# CCIP + figure detection (ONNX models, auto-downloaded from HuggingFace).
dghs-imgutils>=0.4
# GPU inference for the ONNX models. Swap to onnxruntime (CPU) for a slow
# server-side fallback run. The extras declare the CUDA/cuDNN pip packages its
# CUDA provider loads (fc_agent/accel.py preloads them) rather than relying on
# torch happening to install the same ones.
onnxruntime-gpu[cuda,cudnn]
# The crop EMBEDDER (concept bag). torch + torchvision are installed separately
# in the Dockerfile from the cu130 wheel index, so pip never swaps them out;
# transformers loads whatever SigLIP-family model the server announces.
transformers>=4.45
# Crop PROPOSERS — small YOLO detectors (booru_yolo anatomy, COCO person, comic
# panel) that decide where to crop. Uses the torch already installed above.
ultralytics>=8.3
# Control surface + HTTP.
fastapi
uvicorn[standard]
requests
pillow
numpy