Flow-Factory/pyproject.toml at main · X-GenGroup/Flow-Factory · GitHub

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

[project]
name = "flow-factory"
version = "0.1.0"
description = "Unified RL Fine-tuning Framework for Diffusion/Flow-Matching Models"
readme = "README.md"
requires-python = ">=3.10"
license = {text = "Apache-2.0"}
authors = [
    {name = "Flow-Factory Team"}
]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Science/Research",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
]

# Core
dependencies = [
    # Deep Learning Core
    "torch>=2.6.0",
    "torchvision>=0.19.0",
    "torchaudio>=2.4.0",

    # Hugging Face Ecosystem
    "transformers>=4.57.1",
    "diffusers>=0.36.0",
    "accelerate>=1.11.0",
    "peft>=0.17.0",
    "datasets>=3.3.2",
    "tokenizers>=0.22.1",
    "huggingface-hub>=0.35.3",

    # Critical for T5/Flux
    "protobuf>=6.33.2",
    "sentencepiece>=0.2.1",

    # Basic Utils
    "imageio[ffmpeg]>=2.37.2",
    "numpy>=1.26.4",
    "pillow>=10.4.0",
    "einops>=0.8.0",
    "pydantic>=2.8.0",
    "pyyaml>=6.0",
    "requests>=2.31.0",
    "tqdm",
]

[project.optional-dependencies]
# DeepSpeed (ZeRO optimization)
deepspeed = [
    "deepspeed>=0.15.4",
]

# Quantization (8-bit/4-bit)
quantization = [
    "bitsandbytes>=0.45.3",
]

# Experiment tracking
wandb = [ "wandb" ]
swanlab = [ "swanlab" ]

nvidia = [
    "xformers>=0.0.27",
    "nvidia-ml-py",
]

all = [
    "flow-factory[deepspeed,quantization]",
]

[project.scripts]
flow-factory-train = "flow_factory.cli:train_cli"
ff-train = "flow_factory.cli:train_cli"

[tool.setuptools.packages.find]
where = ["src"]

[tool.black]
line-length = 100
target-version = ['py310', 'py311', 'py312']

[tool.isort]
profile = "black"
line_length = 100