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* feat(voice-recognition): add /v1/voice/{verify,analyze,embed} + speaker-recognition backend
Audio analog to face recognition. Adds three gRPC RPCs
(VoiceVerify / VoiceAnalyze / VoiceEmbed), their Go service and HTTP
layers, a new FLAG_SPEAKER_RECOGNITION capability flag, and a Python
backend scaffold under backend/python/speaker-recognition/ wrapping
SpeechBrain ECAPA-TDNN with a parallel OnnxDirectEngine for
WeSpeaker / 3D-Speaker ONNX exports.
The kokoros Rust backend gets matching unimplemented trait stubs —
tonic's async_trait has no defaults, so adding an RPC without Rust
stubs breaks the build (same regression fixed by eb01c772 for face).
Swagger, /api/instructions, and the auth RouteFeatureRegistry /
APIFeatures list are updated so the endpoints surface everywhere a
client or admin UI looks.
Assisted-by: Claude:claude-opus-4-7
* feat(voice-recognition): add 1:N identify + register/forget endpoints
Mirrors the face-recognition register/identify/forget surface. New
package core/services/voicerecognition/ carries a Registry interface
and a local-store-backed implementation (same in-memory vector-store
plumbing facerecognition uses, separate instance so the embedding
spaces stay isolated).
Handlers under /v1/voice/{register,identify,forget} reuse
backend.VoiceEmbed to compute the probe vector, then delegate the
nearest-neighbour search to the registry. Default cosine-distance
threshold is tuned for ECAPA-TDNN on VoxCeleb (0.25, EER ~1.9%).
As with the face registry, the current backing is in-memory only — a
pgvector implementation is a future constructor-level swap.
Assisted-by: Claude:claude-opus-4-7
* feat(voice-recognition): gallery, docs, CI and e2e coverage
- backend/index.yaml: speaker-recognition backend entry + CPU and
CUDA-12 image variants (plus matching development variants).
- gallery/index.yaml: speechbrain-ecapa-tdnn (default) and
wespeaker-resnet34 model entries. The WeSpeaker SHA-256 is a
deliberate placeholder — the HF URI must be curl'd and its hash
filled in before the entry installs.
- docs/content/features/voice-recognition.md: API reference + quickstart,
mirrors the face-recognition docs.
- React UI: CAP_SPEAKER_RECOGNITION flag export (consumers follow face's
precedent — no dedicated tab yet).
- tests/e2e-backends: voice_embed / voice_verify / voice_analyze specs.
Helper resolveFaceFixture is reused as-is — the only thing face/voice
share is "download a file into workDir", so no need for a new helper.
- Makefile: docker-build-speaker-recognition + test-extra-backend-
speaker-recognition-{ecapa,all} targets. Audio fixtures default to
VCTK p225/p226 samples from HuggingFace.
- CI: test-extra.yml grows a tests-speaker-recognition-grpc job
mirroring insightface. backend.yml matrix gains CPU + CUDA-12 image
build entries — scripts/changed-backends.js auto-picks these up.
Assisted-by: Claude:claude-opus-4-7
* feat(voice-recognition): wire a working /v1/voice/analyze head
Adds AnalysisHead: a lazy-loading age / gender / emotion inference
wrapper that plugs into both SpeechBrainEngine and OnnxDirectEngine.
Defaults to two open-licence HuggingFace checkpoints:
- audeering/wav2vec2-large-robust-24-ft-age-gender (Apache 2.0) —
age regression + 3-way gender (female / male / child).
- superb/wav2vec2-base-superb-er (Apache 2.0) — 4-way emotion.
Both are optional and degrade gracefully when transformers or the
model can't be loaded — the engine raises NotImplementedError so the
gRPC layer returns 501 instead of a generic 500.
Emotion classes pass through from the model (neutral/happy/angry/sad
on the default checkpoint); the e2e test now accepts any non-empty
dominant gender so custom age_gender_model overrides don't fail it.
Adds transformers to the backend's CPU and CUDA-12 requirements.
Assisted-by: Claude:claude-opus-4-7
* fix(voice-recognition): pin real WeSpeaker ResNet34 ONNX SHA-256
Replaces the placeholder hash in gallery/index.yaml with the actual
SHA-256 (7bb2f06e…) of the upstream
Wespeaker/wespeaker-voxceleb-resnet34-LM ONNX at ~25MB. `local-ai
models install wespeaker-resnet34` now succeeds.
Assisted-by: Claude:claude-opus-4-7
* fix(voice-recognition): soundfile loader + honest analyze default
Two issues surfaced on first end-to-end smoke with the actual backend
image:
1. torchaudio.load in torchaudio 2.8+ requires the torchcodec package
for audio decoding. Switch SpeechBrainEngine._load_waveform to the
already-present soundfile (listed in requirements.txt) plus a numpy
linear resample to 16kHz. Drops a heavy ffmpeg-linked dep and the
codepath we never exercise (torchaudio's ffmpeg backend).
2. The AnalysisHead was defaulting to audeering/wav2vec2-large-robust-
24-ft-age-gender, but AutoModelForAudioClassification silently
mangles that checkpoint — it reports the age head weights as
UNEXPECTED and re-initialises the classifier head with random
values, so the "gender" output is noise and there is no age output
at all. Make age/gender opt-in instead (empty default; users wire
a cleanly-loadable Wav2Vec2ForSequenceClassification checkpoint via
age_gender_model: option). Emotion keeps its working Superb default.
