Source Code Compilation and Build

Obtain the SGLang source code, build Python wheels and CUDA extension wheels from the source code, and install the build products.

Obtain the SGLang 0.5.10 source code.

git clone --branch v0.5.10 --depth 1 https://github.com/sgl-project/sglang.git

Build a Python wheel from the source code.

cd sglang
SETUPTOOLS_SCM_PRETEND_VERSION=0.5.10 \
python3 -m pip wheel --no-build-isolation --no-deps \
  --wheel-dir /tmp/sglang-build/python ./python

Build a CUDA extension wheel from the source code.

export CUDA_HOME=/usr/local/cuda-13.0 
export PATH=$CUDA_HOME/bin:$PATH
export LD_LIBRARY_PATH=$CUDA_HOME/lib64:${LD_LIBRARY_PATH:-}
export TORCH_CUDA_ARCH_LIST="8.0"
export MAX_JOBS=8 
export NVCC_THREADS=1 
export CMAKE_BUILD_PARALLEL_LEVEL=8 
export CMAKE_ARGS="-DCMAKE_POLICY_VERSION_MINIMUM=3.5 -DCMAKE_CUDA_ARCHITECTURES=80"
export Torch_DIR=$(python3 - <<'PY'
import pathlib 
import torch  

print(pathlib.Path(torch.__file__).resolve().parent / "share" / "cmake" / "Torch") 
PY 
) 
export CMAKE_PREFIX_PATH=$(python3 - <<'PY'
import torch.utils  

print(torch.utils.cmake_prefix_path) 
PY 
)  

python3 -m pip wheel --no-build-isolation --no-deps \
  --wheel-dir /tmp/sglang-build/kernel ./sgl-kernel

Install the local build product.

python3 -m pip install \
  typing_extensions filelock fsspec jinja2 networkx sympy mpmath numpy packaging \
  tqdm requests aiohttp fastapi uvicorn pydantic orjson pyzmq psutil pillow \
  sentencepiece safetensors tokenizers transformers==5.3.0 pybase64 setproctitle \
  partial_json_parser diskcache msgspec interegular lark pycountry pycryptodomex \
  gguf openai anthropic prometheus-client uvloop watchfiles soundfile tiktoken IPython
python3 -m pip install --force-reinstall --no-deps /tmp/sglang-build/kernel/*.whl
python3 -m pip install --force-reinstall --no-deps /tmp/sglang-build/python/*.whl

When installing the local build product, use --no-deps to retain the confirmed CUDA version of PyTorch and prevent the PyTorch version from being replaced during dependency parsing. After the installation is complete, check again that both torch.backends.cuda.is_built() and torch.cuda.is_available() return True.

The following is an example of the build product.

sglang-0.5.10-py3-none-any.whl 
sglang_kernel-0.4.1-*.whl

Parent topic: Developer Guide