Enhance Docker configuration and update dependencies for Realtime Agent Studio

- Updated Dockerfile for the API to include build tools for C++11 required for native extensions.
- Revised requirements.txt to upgrade several dependencies, including FastAPI and SQLAlchemy.
- Expanded docker-compose.yml to add MinIO service for S3-compatible storage and improved health checks for backend and engine services.
- Enhanced README.md in the Docker directory to provide detailed service descriptions and quick start instructions.
- Updated mkdocs.yml to reflect new navigation structure and added deployment overview documentation.
- Introduced new Dockerfiles for the engine and web services, including development configurations for hot reloading.

docs/content/index.md

@@ -1,4 +1,6 @@
-<h1 align="center">Realtime Agent Studio</h1>
+<p align="center">
+  <img src="images/logo.png" alt="Realtime Agent Studio" width="400">
+</p>
 
 <p align="center">
   <strong>构建实时交互音视频智能体的开源工作平台</strong>
@@ -14,7 +16,7 @@
 <p align="center">
   <a href="quickstart/index.md">快速开始</a> ·
   <a href="api-reference/index.md">API 文档</a> ·
-  <a href="deployment/index.md">部署指南</a> ·
+  <a href="getting-started/index.md">安装部署</a> ·
   <a href="roadmap.md">路线图</a>
 </p>
 
@@ -26,8 +28,6 @@ Realtime Agent Studio (RAS) 是一款以大语言模型为核心，构建实时
 
 可以将 RAS 看作 [Vapi](https://vapi.ai)、[Retell](https://retellai.com)、[ElevenLabs Agents](https://elevenlabs.io) 的**开源替代方案**。
 
-![仪表盘](images/dashboard.png)
-
 ---
 
 ## 核心特性
@@ -120,6 +120,7 @@ flowchart LR
 | **后端** | FastAPI (Python 3.10+) |
 | **引擎** | Python, WebSocket, asyncio |
 | **数据库** | SQLite / PostgreSQL |
+| **知识库** |  |
 | **部署** | Docker, Nginx |
 
 ---
@@ -144,7 +145,7 @@ flowchart LR
 
     ---
 
-    环境准备与本地开发配置
+    环境准备、本地开发与 Docker/生产部署
 
 -   :robot: **[助手管理](assistants/index.md)**
 
@@ -170,12 +171,6 @@ flowchart LR
 
     WebSocket 协议与 REST 接口文档
 
--   :cloud: **[部署指南](deployment/index.md)**
-
-    ---
-
-    Docker 与生产环境部署
-
 </div>
 
 ---
@@ -186,8 +181,10 @@ flowchart LR
 
 ```bash
 git clone https://github.com/your-org/AI-VideoAssistant.git
-cd AI-VideoAssistant
+cd docker
 docker-compose up -d
+# for development
+# docker compose --profile dev up -d
 ```
 
 访问 `http://localhost:3000` 即可使用控制台。