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https://github.com/Crosstalk-Solutions/project-nomad.git
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c16cfc3a93
The previous lspci-based GPU detection fails inside Docker containers because lspci isn't available, causing Ollama to always run CPU-only even when a GPU + NVIDIA Container Toolkit are present on the host. Replace with Docker API runtime check (docker.info() -> Runtimes) as primary detection method. This works from inside any container via the mounted Docker socket and confirms both GPU presence and toolkit installation. Keep lspci as fallback for host-based installs and AMD. Also add Docker-based GPU detection to benchmark hardware info — exec nvidia-smi inside the Ollama container to get the actual GPU model name instead of showing "Not detected". Tested on nomad3 (Intel Core Ultra 9 285HX + RTX 5060): AI performance went from 12.7 tok/s (CPU) to 281.4 tok/s (GPU) — a 22x improvement. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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| app | ||
| bin | ||
| commands | ||
| config | ||
| constants | ||
| database | ||
| docs | ||
| inertia | ||
| providers | ||
| public | ||
| resources/views | ||
| start | ||
| tests | ||
| types | ||
| util | ||
| views | ||
| .editorconfig | ||
| .env.example | ||
| ace.js | ||
| adonisrc.ts | ||
| eslint.config.js | ||
| package-lock.json | ||
| package.json | ||
| tailwind.config.ts | ||
| tsconfig.json | ||
| vite.config.ts | ||