Also broaden _infer_age_gender's tensor-shape handling and catch
runtime exceptions so a dodgy age/gender head never takes down the
whole analyze call.
Docs and README updated to match the new policy.
Verified with the branch-scoped gallery on localhost:
- voice/embed → 192-d ECAPA-TDNN vector
- voice/verify → same-clip dist≈6e-08 verified=true; cross-speaker
dist 0.76–0.99 verified=false (as expected)
- voice/register/identify/forget → round-trip works, 404 on unknown id
- voice/analyze → emotion populated, age/gender omitted (opt-in)
Assisted-by: Claude:claude-opus-4-7
* fix(voice-recognition): real CI audio fixtures + fixture-agnostic verify spec
Two issues surfaced after CI actually ran the speaker-recognition e2e
target (I'd curl-tested against a running server but hadn't run the
make target locally):
1. The default BACKEND_TEST_VOICE_AUDIO_* URLs pointed at
huggingface.co/datasets/CSTR-Edinburgh/vctk paths that return 404
(the dataset is gated). Swap them for the speechbrain test samples
served from github.com/speechbrain/speechbrain/raw/develop/ —
public, no auth, correct 16kHz mono format.
2. The VoiceVerify spec required d(file1,file2) < 0.4, assuming
file1/file2 were same-speaker. The speechbrain samples are three
different speakers (example1/2/5), and there is no easy un-gated
source of true same-speaker audio pairs (VoxCeleb/VCTK/LibriSpeech
are all license- or size-gated for CI use). Replace the ceiling
check with a relative-ordering assertion: d(pair) > d(same-clip)
for both file2 and file3 — that's enough to prove the embeddings
encode speaker info, and it works with any three non-identical
clips. Actual speaker ordering d(1,2) vs d(1,3) is logged but not
asserted.
Local run: 4/4 voice specs pass (Health, LoadModel, VoiceEmbed,
VoiceVerify) on the built backend image. 12 non-voice specs skipped
as expected.
Assisted-by: Claude:claude-opus-4-7
* fix(ci): checkout with submodules in the reusable backend_build workflow
The kokoros Rust backend build fails with
failed to read .../sources/Kokoros/kokoros/Cargo.toml: No such file
because the reusable backend_build.yml workflow's actions/checkout
step was missing `submodules: true`. Dockerfile.rust does `COPY .
/LocalAI`, and without the submodule files the subsequent `cargo
build` can't find the vendored Kokoros crate.
The bug pre-dates this PR — scripts/changed-backends.js only triggers
the kokoros image job when something under backend/rust/kokoros or
the shared proto changes, so master had been coasting past it. The
voice-recognition proto addition re-broke it.
Other checkouts in backend.yml (llama-cpp-darwin) and test-extra.yml
(insightface, kokoros, speaker-recognition) already pass
`submodules: true`; this brings the shared backend image builder in
line.
Assisted-by: Claude:claude-opus-4-7
LocalAI website
LocalAI documentation website
Requirement
In this project, the Docsy theme component is pulled in as a Hugo module, together with other module dependencies:
$ hugo mod graph
hugo: collected modules in 566 ms
hugo: collected modules in 578 ms
github.com/google/docsy-example github.com/google/docsy@v0.5.1-0.20221017155306-99eacb09ffb0
github.com/google/docsy-example github.com/google/docsy/dependencies@v0.5.1-0.20221014161617-be5da07ecff1
github.com/google/docsy/dependencies@v0.5.1-0.20221014161617-be5da07ecff1 github.com/twbs/bootstrap@v4.6.2+incompatible
github.com/google/docsy/dependencies@v0.5.1-0.20221014161617-be5da07ecff1 github.com/FortAwesome/Font-Awesome@v0.0.0-20220831210243-d3a7818c253f
If you want to do SCSS edits and want to publish these, you need to install PostCSS
npm install
Running the website locally
Building and running the site locally requires a recent extended version of Hugo.
You can find out more about how to install Hugo for your environment in our
Getting started guide.
Once you've made your working copy of the site repo, from the repo root folder, run:
hugo server
Running a container locally
You can run docsy-example inside a Docker
container, the container runs with a volume bound to the docsy-example
folder. This approach doesn't require you to install any dependencies other
than Docker Desktop on
Windows and Mac, and Docker Compose
on Linux.
-
Build the docker image
docker-compose build -
Run the built image
docker-compose upNOTE: You can run both commands at once with
docker-compose up --build. -
Verify that the service is working.
Open your web browser and type
http://localhost:1313in your navigation bar, This opens a local instance of the docsy-example homepage. You can now make changes to the docsy example and those changes will immediately show up in your browser after you save.
Cleanup
To stop Docker Compose, on your terminal window, press Ctrl + C.
To remove the produced images run:
docker-compose rm
For more information see the Docker Compose documentation.
Troubleshooting
As you run the website locally, you may run into the following error:
➜ hugo server
INFO 2021/01/21 21:07:55 Using config file:
Building sites … INFO 2021/01/21 21:07:55 syncing static files to /
Built in 288 ms
Error: Error building site: TOCSS: failed to transform "scss/main.scss" (text/x-scss): resource "scss/scss/main.scss_9fadf33d895a46083cdd64396b57ef68" not found in file cache
This error occurs if you have not installed the extended version of Hugo. See this section of the user guide for instructions on how to install Hugo.
Or you may encounter the following error:
➜ hugo server
Error: failed to download modules: binary with name "go" not found
This error occurs if you have not installed the go programming language on your system.
See this section of the user guide for instructions on how to install go.