docs: add quick start guide for Alibaba Cloud Function Compute DevPod

Signed-off-by: 117503445 <t117503445@gmail.com>

Author: 117503445

README.md

@@ -80,6 +80,7 @@ Leveraging a multi-role distributed architecture with Ray for flexible resource
 [Converting MCoreAdapter Models to Hugging Face Format](https://alibaba.github.io/ROLL/docs/User%20Guides/Advanced%20Features/megatron_convert_2_hf)  
 [Quick Start: Single-Node Deployment Guide](https://alibaba.github.io/ROLL/docs/Getting%20Started/Quick%20Start/single_node_quick_start)  
 [Quick Start: Multi-Node Deployment Guide](https://alibaba.github.io/ROLL/docs/Getting%20Started/Quick%20Start/multi_nodes_quick_start)  
+[Quick Start: Using Alibaba Cloud Function Compute DevPod for Rapid Development](https://alibaba.github.io/ROLL/docs/Getting%20Started/Quick%20Start/aliyun_serverless_devpod_quick_start)
 [Frequently Asked Questions](https://alibaba.github.io/ROLL/docs/Getting%20Started/FAQ/qa_issues)
 
 ### UserGuide

docs_roll/docs/Getting Started/Quick Start/aliyun_serverless_devpod_quick_start.md

@@ -0,0 +1,47 @@
+# Quick Start: Alibaba Cloud Function Compute DevPod for Rapid Development
+
+> DevPod is a rapid development environment provided by Alibaba Cloud Function Compute that can help you quickly deploy and run the ROLL project.
+
+## Prerequisites
+
+Before you begin, ensure you have completed the following preparations:
+
+- You have an Alibaba Cloud account.
+- You are logged into the [Function Compute FunModel Console](https://fcnext.console.aliyun.com/fun-model).
+- Complete the required RAM role authorization and configuration as guided by the console.
+
+## Create a Training DevPod Environment
+
+1.  Click **Create Model - Custom Development**.
+2.  Select **Custom Environment** and configure as follows:
+    *   **Container Image**: Choose a non-public custom image - Container Image Address - `roll-registry.cn-hangzhou.cr.aliyuncs.com/roll/pytorch:nvcr-24.05-py3-torch260-vllm084`
+    *   **Model Name**: Enter a name, e.g., `roll-dev`
+    *   **Model Source**: Select `No Model`
+    *   **Startup Command**: Keep the default, no modification needed
+    *   **Instance Specification**: Select `GPU Performance Type`
+    *   Click the **DevPod Development & Debugging** button (**Note**: Do *not* click "Create Model Service")
+3.  Wait for deployment to complete (typically 1–2 minutes).
+
+## Configure and Test
+
+### Download the ROLL Project and Install Dependencies
+
+```bash
+# /mnt/ModelName is the default NAS mount point; replace 'roll-dev' with your actual model name
+cd /mnt/roll-dev
+
+# 1. Clone the project code
+git clone https://github.com/alibaba/ROLL.git  
+
+# 2. Install project dependencies
+cd ROLL
+pip install -r requirements_torch260_vllm.txt -i https://mirrors.aliyun.com/pypi/simple/  
+```
+
+### Run a Pipeline Example
+
+```bash
+bash examples/agentic_demo/run_agentic_pipeline_frozen_lake_single_node_demo.sh
+```
+
+For more DevPod usage guidelines, see [https://fun-model-docs.devsapp.net/user-guide/devpod/](https://fun-model-docs.devsapp.net/user-guide/devpod/)

docs_roll/docs/Overview.mdx

@@ -46,6 +46,7 @@ Leveraging a multi-role distributed architecture with Ray for flexible resource
 [Installation](https://alibaba.github.io/ROLL/docs/Getting%20Started/Installation/)  
 [Quick Start: Single-Node Deployment Guide](https://alibaba.github.io/ROLL/docs/Getting%20Started/Quick%20Start/single_node_quick_start)  
 [Quick Start: Multi-Node Deployment Guide](https://alibaba.github.io/ROLL/docs/Getting%20Started/Quick%20Start/multi_nodes_quick_start)  
+[Quick Start: Alibaba Cloud Function Compute DevPod for Rapid Development](https://alibaba.github.io/ROLL/docs/Getting%20Started/Quick%20Start/aliyun_serverless_devpod_quick_start)  
 [Debugging Guide](https://alibaba.github.io/ROLL/docs/Getting%20Started/Debugging%20Guide/debug_guide)  
 [Frequently Asked Questions](https://alibaba.github.io/ROLL/docs/Getting%20Started/FAQ/qa_issues)
 

