* test(omnivoice): expose ignored duration controls
Compile the real wrapper with a model-free engine fixture. Four failing
assertions expose ignored duration, postprocessing, and validation.
Assisted-by: nib:gpt-6-astra
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* feat(omnivoice): add bounded duration controls
Validate request controls before reference reads or native output.
Preserve engine defaults when controls are omitted. Bound forced
single-shot duration to 30 seconds as wrapper resource policy.
Exercise the real native boundary, streaming rejection, and defaults
with synthetic PCM. Document quantization and postprocessing limits.
Assisted-by: nib:gpt-6-astra
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* test(omnivoice): require fixture-free ordinary tests
Expose the ordinary suite regression before isolating native fixtures.
Require selected native tests to reject a missing fixture explicitly.
Assisted-by: nib:gpt-6-astra
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(omnivoice): isolate native fixture tests
Ordinary Go tests must run without a compiled native fixture.
Select fixture specs explicitly in the dedicated gate while keeping
parser tests ordinary and native checks mandatory.
Assisted-by: nib:gpt-6-astra
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>
test: satisfy lint checks for upscale and diagnostics
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
Update stable-diffusion.cpp to its merged Iris support commit and add the original F32 Iris weights with the Qwen3-VL Q4_K_M text encoder to the model gallery.
Assisted-by: nib:gpt-5.6-sol
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(voice-detect): report the encoder family so audio-registered voices are fingerprinted
A voice registered from audio through the voice-detect backend had no
encoder fingerprint, so the parakeet-cpp backend could not tell whether
it was comparable with the loaded speaker model and could only fall back
to the file-name rule.
The voice-detect backend now binds the three new libvoicedetect accessors
with a symbol probe (an older library still loads and reports nothing),
copies the borrowed strings at once and never frees them. It also hashes
the model file once at load. VoiceEmbedResponse gains two optional
fields, encoder_family and encoder_weights ("sha256:<hex>", empty when
the model is not a plain file).
/v1/voice/register stores them as encoder_family and a new
encoder_weights field in the registry entry; model keeps the encoder
name, so the 1:N identify filter by name is unchanged for old entries.
A voice with a family is sent to the backend whatever its file name, and
the backend decides by family. /v1/voice/identify compares the family
when both the stored voice and the probe have one. Old entries load
without the fields and stay unfingerprinted.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* docs(voice-detect): say how a voice with weights but no family is treated
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
* fix(voice-detect): mark the model file open as intended for gosec
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
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>
* feat(diarization): return sound events with include_sounds
A client that wants text, speakers, voice prints and sound events had to
make a diarization call and a separate sound call. Add an include_sounds
request field to /v1/audio/diarization that adds a sounds array of closed
events {start, end, label, confidence}, in seconds.
The parakeet-cpp backend runs a tagger-only scene stream over the clip,
the same stream and thresholds the live path uses, so a clip gives the
same events offline and live. A model with no sound_model companion, or a
backend that does not report sound events, fails with 501 and the stable
code include_sounds_unsupported instead of an empty list. The proto
carries sounds_included so an empty list still means "nothing heard".
The localai-proxy backend forwards the field. Swagger, docs and the
e2e mock backend are updated.
Assisted-by: Claude:claude-sonnet-5-5 [protoc swag go]
* feat(gallery): add parakeet-cpp-multilingual-diarization-speakers-sounds
Same as parakeet-cpp-multilingual-diarization-speakers (TDT 0.6B v3,
Nemotron-3-Diarization, WeSpeaker) plus a CED-Tiny sound_model, so one
model name serves /v1/audio/diarization with include_text,
include_speaker_profiles and include_sounds. It declares the
sound_classification usecase like the realtime scene entries.
Assisted-by: Claude:claude-sonnet-5-5
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
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>
parakeet_capi_speaker_embed_pcm and parakeet_capi_free_floats, which
VoiceEmbed binds, come from this commit.
Assisted-by: Claude Code:claude-sonnet-5-5
VoiceVerify used a fixed distance of 0.5 when the request had none. Read
voice_verify_threshold, a distance in (0, 2), from the model options and
keep 0.5 as the default. The real-library spec now cuts clips from a
two-voice recording and checks the bundle embedding size, the encoder
identity, determinism and the same-voice versus different-voice distance.
