The worker answered model.unload by calling Free on the first backend
process in its map, whatever model the request named. Every idle
scale-down or LRU eviction of one model could therefore empty another
model's backend on the same node. LocalAI still counted that model as
loaded, so its next request failed. A parakeet diarization model then
returned 501 "speaker profiles require a loaded speaker encoder" until
someone reloaded it by hand.
Resolve the target from the model name (all replicas), prefer an
address when the request carries one, and free nothing for an unknown
model.
Also let parakeet-cpp Diarize check the diarization model before the
speaker-profile capability. A backend with nothing loaded now answers
FailedPrecondition, which LocalAI treats as a stale replica and
reloads, instead of a final Unimplemented.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Claude Sonnet 5.5 <noreply@anthropic.com>
* feat(schema): validate portable speaker profiles
Add the versioned profile schema for explicit speaker enrollment.
Validate compatibility against separately supplied loaded-encoder metadata.
Reject unusable speakers, invalid vectors, and inconsistent clean spans.
This slice does not change HTTP routes, backend integration, or the UI.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parakeet): export profiles with transcripts
Export opt-in speaker profiles and trusted encoder metadata.
Replay registrations by ID so duplicate display names keep independent
vectors.
Use one profile-capable diarization for slots, names, and clean spans.
Assign timestamped ASR words to those slots without a second diarization.
Preserve legacy opt-out and no-ASR behavior, and propagate failures.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(audio): enroll portable speaker profiles
Gate profile exports with voice-recognition permission and validate
registration against metadata from the loaded encoder. Preserve audio
enrollment and independent registrations with duplicate display names.
Exclude diarization and registration exchanges before API trace capture
so persisted traces cannot retain profile vectors or JSON audio.
Defer candidate dimensions to trusted loaded metadata. Sort candidates
by registration ID so incompatible profiles cannot suppress legacy voices
through registry iteration order. Keep portable identity checks closed
when trusted metadata is unavailable.
Test persisted traces, explicit slot zero, and selection through offline
and live transport. Document privacy and the ephemeral registry lifecycle.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(ui): remember speakers from diarization
Add a Studio page for diarization and opt-in speaker profiles. Preview
clean intervals from the original recording before explicit registration.
Join profiles by raw speaker labels, preserve duplicate names, and relabel
turns only after a successful save. Discard stale results when the model
or recording changes. Share registration metadata with voice management
without storing vectors or recordings from this flow.
Document permissions and the global, ephemeral registry. Cover enrollment,
permissions, previews, and asynchronous races with mocked Playwright tests.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: clarify HTTP speaker enrollment support
Replace the stale enrollment limitation with the current HTTP workflow.
Distinguish native transport from explicit registration and link its docs.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* chore(parakeet): pin merged speaker profile support
Use the merged commit from mudler/parakeet.cpp#80.
Its tree matches the previously accepted native pin.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs: add diarization enrollment setup example
Connect the existing gallery modes to the speaker enrollment workflow.
Show installation, private profile export, explicit raw-slot registration,
and later recognition without another export.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs(blog): explain diarization speaker profiles
Put the diarization walkthrough on the LocalAI website in the feature PR.
Cover the three gallery modes, explicit enrollment, and privacy limits.
Link setup instructions and keep availability conditional on feature support.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs(blog): focus diarization on everyday use
Explain what users can do with recordings before the setup steps.
Replace the technical walkthrough with a short Studio guide and link
readers to the existing reference for model names and developer use.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs(blog): lead with speaker capabilities
Present speaker recognition through everyday uses and a short UI flow.
Keep technical reference details in the existing documentation.
Assisted-by: OpenAI:unknown
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(diarization): satisfy Go lint checks
Avoid copying protobuf message state when extending backend status, check the multipart reader close result, and document the focused testing.T lint exemptions.
Assisted-by: nib:gpt-5.6-sol
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
