pyproject.toml

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

[project]
name = "sglang"
version = "0.4.2.post2"
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 = ["requests", "tqdm", "numpy", "IPython", "setproctitle"]

[project.optional-dependencies]
runtime_common = [
    "aiohttp", "decord", "fastapi",
    "hf_transfer", "huggingface_hub", "interegular", "modelscope",
    "orjson", "packaging", "pillow", "prometheus-client>=0.20.0",
    "psutil", "pydantic", "python-multipart", "pyzmq>=25.1.2",
    "torchao>=0.7.0", "uvicorn", "uvloop", "xgrammar>=0.1.10"
]
srt = [
    "sglang[runtime_common]", "cuda-python",
    "sgl-kernel>=0.0.3.post1", "torch", "vllm==0.6.4.post1",
    "flashinfer_python>=0.2.0.post2", "outlines>=0.0.44,<0.1.0"
]

# HIP (Heterogeneous-computing Interface for Portability) for AMD
# => base docker rocm/vllm-dev:20241022, not from public vllm whl
srt_hip = ["sglang[runtime_common]", "torch", "vllm==0.6.7.dev2", "outlines==0.1.11", "sgl-kernel>=0.0.3.post1"]
# 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,<0.1.0"]
#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,<0.1.0"]
# 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]", "torch", "outlines>=0.0.44,<0.1.0"]

openai = ["openai>=1.0", "tiktoken"]
anthropic = ["anthropic>=0.20.0"]
litellm = ["litellm>=1.0.0"]
torch_memory_saver = ["torch_memory_saver"]
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*",
]