[Doc] 增加中英文切换

.github/workflows/gh-pages.yml

@@ -15,7 +15,7 @@ jobs:
       - uses: actions/setup-python@v5
         with:
           python-version: 3.x
-      - run: pip install mkdocs-material mkdocs-get-deps mkdocs-material-extensions mkdocs-multilang
+      - run: pip install mkdocs-material mkdocs-get-deps mkdocs-material-extensions mkdocs-multilang mkdocs-static-i18n
       - name: Deploy to GitHub Pages
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

README.md

@@ -1,3 +1,4 @@
+English | [简体中文](README_CN.md) 
 <p align="center">
   <a href="https://github.com/PaddlePaddle/FastDeploy/releases"><img src="https://github.com/user-attachments/assets/42b0039f-39e3-4279-afda-6d1865dfbffb" width="500"></a>
 </p>
@@ -68,7 +69,7 @@ Learn how to use FastDeploy through our documentation:
 - [Offline Inference Development](./docs/offline_inference.md)
 - [Online Service Deployment](./docs/online_serving/README.md)
 - [Full Supported Models List](./docs/supported_models.md)
-- [Optimal Deployment](./docs/optimal_deployment/README.md)
+- [Best Practices](./docs/best_practices/README.md)
 
 ## Supported Models
 

README_CN.md

@@ -0,0 +1,93 @@
+[English](README.md) | 简体中文
+<p align="center">
+  <a href="https://github.com/PaddlePaddle/FastDeploy/releases"><img src="https://github.com/user-attachments/assets/42b0039f-39e3-4279-afda-6d1865dfbffb" width="500"></a>
+</p>
+<p align="center">
+    <a href=""><img src="https://img.shields.io/badge/python-3.10-aff.svg"></a>
+    <a href=""><img src="https://img.shields.io/badge/os-linux-pink.svg"></a>
+    <a href="https://github.com/PaddlePaddle/FastDeploy/graphs/contributors"><img src="https://img.shields.io/github/contributors/PaddlePaddle/FastDeploy?color=9ea"></a>
+    <a href="https://github.com/PaddlePaddle/FastDeploy/commits"><img src="https://img.shields.io/github/commit-activity/m/PaddlePaddle/FastDeploy?color=3af"></a>
+    <a href="https://github.com/PaddlePaddle/FastDeploy/issues"><img src="https://img.shields.io/github/issues/PaddlePaddle/FastDeploy?color=9cc"></a>
+    <a href="https://github.com/PaddlePaddle/FastDeploy/stargazers"><img src="https://img.shields.io/github/stars/PaddlePaddle/FastDeploy?color=ccf"></a>
+
+</p>
+
+<p align="center">
+     <a href="https://trendshift.io/repositories/4046" target="_blank"><img src="https://trendshift.io/api/badge/repositories/4046" alt="PaddlePaddle%2FFastDeploy | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a></br>
+    <a href="https://paddlepaddle.github.io/FastDeploy/zh/get_started/installation/nvidia_gpu/"><b> 安装指导 </b></a>
+    |
+    <a href="https://paddlepaddle.github.io/FastDeploy/zh/get_started/quick_start"><b> 快速入门 </b></a>
+    |
+    <a href="https://paddlepaddle.github.io/FastDeploy/zh/supported_models/"><b> 支持模型列表 </b></a>
+
+</p>
+
+--------------------------------------------------------------------------------
+# FastDeploy 2.0：基于飞桨的大语言模型与视觉语言模型推理部署工具包
