- Pin torch==2.6.0+cu126 and torchvision==0.21.0+cu126 in feature
manifest to prevent NCCL symbol mismatch on CUDA 12.6 base images
- Move lpips after torch in install order to prevent wrong version
resolution from PyPI
- Add einops to upscale-enhance common deps (required by SCUNet)
- Update cpu_fallback_packages to handle multi-package CUDA torch
entries on amd64 without GPU
- Fix gpu.py ONNX CUDA detection: replace hardcoded .so path with
cross-platform session smoke-test
- Fix os.dup(1) crashes on Windows in upscale, enhance_faces, and
noise_removal by wrapping in try/except with sys.stderr fallback
- Guard top-level numpy/cv2 imports in colorize.py and restore.py
with helpful error messages
- Add weights_only=False fallback for torch.load in noise_removal
- Fix integration tests to accept 501 for uninstalled AI features
and 422 for missing system tools (exiftool, libheif)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Authoritative JSON manifest defining all 6 AI feature bundles with:
- Exact pip package versions and platform-specific variants (amd64/arm64)
- pip flags (--no-deps for codeformer, --extra-index-url for torch/paddle)
- postInstall re-pins (numpy==1.26.4 after codeformer)
- Model download entries (direct URL, rembg sessions, HuggingFace snapshots)
- Bundle-to-tool mapping matching shared/features.ts
Used by install_feature.py at runtime to install bundles on demand.
