--extra-index-url https://pypi.nvidia.com
# PyG-style wheels for native graph ops (torch-scatter etc.) keyed to our
# torch+CUDA combo (torch 2.11.0+cu130). MeshGraphNet (used by XMGN/FiGNet)
# requires these; no source-build fallback if a wheel is missing.
--find-links https://data.pyg.org/whl/torch-2.11.0+cu130.html

# HF Spaces' base build appends ``gradio==X``, ``spaces==X``, ``torch<=X``,
# ``uvicorn>=X``, ``websockets>=X`` to the pip install command. Pinning those
# here would cause "ResolutionImpossible" conflicts; let HF manage their
# stack and only pin app-specific deps.
huggingface_hub==1.14.0

# Scientific / mesh stack
numpy==1.26.4
pyvista==0.48.2
plotly==6.7.0
trimesh==4.12.2

# warp-lang is the actual PyPI name (not "nvidia-warp-lang")
warp-lang==1.13.0

# GPU KNN backend used by DoMINO (and faster path for other models). Without
# cuml, physicsnemo's KNN falls back to a naive torch O(N·M) pairwise that
# OOMs on 750k-cell DrivAerML meshes. Both come from pypi.nvidia.com.
# physicsnemo @ d0aebb09 declares required_imports=("cuml>=26.2.0",) on its
# KNN dispatch, so older cuml versions (25.x) are reported "unavailable" at
# runtime and KNN falls back to the OOM-prone naive torch impl.
cuml-cu13==26.2.0
cupy-cuda13x==13.6.0

# MeshGraphNet (XMGN, FiGNet) requires torch-scatter; physicsnemo raises
# ImportError without it. Pulled from PyG's --find-links above.
torch-scatter==2.1.2

# Neither nvidia-physicsnemo nor nvidia-physicsnemo-cfd is on PyPI yet.
# Pin both to specific commits so the Space build is reproducible.
nvidia-physicsnemo @ git+https://github.com/NVIDIA/physicsnemo.git@d0aebb096327e2ab5c35dc64068868c52cd13258
nvidia-physicsnemo-cfd @ git+https://github.com/NVIDIA/physicsnemo-cfd.git@62fe76fc8ecf93872586d2338781cbe2b6af3bd4