+
+## 最新活动
+
+**[2025-07] 《FastDeploy2.0推理部署实测》专题活动已上线!** 完成文心4.5系列开源模型的推理部署等任务，即可获得骨瓷马克杯等FastDeploy2.0官方周边及丰富奖金！🎁 欢迎大家体验反馈～ 📌[报名地址](https://www.wjx.top/vm/meSsp3L.aspx#)   📌[活动详情](https://github.com/PaddlePaddle/FastDeploy/discussions/2728)
+
+## 关于
+
+**FastDeploy** 是基于飞桨（PaddlePaddle）的大语言模型（LLM）与视觉语言模型（VLM）推理部署工具包，提供**开箱即用的生产级部署方案**，核心技术特性包括：
+
+- 🚀 **负载均衡式PD分解**：工业级解决方案，支持上下文缓存与动态实例角色切换，在保障SLO达标和吞吐量的同时优化资源利用率
+- 🔄 **统一KV缓存传输**：轻量级高性能传输库，支持智能NVLink/RDMA选择
+- 🤝 **OpenAI API服务与vLLM兼容**：单命令部署，兼容[vLLM](https://github.com/vllm-project/vllm/)接口
+- 🧮 **全量化格式支持**：W8A16、W8A8、W4A16、W4A8、W2A16、FP8等
+- ⏩ **高级加速技术**：推测解码、多令牌预测（MTP）及分块预填充
+- 🖥️ **多硬件支持**：NVIDIA GPU、昆仑芯XPU、海光DCU、昇腾NPU、天数智芯GPU、燧原GCU、沐曦GPU等
+
+
+## 要求
+
+- 操作系统: Linux
+- Python: 3.10 ~ 3.12
+
+## 安装
+
+FastDeploy 支持在**英伟达（NVIDIA）GPU**、**昆仑芯（Kunlunxin）XPU**、**天数（Iluvatar）GPU**、**燧原（Enflame）GCU** 以及其他硬件上进行推理部署。详细安装说明如下：
+
+- [英伟达 GPU](./docs/zh/get_started/installation/nvidia_gpu.md)
+- [昆仑芯 XPU](./docs/zh/get_started/installation/kunlunxin_xpu.md)
+- [天数 CoreX](./docs/zh/get_started/installation/iluvatar_gpu.md)
+- [燧原 S60](./docs/zh/get_started/installation/Enflame_gcu.md)
+
+**注意:** 我们正在积极拓展硬件支持范围。目前，包括昇腾（Ascend）NPU、海光（Hygon）DCU 和摩尔线程（MetaX）GPU 在内的其他硬件平台正在开发测试中。敬请关注更新！
+
+## 入门指南
+
+通过我们的文档了解如何使用 FastDeploy：
+- [10分钟快速部署](./docs/zh/get_started/quick_start.md)
+- [ERNIE-4.5 部署](./docs/zh/get_started/ernie-4.5.md)
+- [ERNIE-4.5-VL 部署](./docs/zh/get_started/ernie-4.5-vl.md)
+- [离线推理](./docs/zh/offline_inference.md)
+- [在线服务](./docs/zh/online_serving/README.md)
+- [模型支持列表](./docs/zh/supported_models.md)
+- [最佳实践](./docs/zh/best_practices/README.md)
+
+## 支持模型列表
+
+| Model | Data Type | PD Disaggregation | Chunked Prefill | Prefix Caching |  MTP | CUDA Graph | Maximum Context Length |
+|:--- | :------- | :---------- | :-------- | :-------- | :----- | :----- | :----- |
+|ERNIE-4.5-300B-A47B | BF16/WINT4/WINT8/W4A8C8/WINT2/FP8 | ✅| ✅ | ✅|✅(WINT4)| WIP |128K |
+|ERNIE-4.5-300B-A47B-Base| BF16/WINT4/WINT8 | ✅| ✅ | ✅|✅(WINT4)| WIP | 128K |
+|ERNIE-4.5-VL-424B-A47B | BF16/WINT4/WINT8 | WIP | ✅ | WIP | ❌ | WIP |128K |
+|ERNIE-4.5-VL-28B-A3B | BF16/WINT4/WINT8 | ❌ | ✅ | WIP | ❌ | WIP |128K |
+|ERNIE-4.5-21B-A3B | BF16/WINT4/WINT8/FP8  |  ❌ |  ✅ |  ✅ | WIP | ✅|128K |
+|ERNIE-4.5-21B-A3B-Base | BF16/WINT4/WINT8/FP8  |  ❌ |  ✅ |  ✅ | WIP | ✅|128K |
+|ERNIE-4.5-0.3B | BF16/WINT8/FP8  |  ❌ |  ✅ |  ✅ | ❌ | ✅| 128K |
+
+## 进阶用法
+
+- [量化](./docs/zh/quantization/README.md)
+- [分离式部署](./docs/zh/features/disaggregated.md)
+- [投机解码](./docs/zh/features/speculative_decoding.md)
+- [前缀缓存](./docs/zh/features/prefix_caching.md)
+- [分块预填充](./docs/zh/features/chunked_prefill.md)
+
+## 致谢
+
+FastDeploy 依据 [Apache-2.0 开源许可证](./LICENSE). 进行授权。在开发过程中，我们参考并借鉴了 [vLLM](https://github.com/vllm-project/vllm) 的部分代码，以保持接口兼容性，在此表示衷心感谢。

docs/optimal_deployment/ERNIE-4.5-0.3B-Paddle.md → docs/best_practices/ERNIE-4.5-0.3B-Paddle.md

