pyproject.toml

[build-system]
requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "sglang"
version = "0.4.5"
description = "SGLang is yet another fast serving framework for large language models and vision language models."
readme = "README.md"
requires-python = ">=3.8"
license = { file = "LICENSE" }
classifiers = [
    "Programming Language :: Python :: 3",
    "License :: OSI Approved :: Apache Software License",
]
dependencies = ["aiohttp", "requests", "tqdm", "numpy", "IPython", "setproctitle"]

[project.optional-dependencies]
runtime_common = [
    "compressed-tensors",
    "datasets",
    "decord",
    "fastapi",
    "hf_transfer",
    "huggingface_hub",
    "interegular",
    "llguidance>=0.6.15",
    "modelscope",
    "ninja",
    "orjson",
    "packaging",
    "pillow",
    "prometheus-client>=0.20.0",
    "psutil",
    "pydantic",
    "pynvml",
    "python-multipart",
    "pyzmq>=25.1.2",
    "soundfile==0.13.1",
    "torchao>=0.7.0",
    "transformers==4.51.1",
    "uvicorn",
    "uvloop",
    "compressed-tensors",
    "xgrammar==0.1.17",
]

srt = [
    "sglang[runtime_common]",
    "sgl-kernel==0.0.8",
    "flashinfer_python==0.2.3",
    "torch==2.5.1",
    "torchvision==0.20.1",
    "cuda-python",
    "outlines>=0.0.44,<=0.1.11",
    "partial_json_parser",
    "einops",
]

# HIP (Heterogeneous-computing Interface for Portability) for AMD
# => base docker rocm/vllm-dev:20250114, not from public vllm whl
srt_hip = [
    "sglang[runtime_common]",
    "torch",
    "vllm==0.6.7.dev2",
    "outlines==0.1.11"
]

# xpu is not enabled in public vllm and torch whl,
# need to follow https://docs.vllm.ai/en/latest/getting_started/xpu-installation.htmlinstall vllm
srt_xpu = ["sglang[runtime_common]", "outlines>=0.0.44,<=0.1.11"]

# For Intel Gaudi(device : hpu) follow the installation guide
# https://docs.vllm.ai/en/latest/getting_started/gaudi-installation.html
srt_hpu = ["sglang[runtime_common]", "outlines>=0.0.44,<=0.1.11"]

# CPU: currently, there are no pre-built vllm wheels for CPU.
# To install vllm for CPU, please follow the instruction here:
# https://docs.vllm.ai/en/latest/getting_started/installation/cpu/index.html
srt_cpu = ["sglang[runtime_common]", "outlines>=0.0.44,<=0.1.11", "torch"]

openai = ["openai>=1.0", "tiktoken"]
anthropic = ["anthropic>=0.20.0"]
litellm = ["litellm>=1.0.0"]
torch_memory_saver = ["torch_memory_saver>=0.0.4"]
test = [
    "jsonlines",
    "matplotlib",
    "pandas",
    "sentence_transformers",
    "accelerate",
    "peft",
]
all = ["sglang[srt]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]
all_hip = ["sglang[srt_hip]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]
all_xpu = ["sglang[srt_xpu]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]
all_hpu = ["sglang[srt_hpu]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]
all_cpu = ["sglang[srt_cpu]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]

dev = ["sglang[all]", "sglang[test]"]
dev_hip = ["sglang[all_hip]", "sglang[test]"]
dev_xpu = ["sglang[all_xpu]", "sglang[test]"]
dev_hpu = ["sglang[all_hpu]", "sglang[test]"]
dev_cpu = ["sglang[all_cpu]", "sglang[test]"]

[project.urls]
"Homepage" = "https://github.com/sgl-project/sglang"
"Bug Tracker" = "https://github.com/sgl-project/sglang/issues"

[tool.setuptools.package-data]
"sglang" = [
    "srt/layers/moe/fused_moe_triton/configs/*.json",
    "srt/layers/quantization/configs/*.json",
]

[tool.setuptools.packages.find]
exclude = [
    "assets*",
    "benchmark*",
    "docs*",
    "dist*",
    "playground*",
    "scripts*",
    "tests*",
]

[tool.wheel]
exclude = [
    "assets*",
    "benchmark*",
    "docs*",
    "dist*",
    "playground*",
    "scripts*",
    "tests*",
]