Commit Graph

62 Commits

Author SHA1 Message Date
LocalAI [bot]
b0959d4756 feat(api): add GET /v1/models/capabilities endpoint (#10687)
Additive superset of /v1/models that enriches each model entry with the
capabilities it supports plus its input/output modalities
(text / image / audio / video). Clients that only understand /v1/models
are unaffected -- they simply never call the new route.

Audio and video *input* are derived from the model's multimodal limits
(vLLM limit_mm_per_prompt), which no single usecase FLAG expresses. That
gap is exactly why a plain capability list is insufficient and this
enriched endpoint exists: an attachment router can now decide whether an
image/audio/video file can go to the active model directly, or must be
converted/transcribed first.

Capability derivation lives in core/config as the single source of truth
(ModelConfig.Capabilities / InputModalities / OutputModalities /
VisionSupported / ...); the Ollama capability surface now delegates to
it instead of keeping a parallel copy. Vision is gated on
chat/completion capability so a MediaMarker hydrated onto a non-chat
model (e.g. a pure ASR/TTS backend) no longer reports a false vision
capability.

Read-only listing: no new FLAG_* flag, reuses the existing `models`
swagger tag, and intentionally exposes no MCP admin tool (there is
nothing to manage conversationally).

Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-07-05 08:51:55 +02:00
Richard Palethorpe
eb32cd9073 feat(realtime): eager blocking pipeline warm-up + /backend/load API (#10662)
Realtime sessions previously lazy-loaded each pipeline sub-model (VAD,
transcription, LLM, TTS) on first use, so every cold session paid a
per-request model-load stall and load errors only surfaced mid-stream.

Warm the whole pipeline eagerly and blockingly at session start
(including the voice-gate speaker-recognition model, which an enforced
gate blocks each utterance on; compaction's summary_model stays lazy
since it only runs off the response path):
- Add backend.PreloadModel / PreloadModelByName as the single load path
  for every modality (no transcription special-case; backend-omitted
  configs are deprecated).
- The realtime session blocks on Model.Warmup and returns a
  model_load_error to the client if any stage fails to load;
  updateSession warms in the background. Opt out per pipeline with
  pipeline.disable_warmup, exposed as a UI toggle via the
  config-metadata registry.

Add a LocalAI-native POST /backend/load (and /v1/backend/load) that
pre-loads a model -- expanding realtime pipelines into their sub-models
-- as the inverse of /backend/shutdown. There is one preload engine
(backend.PreloadStages): the realtime Warmup methods, /backend/load and
the --load-to-memory startup flag all use it, so --load-to-memory now
also expands pipeline models and records load-failure traces. Pipeline
sub-model alias resolution is likewise shared
(ModelConfigLoader.LoadResolvedModelConfig). Surface the endpoint
everywhere an admin manages models:
- MCP admin tool load_model (httpapi + inproc clients, safety/catalog
  prompts, catalog/dispatch tests).
- "Load into memory" action in the React models UI.
- Swagger regenerated; docs moved to the general backend-monitor page
  since it is not realtime-specific.

Fix a Traces UI crash ("json: unsupported value: -Inf"): audio-snippet
RMS/peak now floor at a finite dBFS, and backend-trace data is sanitized
to drop non-finite floats before marshaling. The sanitizer is
copy-on-write -- it runs on every RecordBackendTrace, so containers are
only re-allocated on the paths that actually changed.

Migrate core/http/openresponses_test.go onto the prebuilt mock-backend
the rest of the http suite already uses -- it was the last spec still
pointing at a real HuggingFace model, so it 404'd wherever no vision
backend was built -- and fix its item_reference specs to send the
spec's "id" field instead of "item_id", which the handler never
accepted.

Assisted-by: Claude:claude-opus-4-8 Claude Code

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-07-03 18:00:37 +02:00
LocalAI [bot]
64150ca7ab fix(distributed): broadcast admin model-config changes across replicas (#10540)
In distributed mode the admin model endpoints (/models/edit, /models/import,
/models/toggle-state and the PATCH config-json endpoint) wrote the YAML to the
shared models dir but reloaded only the local replica's in-memory
ModelConfigLoader. With multiple frontend replicas behind one service, a save
landed on whichever replica handled the request; peers kept serving their stale
in-memory view, so a load-balanced request was a coin-flip between old and new
config (a created alias visible on one replica and missing on the other, an
edited alias target diverging, etc.).

The NATS cache-invalidation channel (SubjectCacheInvalidateModels +
OnModelsChanged) already existed for the gallery install/delete path; these
admin endpoints simply never published on it. Wire them up via a new
GalleryService.BroadcastModelsChanged helper (no-op in standalone mode).

Also fix delete propagation: LoadModelConfigsFromPath is additive and never
drops an entry whose file is gone, so the subscriber hook (which only reloaded
from disk) could not propagate a removal. ApplyRemoteChange now honors the
event op - pruning the element on "delete" and reloading otherwise - and shuts
down any running instance of the affected model so the new config takes effect.
This closes the same latent gap on the gallery delete path.


Assisted-by: Claude:claude-opus-4-8 [Claude Code]

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-27 01:36:57 +02:00
LocalAI [bot]
600dafd20b feat(ced): sound-event classification backend (CED audio tagger) (#10425)
* feat(ced): sketch sound-classification backend (CED audio tagger)

Wires ced.cpp (CED, 527-class AudioSet sound-event tagger; baby cry,
footsteps, glass, alarms, dog bark) into LocalAI as a Go/purego backend.

SKETCH (backend skeleton real; core REST wiring + CI/gallery is a checklist
in DESIGN.md):
- backend/backend.proto: new SoundDetection rpc + SoundClass messages
  (run `make protogen-go` to regenerate pkg/grpc/proto).
- backend/go/ced: main.go (purego dlopen libced.so + ced_capi.h),
  goced.go (Ced gRPC backend: Load + SoundDetection), Makefile
  (clone-at-pin CED_VERSION, ggml static-PIC shared build), run.sh,
  package.sh, .gitignore.
- DESIGN.md: REST /v1/audio/classification wiring (handler/route/capability
  registration checklist), gallery/index + CI registration, and a scoping
  note for the realtime/websocket live-recognition path (sliding-window
  classify over the existing ws transport + voicegate; the ced C-API
  per-PCM entry point is already window-friendly).

Backend code does not compile until protogen-go regenerates the pb types
and a libced.so is built (Makefile clones+builds it).

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ced): REST /v1/audio/classification endpoint + capability registration

Wires the ced sound-event classification backend (AudioSet audio tagger)
end to end through the REST surface, mirroring the transcription path.

