Round 8 reviewer surfaced event-loop stalls (blocking unload from
async routes), incomplete VRAM handoff coverage (is_active /
loading_models / is_export_active not checked), token leaks via
exception messages, /v1 exposure, and several fail-open paths.
Async / event-loop
* routes/inference.py /images/unload, GGUF chat-load handoff,
safetensors chat-load handoff: blocking DiffusionBackend.unload
pushed onto asyncio.to_thread. unload takes _load_lock +
_generate_lock and can block for the full duration of an
in-flight load / generation, which was freezing the FastAPI
worker, SSE stream, and hardware poller for minutes.
* routes/export.py + routes/training.py: same to_thread wrap on
diffusion unload during checkpoint / training start.
GPU-owner handoff completeness
* core/inference/diffusion.py _release_chat_backend_for_diffusion:
llama-server now also unloaded when is_active=True (mid-download
/ startup), not only when is_loaded; flushed in-flight
safetensors loads from loading_models too.
* core/inference/diffusion.py _release_other_gpu_owners_for_
diffusion: export shutdown now also fires when
is_export_active() returns True (checkpoint not yet assigned).
Security / scrubbing
* core/inference/diffusion.py: load failure paths now scrub
hf_token from both _last_error AND the raised RuntimeError
message (the previous scrub only cleared frame locals).
Falls back to a regex strip of hf_[A-Za-z0-9]{20,} to
catch tokens that came in via huggingface_hub default caching.
* routes/inference.py: image lifecycle endpoints moved from
router to studio_router so they no longer answer under
the /v1 OpenAI-compat prefix. Studio-only side effects
(download multi-GB GGUFs, unload chat, etc.) should not be
reachable via an OpenAI-compat client.
* models/inference.py: control-char validator now also rejects
tab. Some log sinks split fields on tab; allowing it left a
log-injection surface.
Fail-closed delete guards
* routes/models.py /delete-cached: llama.cpp and safetensors
branches now fail closed with 503 when their status check
raises (matches the diffusion-side guard added earlier).
* routes/export.py: split the try/except around the training
backend so import failure falls back to 'skip' (no
core.training in this build) while a runtime failure of
get_training_backend()/is_training_active() fails closed.
* routes/models.py /delete-finetuned: diffusion guard now also
compares against relative path candidates (Path.resolve() works
on relative input). Previously a load with a relative repo_id
bypassed the guard.
CUDA cleanup ordering
* core/inference/diffusion.py: split _release() (drops local +
gc.collect) from _drain_cuda_cache() (torch.cuda.empty_cache).
Callers now drain AFTER nulling every reference so the
allocator actually reclaims the freed slabs (previously
empty_cache ran while caller still held a local, which left
the cache pinned).
Generate response (P2 #16)
* routes/inference.py: response uses status()['active_repo_id']
instead of the UI-facing repo_id, so a queued /images/load
promoting a pending model cannot mislabel the just-rendered
image with the new model's identity.
Test wiring
* tests/test_diffusion_routes.py: mount inf.studio_router on the
test app so /images/* routes are reachable now that they live
on the Studio-only router.
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