**: 将特定任务委派给其他智能体
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1. [**Tools**](https://openai.github.io/openai-agents-python/tools/): 多种工具使智能体能够执行操作(函数、MCP、托管工具)
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1. [**Guardrails**](https://openai.github.io/openai-agents-python/guardrails/): 可配置的安全检查,用于输入和输出验证
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1. [**Human in the loop**](https://openai.github.io/openai-agents-python/human_in_the_loop/): 内置机制,可在智能体运行过程中引入人工参与
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1. [**Sessions**](https://openai.github.io/openai-agents-python/sessions/): 跨智能体运行自动管理对话历史
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1. [**Tracing**](https://openai.github.io/openai-agents-python/tracing/): 内置智能体运行追踪,便于查看、调试和优化工作流
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1. [**Realtime Agents**](https://openai.github.io/openai-agents-python/realtime/quickstart/): 使用 `gpt-realtime-2.1` 构建功能完备的强大语音智能体
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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.
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浏览 [examples](https://github.com/openai/openai-agents-python/tree/main/examples) 目录查看 SDK 的实际用法,并阅读我们的 [documentation](https://openai.github.io/openai-agents-python/) 了解更多详情。
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## Get started
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## 快速开始
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To get started, set up your Python environment (Python 3.10 or newer required), and then install OpenAI Agents SDK package.
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开始前,请先配置 Python 环境(需要 Python 3.10 或更高版本),然后安装 OpenAI Agents SDK 包。
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### venv
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pip install openai-agents
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```
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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]'`.
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如需语音支持,请使用可选的 `voice` 依赖组安装:`pip install 'openai-agents[voice]'`。如需 Redis 会话支持,请使用可选的 `redis` 依赖组安装:`pip install 'openai-agents[redis]'`。
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### uv
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If you're familiar with [uv](https://docs.astral.sh/uv/), installing the package would be even easier:
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如果你熟悉 [uv](https://docs.astral.sh/uv/), 安装该包会更加简便:
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```bash
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uv init
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uv add openai-agents
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```
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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]'`.
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如需语音支持,请使用可选的 `voice` 依赖组安装:`uv add 'openai-agents[voice]'`。如需 Redis 会话支持,请使用可选的 `redis` 依赖组安装:`uv add 'openai-agents[redis]'`。
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## Run your first agents
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## 运行你的第一个智能体
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The SDK supports three primary ways to run agents. Set the `OPENAI_API_KEY` environment variable before running any of these examples.
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SDK 支持三种主要方式来运行智能体。在运行以下任一示例之前,请设置 `OPENAI_API_KEY` 环境变量。
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### Run a sandbox agent
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### 运行沙盒智能体
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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.
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当智能体需要检查文件、运行命令、应用补丁,或在较长任务中保持工作区状态时,请使用 [`SandboxAgent`](https://openai.github.io/openai-agents-python/sandbox_agents)。
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```python
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from agents import Runner
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print(result.final_output)
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```
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### Run a text agent
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### 运行文本智能体
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Use a text `Agent` for workflows that do not need a persistent realtime connection or a sandbox workspace.
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对于不需要持久实时连接或沙盒工作区的工作流,请使用文本 `Agent`。
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```python
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from agents import Agent, Runner
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# Infinite loop's dance.
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```
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(_For Jupyter notebook users, see [hello_world_jupyter.ipynb](https://github.com/openai/openai-agents-python/blob/main/examples/basic/hello_world_jupyter.ipynb)_)
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(_Jupyter notebook 用户请参阅 [hello_world_jupyter.ipynb](https://github.com/openai/openai-agents-python/blob/main/examples/basic/hello_world_jupyter.ipynb)_)
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### Run a realtime agent
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### 运行实时智能体
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Use a [`RealtimeAgent`](https://openai.github.io/openai-agents-python/realtime/quickstart/) for low-latency, server-side voice and multimodal experiences over WebSocket.
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通过 WebSocket 实现低延迟、服务端语音与多模态体验时,请使用 [`RealtimeAgent`](https://openai.github.io/openai-agents-python/realtime/quickstart/)。
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```python
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import asyncio
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asyncio.run(main())
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```
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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.
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浏览 [examples](https://github.com/openai/openai-agents-python/tree/main/examples) 目录查看 SDK 的实际用法,并阅读我们的 [documentation](https://openai.github.io/openai-agents-python/) 了解更多详情。
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## Acknowledgements
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## 致谢
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We'd like to acknowledge the excellent work of the open-source community, especially:
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我们要感谢开源社区的杰出贡献,尤其是:
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- [Pydantic](https://docs.pydantic.dev/latest/)
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- [Requests](https://github.com/psf/requests)
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- [MCP Python SDK](https://github.com/modelcontextprotocol/python-sdk)
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- [Griffe](https://github.com/mkdocstrings/griffe)
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This library has these optional dependencies:
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本库包含以下可选依赖:
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- [websockets](https://github.com/python-websockets/websockets)
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- [SQLAlchemy](https://github.com/sqlalchemy/sqlalchemy)
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- [any-llm](https://github.com/mozilla-ai/any-llm) and [LiteLLM](https://github.com/BerriAI/litellm)
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We also rely on the following tools to manage the project:
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我们还依赖以下工具来管理项目:
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- [uv](https://github.com/astral-sh/uv) and [ruff](https://github.com/astral-sh/ruff)
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- [mypy](https://github.com/python/mypy) and [Pyright](https://github.com/microsoft/pyright)
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- [pytest](https://github.com/pytest-dev/pytest) and [Coverage.py](https://github.com/coveragepy/coveragepy)
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- [MkDocs](https://github.com/squidfunk/mkdocs-material)
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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.
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我们致力于持续将 Agents SDK 构建为开源框架,以便社区中的其他人能够在我们的方法基础上进行扩展。
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