- Handler: core/http/endpoints/openai/sound_classification.go parses the
  multipart audio upload, temp-files it, resolves the model config and
  calls the SoundDetection RPC; returns {model, detections[]} JSON.
- Backend wrapper: core/backend/sound_classification.go (ModelSoundDetection)
  loads the model and normalizes the proto response into schema types.
- Schema: core/schema/sound_classification.go (SoundClassificationResult).
- gRPC layer: SoundDetection wired through the LocalAI wrapper (interface,
  Backend client, Client, embed, server, base default) so the loader-typed
  client exposes the RPC; proto regenerated via make protogen-go.
- Route: POST /v1/audio/classification (+ /audio/classification alias) with
  the audio/multipart default-model middleware in routes/openai.go.
- Capability surfaces: swagger @Tags/@Router on the handler; FLAG_SOUND_
  CLASSIFICATION usecase flag + UsecaseSoundClassification + UsecaseInfoMap +
  GuessUsecases + ModalityGroups + GetAllModelConfigUsecases; meta usecase
  option; /api/instructions audio area updated; auth RouteFeatureRegistry +
  FeatureAudioClassification (APIFeatures, default ON) + FeatureMetas; UI
  usecaseFilters, capabilities.js CAP_SOUND_CLASSIFICATION, Models.jsx filter
  + i18n; docs page features/audio-classification.md + whats-new + crosslink.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ced): realtime sound-event detection over the websocket API

When a realtime pipeline configures a sound-classification model, each
VAD-committed utterance (the same window the transcription path produces)
is also run through the CED sound-event classifier and the scored AudioSet
tags are emitted as a new server event. No new backend rpc is needed: the
SoundDetection gRPC method already exists on this branch.

- config: add Pipeline.SoundDetection (yaml/json sound_detection,omitempty)
  beside Transcription/VAD.
- realtime: add Model.SoundDetection(ctx, audio, topK, threshold) to the
  ModelInterface; implement it on wrappedModel and transcriptOnlyModel by
  calling backend.ModelSoundDetection with the session's sound-classification
  model config (mirrors how Transcribe dispatches). Load the optional config
  in newModel / newTranscriptionOnlyModel; nil config keeps it additive.
- types: add ConversationItemSoundDetectionEvent (item_id, content_index,
  detections[]{label,score,index}) with type conversation.item.sound_detection,
  its ServerEventType constant and MarshalJSON, mirroring the transcription
  completed event.
- realtime: add emitSoundDetection (unary path: classify the committed window,
  build the event, t.SendEvent) and wire it at the utterance-commit hook right
  after emitTranscription; gated on session.SoundDetectionEnabled (resolved
  from Pipeline.SoundDetection at session setup, defaults top_k=5, threshold=0).
  Its error is logged via xlog but never aborts the turn.
- test: Ginkgo specs for emitSoundDetection (tags emitted, empty detections,
  classifier error) plus a SoundDetection method on the fakeModel double.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(ced): implement SoundDetection in nodes backend test doubles

The SoundDetection method added to the grpc backend interface left two
test doubles (fakeBackendClient, fakeGRPCBackend) incomplete, so
core/services/nodes failed to compile under `go vet`/`go test` (go build
missed it: the doubles live in _test.go). Add the method to both,
mirroring their existing Detect mock. Repairs CI for the nodes package.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ced): decouple realtime sound detection from VAD (sound-only sessions)

Sound-event detection must activate on sounds, not speech, so it no longer
runs through the voice VAD/transcription path. A sound-detection-only
pipeline (sound_detection set, no transcription/LLM) now:

- is accepted by prepareRealtimeConfig (sound_detection counts as a pipeline
  stage),
- builds a lightweight model via newSoundDetectionOnlyModel (no VAD/STT/LLM/TTS
  loaded), and
- defaults the session to turn_detection none (no VAD) with no transcription
  stage, so the client drives windowing via input_audio_buffer.commit
  (option A: client-side sliding window). The per-PCM C-API already supports
  arbitrary windows.

commitUtterance gains a sound-only branch: it emits the
conversation.item.sound_detection event (scored AudioSet tags) and stops -
no transcription, no LLM response. generateResponse is now guarded on a
transcription stage being present, so a sound-only turn never invokes the LLM.

Existing transcription/VAD sessions are unchanged (additive). Added a
commitUtterance sound-only Ginkgo spec asserting it emits the sound event and
neither transcribes nor generates a response. go vet + golangci-lint
(new-from-merge-base) clean; openai suite green.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ced): register sound-classification backend in gallery + CI

Mechanical backend-image registration for the ced sound-event classifier,
mirroring the parakeet-cpp Go/purego backend everywhere it is wired up.

- .github/backend-matrix.yml: add the ced build matrix, field-for-field copies
  of the parakeet-cpp entries (cpu amd64/arm64, cublas cuda 12/13 amd64,
  l4t cuda-13 arm64, l4t-jetpack cuda-12 arm64, sycl f32/f16, vulkan
  amd64/arm64, rocm hipblas, and the metal darwin entry), changing only
  backend and tag-suffix. dockerfile stays ./backend/Dockerfile.golang.
- backend/index.yaml: add the &ced meta anchor (capabilities map per platform)
  plus ced-development and the per-arch image entries, each uri/mirror
  tag-suffix matching the matrix exactly. The model gallery (GGUF) entry is
  intentionally deferred pending the HuggingFace publish (TODO note inline).
- scripts/changed-backends.js: add an explicit item.backend === "ced" branch in
  inferBackendPath mapping to backend/go/ced/, same mechanism and ordering as
  the parakeet-cpp branch (before the generic golang fallthrough).
- .github/workflows/bump_deps.yaml: register mudler/ced.cpp -> CED_VERSION in
  backend/go/ced/Makefile so the daily bot bumps the pin.
- swagger/{docs.go,swagger.json,swagger.yaml}: regenerated via make swagger so
  the existing /v1/audio/classification annotations land in the generated spec.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ced): server-side windowing for realtime sound detection (option B)

Adds an optional server-driven sliding-window classifier so a sound-only
realtime client only has to stream audio (no input_audio_buffer.commit):

- Pipeline.sound_detection_window_ms / sound_detection_hop_ms config knobs.
  When both > 0 on a sound-only session, the server classifies the last
  window of streamed audio every hop and emits a conversation.item.sound_
  detection event; the input buffer is trimmed to one window so a long
  stream stays bounded. When unset, the session stays client-driven
  (option A). Runs independent of VAD (sound events are not speech).
- handleSoundWindow (ticker) + classifySoundWindow (one tick, extracted so
  it is unit-testable) + writeWindowWAV, which declares the true
  InputSampleRate (NewWAVHeaderWithRate) so the classifier resamples
  correctly. Goroutine is started after toggleVAD and torn down with the
  session (close + wg.Wait).
- Register pipeline.sound_detection (+window_ms/hop_ms) in the config meta
  registry; the earlier realtime commit added pipeline.sound_detection
  without a registry entry, failing TestAllFieldsHaveRegistryEntries. This
  fixes that and covers the two new knobs.

