build: the agent installs one CUDA-13 stack instead of two, the web image drops ML packages it never imported, and Redis moves to 8 (1451, 1452)

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

Dockerfile

@@ -36,11 +36,6 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
         libwebp7 \
         libpng16-16 \
         ca-certificates \
-    # opencv-python-headless (via requirements-ml.txt) links these even in its
-    # headless build. Came from Dockerfile.ml when the images merged
-    # (milestone 422 step 6).
-        libgl1 \
-        libglib2.0-0 \
     && rm -rf /var/lib/apt/lists/*
 
 WORKDIR /app
@@ -61,7 +56,8 @@ RUN pip install -r requirements.txt
 #
 #   torch 2.12.1+cpu wheel     192.3 MB
 #   torchvision 0.27.1+cpu       1.8 MB
-#   transformers / onnxruntime / opencv / sklearn and friends
+#   transformers / onnxruntime / opencv / sklearn and friends (opencv and
+#   onnxruntime since dropped, #1451 — nothing here imported them)
 #                               62.0, 35.3, 23.6, 16.7, 12.3, 9.2, 6.9 MB
 #   largest newly-pushed layer 222.07 MB
 #
@@ -85,7 +81,7 @@ RUN pip install -r requirements.txt
 # CPU-only torch from the PyTorch CPU index. Nothing here uses a GPU — the
 # GPU agent is a separate service with its own image.
 RUN pip install --index-url https://download.pytorch.org/whl/cpu \
-        "torch>=2.12,<3.0" "torchvision>=0.27,<0.28"
+        "torch>=2.14" "torchvision>=0.29"
 RUN pip install -r requirements-ml.txt
 
 # Where the model lands. Deliberately NOT a VOLUME instruction: that mints an