Assisted-by: Claude Code:claude-sonnet-5-5
Bind parakeet_capi_speaker_embed_pcm and parakeet_capi_free_floats with a
Dlsym probe and implement VoiceEmbed on the speaker context, so a model
with a speaker_model or a bundle speaker_component can serve the
realtime voice_recognition stage and /v1/voice/*. The response carries
the sha256 identity of the encoder weights.
VoiceVerify embeds both clips and compares them by cosine distance. It
refuses anti_spoofing because there is no such head.
A libparakeet.so without the symbols answers Unimplemented, and a model
without a speaker encoder answers FailedPrecondition.
Assisted-by: Claude Code:claude-sonnet-5-5
* chore(parakeet-cpp): bump parakeet.cpp to 2de154c
Brings in the speaker registry encoder fingerprint, the VAD segment trim
and the opt-in word filter, a fix for a per-call thread count that stayed
set on the process-wide backend after a Silero VAD pass, and bundle
components loaded from memory.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* feat(parakeet-cpp): encoder fingerprint for speaker naming, vad_trim and guard_* options
Speaker naming. A registered voice now carries the encoder that made it:
the embedding family (voicedetect:<arch>:<name>:<dim>) and the sha256 of
the weights. The backend reports the family of the loaded speaker model in
Status, voice enrollment from speaker_profiles stores it as encoder_family
(old entries load without it), and the registry sent to parakeet.cpp is
built with parakeet_capi_speaker_registry_add_embedding_fp. The library
then refuses a registry of another encoder family and the error names both
families; another quantization of the same family only warns. A voice with
only a weights hash gets the loaded family when the hashes are equal.
Voices without a fingerprint (registered from audio: libvoicedetect cannot
report one) keep the file-name rule and are used with a warning. The
library cannot mix them with fingerprinted voices in one registry, so a
request that has any uses the old registry for all. speaker_strict:true
drops them instead. A library without the symbols behaves as before.
Transcription. vad_trim (seconds, 0 keeps the whole cuts) goes through the
VAD options JSON, so it reaches /v1/vad and the segmenter. The guard_*
options guard_min_local_conf, guard_local_radius and guard_drop_punct_only
turn on the word filter through parakeet_capi_transcribe_path_json_with,
or through the segmenter with vad:true. They are off by default, bad
values fail the load, and a library without the symbol fails it with a
clear message. The dropped word count is logged at debug level.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parakeet-cpp): load bundle GGUF files and use their components by role
A bundle GGUF holds several models (ASR, VAD, diarization, sound events,
speaker encoder) in one file, each with its own licence. Detect a bundle
at load through parakeet_capi_bundle_components_json and open components
with parakeet_capi_load_component. The three symbols are probed together,
so an older libparakeet.so still loads plain files as before.
The only ASR component is the primary model; bundle_asr:<name> picks one
when there are several. A Silero VAD component of the primary bundle is
loaded without an option and serves /v1/vad and vad:true. The diar, ced
and voice components load on request: diar_component, sound_component and
speaker_component, or a companion option (diarization_model, sound_model,
speaker_model, vad_model) that names a bundle, even the model file itself.
vad_component picks a VAD component and implies vad:true.
A role the bundle cannot fill fails the load with the component list, and
a diarization or sound request on a model without that role names the
bundle components. Every existing option and single-file model behaves as
before.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* chore(parakeet-cpp): bump parakeet.cpp to 781a973
Brings in the bundle GGUF format and its C-API (parakeet_capi_load_component,
parakeet_capi_bundle_components_json, parakeet_capi_load_error).
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* feat(parakeet-cpp): gallery entries for the bundle GGUF files, docs
Add parakeet-cpp-bundle-small (338 MB: Parakeet TDT+CTC 110M, Nemotron-3-
Diarization, CED-Small, WeSpeaker ResNet34-LM, Silero VAD), -standard
(1.1 GB, Parakeet TDT 0.6B v3 instead of the 110M model) and
-moondream-redux (215 MB: packed Redux and Silero VAD, CPU only). One
install serves transcription, VAD, diarization, sound events and speaker
naming through the component options. The existing single-purpose entries
stay.
