Clean up server args & Add CI scripts (#12124)

docs/get_started/install.md

@@ -3,7 +3,7 @@
 You can install SGLang using one of the methods below.
 
 This page primarily applies to common NVIDIA GPU platforms.
-For other or newer platforms, please refer to the dedicated pages for [AMD GPUs](../platforms/amd_gpu.md), [Intel Xeon CPUs](../platforms/cpu_server.md), [NVIDIA Jetson](../platforms/nvidia_jetson.md), [Ascend NPUs](../platforms/ascend_npu.md).
+For other or newer platforms, please refer to the dedicated pages for [AMD GPUs](../platforms/amd_gpu.md), [Intel Xeon CPUs](../platforms/cpu_server.md), [TPU](../platforms/tpu.md), [NVIDIA DGX Spark](https://lmsys.org/blog/2025-10-13-nvidia-dgx-spark/), [NVIDIA Jetson](../platforms/nvidia_jetson.md), [Ascend NPUs](../platforms/ascend_npu.md).
 
 ## Method 1: With pip or uv
 

python/sglang/launch_server.py

@@ -12,10 +12,12 @@ if __name__ == "__main__":
 
     try:
         if server_args.grpc_mode:
+            # Handle gRPC server
             from sglang.srt.entrypoints.grpc_server import serve_grpc
 
             asyncio.run(serve_grpc(server_args))
         else:
+            # Handle HTTP server
             from sglang.srt.entrypoints.http_server import launch_server
 
             launch_server(server_args)

python/sglang/srt/utils/common.py

@@ -138,6 +138,7 @@ def is_xpu() -> bool:
     return hasattr(torch, "xpu") and torch.xpu.is_available()
 
 
+@lru_cache(maxsize=1)
 def is_npu() -> bool:
     return hasattr(torch, "npu") and torch.npu.is_available()