The health check now reports what unmanaged VRAM actually costs rather than just
how much of it there is: "0.82 GB held by python (842 MB)" becomes "5 model(s) fit
within 15.42 GB but not the 14.60 GB actually available", naming them.
Getting that arithmetic right took a correction. The first version subtracted only
the desktop and the unmanaged process, and so reported a 14.93 GB model as fitting
against a real ceiling of 14.60 GB -- the same model the service had just refused
with 507. ComfyUI keeps a few hundred MB of CUDA context for as long as the process
lives, which a purge does not free, so it is not available either. The floor is taken
from the minimum ComfyUI VRAM in recent telemetry rather than its current value,
which could be a 7 GB checkpoint mid-generation.
The verifier's reclaim stage now re-runs a graph immediately beforehand to reset the
30 s idle window, since a large model takes longer than that to load and the purge
was freeing ComfyUI mid-load, so the reclaim path was never reached.
Tests: 199 (was 192). The new ones pin the ceiling arithmetic, including that a model
too large to fit on the card at all is not blamed on the third-party process.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The engine subtitles were hardcoded: "FlashAttention + Q4 KV Cache" and "DynamicVRAM
+ Pinned Async Offload". The first turned out to be accurate -- OLLAMA_FLASH_ATTENTION
and OLLAMA_KV_CACHE_TYPE really are set -- which is worse than being wrong, because it
would have gone on looking accurate after the settings changed.
engines.py reads both engines' real configuration: the ollama service environment via
systemd, and ComfyUI's own /system_stats for version, allocator, VRAM mode and argv.
Exposed at GET /api/engines, as an MCP tool, and in the dashboard subtitles with the
full settings list as a tooltip.
The settings worth surfacing are the ones that dictate how this service must behave
and that previously had to be discovered by reading journald: OLLAMA_NUM_PARALLEL=1
is why an unload queues behind a running generation and is reported as deferred
rather than failed, and OLLAMA_MAX_LOADED_MODELS=1 is why every swap evicts the
previous model. Each is reported with that explanation attached.
Writing the tests found a bug in the new code: (system.get("python_version") or
"").split()[0] raises IndexError when ComfyUI omits the field, and the surrounding
except would have swallowed it and reported ComfyUI as entirely offline.
Tests: 192 (was 182).
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Self-check. Fan control failed for an entire session -- recoverably, and completely
invisibly. It appeared once, inside one field of one log line, and nothing ever
asked whether fan control worked. health.py now checks everything this service
depends on (NVML, passwordless sudo for nvidia-smi, fan control via the headless X
server, overclock drift, the telemetry store, residency measurement capability,
model directories, the ComfyUI websocket, and both upstream HTTP services) and
reports for each one what is broken, what that breaks, and how to fix it. Exposed at
GET /api/health, as an MCP tool, and as a dashboard panel that collapses to a badge
when healthy and expands to impact-and-fix when not. Current state: 9 ok, 1 degraded
(the known cachestat permission limit on Ollama's blobs).
A self-check that returns ok while a dependency is broken is worse than none, so the
tests drive each check to its failure state -- including the exact "Error resolving
target specification 'gpu:0'" string from the original incident -- and assert that a
check which raises surfaces as failed rather than taking down the endpoint.
SSE payload. The installed-model catalog was 10.6 KB of a 13.1 KB frame, 81% of the
stream, re-sent to every subscriber every second despite changing only when a model
is pulled or removed: 135 MB/hour across three tabs. It is now sent on a
subscriber's first frame and whenever the set changes; the client keeps the last
known list. Steady-state frames dropped from 14041 to 3664 bytes, a 74% reduction,
and /api/stats still returns the complete snapshot for API consumers.
Tests: 182 (was 169).
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
The stale-readback bug fixed in f5917a0 was a class, not an instance. Two more:
- ram_optimizer's residency report cached for 15s and was never invalidated when
anything warmed a file, so warming a model and then looking at residency showed
the state from before the warm. warm_file_to_ram now invalidates it.
- _PID_KIND_CACHE was keyed on pid alone and never expired. Linux recycles PIDs, so
a stale entry could attribute a new process's VRAM to Ollama or ComfyUI -- inside
the very snapshot the yield barrier trusts to decide whether VRAM was released.
Now keyed by (pid, process start time) and bounded.
Unmanaged VRAM. Investigating a persistence-mode warning turned up a third GPU
consumer this service does not model: stt_relay.py, holding 842 MB for nearly three
days. It was bucketed as "system" alongside gnome-shell's 3.9 MB. That conflation
matters, because ComfyUI's memory can be reclaimed and a third party's cannot, and
the reclaim path assumed ComfyUI was always to blame for missing headroom.
Processes are now bucketed ollama | comfy | desktop | unmanaged. The breakdown
reports desktop_gb and unmanaged_gb separately and names the unmanaged processes;
when a reclaim-and-retry still fails, the error identifies them rather than
implying ComfyUI was at fault; and the dashboard shows the unreclaimable total, so
headroom the arbitrator can never give back is visible rather than inferred.
Checked and deliberately not changed: persistence mode reads Disabled, but
nvidia-persistenced is active and two clients hold the GPU open continuously, so
the driver never unloads. The nvidia-smi warning is legacy noise here and is not a
source of the profile drift.
Tests: 169 (was 164). The new ones cover the bucketing, and one existing test used
Xorg as its "unknown process" fixture -- correct before a display server had its own
bucket, wrong after.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Tests. First automated coverage for the project: 164 tests, 2.7s, no GPU or network.
An autouse fixture stubs overclock_manager._sh -- the single choke point for every
nvidia-smi/nvidia-settings write -- so no test can mutate the card. They deliberately
pin the empirically measured constants that would otherwise rot silently: the cold and
warm load figures behind the cache-hit thresholds, the warm_confident residency rule,
and the busy/stalled yield split. One test asserts RAM_HIT_GBPS stays at or below the
measured 2.63 GB/s warm load, so the old physically unreachable 5.0 GB/s bar cannot
come back.
Three bugs the suite surfaced, now fixed:
- autotune._subsample(values, 1) divided by zero; the early return only covered
len(values) <= max_steps.
- telemetry_store.stop() flushed its local pending list but never drained the queue,
silently losing rows submitted just before a shutdown -- exactly when the last
events matter.
- ram_optimizer.page_residency's zero-byte short-circuit omitted keys every other
return path provides, so a 0-byte file was planned for warming.
Reclaim. The README has claimed bidirectional arbitration from the start, but only one
direction was ever automatic. Establishing what actually happens took a controlled test
with the service stopped: with ComfyUI holding 6.83 GB, Ollama does not spill to the CPU
on this box -- it aborts with "cudaMalloc failed: out of memory", because n_gpu_layers is
pinned to 99 and it will not reduce the layer count. So both failure modes are handled:
_check_ollama_starved watches size_vram < size for the default configuration where Ollama
does spill, and switch_ollama_model catches the hard OOM, reclaims VRAM from an idle
ComfyUI and retries once. The request that returned HTTP 500 from Ollama directly now
succeeds through HyperSwap, loading at 3.85 GB/s after reclaiming 6.83 GB.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