A bundle has no single licence, so the entries use license: other and
state the licence and credit of each component in the description, with
the upstream inconsistency of the CED licence. The docs get a section on
bundles in audio-to-text with the entries, the roles, the options and the
licence notice, and pointers from the VAD, diarization and sound
classification pages. A gallery test checks the file names, checksums,
usecases and options.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parakeet-cpp): add gallery entries for the VAD-only Moondream slices
Add parakeet-cpp-vad-moondream-redux and parakeet-cpp-vad-moondream-ultra.
They install the VAD head of Moondream Redux and Ultra (Q8_0) as small
files of 10 MB and 6 MB, cut out of the full models without retraining,
for the VAD endpoint. The files cannot transcribe, and a transcription
request fails with a clear error.
The files load only with a parakeet.cpp build that has VAD-only GGUF
support (parakeet.cpp pull request 87). The backend pin must move to a
commit that includes it before these entries work in a released image.
The parakeet-cpp-vad entry keeps installing Silero.
The docs list the files with the size, load time and memory compared
with loading a whole model. A gallery test checks the usecase, the file
name and the checksum of each entry.
Assisted-by: Claude Code:claude-sonnet-5-5 [golangci-lint]
* chore(parakeet-cpp): bump parakeet.cpp to e53a253
Brings in the VAD-only GGUF loader.
Assisted-by: Claude Code:claude-sonnet-5-5 [git] [gh]
* docs(gallery): link the parakeet.cpp VAD docs instead of the merged PR
Assisted-by: Claude Code:claude-sonnet-5-5 [git]
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(parakeet-cpp): implement the VAD call and add the vad_model option
The backend now serves the VAD gRPC call (POST /vad and /v1/vad) with the
standalone VAD of libparakeet. It accepts a Silero VAD GGUF as the model
file, or an ASR model with a VAD head (Moondream Ultra and Redux). The
request audio is float32 PCM at 16 kHz; the response lists the speech
segments in seconds, like the silero-vad backend. A model with neither
fails the request with the library message.
The vad_threshold, vad_min_pause, vad_min_speech, vad_speech_pad and
vad_max_segment options tune the segmenter. Unset values keep the
defaults of the detector in use, and a bad value fails the load.
The vad_model option names a Silero GGUF, resolved against the models
directory like the other companion files. It lets any ASR model cut long
audio at pauses through parakeet_capi_transcribe_path_json_vad_with, and
it implies vad. vad:true alone still uses the model's own head.
The new symbols are probed like the existing optional ones. A library
without them still loads; the feature that needs one fails with a clear
message only when it is used.
Assisted-by: Claude:claude-sonnet-5-5 [go test]
* feat(gallery): add parakeet-cpp VAD entries and a v3 plus Silero example
Add VAD-only entries for the parakeet-cpp backend: the VAD heads of
Moondream Redux (packed, CPU) and Ultra (Q8_0), which share their files
with the existing ASR entries, and Silero VAD v6.2.3 as a GGUF (MIT,
Silero Team). The parakeet-cpp-vad entry installs Silero; it has no variants,
because variant ranking prefers the larger build that fits and these are
different detectors.
Add parakeet-cpp-tdt-0.6b-v3-silero-vad, a v3 entry that sets vad_model
so long audio is cut at pauses by Silero.
The Silero GGUF entries point at the intended Hugging Face URL of the
file; the existing silero-vad entries are unchanged. A test checks the
usecases, the shared files and the default entry and the vad_model reference.
Assisted-by: Claude:claude-sonnet-5-5 [go test]
* docs: describe parakeet-cpp VAD and the vad_model option
Document the VAD endpoint on the parakeet-cpp backend (Silero GGUF and
the VAD heads of Moondream Ultra and Redux), the vad_* tuning options,
and the vad_model option that lets an ASR model without a VAD head cut
long audio with Silero.
Assisted-by: Claude:claude-sonnet-5-5
* chore(parakeet-cpp): bump parakeet.cpp to 6165e3d
Pin the release that adds the standalone VAD (Ultra/Redux head and
Silero) and the C API calls the backend now uses.
Assisted-by: Claude:claude-sonnet-5-5
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* chore(parakeet-cpp): bump parakeet.cpp to 11c1a0f
Picks up support for the Moondream Ultra and Redux models and the
VAD-segmented transcription entry point (C-API ABI is still 10).
