gaia/pyproject.toml at main · amd/gaia · GitHub

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[tool.black]
line-length = 88
target-version = ['py312']
exclude = '''
(
  /(
    | \.eggs
    | \.git
    | \.hg
    | \.mypy_cache
    | \.tox
    | \.venv
    | _build
    | buck-out
    | node_modules
  )/
)
'''

[tool.isort]
profile = "black"
line_length = 88
skip_gitignore = true
skip = [".git", "__pycache__", "venv", ".venv", ".mypy_cache", ".tox", ".eggs", "_build", "buck-out", "node_modules"]

[tool.mypy]
python_version = "3.12"
warn_return_any = true
warn_unused_configs = true
ignore_missing_imports = true
exclude = [
    "^venv/",
    "^.venv/",
    "^node_modules/",
]

[tool.bandit]
exclude_dirs = [".git", "__pycache__", "venv", ".venv", ".mypy_cache", ".tox", ".eggs", "_build", "buck-out", "node_modules"]
skips = ["B101"]  # Skip assert warnings (common in tests)

[tool.pytest.ini_options]
markers = [
    "slow: marks tests as slow (real Docker operations, may take > 5 seconds)",
    "integration: marks tests as integration tests (require external services like Lemonade server)",
]
testpaths = ["tests"]
python_files = ["test_*.py"]
python_classes = ["Test*"]
python_functions = ["test_*"]
addopts = "--tb=short --strict-markers"
asyncio_mode = "auto"

# UV configuration for PyTorch CPU-only builds
# GAIA is optimized for AMD hardware and doesn't require NVIDIA/CUDA dependencies
# This ensures torch, torchvision, and torchaudio are installed from CPU-only index
[[tool.uv.index]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
explicit = true

[tool.uv.sources]
torch = [{ index = "pytorch-cpu" }]
torchvision = [{ index = "pytorch-cpu" }]
torchaudio = [{ index = "pytorch-cpu" }]