""" LightX2V Setup Script Minimal installation for VAE models only """ import os from setuptools import find_packages, setup # Read the README file def read_readme(): readme_path = os.path.join(os.path.dirname(__file__), "README.md") if os.path.exists(readme_path): with open(readme_path, "r", encoding="utf-8") as f: return f.read() return "" # Core dependencies for VAE models vae_dependencies = [ "torch>=2.0.0", "numpy>=1.20.0", "einops>=0.6.0", "loguru>=0.6.0", ] # Full dependencies for complete LightX2V full_dependencies = [ "packaging", "ninja", "torch", "torchvision", "diffusers", "transformers", "tokenizers", "tqdm", "accelerate", "safetensors", "opencv-python", "numpy", "imageio", "imageio-ffmpeg", "einops", "loguru", "ftfy", "gradio", "aiohttp", "pydantic", "fastapi", "uvicorn", "requests", "decord", ] setup( name="lightx2v", version="1.0.0", author="LightX2V Team", author_email="", description="LightX2V: High-performance video generation models with optimized VAE", long_description=read_readme(), long_description_content_type="text/markdown", url="https://github.com/ModelTC/LightX2V", packages=find_packages(include=["lightx2v", "lightx2v.*"]), classifiers=[ "Development Status :: 4 - Beta", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved :: Apache Software License", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Topic :: Scientific/Engineering :: Artificial Intelligence", ], python_requires=">=3.8", install_requires=vae_dependencies, extras_require={ "full": full_dependencies, "vae": vae_dependencies, }, include_package_data=True, zip_safe=False, )