Assisted-by: Claude:claude-sonnet-5-5
* feat(parakeet-cpp): add vad option for long-audio transcription
Models with a VAD head (Moondream Ultra and Redux) can cut long audio at
pauses. Setting vad:true in the model options routes offline
transcription through parakeet_capi_transcribe_path_json_vad. The symbol
is probed at startup like the other optional entry points, and vad:true
fails the load with a clear message when the library lacks it. A model
without a VAD head fails the request with the library's own message.
The option is off by default and does not affect streaming.
Also say in the load error that a packed ternary Redux model is CPU only,
because the library reports its refusal on a GPU backend through its log,
not through the C API.
Assisted-by: Claude:claude-sonnet-5-5
* feat(gallery): add Moondream Ultra and Redux for parakeet-cpp
Add five entries from the public parakeet-cpp GGUF repository: Ultra in
F16 and Q8_0, and Redux as packed ternary (CPU only, offline only) and
as dequantized F16 and Q8_0 (any backend). The entries enable vad:true so
long audio is cut at pauses. Checksums come from the repository's LFS
metadata. The weights are CC-BY-4.0.
Assisted-by: Claude:claude-sonnet-5-5
* docs(parakeet-cpp): document Moondream Ultra, Redux and the vad option
Assisted-by: Claude:claude-sonnet-5-5
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
* feat(silero-vad): allow threshold/silence/pad via model options
Signed-off-by: anton ziderer <Antonziderer@mail.ru>
Co-authored-by: Cursor <cursoragent@cursor.com>
* fix(silero-vad): ignore NaN thresholds
NaN passes the detector validation but prevents speech comparisons from succeeding.
Ignore it like malformed input and document the option validation.
Convert the option tests to Ginkgo and cover invalid overrides.
Assisted-by: Codex:gpt-6
Signed-off-by: anton ziderer <Antonziderer@mail.ru>
---------
Signed-off-by: anton ziderer <Antonziderer@mail.ru>
Co-authored-by: Cursor <cursoragent@cursor.com>
Co-authored-by: localai-org-maint-bot <306269227+localai-org-maint-bot@users.noreply.github.com>
* feat(gallery): add nimble-9b-vllm-cpp decision model
Add Bespoke Nimble 9B, converted for vllm.cpp and pinned to the weights
commit 52eead25 of mudler/Bespoke-Nimble-9B-vllm-cpp (HEAD only adds the
model card). It is a redistribution of bespokelabs/Bespoke-Nimble-9B
with the LoRA merged into Qwen3.5-9B; config.json names NimbleModel, so
no hf_overrides are needed.
The artifact sits under overrides, where the installer reads it. The
entry sets an 8192-token context, Nimble's own prompt limit, and a KV
pool of 1024 blocks of 32 tokens for 4 sequences (about 1 GiB at 32 KiB
per token for the 8 full-attention layers).
Installed with local-ai models install and served on CPU through the
vllm-cpp backend: the model card's billing request gives billing
(0.986), refund 0.998 and urgency 0.33. Peak resident memory was
18.4 GB, so the description asks for about 20 GB of free RAM.
List the entry in the decisions gallery table. CLM stays out of the
gallery: the pinned engine cannot load the published head layout.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-sonnet-5-5
* feat(gallery): add clm-v0.1-8b-vllm-cpp and bump vllm.cpp for CLM
The CLM checkpoint on mudler/CLM-v0.1-8B-vllm-cpp stores the heads with
the reference's own tensor names (state_head.inp, hidden.N, norms.N,
out). The pinned vllm.cpp 96788348 still expects the old .0/.2/.4/.6
layout and refuses the load with "head.safetensors incomplete for
state_head". vllm.cpp a19294a9 matches the reference layout and adds the
converter that produced the upload, so move the pin there. The ABI stays
at v30.
Add the CLM entry, pinned to the weights commit 0d1903b1 (HEAD only adds
the model card), with a 4096-token context and a KV pool for 4 sequences
(about 2.25 GiB at 144 KiB per token for Qwen3-8B).
Installed with local-ai models install and served on CPU against a
libvllm built at a19294a9: the model card example (john works at google,
entity type) gives person 0.950, the same as the card. Peak resident
memory was 17.9 GB.
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-sonnet-5-5
---------
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
When an Anthropic model declines to answer, the Messages API returns
HTTP 200 with `stop_reason: "refusal"` and empty `content`. The
translate mode mapped that to a normal reply with no content, so the
OpenAI-compatible response looked like a successful completion
(`finish_reason: "stop"`, empty message). Routers, agents and UIs could
not tell "the model declined" from "the model had nothing to say", and
no fallback was triggered.
