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sglang/python/pyproject.toml

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[build-system]
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requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"
[project]
name = "sglang"
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version = "0.5.0rc0"
description = "SGLang is yet another fast serving framework for large language models and vision language models."
readme = "README.md"
requires-python = ">=3.10"
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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 = [
"blobfile==3.0.0",
"build",
"compressed-tensors",
"datasets",
"einops",
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"fastapi",
"hf_transfer",
"huggingface_hub",
"interegular",
"llguidance>=0.7.11,<0.8.0",
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"modelscope",
"msgspec",
"ninja",
"openai==1.99.1",
"openai-harmony==0.0.3",
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"orjson",
"outlines==0.1.11",
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"packaging",
"partial_json_parser",
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"pillow",
"prometheus-client>=0.20.0",
"psutil",
"pydantic",
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"pynvml",
"pybase64",
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"python-multipart",
"pyzmq>=25.1.2",
"sentencepiece",
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"soundfile==0.13.1",
"scipy",
"timm==1.0.16",
"tiktoken",
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"torchao==0.9.0",
"transformers==4.55.0",
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"uvicorn",
"uvloop",
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"xgrammar==0.1.22",
]
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srt = [
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"sglang[runtime_common]",
"sgl-kernel==0.3.4",
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"torch==2.8.0",
"torchaudio==2.8.0",
"torchvision",
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"cuda-python",
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"flashinfer_python==0.2.11.post1",
]
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blackwell = [
"sglang[runtime_common]",
"sgl-kernel",
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"torch==2.8.0",
"torchaudio==2.8.0",
"torchvision",
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"cuda-python",
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"flashinfer_python==0.2.11.post1",
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]
# HIP (Heterogeneous-computing Interface for Portability) for AMD
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# => base docker rocm/vllm-dev:20250114, not from public vllm whl
srt_hip = [
"sglang[runtime_common]",
"torch",
"petit_kernel==0.0.2",
"wave-lang==1.0.1",
]
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# CPU: torch wheel for CPU needs to be installed from https://download.pytorch.org/whl/cpu
srt_cpu = ["sglang[runtime_common]", "einops"]
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# 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]"]
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# 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]"]
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# https://vllm-ascend.readthedocs.io/en/latest/installation.html
srt_npu = ["sglang[runtime_common]"]
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openai = ["openai==1.99.1", "tiktoken"]
anthropic = ["anthropic>=0.20.0"]
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litellm = ["litellm>=1.0.0"]
torch_memory_saver = ["torch_memory_saver==0.0.8"]
decord = ["decord"]
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test = [
"accelerate",
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"expecttest",
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"jsonlines",
"matplotlib",
"pandas",
"peft",
"sentence_transformers",
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"pytest",
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]
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all = ["sglang[srt]", "sglang[openai]", "sglang[anthropic]", "sglang[torch_memory_saver]", "sglang[decord]"]
all_hip = ["sglang[srt_hip]", "sglang[openai]", "sglang[anthropic]", "sglang[decord]"]
all_xpu = ["sglang[srt_xpu]", "sglang[openai]", "sglang[anthropic]", "sglang[decord]"]
all_hpu = ["sglang[srt_hpu]", "sglang[openai]", "sglang[anthropic]", "sglang[decord]"]
all_cpu = ["sglang[srt_cpu]", "sglang[openai]", "sglang[anthropic]", "sglang[decord]"]
all_npu = ["sglang[srt_npu]", "sglang[openai]", "sglang[anthropic]", "sglang[decord]"]
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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]"]
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dev_cpu = ["sglang[all_cpu]", "sglang[test]"]
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[project.urls]
"Homepage" = "https://github.com/sgl-project/sglang"
"Bug Tracker" = "https://github.com/sgl-project/sglang/issues"
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[tool.setuptools.package-data]
"sglang" = [
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"srt/layers/moe/fused_moe_triton/configs/*/*.json",
"srt/layers/quantization/configs/*.json",
"srt/mem_cache/storage/hf3fs/hf3fs_utils.cpp",
]
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[tool.setuptools.packages.find]
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exclude = [
"assets*",
"benchmark*",
"docs*",
"dist*",
"playground*",
"scripts*",
"tests*",
]
[tool.wheel]
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exclude = [
"assets*",
"benchmark*",
"docs*",
"dist*",
"playground*",
"scripts*",
"tests*",
]
[tool.codespell]
ignore-words-list = "ans, als, hel, boostrap, childs, te, vas, hsa, ment"
skip = "*.json,*.jsonl,*.patch,*.txt"