@@ -2,7 +2,8 @@
 ## Environmental Preparation
 ### 1.1 Hardware requirements
 The minimum number of GPUs required to deploy `ERNIE-4.5-0.3B` on the following hardware for each quantization is as follows:
-|  | WINT8 | WINT4 | FP8 |
+
+| | WINT8 | WINT4 | FP8 |
 |-----|-----|-----|-----|
 |H800 80GB| 1 | 1 | 1 |
 |A800 80GB| 1 | 1 | / |

docs/optimal_deployment/ERNIE-4.5-21B-A3B-Paddle.md → docs/best_practices/ERNIE-4.5-21B-A3B-Paddle.md

@@ -2,7 +2,8 @@
 ## Environmental Preparation
 ### 1.1 Hardware requirements
 The minimum number of GPUs required to deploy `ERNIE-4.5-21B-A3B` on the following hardware for each quantization is as follows:
-|  | WINT8 | WINT4 | FP8 |
+
+| | WINT8 | WINT4 | FP8 |
 |-----|-----|-----|-----|
 |H800 80GB| 1 | 1 | 1 |
 |A800 80GB| 1 | 1 | / |

docs/optimal_deployment/ERNIE-4.5-300B-A47B-Paddle.md → docs/best_practices/ERNIE-4.5-300B-A47B-Paddle.md

@@ -2,7 +2,8 @@
 ## Environmental Preparation
 ### 1.1 Hardware requirements
 The minimum number of GPUs required to deploy `ERNIE-4.5-300B-A47B` on the following hardware for each quantization is as follows:
-|  | WINT8 | WINT4 | FP8 | WINT2 | W4A8 |
+
+| | WINT8 | WINT4 | FP8 | WINT2 | W4A8 |
 |-----|-----|-----|-----|-----|-----|
 |H800 80GB| 8 | 4 | 8 | 2 | 4 |
 |A800 80GB| 8 | 4 | / | 2 | 4 |

docs/optimal_deployment/ERNIE-4.5-VL-28B-A3B-Paddle.md → docs/best_practices/ERNIE-4.5-VL-28B-A3B-Paddle.md

@@ -5,6 +5,7 @@
 ### 1.1 Support Status
 
 The minimum number of cards required for deployment on the following hardware is as follows:
+
 | Device [GPU Mem] | WINT4 | WINT8 | BFLOAT16 |
 |:----------:|:----------:|:------:| :------:|
 | A30 [24G] | 2 | 2 | 4 |

docs/optimal_deployment/ERNIE-4.5-VL-424B-A47B-Paddle.md → docs/best_practices/ERNIE-4.5-VL-424B-A47B-Paddle.md

@@ -4,6 +4,7 @@
 ## 1. Environment Preparation
 ### 1.1 Support Status
 The minimum number of cards required for deployment on the following hardware is as follows:
+
 | Device [GPU Mem] | WINT4 | WINT8 | BFLOAT16 |
 |:----------:|:----------:|:------:| :------:|
 | H20 [144G] | 8 | 8 |  8 |

docs/zh/optimal_deployment/ERNIE-4.5-0.3B-Paddle.md → docs/zh/best_practices/ERNIE-4.5-0.3B-Paddle.md

@@ -2,6 +2,7 @@
 ## 一、环境准备
 ### 1.1 支持情况
 ERNIE-4.5-0.3B 各量化精度，在下列硬件上部署所需要的最小卡数如下：
+
 |  | WINT8 | WINT4 | FP8 |
 |-----|-----|-----|-----|
 |H800 80GB| 1 | 1 | 1 |

docs/zh/optimal_deployment/ERNIE-4.5-21B-A3B-Paddle.md → docs/zh/best_practices/ERNIE-4.5-21B-A3B-Paddle.md

@@ -2,6 +2,7 @@
 ## 一、环境准备
 ### 1.1 支持情况
 ERNIE-4.5-21B-A3B 各量化精度，在下列硬件上部署所需要的最小卡数如下：
+
 |  | WINT8 | WINT4 | FP8 |
 |-----|-----|-----|-----|
 |H800 80GB| 1 | 1 | 1 |

docs/zh/optimal_deployment/ERNIE-4.5-300B-A47B-Paddle.md → docs/zh/best_practices/ERNIE-4.5-300B-A47B-Paddle.md

