98 lines
3.4 KiB
TOML
98 lines
3.4 KiB
TOML
[build-system]
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requires = ["setuptools>=61.0", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "sglang"
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version = "0.4.2.post4"
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description = "SGLang is yet another fast serving framework for large language models and vision language models."
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readme = "README.md"
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requires-python = ">=3.8"
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license = { file = "LICENSE" }
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classifiers = [
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"Programming Language :: Python :: 3",
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"License :: OSI Approved :: Apache Software License",
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]
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dependencies = ["requests", "tqdm", "numpy", "IPython", "setproctitle"]
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[project.optional-dependencies]
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runtime_common = [
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"aiohttp", "decord", "fastapi",
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"hf_transfer", "huggingface_hub", "interegular", "modelscope",
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"orjson", "packaging", "pillow", "prometheus-client>=0.20.0",
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"psutil", "pydantic", "python-multipart", "pyzmq>=25.1.2",
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"torchao>=0.7.0", "uvicorn", "uvloop", "xgrammar>=0.1.10"
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]
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srt = [
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"sglang[runtime_common]", "cuda-python",
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"sgl-kernel>=0.0.3.post5", "torch", "vllm>=0.6.4.post1,<=0.7.2",
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"flashinfer_python>=0.2.0.post2", "outlines>=0.0.44,<=0.1.11"
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]
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# HIP (Heterogeneous-computing Interface for Portability) for AMD
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# => base docker rocm/vllm-dev:20241022, not from public vllm whl
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srt_hip = ["sglang[runtime_common]", "torch", "vllm==0.6.7.dev2", "outlines==0.1.11", "sgl-kernel>=0.0.3.post1"]
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# xpu is not enabled in public vllm and torch whl,
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# need to follow https://docs.vllm.ai/en/latest/getting_started/xpu-installation.htmlinstall vllm
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srt_xpu = ["sglang[runtime_common]", "outlines>=0.0.44,<0.1.0"]
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#For Intel Gaudi(device : hpu) follow the installation guide
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#https://docs.vllm.ai/en/latest/getting_started/gaudi-installation.html
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srt_hpu = ["sglang[runtime_common]", "outlines>=0.0.44,<0.1.0"]
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# CPU: currently, there are no pre-built vllm wheels for CPU.
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# To install vllm for CPU, please follow the instruction here:
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# https://docs.vllm.ai/en/latest/getting_started/installation/cpu/index.html
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srt_cpu = ["sglang[runtime_common]", "torch", "outlines>=0.0.44,<0.1.0"]
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openai = ["openai>=1.0", "tiktoken"]
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anthropic = ["anthropic>=0.20.0"]
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litellm = ["litellm>=1.0.0"]
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torch_memory_saver = ["torch_memory_saver"]
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test = [
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"jsonlines",
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"matplotlib",
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"pandas",
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"sentence_transformers",
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"accelerate",
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"peft",
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]
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all = ["sglang[srt]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]
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all_hip = ["sglang[srt_hip]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]
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all_xpu = ["sglang[srt_xpu]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]
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all_hpu = ["sglang[srt_hpu]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]
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all_cpu = ["sglang[srt_cpu]", "sglang[openai]", "sglang[anthropic]", "sglang[litellm]"]
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dev = ["sglang[all]", "sglang[test]"]
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dev_hip = ["sglang[all_hip]", "sglang[test]"]
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dev_xpu = ["sglang[all_xpu]", "sglang[test]"]
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dev_hpu = ["sglang[all_hpu]", "sglang[test]"]
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dev_cpu = ["sglang[all_cpu]", "sglang[test]"]
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[project.urls]
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"Homepage" = "https://github.com/sgl-project/sglang"
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"Bug Tracker" = "https://github.com/sgl-project/sglang/issues"
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[tool.setuptools.package-data]
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"sglang" = ["srt/layers/moe/fused_moe_triton/configs/*.json", "srt/layers/quantization/configs/*.json"]
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[tool.setuptools.packages.find]
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exclude = [
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"assets*",
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"benchmark*",
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"docs*",
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"dist*",
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"playground*",
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"scripts*",
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"tests*",
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]
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[tool.wheel]
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exclude = [
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"assets*",
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"benchmark*",
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"docs*",
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"dist*",
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"playground*",
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"scripts*",
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"tests*",
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]
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