Tests: classifySoundWindow emits an event + trims the buffer to one window,
no-ops on too-little audio; writeWindowWAV declares the given sample rate.
go build/vet + golangci-lint (new-from-merge-base) clean; config + openai
suites green.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ced): add ced-base GGUF model gallery entries (f16 + q8_0)

The ced-base weights are now published at mudler/ced-base-gguf (Apache-2.0,
converted from mispeech/ced-base). Adds gallery/ced.yaml (backend: ced +
known_usecases: sound_classification) and two gallery/index.yaml entries
(ced-base-f16 default, ced-base-q8 smallest) with sha256-pinned files, and
removes the now-resolved TODO from backend/index.yaml.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ced): add tiny/mini/small GGUF model gallery entries

Publishes the rest of the CED family (same architecture, metadata-driven port
verified end-to-end on ced-tiny) to mudler/ced-{tiny,mini,small}-gguf and adds
their f16 + q8_0 gallery entries:

  ced-tiny  (5.5M, edge/Pi-class)  f16 11MB / q8_0 6MB
  ced-mini  (9.6M)                 f16 19MB / q8_0 11MB
  ced-small (22M)                  f16 42MB / q8_0 23MB

All sha256-pinned. ced-base remains the accuracy default.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(ced): point gallery entries at the consolidated mudler/ced-gguf repo

All CED quantizations (tiny/mini/small/base, f16/q8_0) now live in a single
HuggingFace repo, mudler/ced-gguf, instead of per-model repos. Repoint the 8
gallery model entries' urls + file uris accordingly. sha256 and filenames are
unchanged.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(ced): bump CED_VERSION to the short-clip fix

Pin the ced backend to ced.cpp 99c6ed3, which fixes a crash on any clip
shorter than target_length (~10.11s): time_pos_embed was added at its full
63-frame grid instead of being sliced to the clip's actual time grid, tripping
ggml_can_repeat in ggml_add. Surfaced by the live realtime e2e (sub-10s
windows) and gated with a short-clip parity test upstream.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* docs(ced): list ced.cpp as a LocalAI-team engine + backend-guide directive

- README.md: add ced.cpp to the "native C/C++/GGML engines developed and
  maintained by the LocalAI project" table.
- docs/content/features/backends.md: add a Sound Classification backend
  category (sound-event classification / audio tagging) listing ced.cpp.
- .agents/adding-backends.md: add a "Documenting the backend" section and two
  verification-checklist items requiring new backends to be documented in the
  backends.md category list, and in-house native engines to be added to the
  README maintained-engines table. This directive was missing.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(ced): repin CED_VERSION to the v0.1.0 release commit

ced.cpp history was squashed into a single release commit (tagged v0.1.0), so
the previous pin (99c6ed3) no longer exists upstream. Pin to c04ac14, the
v0.1.0 release commit, so the backend builds against a commit that exists.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(ced): silence gosec G304/G103 + govet unsafeptr on audited paths

- sound_classification.go: os.Create(dst) where dst = temp dir + path.Base of
  the upload (no traversal). #nosec G304, matching the depth-anything-cpp handler.
- goced.go: reading a NUL-terminated C string from a libced-owned buffer.
  #nosec G103 (gosec) + //nolint:govet (golangci-lint's unsafeptr check), since
  the uintptr is a C-owned malloc'd buffer, not Go-GC memory.

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>
2026-06-22 01:00:28 +02:00
LocalAI [bot]
9565db5f94 feat(models): model aliases - redirect a model name to another configured model (#10414)
* feat(config): add model alias field and self-validation

Add ModelConfig.Alias (yaml: alias), IsAlias(), and an alias
short-circuit at the top of Validate() that rejects self-reference and
forbids setting backend/parameters.model on a pure-redirect alias.

Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(config): resolve and validate model alias targets in the loader

Assisted-by: Claude:opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(middleware): resolve model aliases and stamp requested/served identity

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(modeladmin): reject alias configs with invalid targets on create/edit

Validate alias targets at create/swap entry points (ImportModelEndpoint,
EditYAML, PatchConfig) so a dangling, chained, or disabled alias target is
rejected at save time rather than surfacing as a runtime error.

Assisted-by: Claude:opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(api): add GET /api/aliases to list model aliases

Adds an admin-gated read-only endpoint that lists every model alias
config as {name, target} pairs, backed by the loader's existing
GetAllModelsConfigs().

Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(mcp): add set_alias and list_aliases tools

Expose model-alias management over the LocalAI Assistant MCP surface:
list_aliases (read-only, GET /api/aliases) and set_alias (mutating).
SetAlias is swap-first: PATCH /api/models/config-json/:name swaps an
existing alias's target (validated, non-destructive) and a 404 falls
back to POST /models/import to create a fresh {name, alias} config. The
inproc client mirrors this via ConfigService.PatchConfig + a create path
modeled on ImportModelEndpoint. Deletion reuses delete_model.

Assisted-by: Claude:claude-opus-4 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* style(mcp): replace em dashes in alias tool comments

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(config-meta): expose alias as a model-select field

Add an 'alias' section to DefaultSections() and an 'alias' field override
in DefaultRegistry() so the schema-driven React editor renders the new
top-level ModelConfig.Alias field as a model picker in its own section.

Assisted-by: Claude:opus-4.8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ui): add alias template card and Manage alias badge

Add an 'Alias / Routing' template to the create-flow gallery that seeds a
minimal name + alias config, and a read-only 'alias -> target' badge on the
Manage Models tab. The capabilities row payload does not carry the alias
field, so the badge resolves targets from GET /api/aliases looked up by name.

Assisted-by: Claude:claude-opus-4 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* docs: document model aliases

Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* docs(swagger): regenerate for GET /api/aliases

Adds the /api/aliases path and AliasInfo schema generated from the
ListAliasesEndpoint annotation.

Assisted-by: Claude:claude-opus-4-8 [Claude Code]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test(localai): check os.RemoveAll error in aliases_test

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix: correct alias conversion docs and advertise /api/aliases in instructions

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(mcp): write alias config 0600 to satisfy gosec G306

The inproc createAlias path wrote the alias YAML with 0644, which gosec
flags as a new G306 finding on the PR. The LocalAI process is the sole
reader/writer of model configs, so 0600 is correct and keeps the scan clean.

Assisted-by: Claude:claude-opus-4-8 [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>
2026-06-20 22:38:42 +02:00
LocalAI [bot]
294170d3ed feat(backend): add depth-anything (Depth Anything 3) C++/ggml backend + gallery (#10352)
* feat(backend): add depth-anything (Depth Anything 3) C++/ggml backend + gallery

Mirrors the locate-anything-cpp backend to register a new depth-anything
backend that wraps the Depth Anything 3 ggml port (depth-anything.cpp) via
purego (cgo-less, no Python at inference).

- backend/go/depth-anything-cpp/: gRPC backend (Load + Predict + GenerateImage),
  purego binding to the da_capi_* C ABI, CMake/Makefile/run/package/test scripts
  building depth-anything.cpp's DA_SHARED static .so per CPU variant.
- backend/index.yaml: depth-anything backend meta + all hardware-variant
  capability entries (cpu/cuda12/cuda13/intel-sycl-f32+f16/vulkan/nvidia-l4t).
- gallery/index.yaml: 8 Depth Anything 3 GGUF models (base q4_k/q8_0/f16/f32,
  small, large, giant, mono-large).
- .github/backend-matrix.yml: one build entry per hardware variant.

Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(depth): typed Depth RPC + REST endpoint exposing full DA3 data

Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(depth): pin depth-anything.cpp to e0b6814 (ABI 3 dense C-API)

The Depth RPC handler calls da_capi_depth_dense / da_capi_points (C-API ABI 3);
pin the native build to the commit that exports them.

Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(depth): pin depth-anything.cpp to v0.1.0 release (b515c31)

Repoint the native version from the now-orphaned e0b6814 to the
b515c31 release commit, kept alive by the upstream v0.1.0 tag.
C-API is unchanged (da_capi_abi_version == 3).

Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(depth): wire depth-anything-cpp into build, CI bump, and importer

The backend dir, gallery index, and CI build-matrix were present but the
backend was never wired into the integration points that adding-backends.md
requires:

- root Makefile: add to .NOTPARALLEL, the test-extra chain, a BACKEND_*
  definition, the docker-build target eval, and docker-build-backends
  (mirrors parakeet-cpp; the backend's own Makefile already documented that
  its `test` target is driven by test-extra).
- bump_deps.yaml: register the DEPTHANYTHING_VERSION pin so the daily
  auto-bump bot tracks mudler/depth-anything.cpp master (it cannot see an
  unregistered Makefile pin).
- import form: add a preference-only KnownBackend entry so depth-anything is
  selectable at /import-model (mirrors sam3-cpp; no reliable GGUF auto-detect
  signal, so pref-only per the doc's default).

changed-backends.js needs no entry: the generic golang suffix branch already
resolves backend/go/depth-anything-cpp/.

Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(depth): auto-detect importer for depth-anything GGUFs

Replace the preference-only entry with a real auto-detect importer
(mirrors parakeet-cpp / locate-anything):

- DepthAnythingImporter matches a .gguf whose name carries a
  depth-anything token (depth-anything-<size>-<quant>.gguf), so
  /import-model recognises mudler/depth-anything.cpp-gguf repos and direct
  GGUF URLs without an explicit backend preference. preferences.backend=
  "depth-anything" still forces it.
- Registered before LlamaCPPImporter so its GGUF bundles aren't claimed by
  the generic .gguf importer; the narrow name match means it cannot claim
  arbitrary llama GGUFs or the upstream safetensors PyTorch repos.
- Multi-quant repos pick the smallest quant by default (q4_k -> ... -> f32,
  depth stays >0.998 corr even at q4_k); quantizations preference overrides.
- Drops the now-redundant knownPrefOnlyBackends entry (importer-backed
  backends are not listed there, matching parakeet-cpp).
- Table-driven Ginkgo test covers detection, negative cases (llama GGUF,
  upstream safetensors), default/override/fallback quant pick, and direct
  URL import. 10/10 specs pass.

Assisted-by: Claude:claude-opus-4-8
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(depth): check conn.Close error in grpc Depth client (errcheck)

The new Depth() client method used a bare `defer conn.Close()`. golangci-lint
runs with new-from-merge-base, so although the 39 sibling methods use the same
bare form (grandfathered), the newly added line trips errcheck. Drop the result
explicitly to satisfy the linter.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8

* fix(depth): bump depth-anything.cpp to v0.1.1 (embeddable CMake)

v0.1.0 (b515c31) used ${CMAKE_SOURCE_DIR} for its include dirs, which
points at the parent project when built via add_subdirectory() as this
backend does, so the container build failed with missing stb_image.h /
da_gguf_keys.h. v0.1.1 (2d42897) switches to project-relative paths.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8

* fix(depth): resolve gosec findings in the backend wrapper

The code-scanning gate flagged three new failure-level alerts in
godepthanythingcpp.go (gosec runs with -no-fail; GitHub gates on new alerts):

- G301: export dirs were created with 0o755. Tighten to 0o750 (no world
  access needed for backend-written export output).
- G304: writeDepthPNG creates req.GetDst(). That path is chosen by the
  LocalAI core as the intended output destination (same pattern every
  image backend uses), not attacker input, so annotate with #nosec G304
  and document why.

The remaining G103 "audit unsafe" notes on the unsafe.Slice C-buffer copies
are warning-level (the same purego interop whisper/parakeet use) and do not
gate the check, per the supertonic exclusion precedent in secscan.yaml.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8

* fix(depth): bump depth-anything.cpp to v0.1.2 (CUDA cross-build arch)

v0.1.1 forced CMAKE_CUDA_ARCHITECTURES=native, which breaks the GPU-less
l4t/cublas CI builds (nvcc "Unsupported gpu architecture 'compute_'" on
CMake 3.22). v0.1.2 (442eea4) drops the override and lets ggml pick its
default cross-build arch list.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-8

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-06-16 16:28:28 +02:00
LocalAI [bot]
06e777b75e feat(distributed): gated X-LocalAI-Node response header (middleware + wrapper) (#9976)
* feat(distributed): add per-request node ID context holder

Introduce pkg/distributedhdr, a leaf package carrying a per-request
*atomic.Value holder for the picked worker node ID from the
SmartRouter (core/services/nodes) up to the HTTP response writer
wrapper (core/http/middleware). Avoids the import cycle that a shared
key in either consumer would create.

Exposes NewHolder, WithHolder, Holder, Stamp, Load, Inherit. The
holder is atomic.Value so cross-goroutine publish from the router to
the response writer wrapper is race-clean.

Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(distributed): add ExposeNodeHeader middleware + response writer wrapper

New ApplicationConfig.ExposeNodeHeader bool + --expose-node-header CLI
flag / LOCALAI_EXPOSE_NODE_HEADER env var (default off; the node ID
reveals internal topology and is opt-in).

The middleware creates a per-request *atomic.Value holder, attaches it
to c.Request().Context() via distributedhdr.WithHolder, and wraps
c.Response().Writer with a custom http.ResponseWriter that sets the
X-LocalAI-Node header on first Write / WriteHeader / Flush by reading
the holder. Implements http.Flusher, http.Hijacker, Unwrap so it
composes cleanly with Echo and http.NewResponseController.

request.go propagates the holder onto derived contexts via
distributedhdr.Inherit so the holder survives the correlation-ID
context replacement.

Unit + race-clean concurrency + integration specs.

Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(distributed): stamp node ID in router and wire middleware to inference routes

ModelRouterAdapter.Route stamps the picked node ID into the
per-request holder via distributedhdr.Stamp(ctx, result.Node.ID) right
after replica selection.

Wire ExposeNodeHeader middleware to:
- OpenAI chat/completion/embeddings + audio transcriptions/speech + image generations/inpainting
- Anthropic /v1/messages
- Ollama /api/chat, /api/generate, /api/embed, /api/embeddings
- Jina /v1/rerank
- LocalAI /v1/vad

The middleware's wrapper reads the holder on first byte and sets the
X-LocalAI-Node response header before delegating to the underlying
writer. Per-request scope means no race under concurrent multi-replica
routing.

Assisted-by: Claude:claude-opus-4-7[1m]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(distributed): thread request context through backend Load + cover ctx propagation

Five non-OpenAI backend helpers were silently using app.Context instead
of the request context for the gRPC backend call: transcription, TTS,
image generation, rerank, VAD. Effect: distributedhdr.Stamp in the
router callback was a silent no-op for these paths, AND client
cancellation didn't propagate to in-flight inference.

Thread c.Request().Context() (or the equivalent input.Context after
the request middleware has installed the correlation-ID derived
context) through each helper and into ModelOptions via
model.WithContext(ctx). ImageGeneration's signature gains a leading
ctx parameter; in-tree callers (openai image, openai inpainting,
openai inpainting_test) are updated to match.

