diff --git a/README.md b/README.md
index da04645..0935a23 100644
--- a/README.md
+++ b/README.md
@@ -1,9 +1,15 @@
+
+> [!NOTE]
+> 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。
+> [English](./README.en.md) · [原始项目](https://github.com/livekit/agents) · [上游 README](https://github.com/livekit/agents/blob/HEAD/README.md)
+> 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。
+
+
-Looking for the JS/TS library? Check out [AgentsJS](https://github.com/livekit/agents-js)
+在找 JS/TS 库?请查看 [AgentsJS](https://github.com/livekit/agents-js)
-## What is Agents?
+## Agents 是什么?
-The Agent Framework is designed for building realtime, programmable participants
-that run on servers. Use it to create conversational, multi-modal voice
-agents that can see, hear, and understand.
+Agent Framework 专为构建在服务器上运行的实时、可编程参与者而设计。使用它可以创建能够看、听和理解的对话式、多模态语音智能体(voice agents)。
-## Features
+## 功能特性
-- **Flexible integrations**: A comprehensive ecosystem to mix and match the right STT, LLM, TTS, and Realtime API to suit your use case.
-- **Integrated job scheduling**: Built-in task scheduling and distribution with [dispatch APIs](https://docs.livekit.io/agents/build/dispatch/) to connect end users to agents.
-- **Extensive WebRTC clients**: Build client applications using LiveKit's open-source SDK ecosystem, supporting all major platforms.
-- **Telephony integration**: Works seamlessly with LiveKit's [telephony stack](https://docs.livekit.io/sip/), allowing your agent to make calls to or receive calls from phones.
-- **Exchange data with clients**: Use [RPCs](https://docs.livekit.io/home/client/data/rpc/) and other [Data APIs](https://docs.livekit.io/home/client/data/) to seamlessly exchange data with clients.
-- **Semantic turn detection**: Uses a transformer model to detect when a user is done with their turn, helps to reduce interruptions.
-- **MCP support**: Native support for MCP. Integrate tools provided by MCP servers with one line of code.
-- **Builtin test framework**: Write tests and use judges to ensure your agent is performing as expected.
-- **Open-source**: Fully open-source, allowing you to run the entire stack on your own servers, including [LiveKit server](https://github.com/livekit/livekit), one of the most widely used WebRTC media servers.
+- **灵活的集成**:全面的生态系统,可按需混搭合适的 STT、LLM、TTS 和 Realtime API。
+- **集成的任务调度**:内置任务调度与分发,配合 [dispatch APIs](https://docs.livekit.io/agents/build/dispatch/) 将终端用户连接到智能体。
+- **丰富的 WebRTC 客户端**:使用 LiveKit 的开源 SDK 生态系统构建客户端应用,支持所有主流平台。
+- **电话集成**:与 LiveKit 的 [telephony stack](https://docs.livekit.io/sip/), 无缝配合,使智能体能够拨打或接听电话。
+- **与客户端交换数据**:使用 [RPCs](https://docs.livekit.io/home/client/data/rpc/) 及其他 [Data APIs](https://docs.livekit.io/home/client/data/) 与客户端无缝交换数据。
+- **语义化话轮检测(Semantic turn detection)**:使用 transformer 模型检测用户是否已完成当前话轮,有助于减少打断。
+- **MCP 支持**:原生支持 MCP。一行代码即可集成 MCP 服务器提供的工具。
+- **内置测试框架**:编写测试并使用评判器(judges)确保智能体按预期运行。
+- **开源**:完全开源,允许你在自己的服务器上运行整个技术栈,包括使用最广泛的 WebRTC 媒体服务器之一 [LiveKit server](https://github.com/livekit/livekit),。
-## Installation
+## 安装
-To install the core Agents library, along with plugins for popular model providers:
+安装核心 Agents 库以及常用模型提供商的插件:
```bash
pip install "livekit-agents[openai,deepgram,cartesia]"
```
-## Docs and guides
+## 文档与指南
-Documentation on the framework and how to use it can be found [here](https://docs.livekit.io/agents/)
+有关该框架及其使用方法的文档可[在此](https://docs.livekit.io/agents/) 查阅。
-### Building with AI coding agents
+### 使用 AI 编程智能体进行开发
-If you're using an AI coding assistant to build with LiveKit Agents, we recommend the following setup for the best results:
+如果你使用 AI 编程助手来基于 LiveKit Agents 进行开发,我们建议采用以下配置以获得最佳效果:
-1. **Install the [LiveKit Docs MCP server](https://docs.livekit.io/mcp)** — Gives your coding agent access to up-to-date LiveKit documentation, code search across LiveKit repositories, and working examples.
