4c05131536
- Revised mkdocs.yml to reflect the new site name and description, enhancing clarity for users. - Added a changelog.md to document important changes and updates for the project. - Introduced a roadmap.md to outline development plans and progress for future releases. - Expanded index.md with a comprehensive overview of the platform, including core features and installation instructions. - Enhanced concepts documentation with detailed explanations of assistants, engines, and their configurations. - Updated configuration documentation to provide clear guidance on environment setup and service configurations. - Added extra JavaScript for improved user experience in the documentation site.
191 lines
3.9 KiB
Markdown
191 lines
3.9 KiB
Markdown
# 安装部署
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本章节介绍如何安装和配置 Realtime Agent Studio (RAS) 开发环境。
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---
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## 系统组件
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RAS 由三个核心服务组成：
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```mermaid
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flowchart LR
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subgraph Services["服务组件"]
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Web[Web 前端<br/>React + TypeScript]
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API[API 服务<br/>FastAPI]
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Engine[Engine 服务<br/>WebSocket]
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end
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subgraph Storage["数据存储"]
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DB[(SQLite/PostgreSQL)]
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end
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Web -->|REST| API
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Web -->|WebSocket| Engine
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API <--> DB
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Engine <--> API
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```
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| 组件 | 端口 | 说明 |
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|------|------|------|
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| **Web 前端** | 3000 | React + TypeScript 管理控制台 |
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| **API 服务** | 8080 | Python FastAPI 后端 |
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| **Engine 服务** | 8000 | 实时对话引擎（WebSocket） |
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---
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## 快速安装
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### 方式一：Docker Compose（推荐）
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最快捷的启动方式，适合快速体验和生产部署。
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```bash
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# 1. 克隆项目
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git clone https://github.com/your-org/AI-VideoAssistant.git
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cd AI-VideoAssistant
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# 2. 启动服务
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docker-compose up -d
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# 3. 访问控制台
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open http://localhost:3000
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```
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!!! tip "首次启动"
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首次启动需要构建镜像，可能需要几分钟时间。
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### 方式二：本地开发
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适合需要修改代码的开发者。
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#### 1. 克隆项目
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```bash
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git clone https://github.com/your-org/AI-VideoAssistant.git
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cd AI-VideoAssistant
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```
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#### 2. 启动 API 服务
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```bash
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cd api
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python -m venv venv
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source venv/bin/activate # Windows: venv\Scripts\activate
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pip install -r requirements.txt
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uvicorn main:app --host 0.0.0.0 --port 8080 --reload
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```
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#### 3. 启动 Engine 服务
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```bash
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cd engine
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python -m venv venv
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source venv/bin/activate
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pip install -r requirements.txt
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python main.py
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```
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#### 4. 启动 Web 前端
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```bash
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cd web
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npm install
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npm run dev
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```
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访问 `http://localhost:3000`
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---
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## 验证安装
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### 检查服务状态
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| 服务 | URL | 预期结果 |
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|------|-----|---------|
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| Web | http://localhost:3000 | 看到登录/控制台页面 |
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| API | http://localhost:8080/docs | 看到 Swagger 文档 |
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| Engine | http://localhost:8000/health | 返回 `{"status": "ok"}` |
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### 测试 WebSocket 连接
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```javascript
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const ws = new WebSocket('ws://localhost:8000/ws?assistant_id=test');
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ws.onopen = () => console.log('Connected!');
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ws.onerror = (e) => console.error('Error:', e);
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```
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---
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## 目录结构
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```
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AI-VideoAssistant/
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├── web/ # React 前端
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│ ├── src/
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│ │ ├── components/ # UI 组件
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│ │ ├── pages/ # 页面
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│ │ ├── stores/ # Zustand 状态
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│ │ └── api/ # API 客户端
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│ └── package.json
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├── api/ # FastAPI 后端
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│ ├── app/
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│ │ ├── routers/ # API 路由
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│ │ ├── models/ # 数据模型
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│ │ └── services/ # 业务逻辑
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│ └── requirements.txt
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├── engine/ # 实时交互引擎
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│ ├── app/
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│ │ ├── pipeline/ # 管线引擎
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│ │ └── multimodal/ # 多模态引擎
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│ └── requirements.txt
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├── docker/ # Docker 配置
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│ └── docker-compose.yml
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└── docs/ # 文档
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```
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---
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## 常见问题
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### 端口被占用
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```bash
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# 查看端口占用
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# Linux/Mac
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lsof -i :3000
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# Windows
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netstat -ano | findstr :3000
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```
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修改对应服务的端口配置后重启。
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### Docker 构建失败
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```bash
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# 清理 Docker 缓存
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docker system prune -a
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# 重新构建
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docker-compose build --no-cache
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```
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### Python 依赖安装失败
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确保使用 Python 3.10+：
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```bash
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python --version # 需要 3.10+
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```
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---
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## 下一步
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- [环境要求](requirements.md) - 详细的软件版本要求
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- [配置说明](configuration.md) - 环境变量配置指南
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- [快速开始](../quickstart/index.md) - 创建第一个助手
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- [Docker 部署](../deployment/docker.md) - 生产环境部署
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