@@ -2,6 +2,7 @@
 ## 一、环境准备
 ### 1.1 支持情况
 ERNIE-4.5-300B-A47B各量化精度，在下列硬件上部署所需要的最小卡数如下：
+
 |  | WINT8 | WINT4 | FP8 | WINT2 | W4A8 |
 |-----|-----|-----|-----|-----|-----|
 |H800 80GB| 8 | 4 | 8 | 2 | 4 |

docs/zh/optimal_deployment/ERNIE-4.5-VL-28B-A3B-Paddle.md → docs/zh/best_practices/ERNIE-4.5-VL-28B-A3B-Paddle.md

@@ -4,6 +4,7 @@
 ## 一、环境准备
 ### 1.1 支持情况
 在下列硬件上部署所需要的最小卡数如下：
+
 | 设备[显存] | WINT4 | WINT8 | BFLOAT16 |
 |:----------:|:----------:|:------:| :------:|
 | A30 [24G] | 2 | 2 | 4 |

docs/zh/optimal_deployment/ERNIE-4.5-VL-424B-A47B-Paddle.md → docs/zh/best_practices/ERNIE-4.5-VL-424B-A47B-Paddle.md

@@ -4,6 +4,7 @@
 ## 一、环境准备
 ### 1.1 支持情况
 在下列硬件上部署所需要的最小卡数如下：
+
 | 设备[显存] | WINT4 | WINT8 | BFLOAT16 |
 |:----------:|:----------:|:------:| :------:|
 | H20 [144G] | 8 | 8 |  8 |

