AngelSlim/setup.py at main · Tencent/AngelSlim · GitHub

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# Copyright 2025 Tencent Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Setup for pip package."""
import subprocess

from setuptools import find_packages, setup

BASE_VERSION = None

if "main" in subprocess.getoutput("git branch"):
    BASE_VERSION = "0.0.0_dev"
else:
    tag_list = subprocess.getoutput("git tag").split("\n")
    BASE_VERSION = tag_list[-1]


def get_version_with_cuda_torch():
    """Generate version string with CUDA and PyTorch version suffix.

    Example: 0.0.0_dev+cu128.torch2.10
    """
    try:
        import torch

        # Get CUDA version (e.g., "12.8" -> "128")
        cuda_version = torch.version.cuda
        if cuda_version:
            cuda_version = cuda_version.replace(".", "")
        else:
            cuda_version = "cpu"

        # Get PyTorch version (e.g., "2.10.0" -> "2.10")
        torch_version = torch.__version__.split("+")[0]  # Remove any existing suffix
        torch_major_minor = ".".join(torch_version.split(".")[:2])

        return f"{BASE_VERSION}+cu{cuda_version}.torch{torch_major_minor}"
    except ImportError:
        # torch not installed, return base version
        return BASE_VERSION


TOOLS_VERSION = get_version_with_cuda_torch()


def get_requirements(filename):
    """Load dependency packages from specified requirements file"""
    with open(filename) as f:
        return [
            line.strip()
            for line in f.readlines()
            if line.strip() and not line.startswith(("#", "-"))
        ]


setup(
    name="angelslim",
    version=TOOLS_VERSION,
    description=("A toolkit for compress llm model."),
    long_description="Tools for llm model compression",
    url="https://github.com/Tencent/AngelSlim",
    author="Tencent Author",
    # Core dependencies: installed by default
    install_requires=get_requirements("requirements/requirements.txt"),
    # Define optional dependency groups
    extras_require={
        # Install all optional features: pip install angelslim[all]
        "all": (
            get_requirements("requirements/requirements_speculative.txt")
            + get_requirements("requirements/requirements_diffusion.txt")
            + get_requirements("requirements/requirements_multimodal.txt")
            + get_requirements("requirements/requirements_benchmark.txt")
        ),
        # Install speculative sampling functionality: pip install angelslim[speculative]
        "speculative": get_requirements("requirements/requirements_speculative.txt"),
        # Install Diffusion functionality: pip install angelslim[diffusion]
        "diffusion": get_requirements("requirements/requirements_diffusion.txt"),
        # Install multimodal functionality: pip install angelslim[multimodal]
        "multimodal": get_requirements("requirements/requirements_multimodal.txt"),
        # Install benchmark functionality: pip install angelslim[benchmark]
        "benchmark": get_requirements("requirements/requirements_benchmark.txt"),
    },
    packages=find_packages(),
    python_requires=">=3.0",
    # PyPI package information.
    classifiers=[
        "Development Status :: 4 - Beta",
        "Intended Audience :: Developers",
        "Intended Audience :: Education",
        "Intended Audience :: Science/Research",
        "License :: OSI Approved :: Apache Software License",
        "Programming Language :: Python :: 3.8",
        "Programming Language :: Python :: 3.9",
        "Programming Language :: Python :: 3.10",
        "Programming Language :: Python :: 3.12",
        "Topic :: Scientific/Engineering",
        "Topic :: Scientific/Engineering :: Mathematics",
        "Topic :: Scientific/Engineering :: Artificial Intelligence",
        "Topic :: Software Development",
        "Topic :: Software Development :: Libraries",
        "Topic :: Software Development :: Libraries :: Python Modules",
    ],
    license="License for AngelSlim",
    keywords=("Tencent large language model model-optimize compression toolkit."),
)