fix(openai-compat): reuse cached engine instances in _resolve_engine - #1614
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The direct engine-ID path in /v1/audio/speech constructed a fresh backend per request (return cls()). For SubprocessBackend engines that meant: a new sidecar process, a full torch import and an engine model reload on EVERY request (measured ~28s floor per pockettts request on an M3 Pro), plus another atexit hook registration each time — exactly what get_engine_instance_for()'s docstring warns against. Route the explicit-ID path through the same cached-singleton seam the active-engine path already uses. Unknown/unavailable IDs keep their 400s; tts-1/tts-1-hd and the OmniVoiceBackend special case are unchanged.
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📝 WalkthroughWalkthroughThe OpenAI-compatible router now caches explicit engine instances, unloads outgoing engines during switches or return to OmniVoice, and preserves unknown-engine errors. Regression tests cover reuse, construction count, HTTP 400 responses, and unloading. ChangesOpenAI speech engine caching
Estimated code review effort: 3 (Moderate) | ~20 minutes Merge Risk: 🟠 High · up to The cached explicit-engine path can unload an engine while another request is using it, retain an old explicit engine when switching to tts-1 or tts-1-hd, and reuse an mlx-audio instance after its selected model changes. These can cause request failures, resource retention, or serving the wrong model, so the PR is not merge-ready until the lifecycle and cache-key handling are corrected. Suggested reviewers: 🚥 Pre-merge checks | ✅ 6 | ❌ 3❌ Failed checks (3 warnings)
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Actionable comments posted: 1
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Inline comments:
In `@backend/api/routers/openai_compat.py`:
- Around line 183-186: Update the /engines/select model-change flow to
invalidate the cached MLXAudioBackend instance when mlx_audio_model_id changes:
unload the existing instance and remove its get_engine_instance_for() cache
entry before future requests reuse it. Preserve the singleton behavior for
unchanged models, and add a regression test confirming a new instance is created
with the selected model.
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| Filename | Overview |
|---|---|
| backend/api/routers/openai_compat.py | Reuses cached explicit engines and adds pre-warm eviction, but previously reported active-use synchronization and active-instance reconciliation defects remain. |
| tests/test_openai_speech_engine_cache.py | Covers singleton reuse, unknown IDs, and sequential explicit-engine eviction, but not the two outstanding lifecycle paths. |
| CHANGELOG.md | Adds a correctly formatted Unreleased entry describing cached engine reuse and single-engine residency. |
Reviews (4): Last reviewed commit: "Merge main into fix/openai-speech-engine..." | Re-trigger Greptile
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Review follow-up (Greptile/CodeRabbit on debpalash#1614): caching instances without a switch rule would let each distinct explicit engine ID stay resident, accumulating sidecars / multi-GB in-process models. Mirror get_active_tts_backend's MM2-01 switch rule: a different explicit ID (omnivoice included, which resolves to the active engine) unloads the outgoing instance first, best-effort.
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Valid finding — fixed in 13c14e2: explicit-ID switches now mirror get_active_tts_backend's MM2-01 rule (unload the outgoing engine first, best-effort), with a regression test. OmniVoiceBackend explicit requests also unload the outgoing explicit engine before resolving to the active one. |
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Actionable comments posted: 3
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Inline comments:
In `@backend/api/routers/openai_compat.py`:
- Around line 201-204: The active-engine alias handling in the OpenAI-compatible
router must also unload any previously loaded explicit engine before returning
the active backend. Update the tts-1 and tts-1-hd alias path to clear
_explicit_engine through the existing cleanup mechanism, preserving the
subsequent get_active_tts_backend() behavior.
- Around line 201-213: Update the explicit-engine lifecycle around
_unload_explicit_engine and get_engine_instance_for to track in-flight requests,
including requests awaiting ensure_ready() or generation. When switching model
IDs, defer unloading the outgoing engine until its active-request count reaches
zero, then release it; preserve reuse of the cached singleton and immediate
unloading when the engine is idle.
In `@tests/test_openai_speech_engine_cache.py`:
- Around line 67-100: Extend the cache tests with an
explicit-engine-to-“omnivoice” transition case, using the existing
_resolve_engine test setup and unload tracking. Assert the explicitly resolved
engine is unloaded before the active backend is resolved, covering the cleanup
path in _resolve_engine and preserving the existing explicit-ID switch behavior.
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Reviewed — the diagnosis and the fix are both right, and the measured ~28s → single-digit is a real win. Two notes, one of which is me retracting a concern: Not a problem (checked): I went looking for a race on the new module-global That safety is invisible in the code, though, and it's one refactor deep — dropping Blocking: Happy to land it as soon as the changelog entry is in and CI reports. |
… not a router-local cache The explicit-ID unload cache (13c14e2) kept its own instance ref keyed by model id. The shared engine cache is deliberately keyed by CLASS (registry rebinds, idle sweeps and engine_memory eviction all mutate it), so the router's id-keyed ref could go stale and keep serving an instance the lifecycle system no longer tracked — caught by test_openai_speech_toggle_off_sends_raw_text in full-suite order, and it also introduced a novel unload path that ignored the OMNIVOICE_SINGLE_ENGINE_RESIDENT opt-out. Drop the router-local cache entirely: _resolve_engine returns the shared cached singleton (get_engine_instance_for), and create_speech calls evict_other_tts_engines(backend.id) before warming the engine — the exact seam /generate uses. That covers every transition (explicit id → explicit id, explicit id → tts-1/omnivoice aliases), honors the policy opt-out, and leaves no per-router state to drift. Regression pinned at the route level in test_speech_request_evicts_other_resident_engines.
415 chars against the 400 the style test allows — CI would have failed on it.
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Both items resolved — the shared-seam restructure is better than the comment I asked for (no router-local state left to reason about), and the changelog entry is in. One maintainer commit on top: your entry ran 415 chars against the 400-char one-liner limit |
2 participants
What
_resolve_enginein/v1/audio/speechconstructed a fresh backend instance per request (return cls()) whenever the client passes an explicit engine ID asmodel. For SubprocessBackend engines (pockettts, omnivoice-subprocess, ...) each request therefore:SubprocessBackendatexit hook (the leakget_engine_instance's docstring explicitly warns about),The fix routes the explicit-ID path through the existing cached-singleton seam,
get_engine_instance_for— the same reuse thetts-1/tts-1-hdpath already gets via the active-engine instance.Behavior preserved
tts-1/tts-1-hdand theOmniVoiceBackend→ active-engine special case untouched.Testing
tests/test_openai_speech_engine_cache.py: two resolves of the same explicit ID return the same instance with exactly one construction; unknown IDs still 400./v1/audio/speechnow reuses cached engine instances for explicit engine IDs and unloads the outgoing engine when the ID changes. This prevents repeated subprocess creation, Torch imports, model loads, andatexitregistrations. Tests verify reuse, unloading, and unchanged 400 responses for unknown IDs.