3 Commits

Include renames

Author	SHA1	Message	Date
bvandeusenandClaude Opus 5.5	cc53d8db7b	feat: a GPU agent on the CPU shows as degraded, in the System view and on its own page (4410) ... torch and onnxruntime both fall back to the CPU without raising, so the agent that ran CPU-bound for weeks after a driver update leased and checked in like a healthy one. - The agent sends its startup accel report on every lease and heartbeat. - The server keeps a bounded copy on the roster row. A running agent with a runtime off the GPU becomes `degraded`, with a sentence naming the runtime and the reason. - The top nav shows it amber. - The agent page carries a banner, and its pill reads "CPU only". Also: the bandwidth field gets the page's − / + stepper, and both number fields drop the browser's spin arrows. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LVjrnpQjRgHdvq95rASoiR	2026-09-24 19:09:07 -04:00
bvandeusenandClaude Opus 5.5	42a40d71a4	fix: the agent's ONNX check asks CUDA for a device instead of trusting that the libraries loaded (1451) ... It reported "onnx on GPU" beside torch failing cuInit with "CUDA unknown error". Every library resolved, but no device could be used. The check now calls cudaGetDeviceCount and reports the CUDA error when there is one. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01LVjrnpQjRgHdvq95rASoiR	2026-09-24 18:28:26 -04:00
bvandeusenandClaude Opus 5.5	7a09dc3cda	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	2026-09-24 17:45:39 -04:00