ModelEmbedding gains a leading ctx parameter for the same reason; the
openai and ollama embedding handlers pass the request context through.

chat_stream_workers.go defers the initial role=assistant chunk
emission until the first token callback so the wrapper's lazy
X-LocalAI-Node lookup against the loader runs AFTER ml.Load has
stamped the per-modelID node ID; semantically identical for clients
(role still arrives before any text).

Regression test core/backend/ctx_propagation_test.go pins ctx
propagation for all five helpers.

Docs updated to enumerate the full endpoint coverage of the
--expose-node-header flag.

Assisted-by: Claude:claude-opus-4-7[1m]
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>
2026-05-25 10:51:48 +02:00
Richard Palethorpe
6a80e23733 feat(middleware): Model routing, PII filtering, Cloud model proxies (#9802)
Add a routing middleware stack and a cloud-proxy backend.

* cloud-proxy: a Go gRPC backend that forwards OpenAI- and
  Anthropic-shaped chat requests to upstream providers, with an
  optional translate mode (OpenAI request -> Anthropic /v1/messages
  -> OpenAI response) and full tool-calling support.

* routing: admission control, content-aware model routing
  (embedding cache + classifier + rerank + Arch-Router score),
  PII detection/redaction (regex + NER) with streaming filter and
  OpenAI/Anthropic adapters, and a per-user/per-key billing recorder
  backed by GORM or in-memory storage.

* middleware: UsageMiddleware records usage via the billing recorder,
  plus admission, route-model, usage-stamp and trace middlewares.

* observability: BackendTrace ring buffer stores full request bodies
  (capped), MITM proxy emits structured trace events, and router
  classifier decisions surface at /api/router/decide.

* gallery: Arch-Router-1.5B (Q4_K_M and Q8_0).

* UI: cloud-proxy model-editor fields, classifier system-prompt and
  score-normalization config, and a Traces page rendering request
  bodies.

Assisted-by: claude-code:claude-opus-4-7 [Read] [Edit] [Bash]

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-25 09:28:27 +02:00
Ettore Di Giacinto
e86ade54a6 feat(api): add /v1/audio/diarization endpoint with sherpa-onnx + vibevoice.cpp (#9654)
* feat(api): add /v1/audio/diarization endpoint with sherpa-onnx + vibevoice.cpp

Closes #1648.

OpenAI-style multipart endpoint that returns "who spoke when". Single
endpoint instead of the issue's three-endpoint sketch (refactor /vad,
/vad/embedding, /diarization) — the typical client wants one call, and
embeddings can land later as a sibling without breaking this surface.

Response shape borrows from Pyannote/Deepgram: segments carry a
normalised SPEAKER_NN id (zero-padded, stable across the response) plus
the raw backend label, optional per-segment text when the backend bundles
ASR, and a speakers summary in verbose_json. response_format also accepts
rttm so consumers can pipe straight into pyannote.metrics / dscore.

Backends:

* vibevoice-cpp — Diarize() reuses the existing vv_capi_asr pass.
  vibevoice's ASR prompt asks the model to emit
  [{Start,End,Speaker,Content}] natively, so diarization is a by-product
  of the same pass; include_text=true preserves the transcript per
  segment, otherwise we drop it.

* sherpa-onnx — wraps the upstream SherpaOnnxOfflineSpeakerDiarization
  C API (pyannote segmentation + speaker-embedding extractor + fast
  clustering). libsherpa-shim grew config builders, a SetClustering
  wrapper for per-call num_clusters/threshold overrides, and a
  segment_at accessor (purego can't read field arrays out of
  SherpaOnnxOfflineSpeakerDiarizationSegment[] directly).

Plumbing: new Diarize gRPC RPC + DiarizeRequest / DiarizeSegment /
DiarizeResponse messages, threaded through interface.go, base, server,
client, embed. Default Base impl returns unimplemented.

Capability surfaces all updated: FLAG_DIARIZATION usecase,
FeatureAudioDiarization permission (default-on), RouteFeatureRegistry
entries for /v1/audio/diarization and /audio/diarization, audio
instruction-def description widened, CAP_DIARIZATION JS symbol,
swagger regenerated, /api/instructions discovery map updated.

Tests:

* core/backend: speaker-label normalisation (first-seen → SPEAKER_NN,
  per-speaker totals, nil-safety, fallback to backend NumSpeakers when
  no segments).

* core/http/endpoints/openai: RTTM rendering (file-id basename, negative
  duration clamping, fallback id).

* tests/e2e: mock-backend grew a deterministic Diarize that emits
  raw labels "5","2","5" so the e2e suite verifies SPEAKER_NN
  remapping, verbose_json speakers summary + transcript pass-through
  (gated by include_text), RTTM bytes content-type, and rejection of
  unknown response_format. mock-diarize model config registered with
  known_usecases=[FLAG_DIARIZATION] to bypass the backend-name guard.

Docs: new features/audio-diarization.md (request/response, RTTM example,
sherpa-onnx + vibevoice setup), cross-link from audio-to-text.md, entry
in whats-new.md.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(diarization): correct sherpa-onnx symbol name + lint cleanup

CI failures on #9654:

* sherpa-onnx-grpc-{tts,transcription} and sherpa-onnx-realtime panicked
  at backend startup with `undefined symbol: SherpaOnnxDestroyOfflineSpeakerDiarizationResult`.
  Upstream's actual symbol is SherpaOnnxOfflineSpeakerDiarizationDestroyResult
  (Destroy in the middle, not the prefix); the rest of the diarization
  surface follows the same naming pattern. The mismatched name made
  purego.RegisterLibFunc fail at dlopen time and crashed the gRPC server
  before the BeforeAll could probe Health, taking down every sherpa-onnx
  test job — not just the diarization-related ones.

* golangci-lint flagged 5 errcheck violations on new defer cleanups
  (os.RemoveAll / Close / conn.Close); wrap each in a `defer func() { _ = X() }()`
  closure (matches the pattern other LocalAI files use for new code, since
  pre-existing bare defers are grandfathered in via new-from-merge-base).

* golangci-lint also flagged forbidigo violations: the new
  diarization_test.go files used testing.T-style `t.Errorf` / `t.Fatalf`,
  which are forbidden by the project's coding-style policy
  (.agents/coding-style.md). Convert both files to Ginkgo/Gomega
  Describe/It with Expect(...) — they get picked up by the existing
  TestBackend / TestOpenAI suites, no new suite plumbing needed.

* modernize linter: tightened the diarization segment loop to
  `for i := range int(numSegments)` (Go 1.22+ idiom).

Verified locally: golangci-lint with new-from-merge-base=origin/master
reports 0 issues across all touched packages, and the four mocked
diarization e2e specs in tests/e2e/mock_backend_test.go still pass.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(vibevoice-cpp): convert non-WAV input via ffmpeg + raise ASR token budget

Confirmed end-to-end against a real LocalAI instance with vibevoice-asr-q4_k
loaded and the multi-speaker MP3 sample at vibevoice.cpp/samples/2p_argument.mp3:
both /v1/audio/transcriptions and /v1/audio/diarization now succeed and
return correctly attributed speaker turns for the full clip.