docs_roll/i18n/zh-Hans/docusaurus-plugin-content-docs/current/Getting Started/Quick Start/aliyun_serverless_devpod_quick_start.md

@@ -0,0 +1,47 @@
+# 快速上手：使用阿里云函数计算 DevPod 进行快速开发
+
+> DevPod 是阿里云函数计算提供的一种快速开发环境，可以帮助您快速部署和运行 ROLL 项目。
+
+## 先决条件
+
+在开始之前，请确保您已完成以下准备工作：
+
+- 拥有一个阿里云账号
+- 登录 [函数计算 FunModel 控制台](https://fcnext.console.aliyun.com/fun-model)
+- 根据控制台指引，完成 RAM 相关的角色授权等配置
+
+## 创建训练 DevPod 环境
+
+1.  点击 **创建模型 - 自定义开发**。
+2.  选择 **自定义环境**，并按如下配置：
+    *   **容器镜像**：选择不可公开访问的自定义镜像 - 容器镜像地址 - `roll-registry.cn-hangzhou.cr.aliyuncs.com/roll/pytorch:nvcr-24.05-py3-torch260-vllm084`
+    *   **模型名称**：输入一个名称，例如 `roll-dev`
+    *   **模型来源**：选中 `无模型`
+    *   **启动命令**：保持默认，无需修改
+    *   **实例规格**：选择 `GPU性能型`
+    *   点击 **DevPod开发调试** 按钮（**注意**：不要点击"创建模型服务"）
+3.  等待部署成功（通常 1–2 分钟）。
+
+## 配置和测试
+
+### 下载 ROLL 项目并安装依赖
+
+```bash
+# /mnt/模型名称 为默认的 NAS 挂载点，请将 roll-dev 修改为实际的模型名称
+cd /mnt/roll-dev
+
+# 1. 克隆项目代码
+git clone https://github.com/alibaba/ROLL.git
+
+# 2. 安装项目依赖
+cd ROLL
+pip install -r requirements_torch260_vllm.txt -i https://mirrors.aliyun.com/pypi/simple/
+```
+
+### 运行 pipeline 示例
+
+```bash
+bash examples/agentic_demo/run_agentic_pipeline_frozen_lake_single_node_demo.sh
+```
+
+更多 DevPod 使用指南，见 [https://fun-model-docs.devsapp.net/user-guide/devpod/](https://fun-model-docs.devsapp.net/user-guide/devpod/)

docs_roll/i18n/zh-Hans/docusaurus-plugin-content-docs/current/Overview.mdx

@@ -48,6 +48,7 @@ Leveraging a multi-role distributed architecture with Ray for flexible resource
 [安装指南](https://alibaba.github.io/ROLL/zh-Hans/docs/Getting%20Started/Installation/)  
 [快速上手：单机版部署指南](https://alibaba.github.io/ROLL/zh-Hans/docs/Getting%20Started/Quick%20Start/single_node_quick_start)  
 [快速上手：多节点部署指南](https://alibaba.github.io/ROLL/zh-Hans/docs/Getting%20Started/Quick%20Start/multi_nodes_quick_start)  
+[快速上手：使用阿里云函数计算 DevPod 进行快速开发](https://alibaba.github.io/ROLL/zh-Hans/docs/Getting%20Started/Quick%20Start/aliyun_serverless_devpod_quick_start)  
 [ROLL 调试指南](https://alibaba.github.io/ROLL/zh-Hans/docs/Getting%20Started/Debugging%20Guide/debug_guide)  
 [常见问题解答 (Q&A)](https://alibaba.github.io/ROLL/zh-Hans/docs/Getting%20Started/FAQ/qa_issues)