docs/zh/get_started/installation/iluvatar_gpu.md

@@ -3,6 +3,7 @@
 
 ## 准备机器
 首先您需要准备以下配置的机器
+
 | CPU | 内存 | 天数 | 硬盘|
 |-----|------|-----|-----|
 | x86 | 1TB| 8xBI150| 1TB|

mkdocs.yml

@@ -1,13 +1,102 @@
 site_name: 'FastDeploy 2.0: Large Language Model Deployement'
+repo_url: https://github.com/PaddlePaddle/FastDeploy
+repo_name: FastDeploy
+
+theme:
+  name: material
+  highlightjs: true
+  icon:
+    repo: fontawesome/brands/github
+  palette:
+    - media: "(prefers-color-scheme: light)" # 浅色
+      scheme: default
+      primary: indigo
+      accent: indigo
+      toggle:
+        icon: material/brightness-7
+        name: Switch to dark mode
+    - media: "(prefers-color-scheme: dark)" # 深色
+      scheme: slate
+      primary: black
+      accent: indigo
+      toggle:
+        icon: material/brightness-4
+        name: Switch to system preference
+
+plugins:
+  - search
+  - i18n:
+      docs_structure: folder
+      fallback_to_default: true
+      reconfigure_material: true
+      reconfigure_search: true
+      languages:
+        - locale: en
+          default: true
+          name: English
+          site_name: 'FastDeploy 2.0: Large Language Model Deployement'
+          build: true
+        - locale: zh
+          name: 简体中文
+          site_name: 飞桨大语言模型推理部署工具包
+          link: /zh/
+          nav_translations:
+            FastDeploy 2.0: FastDeploy 2.0
+            Quick Start: 快速入门
+            Installation: 安装
+            Nvidia GPU: 英伟达 GPU
+            KunlunXin XPU: 昆仑芯 XPU
+            HYGON DCU: 海光 DCU
+            Enflame S60: 燧原 S60
+            Iluvatar CoreX: 天数 CoreX
+            Quick Deployment For ERNIE-4.5-0.3B: ERNIE-4.5-0.3B快速部署
+            Quick Deployment for ERNIE-4.5-VL-28B-A3B: ERNIE-4.5-VL-28B-A3B快速部署
+            ERNIE-4.5-300B-A47B: ERNIE-4.5-300B-A47B快速部署
+            ERNIE-4.5-VL-424B-A47B: ERNIE-4.5-VL-424B-A47B快速部署
+            Online Serving: 在线服务
+            OpenAI-Compitable API Server: 兼容 OpenAI 协议的服务化部署
+            Monitor Metrics: 监控Metrics
+            Scheduler: 调度器
+            Offline Inference: 离线推理
+            Optimal Deployment: 最佳实践
+            ERNIE-4.5-0.3B: ERNIE-4.5-0.3B
+            ERNIE-4.5-21B-A3B: ERNIE-4.5-21B-A3B
+            ERNIE-4.5-300B-A47B: ERNIE-4.5-300B-A47B
+            ERNIE-4.5-VL-28B-A3B: ERNIE-4.5-VL-28B-A3B
+            ERNIE-4.5-VL-424B-A47B: ERNIE-4.5-VL-424B-A47B
+            FAQ: 常见问题
+            Quantization: 量化
+            Overview: 概述
+            Online Quantization: 在线量化
+            WINT2 Quantization: WINT2量化
+            Features: 特性
+            Prefix Caching: 前缀缓存
+            Disaggregation: 分离式部署
+            Chunked Prefill: 分块预填充
+            Load Balance: 负载均衡
+            Speculative Decoding: 投机解码
+            Structured Outputs: 结构化输出
+            Reasoning Output: 思考链内容
+            Early Stop: 早停功能
+            Plugins: 插件机制
+            Sampling: 采样策略
+            Supported Models: 支持模型列表
+            Benchmark: 基准测试
+            Usage: 用法
+            Log Description: 日志说明
+            Code Overview: 代码概述
+            Environment Variables: 环境变量
+
 nav:
   - 'FastDeploy 2.0': index.md
   - 'Quick Start':
       - Installation:
           - 'Nvidia GPU': get_started/installation/nvidia_gpu.md
           - 'KunlunXin XPU': get_started/installation/kunlunxin_xpu.md
+          - 'HYGON DCU': get_started/installation/hygon_dcu.md
           - 'Enflame S60': get_started/installation/Enflame_gcu.md
           - 'Iluvatar CoreX': get_started/installation/iluvatar_gpu.md
-      - 'Quick Deployment For ERNIE-4.5-0.3B-Paddle': get_started/quick_start.md
+      - 'Quick Deployment For ERNIE-4.5-0.3B': get_started/quick_start.md
       - 'Quick Deployment for ERNIE-4.5-VL-28B-A3B': get_started/quick_start_vl.md
       - 'ERNIE-4.5-300B-A47B': get_started/ernie-4.5.md
       - 'ERNIE-4.5-VL-424B-A47B': get_started/ernie-4.5-vl.md
@@ -16,28 +105,32 @@ nav:
       - 'Monitor Metrics': online_serving/metrics.md
       - 'Scheduler': online_serving/scheduler.md
   - 'Offline Inference': offline_inference.md
-  - Quantiation:
+  - Optimal Deployment:
+      - ERNIE-4.5-0.3B: best_practices/ERNIE-4.5-0.3B-Paddle.md
+      - ERNIE-4.5-21B-A3B: best_practices/ERNIE-4.5-21B-A3B-Paddle.md
+      - ERNIE-4.5-300B-A47B: best_practices/ERNIE-4.5-300B-A47B-Paddle.md
+      - ERNIE-4.5-VL-28B-A3B: best_practices/ERNIE-4.5-VL-28B-A3B-Paddle.md
+      - ERNIE-4.5-VL-424B-A47B: best_practices/ERNIE-4.5-VL-424B-A47B-Paddle.md
+      - FAQ: best_practices/FAQ.md
+  - Quantization:
       - 'Overview': quantization/README.md
       - 'Online Quantization': quantization/online_quantization.md
       - 'WINT2 Quantization': quantization/wint2.md
   - Features:
       - 'Prefix Caching': features/prefix_caching.md
-      - 'Disaggration': features/disaggregated.md
+      - 'Disaggregation': features/disaggregated.md
       - 'Chunked Prefill': features/chunked_prefill.md
       - 'Load Balance': features/load_balance.md
       - 'Speculative Decoding': features/speculative_decoding.md
       - 'Structured Outputs': features/structured_outputs.md
       - 'Reasoning Output': features/reasoning_output.md
+      - 'Early Stop': features/early_stop.md
+      - 'Plugins': features/plugins.md
+      - 'Sampling': features/sampling.md
   - 'Supported Models': supported_models.md
   - Benchmark: benchmark.md
   - Usage:
       - 'Log Description': usage/log.md
       - 'Code Overview': usage/code_overview.md
       - 'Environment Variables': usage/environment_variables.md
-theme:
-  name: 'material'
-  highlightjs: true
-  icon:
-    repo: fontawesome/brands/github
-repo_url: https://github.com/PaddlePaddle/FastDeploy
-repo_name: FastDeploy
+