bvandeusenandClaude Opus 5.5
7a09dc3cda
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Agent: - The image ran PyPI's CUDA-13 torch 2.14 and onnxruntime-gpu 1.30 on a CUDA 12.9 cudnn-runtime base. requirements.txt had silently replaced the Dockerfile's torch 2.6+cu124, because ultralytics pulls torchvision, which pulls its own torch. That left ~3 GB of base libraries and a ~3 GB torch nothing loaded: 10 GB compressed. - Now: an nvidia/cuda 13.0.3 `base` image, with torch and torchvision installed together from cu130. CUDA and cuDNN come from the nvidia-* pip packages; onnxruntime-gpu declares its [cuda,cudnn] extras. - fc_agent/accel.py preloads those libraries for onnxruntime. It then logs, and reports in /status, whether torch and the ONNX CUDA provider actually got the GPU, since both fall back to the CPU silently. Web image: - Drop opencv-python-headless and onnxruntime, plus the opencv-only apt libs. Both have been listed since the scaffold and nothing in backend/ imports them. - torch/torchvision move to 2.14/0.29, and the unexplained caps are lifted (rule 154). Redis: 8-alpine in both compose files and both CI service containers. That gives an AGPLv3 licence option, where 7.4 was RSAL/SSPL only. The client moves to >=8.1. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LVjrnpQjRgHdvq95rASoiR
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895 B
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21 lines
895 B
Plaintext
# CCIP + figure detection (ONNX models, auto-downloaded from HuggingFace).
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dghs-imgutils>=0.4
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# GPU inference for the ONNX models. Swap to onnxruntime (CPU) for a slow
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# server-side fallback run. The extras declare the CUDA/cuDNN pip packages its
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# CUDA provider loads (fc_agent/accel.py preloads them) rather than relying on
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# torch happening to install the same ones.
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onnxruntime-gpu[cuda,cudnn]
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# The crop EMBEDDER (concept bag). torch + torchvision are installed separately
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# in the Dockerfile from the cu130 wheel index, so pip never swaps them out;
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# transformers loads whatever SigLIP-family model the server announces.
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transformers>=4.45
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# Crop PROPOSERS — small YOLO detectors (booru_yolo anatomy, COCO person, comic
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# panel) that decide where to crop. Uses the torch already installed above.
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ultralytics>=8.3
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# Control surface + HTTP.
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fastapi
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uvicorn[standard]
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requests
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pillow
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numpy
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