+1. **安装 [LiveKit Docs MCP server](https://docs.livekit.io/mcp)**** — 让你的编程智能体访问最新的 LiveKit 文档、跨 LiveKit 仓库的代码搜索以及可用的示例。
-2. **Install the [LiveKit Agent Skill](https://github.com/livekit/agent-skills)** — Provides your coding agent with architectural guidance and best practices for building voice AI applications, including workflow design, handoffs, tasks, and testing patterns.
+2. **安装 [LiveKit Agent Skill](https://github.com/livekit/agent-skills)**** — 为你的编程智能体提供构建语音 AI 应用的架构指导与最佳实践,包括工作流设计、交接(handoffs)、任务和测试模式。
```shell
npx skills add livekit/agent-skills --skill livekit-agents
```
-The Agent Skill works best alongside the MCP server: the skill teaches your agent *how to approach* building with LiveKit, while the MCP server provides the *current API details* to implement it correctly.
+Agent Skill 与 MCP 服务器配合使用效果最佳:Skill 教会你的智能体*如何着手*基于 LiveKit 进行开发,而 MCP 服务器提供*最新的 API 细节*以确保正确实现。
-## Core concepts
+## 核心概念
-- Agent: An LLM-based application with defined instructions.
-- AgentSession: A container for agents that manages interactions with end users.
-- entrypoint: The starting point for an interactive session, similar to a request handler in a web server.
-- AgentServer: The main process that coordinates job scheduling and launches agents for user sessions.
+- Agent:具有明确定义指令的基于 LLM 的应用。
+- AgentSession:管理智能体与终端用户交互的容器。
+- entrypoint:交互式会话的入口,类似于 Web 服务器中的请求处理器。
+- AgentServer:协调任务调度并为用户会话启动智能体的主进程。
-## Usage
+## 用法
-### Simple voice agent
+### 简单语音智能体
---
@@ -136,17 +140,17 @@ if __name__ == "__main__":
cli.run_app(server)
```
-You'll need the following environment variables for this example:
+运行此示例需要以下环境变量:
- LIVEKIT_URL
- LIVEKIT_API_KEY
- LIVEKIT_API_SECRET
-### Multi-agent handoff
+### 多智能体交接
---
-This code snippet is abbreviated. For the full example, see [multi_agent.py](examples/voice_agents/multi_agent.py)
+此代码片段为节选。完整示例请参阅 [multi_agent.py](examples/voice_agents/multi_agent.py)
```python
...
@@ -213,9 +217,9 @@ async def entrypoint(ctx: JobContext):
...
```
-### Testing
+### 测试
-Automated tests are essential for building reliable agents, especially with the non-deterministic behavior of LLMs. LiveKit Agents include native test integration to help you create dependable agents.
+自动化测试对于构建可靠的 Agent 至关重要,尤其是在 LLM(大语言模型)具有非确定性行为的情况下。LiveKit Agents 内置了测试集成,可帮助你创建稳定可靠的 Agent。
```python
@pytest.mark.asyncio
@@ -237,24 +241,24 @@ async def test_no_availability() -> None:
```
-## Examples
+## 示例
-For more examples and detailed setup instructions, see the [examples directory](examples/). For even more examples, see the [python-agents-examples](https://github.com/livekit-examples/python-agents-examples) repository.
+更多示例和详细设置说明,请参阅 [examples 目录](examples/)。如需更多示例,请参阅 [python-agents-examples](https://github.com/livekit-examples/python-agents-examples) 仓库。
🎙️ Starter Agent-A starter agent optimized for voice conversations. +针对语音对话优化的入门 Agent。 |
🔄 Multi-user push to talk-Responds to multiple users in the room via push-to-talk. +通过按键通话(push-to-talk)响应房间内多位用户。 |
🎵 Background audio-Background ambient and thinking audio to improve realism. +背景环境音和思考音效,提升真实感。 |
🛠️ Dynamic tool creation-Creating function tools dynamically. +动态创建函数工具。 |
☎️ Outbound caller-Agent that makes outbound phone calls +进行外呼电话的 Agent |
📋 Structured output-Using structured output from LLM to guide TTS tone. +使用 LLM 的结构化输出来指导 TTS 语调。 |
🔌 MCP support-Use tools from MCP servers +使用 MCP 服务器提供的工具 |
💬 Text-only agent-Skip voice altogether and use the same code for text-only integrations +完全跳过语音,使用相同代码进行纯文本集成 |
📝 Multi-user transcriber-Produce transcriptions from all users in the room +为房间内所有用户生成转录文本 |
🎥 Video avatars-Add an AI avatar with Tavus, Bithuman, LemonSlice, and more +使用 Tavus、Bithuman、LemonSlice 等添加 AI 虚拟形象 |
🍽️ Restaurant ordering and reservations-Full example of an agent that handles calls for a restaurant. +处理餐厅来电的完整 Agent 示例。 |
👁️ Gemini Live vision-Full example (including iOS app) of Gemini Live agent that can see. +具备视觉能力的 Gemini Live Agent 完整示例(含 iOS 应用)。 |