pyproject.toml

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "cinemap"
version = "0.1.0"
description = "CineMap — agentic video generation for large-scale EM segmentation data (Neuroglancer + Blender, Claude-directed keyframe timeline)"
readme = "plan.md"
requires-python = ">=3.11"
authors = [{ name = "zouinkhim" }]

# Python runtime dependencies. Add new deps HERE, then:
#   conda run -n mv_env pip install -e .
# (Blender ships as the `bpy` pip wheel below — installed by `pip install -e .`.)
dependencies = [
  # --- backend / API ---
  "fastapi",
  "uvicorn[standard]",
  "websockets",
  "pydantic>=2",
  "python-multipart",
  # --- agent ---
  "anthropic",
  # --- visualization / state ---
  "neuroglancer",
  "selenium",       # drives neuroglancer.webdriver for headless screenshots
                    # (needs chromium + chromedriver binaries, installed into mv_env via conda-forge)
  # --- data access ---
  "cloud-volume",   # precomputed volumes + meshes
  "tensorstore",    # zarr/n5/ome-zarr array + metadata reads
  "zarr<3",         # cloud-volume / ome compatibility
  "trimesh",        # mesh load/convert for Blender import
  "scikit-image",   # marching-cubes mesh generation from label volumes
  # --- blender (render worker) ---
  "bpy",            # Blender as a Python module (Cycles); run in a subprocess script for isolation
  # --- core ---
  "numpy<2",        # bpy 5.x requires numpy<2; keep the whole env on 1.x
  "pillow",
  "imageio-ffmpeg", # bundles an ffmpeg binary (don't rely on a system ffmpeg on PATH)
  "scipy",          # slerp / interpolation helpers
]

[project.optional-dependencies]
dev = ["ruff", "pytest"]

[tool.hatch.build.targets.wheel]
packages = ["src/cinemap"]

[tool.ruff]
line-length = 100
target-version = "py311"