[build-system]
requires = ["setuptools>=77", "wheel"]
build-backend = "setuptools.build_meta"

[project]
name = "sgjm"
version = "2026.6.5"
description = "Speculative Graph JEPA Model — hybrid Mamba-2/attention speculative decoder, MLX + PyTorch (CUDA/ROCm) training"
readme = "README.md"
requires-python = ">=3.10"
license = "Apache-2.0"
license-files = ["LICENSE", "NOTICE"]
authors = [{ name = "Adam Pippert", email = "adam.pippert@gmail.com" }]
keywords = ["speculative-decoding", "mamba", "jepa", "language-model", "mlx", "pytorch"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: Apache Software License",
    "Programming Language :: Python :: 3",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
]
dependencies = []

[project.urls]
Homepage = "https://github.com/AdamPippert/SGJM"
Repository = "https://github.com/AdamPippert/SGJM"
"Model Card" = "https://huggingface.co/CoastalDigitalResearch/SGJM"

[project.optional-dependencies]
# Pick exactly one backend extra plus dev:
#   pip install -e '.[cpu,dev]'                         # any platform, slow
#   pip install -e '.[cuda,dev]'                        # NVIDIA + CUDA wheels (default PyPI)
#   pip install -e '.[mlx,dev]'                         # macOS Apple Silicon (M1/M2/M3/M4)
# ROCm/Strix Halo: do NOT use the [rocm] extra alone — torch ROCm wheels live
# on a separate index. Install with:
#   pip install --index-url https://download.pytorch.org/whl/rocm6.2 torch
#   pip install -e '.[rocm,dev]'
cpu = ["torch>=2.4", "numpy>=1.26"]
cuda = ["torch>=2.4", "numpy>=1.26"]
rocm = ["numpy>=1.26"]
mlx = ["mlx>=0.18", "numpy>=1.26"]
# HuggingFace publishing glue (config/modeling adapter + checkpoint converter).
# Needs a torch backend extra too (cpu/cuda/rocm) to actually build a model.
hf = ["transformers>=4.40", "safetensors>=0.4"]
dev = ["pytest>=8.0"]

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

[tool.pytest.ini_options]
testpaths = ["tests"]
addopts = "-q"