Return an explicit error for `stop_reason: "refusal"` in both the
non-streaming path and the streaming path (`message_delta`). Regular
replies, including empty `end_turn` replies, are unchanged.
Assisted-by: Claude:claude-opus-5-5
Signed-off-by: Stefan Walcz <stefan.walcz@walcz.de>
* 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>
* feat(voice): list registered voices and record which encoder made them
The voice registry could register, identify and forget but not list, and
it did not remember which speaker encoder produced an embedding. Add
Metadata.Model and Registry.List, answered from the index the store
registry already keeps for Forget. Needed so a backend can be given the
registered voices that match its own speaker encoder.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* feat(voice): store the encoder model with a registered voice
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* feat(voice): pick the registered voices that match a speaker model
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* feat(proto): carry known voices and speaker names on diarize and live messages
Assisted-by: Claude:claude-haiku-4-5 [Claude Code]
* feat(diarization): name speakers from the voice registry
When a diarization model has a speaker_model option, the endpoint sends
the registered voices made by that encoder to the backend. The backend's
name and name_score come back as extra fields next to the normalized
SPEAKER_NN speaker, and the speakers summary carries the first name seen
for each speaker. RTTM output and results without names are unchanged.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* feat(live): pass registered voices to a live session and surface speaker names
Live sessions now send the registered voices that match the model's
speaker_model to the backend, and each speaker segment carries the name
the backend matched. The realtime segment event gains an optional
speaker_name field.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* feat(parakeet-cpp): load a speaker model and build per-request voice registries
Adds the speaker bindings (ABI v9 and v10, probed separately), the
speaker_model, speaker_threshold and speaker_margin options, and a
per-request registry builder over the known voices.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* feat(parakeet-cpp): name the speakers in Diarize from the known voices
Diarize builds a per-request speaker registry from the known voices when a
speaker model is loaded, calls the named C functions, and puts each slot's
registered name and score on the segments. The registry is freed on every
path. A library without ABI 10 reports Unimplemented instead of dropping
the names.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* feat(parakeet-cpp): name speakers in the live scene stream
The live scene stream now begins with a known-voice registry when a
speaker model is loaded and the live config carries voices, and each
closed speaker segment takes its slot's current name from the feed's
names map. A segment that closes before its slot is identified has an
empty name. The registry is freed after the stream, on every path.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* feat(gallery): speaker naming entries and docs for parakeet-cpp
Add three gallery entries that load the WeSpeaker ResNet34 speaker model
next to the diarization or realtime scene models, and document speaker
names in the voice recognition, diarization, audio to text and realtime
pages.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* fix(parakeet-cpp): skip an unusable registered voice instead of failing the request
A registered voice with the wrong embedding size, or one the C side
refused, failed the whole diarization request, so one legacy voice broke
the model for every user. Skip such voices with a warning that does not
carry the voice name, and take the plain path when none is left.
Also map an exact 0 speaker threshold or margin to a tiny positive value,
since the C side reads 0 as "use the default", and fix a stale comment
about which contexts Free() walks.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* fix(diarization): warn once per model about voices from another encoder; document the privacy limit
The different-encoder warning fired on every request. Log it once per
feature and speaker model, then at debug level. Document that the global
voice registry lets any caller of a speaker_model model learn matching
names, and that skipped wrong-sized voices are logged.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
* chore(parakeet-cpp): bump parakeet.cpp to 8c8cec0 (C-API v10) and check speaker naming against the real library
The pin moves from 623a968 to 8c8cec0, which brings in everything merged
in parakeet.cpp since: the voice identification change (C-API v9, #78) and
raw-embedding enroll plus diarize-only speaker naming (C-API v10, #79).
New real-library specs (gated on PARAKEET_BACKEND_TEST_SPEAKER_MODEL,
_DIAR_MODEL, _WAV and, for the live path, _STREAM_MODEL) name the two
speakers of two_speakers.wav from a committed pair of WeSpeaker embeddings,
with the voices passed in reversed order. They also check that the float32
threshold reaches C through purego. The shared test loader now registers
the v9/v10 and scene symbols as main.go does.
The rebase onto origin/master had no conflicts.
Assisted-by: Claude:claude-sonnet-5-5 [Claude Code]
---------
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
