[project]
name = "operation-room-monitor-server"
version = "0.1.0"
description = "Operation room monitor API server"
requires-python = ">=3.13"
dependencies = [
    "asyncpg>=0.31.0",
    "greenlet>=3.1.0",
    "minio>=7.2.15",
    "baidu-aip>=4.16.13",
    "chardet>=7.4.3",
    "fastapi>=0.136.0",
    "loguru>=0.7.3",
    "openpyxl>=3.1.5",
    "pillow>=12.2.0",
    "pydantic-settings>=2.13.1",
    "python-multipart>=0.0.26",
    "sqlalchemy>=2.0.49",
    "ultralytics>=8.4.40",
    "uvicorn[standard]>=0.44.0",
    "rich>=15.0.0",
]

[project.scripts]
operation-room-monitor-server = "main:main"

# Use PyTorch CPU wheels from the official index so:
# - Linux Docker builds (incl. Docker Desktop on Mac) do not install NVIDIA CUDA pip bundles.
# - Native macOS still resolves to the correct macosx_* wheels from the same index.
# For NVIDIA servers, use a separate CUDA torch install or override in a dedicated prod Dockerfile.
[tool.uv]
index-strategy = "unsafe-best-match"

[[tool.uv.index]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"

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

[dependency-groups]
dev = [
    "httpx>=0.28.0",
    "pytest>=8.3.0",
    "pytest-asyncio>=0.25.0",
    "aiosqlite>=0.21.0",
]

[tool.pytest.ini_options]
asyncio_mode = "auto"
testpaths = ["tests"]