[diffusion][llm] macOS support (#19549)

Signed-off-by: Xiaodong Ye <yeahdongcn@gmail.com>
Co-authored-by: Mick <mickjagger19@icloud.com>

docs/diffusion/environment_variables.md

@@ -1,3 +1,9 @@
+## Apple MPS
+
+| Environment Variable | Default | Description                                                  |
+|----------------------|---------|--------------------------------------------------------------|
+| `SGLANG_USE_MLX`     | not set | Set to `1` to enable MLX fused Metal kernels for norm ops on MPS |
+
 ## Caching Acceleration
 
 These variables configure caching acceleration for Diffusion Transformer (DiT) models.

docs/diffusion/index.md

@@ -7,7 +7,11 @@ SGLang Diffusion is an inference framework for accelerated image and video gener
 - **Broad Model Support**: Wan series, FastWan series, Hunyuan, Qwen-Image, Qwen-Image-Edit, Flux, Z-Image, GLM-Image, and more
 - **Fast Inference**: Optimized kernels, efficient scheduler loop, and Cache-DiT acceleration
 - **Ease of Use**: OpenAI-compatible API, CLI, and Python SDK
-- **Multi-Platform**: NVIDIA GPUs (H100, H200, A100, B200, 4090), AMD GPUs (MI300X, MI325X) and Ascend NPU (A2, A3)
+- **Multi-Platform**:
+  - NVIDIA GPUs (H100, H200, A100, B200, 4090)
+  - AMD GPUs (MI300X, MI325X)
+  - Ascend NPU (A2, A3)
+  - Apple Silicon (M-series via MPS)
 
 ---
 

docs/diffusion/installation.md

@@ -69,7 +69,7 @@ For detailed ROCm system configuration and installation from source, see [AMD GP
 
 ## Platform-Specific: MUSA (Moore Threads GPUs)
 
-For Moore Threads GPUs (MTGPU) with the MUSA software stack:
+For Moore Threads GPUs (MTGPU) with the MUSA software stack, please follow the instructions below to install from source:
 
 ```bash
 # Clone the repository
@@ -93,3 +93,28 @@ sglang generate --model-path black-forest-labs/FLUX.1-dev \
     --prompt "A logo With Bold Large text: SGL Diffusion" \
     --save-output
 ```
+
+## Platform-Specific: Apple MPS
+
+For Apple MPS, please follow the instructions below to install from source:
+
+```bash
+# Install ffmpeg
+brew install ffmpeg
+
+# Install uv
+brew install uv
+
+# Clone the repository
+git clone https://github.com/sgl-project/sglang.git
+cd sglang
+
+# Create and activate a virtual environment
+uv venv -p 3.11 sglang-diffusion
+source sglang-diffusion/bin/activate
+
+# Install the Python packages
+uv pip install --upgrade pip
+rm -f python/pyproject.toml && mv python/pyproject_other.toml python/pyproject.toml
+uv pip install -e "python[all_mps]"
+```