Two latent issues surfaced once the diarization endpoint actually exercised
the backend with a non-trivial input:

1. vv_capi_asr only accepts WAV via load_wav_24k_mono. The previous code
   passed the uploaded path straight through, so anything that wasn't
   already a 24 kHz mono s16le WAV failed at the C side with rc=-8 and
   the very unhelpful "vv_capi_asr failed". prepareWavInput shells out
   to ffmpeg ("-ar 24000 -ac 1 -acodec pcm_s16le") in a per-call temp
   dir, matching the rate the model was trained on; both AudioTranscription
   and Diarize now route through it. This is the same shape sherpa-onnx
   uses (utils.AudioToWav), but vibevoice needs 24 kHz rather than 16 kHz
   so we don't reuse that helper.

2. The C ABI's max_new_tokens defaults to 256 when 0 is passed. That's
   fine for a five-second clip but not for anything past ~10 s — vibevoice
   stops mid-JSON, the parse fails, and the caller sees a hard error.
   Pass a much larger budget (16 384 ≈ ~9 minutes of speech at the
   model's ~30 tok/s rate); generation stops at EOS so this is a cap
   rather than a target.

3. As a defensive belt-and-braces, mirror AudioTranscription's existing
   "fall back to a single segment if the model emits non-JSON text"
   pattern in Diarize, so partial / unusual model output never produces
   a 500. This kept the endpoint usable while diagnosing (1) and (2),
   and is the right behaviour to keep.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(vibevoice-cpp): pass valid WAVs through directly so ffmpeg is not required at runtime

Spotted by tests-e2e-backend (1.25.x): the previous fix forced every
incoming audio file through `ffmpeg -ar 24000 ...`, which meant the
backend container — which does not ship ffmpeg — failed even for the
existing happy path where the caller already uploads a WAV. The
container-side error was:

    rpc error: code = Unknown desc = vibevoice-cpp: ffmpeg convert to
    24k mono wav: exec: "ffmpeg": executable file not found in $PATH

Reading vibevoice.cpp's audio_io.cpp, `load_wav_24k_mono` uses drwav and
already accepts any PCM/IEEE-float WAV at any sample rate, downmixes
multi-channel input to mono, and resamples to 24 kHz internally. So the
only inputs that genuinely need an external converter are non-WAV
formats (MP3, OGG, FLAC, ...).

Detect WAVs by RIFF/WAVE magic at bytes 0..3 / 8..11 and pass them
straight through with a no-op cleanup; everything else still goes
through ffmpeg with the same 24 kHz mono s16le target. The result:

* Container builds without ffmpeg keep working for WAV uploads
  (the e2e-backends fixture is jfk.wav at 16 kHz mono s16le).
* MP3 and other non-WAV inputs still get the new ffmpeg conversion
  path so the diarization endpoint stays useful.
* If the caller uploads a non-WAV but ffmpeg isn't on PATH, the
  surfaced error is still descriptive enough to act on.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* fix(ci): make gcc-14 install in Dockerfile.golang best-effort for jammy bases

The LocalVQE PR (bb033b16) made `gcc-14 g++-14` an unconditional apt
install in backend/Dockerfile.golang and pointed update-alternatives at
them. That works on the default `BASE_IMAGE=ubuntu:24.04` (noble has
gcc-14 in main), but every Go backend that builds on
`nvcr.io/nvidia/l4t-jetpack:r36.4.0` — jammy under the hood — now fails
at the apt step:

    E: Unable to locate package gcc-14

This blocked unrelated jobs:
backend-jobs(*-nvidia-l4t-arm64-{stablediffusion-ggml, sam3-cpp, whisper,
acestep-cpp, qwen3-tts-cpp, vibevoice-cpp}). LocalVQE itself is only
matrix-built on ubuntu:24.04 (CPU + Vulkan), so it doesn't actually
need gcc-14 anywhere else.

Make the gcc-14 install conditional on the package being available in
the configured apt repos. On noble: identical behaviour to today (gcc-14
installed, update-alternatives points at it). On jammy: skip the
gcc-14 stanza entirely and let build-essential's default gcc take over,
which is what the other Go backends compile with anyway.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-05 15:10:13 +02:00
Richard Palethorpe
bb033b16a9 feat: add LocalVQE backend and audio transformations UI (#9640)
feat(audio-transform): add LocalVQE backend, bidi gRPC RPC, Studio UI

Introduce a generic "audio transform" capability for any audio-in / audio-out
operation (echo cancellation, noise suppression, dereverberation, voice
conversion, etc.) and ship LocalVQE as the first backend implementation.

Backend protocol:
- Two new gRPC RPCs in backend.proto: unary AudioTransform for batch and
  bidirectional AudioTransformStream for low-latency frame-by-frame use.
  This is the first bidi stream in the proto; per-frame unary at LocalVQE's
  16 ms hop would be RTT-bound. Wire it through pkg/grpc/{client,server,
  embed,interface,base} with paired-channel ergonomics.

LocalVQE backend (backend/go/localvqe/):
- Go-Purego wrapper around upstream liblocalvqe.so. CMake builds the upstream
  shared lib + its libggml-cpu-*.so runtime variants directly — no MODULE
  wrapper needed because LocalVQE handles CPU feature selection internally
  via GGML_BACKEND_DL.
- Sets GGML_NTHREADS from opts.Threads (or runtime.NumCPU()-1) — without it
  LocalVQE runs single-threaded at ~1× realtime instead of the documented
  ~9.6×.
- Reference-length policy: zero-pad short refs, truncate long ones (the
  trailing portion can't have leaked into a mic that wasn't recording).
- Ginkgo test suite (9 always-on specs + 2 model-gated).

HTTP layer:
- POST /audio/transformations (alias /audio/transform): multipart batch
  endpoint, accepts audio + optional reference + params[*]=v form fields.
  Persists inputs alongside the output in GeneratedContentDir/audio so the
  React UI history can replay past (audio, reference, output) triples.
- GET /audio/transformations/stream: WebSocket bidi, 16 ms PCM frames
  (interleaved stereo mic+ref in, mono out). JSON session.update envelope
  for config; constants hoisted in core/schema/audio_transform.go.
- ffmpeg-based input normalisation to 16 kHz mono s16 WAV via the existing
  utils.AudioToWav (with passthrough fast-path), so the user can upload any
  format / rate without seeing the model's strict 16 kHz constraint.
- BackendTraceAudioTransform integration so /api/backend-traces and the
  Traces UI light up with audio_snippet base64 and timing.
- Routes registered under routes/localai.go (LocalAI extension; OpenAI has
  no /audio/transformations endpoint), traced via TraceMiddleware.

Auth + capability + importer:
- FLAG_AUDIO_TRANSFORM (model_config.go), FeatureAudioTransform (default-on,
  in APIFeatures), three RouteFeatureRegistry rows.
- localvqe added to knownPrefOnlyBackends with modality "audio-transform".
- Gallery entry localvqe-v1-1.3m (sha256-pinned, hosted on
  huggingface.co/LocalAI-io/LocalVQE).

