The GpuPassthroughRemediationProvider probed GPU passthrough by exec'ing `nvidia-smi` inside nomad_ollama. When Ollama was created CPU-only — most commonly because the NVIDIA container runtime was registered with Docker only AFTER the AI Assistant was first installed (DockerService attaches a GPU DeviceRequest only when 'nvidia' is in docker.info().Runtimes at install time) — the container ships no nvidia-smi, so the exec returned an error string whose letters the alphabetic-output check mistook for "passthrough healthy". That false negative suppressed all auto-remediation, leaving Ollama silently stuck on CPU (models run at a fraction of a token per second) until the user manually clicked "Fix: Reinstall AI Assistant". Replace the nvidia-smi probe with Ollama's own "inference compute" startup log line — the ground truth for whether a GPU backend actually loaded — via a new, unit-tested classifyOllamaComputeBackend() helper. One signal covers both the "created CPU-only" case and the original "DeviceRequests present but the toolkit binding tore" case. Add a cooldown on gpu.autoRemediatedAt so a GPU that genuinely cannot be accelerated (an architecture Ollama has no kernels for) does not trigger a reinstall on every admin boot. Co-Authored-By: Claude <noreply@anthropic.com> |
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| .. | ||
| gpu_passthrough_remediation_provider.ts | ||
| kiwix_migration_provider.ts | ||
| map_static_provider.ts | ||
| qdrant_restart_policy_provider.ts | ||
| version_check_provider.ts | ||