React UI:
- New /app/transform page surfaced via a dedicated "Enhance" sidebar
  section (sibling of Tools / Biometrics) — the page is enhancement, not
  generation, so it lives outside Studio. Two AudioInput components
  (Upload + Record tabs, drag-drop, mic capture).
- Echo-test button: records mic while playing the loaded reference through
  the speakers — the mic naturally picks up speaker bleed, giving a real
  (mic, ref) pair for AEC testing without leaving the UI.
- Reusable WaveformPlayer (canvas peaks + click-to-seek + audio controls)
  and useAudioPeaks hook (shared module-scoped AudioContext to avoid
  hitting browser context limits with three players on one page); migrated
  TTS, Sound, Traces audio blocks to use it.
- Past runs saved in localStorage via useMediaHistory('audio-transform') —
  the history entry stores all three URLs so clicking re-renders the full
  triple, not just the output.

Build + e2e:
- 11 matrix entries removed from .github/workflows/backend.yml (CUDA, ROCm,
  SYCL, Metal, L4T): upstream supports only CPU + Vulkan, so we ship those
  two and let GPU-class hardware route through Vulkan in the gallery
  capabilities map.
- tests-localvqe-grpc-transform job in test-extra.yml (gated on
  detect-changes.outputs.localvqe).
- New audio_transform capability + 4 specs in tests/e2e-backends.
- Playwright spec suite in core/http/react-ui/e2e/audio-transform.spec.js
  (8 specs covering tabs, file upload, multipart shape, history, errors).

Docs:
- New docs/content/features/audio-transform.md covering the (audio,
  reference) mental model, batch + WebSocket wire formats, LocalVQE param
  keys, and a YAML config example. Cross-links from text-to-audio and
  audio-to-text feature pages.

Assisted-by: Claude:claude-opus-4-7 [Bash Read Edit Write Agent TaskCreate]

Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-05-04 22:07:11 +02:00
Ettore Di Giacinto
bcef72b9c1 feat: localai assistant chat modality (#9602)
* fix(tests): inline model_test fixtures after tests/models_fixtures removal

The previous reorg removed tests/models_fixtures/ but core/config/model_test.go
still read CONFIG_FILE/MODELS_PATH env vars pointing into that directory, so
`make test` failed with "open : no such file or directory" on the readConfigFile
spec (the suite ran with --fail-fast and bailed before openresponses_test).

Inline the YAMLs (config/embeddings/grpc/rwkv/whisper) directly into the test
file, materialise them into a per-test tmpdir via BeforeEach, and drop the
env-var lookups. The test no longer depends on Makefile plumbing.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: claude-code:claude-opus-4-7 [Edit] [Write] [Bash]

* refactor(modeladmin): extract model-admin helpers into a service package

Lift the bodies of EditModelEndpoint, PatchConfigEndpoint,
ToggleStateModelEndpoint, TogglePinnedModelEndpoint and
VRAMEstimateEndpoint into core/services/modeladmin so the same logic can
be called by non-HTTP clients (notably the in-process MCP server that
backs the LocalAI Assistant chat modality, landing in a follow-up commit).

The HTTP handlers shrink to thin shells that parse echo inputs, call the
matching helper, map typed errors (ErrNotFound, ErrConflict,
ErrPathNotTrusted, ErrBadAction, ...) to the existing HTTP status codes,
and render the existing response shapes. No REST-surface behaviour change;
the existing localai endpoint tests cover the regression net.

Adds focused unit tests for each helper against tmp-dir-backed
ModelConfigLoader fixtures (deep-merge patch, rename + conflict, path
separator guard, toggle/pin enable/disable, sync callback).

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(assistant): LocalAI Assistant chat modality with in-memory MCP server

Adds a chat modality, admin-only, that wires the chat session to an
in-memory MCP server exposing LocalAI's own admin/management surface as
tools. An admin can install models, manage backends, edit configs and
check status by chatting; the LLM calls tools like gallery_search,
install_model, import_model_uri, list_installed_models, edit_model_config
and surfaces the results.

Same Go package powers two modes:

  pkg/mcp/localaitools/

    NewServer(client, opts) builds an MCP server that registers the
    19-tool admin catalog. The LocalAIClient interface has two impls:

    - inproc.Client — calls services directly (no HTTP loopback,
      no synthetic admin API key). Used in-process by the chat handler.
    - httpapi.Client — calls the LocalAI REST API. Used by the new
      `local-ai mcp-server --target=…` subcommand to control a remote
      LocalAI from a stdio MCP host.

    Tools and their embedded skill prompts are agnostic to which client
    backs them. Skill prompts are markdown files under prompts/, embedded
    via go:embed and assembled into the system prompt at server init.

Wiring:

  - core/http/endpoints/mcp/localai_assistant.go — process-wide holder
    that spins up the in-memory MCP server once at Application start
    using paired net.Pipe transports, then reuses LocalToolExecutor
    (no fork) for every chat request that opts in.

  - core/http/endpoints/openai/chat.go — small branch ahead of the
    existing MCP block: when metadata.localai_assistant=true,
    defense-in-depth admin check + executor swap + system-prompt
    injection. All downstream tool dispatch is unchanged.

  - core/http/auth/{permissions,features}.go — adds
    FeatureLocalAIAssistant; gating happens at the chat handler entry
    plus admin-only `/api/settings`.

  - core/cli/{run.go,cli.go,mcp_server.go} —
    LOCALAI_DISABLE_ASSISTANT flag (runtime-toggleable via Settings, no
    restart), plus `local-ai mcp-server` stdio subcommand.

  - core/config/runtime_settings.go — `localai_assistant_enabled`
    runtime setting; the chat handler reads `DisableLocalAIAssistant`
    live at request entry.

UI:

  - Home.jsx — prominent self-explanatory CTA card on first run
    ("Manage LocalAI by chatting"); collapses to a compact
    "Manage by chat" button in the quick-links row once used,
    persisted via localStorage.
  - Chat.jsx — admin-only "Manage" toggle in the chat header,
    "Manage mode" badge, dedicated empty-state copy, starter chips.
  - Settings.jsx — "LocalAI Assistant" section with the runtime
    enable toggle.
  - useChat.js — `localaiAssistant` flag on the chat schema; injects
    `metadata.localai_assistant=true` on requests when active.

Distributed mode: the in-memory MCP server lives only on the head node;
inproc.Client wraps already-distributed-aware services so installs
propagate to workers via the existing GalleryService machinery.

Documentation: `.agents/localai-assistant-mcp.md` is the contributor
contract — when adding an admin REST endpoint, also add a LocalAIClient
method, an inproc + httpapi impl, a tool registration, and a skill
prompt update; the AGENTS.md index links to it.

Out of scope (follow-ups): per-tool RBAC granularity for non-admin
read-only access; streaming mcp_tool_progress for long installs;
React Vitest rig for the UI changes.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(assistant): extract tool/capability/MiB/server-name constants

The MCP tool surface, capability tag set, server-name default, and the
chat-handler metadata key were repeated as bare string literals across
seven files. Renaming any one required hand-editing every call site and
risked code/test/prompt drift.

This pulls them into typed constants:

- pkg/mcp/localaitools/tools.go — Tool* constants for the 19 MCP tools,
  plus DefaultServerName.
- pkg/mcp/localaitools/capability.go — typed Capability + constants for
  the capability tag set the LLM passes to list_installed_models. The
  type rides through LocalAIClient.ListInstalledModels and replaces the
  triplet of "embed"/"embedding"/"embeddings" with the single
  CapabilityEmbeddings.
- pkg/mcp/localaitools/inproc/client.go — bytesPerMiB constant for the
  VRAMEstimate byte→MB conversion.
- core/http/endpoints/mcp/tools.go — MetadataKeyLocalAIAssistant for the
  "localai_assistant" request-metadata key consumed by the chat handler.

Tool registrations, the test catalog, the dispatch table, the validation
fixtures, and the fake/stub clients all reference the constants. The
embedded skill prompts under prompts/ keep their bare strings (go:embed
markdown can't import Go constants); the existing TestPromptsContain
SafetyAnchors guards the alignment.

No behaviour change. All tests pass with -race.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(modeladmin): typed Action for ToggleState/TogglePinned

The toggle/pin verbs were bare strings everywhere — handler signatures,
service implementations, MCP tool args, the fake/stub clients, the
inproc and httpapi LocalAIClient impls, plus 4 test files. A typo in
any caller silently fell through to the runtime "must be 'enable' or
'disable'" check.

Introduce core/services/modeladmin.Action (string alias) with
ActionEnable, ActionDisable, ActionPin, ActionUnpin and a small Valid
helper. The compiler now catches mismatches at every boundary; renames
ripple through one source of truth.

LocalAIClient.ToggleModelState/Pinned signatures change to take
modeladmin.Action. The package is brand-new and unreleased so this is
a free public-API tightening.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(assistant): respect ctx cancellation on gallery channel sends

InstallModel, DeleteModel, ImportModelURI, InstallBackend and
UpgradeBackend all pushed onto galleryop channels with bare sends. If the
worker was paused or the buffer full, the chat-handler goroutine blocked
forever — the LLM kept polling and the request leaked.

Wrap the five sends in a sendModelOp/sendBackendOp helper that selects
on ctx.Done() so a cancelled chat completion surfaces context.Canceled
back to the LLM instead of hanging.

Adds inproc/client_test.go with a pre-cancelled-ctx regression test on
InstallModel; the helpers are shared so the same guarantee covers the
other four call sites.

Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(assistant): graceful shutdown for in-memory holder and stdio CLI

Two related leaks:

- Application.start() built the LocalAIAssistantHolder but never wired
  Close() into the graceful-termination chain — the in-memory MCP
  transport pair stayed alive until process exit, and the goroutines
  behind net.Pipe() didn't drain. Hook into the existing
  signals.RegisterGracefulTerminationHandler chain (same pattern as
  core/http/endpoints/mcp/tools.go:770).

- core/cli/mcp_server.go ran srv.Run with context.Background(); a
  Ctrl-C from the host (Claude Desktop, mcphost, npx inspector) or a
  SIGTERM from process supervision left the stdio loop reading from a
  closed pipe. Switch to signal.NotifyContext to surface the signal
  through ctx and let srv.Run drain.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(assistant): typed HTTPError + propagate prompt walk error

The httpapi client detected "no such job" by substring-matching on the
error string ("404", "could not find") — brittle to status-code
formatting changes and to LocalAI fixing /models/jobs/:uuid to return a
proper 404. Replace with a typed *HTTPError whose Is() method honours
errors.Is(err, ErrHTTPNotFound). The 500-with-"could not find" branch
stays as a transitional fallback documented in Is().

Same change covers ListNodes' 404 fallback for the /api/nodes endpoint.

Adds httptest tests for both 404 and the legacy 500 path, plus a
direct errors.Is exposure test so external callers (the standalone
stdio CLI host) can match without re-string-parsing.

Also tightens prompts.SystemPrompt: panic when fs.WalkDir on the
embedded FS fails. The only realistic cause is a build-time //go:embed
misconfiguration; serving an empty system prompt to the LLM is much
worse than crashing init. TestSystemPromptIncludesAllEmbeddedFiles
catches regressions in CI.

Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(modeladmin): atomic writes for model config files

The five sites that wrote model YAML used os.WriteFile, which opens
with O_TRUNC|O_WRONLY|O_CREATE. A crash mid-write left the destination
truncated and the model unloadable until manual repair. Pre-existing
behaviour inherited from the original endpoint handlers — fix once now
that there's a single helper.

Adds writeFileAtomic: writes to a sibling temp file, chmods, syncs via
Close(), then os.Rename. Same-directory temp keeps the rename atomic on
the same filesystem; cleanup runs on every error path so stray temps
don't accumulate. No new dependency.

Applied to:
- ConfigService.PatchConfig
- ConfigService.EditYAML (both rename and in-place branches)
- mutateYAMLBoolFlag (drives ToggleState + TogglePinned)

atomic_test.go covers the happy path plus a read-only-dir failure case
that asserts the original file is preserved (skipped on Windows where
the chmod trick is POSIX-specific).

Assisted-by: Claude:claude-opus-4-7 [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(assistant): prune dead code, mark stub, document conventions

Three small cleanups landing together:

- Drop the unused errNotImplemented sentinel from inproc/client.go.
  All five methods that used to return it are wired to modeladmin
  helpers since the Phase B commit; the package var is dead.

- Annotate httpapi.Client.GetModelConfig as a known stub. LocalAI's
  /models/edit/:name returns rendered HTML, not JSON, so the standalone
  CLI's get_model_config tool surfaces a clear error to the LLM. A
  future JSON-only /api/models/config-yaml/:name endpoint is tracked in
  the agent contract; FIXME points at it.

- Extend `.agents/localai-assistant-mcp.md` with a "Code conventions"
  section that documents the audit-driven rules: tool/Capability/Action
  constants, errors.Is over substring matching, ctx-aware channel
  sends, atomic writes, and graceful shutdown. Refresh the file map so
  it lists tools.go and capability.go and drops the removed
  tools_bootstrap.go.

The tools_models.go diff is a comment-only change explaining why the
ModelName empty-string check stays at the tool layer (consistency
across LocalAIClient implementations, since the SDK schema validator
only enforces presence, not non-empty).

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test(assistant): convert test files to ginkgo + gomega

The repo convention (per core/http/endpoints/localai/*_test.go,
core/gallery/**, etc.) is Ginkgo v2 with Gomega assertions. The tests I
introduced for the assistant feature used vanilla testing.T, which made
them stand out and stripped the BDD structure the rest of the suite
relies on.

Convert every test file in the assistant scope to Ginkgo:

  pkg/mcp/localaitools/
    dto_test.go            — Describe("DTOs round-trip through JSON")
    prompts_test.go        — Describe("SystemPrompt assembler")
    server_test.go         — Describe("Server tool catalog"),
                              Describe("Tool dispatch"),
                              Describe("Tool error surfacing"),
                              Describe("Argument validation"),
                              Describe("Concurrent tool calls")
    parity_test.go         — Describe("LocalAIClient parity"),
                              hosts the suite's single RunSpecs (the file
                              is package localaitools_test so it can
                              import httpapi without an import cycle;
                              Ginkgo aggregates Describes from both the
                              internal and external test packages into
                              one run).
    httpapi/client_test.go — Describe("httpapi.Client against the
                              LocalAI admin REST surface"),
                              Describe("ErrHTTPNotFound"),
                              Describe("Bearer token")
    inproc/client_test.go  — Describe("inproc.Client cancellation")

  core/services/modeladmin/
    config_test.go         — Describe("ConfigService") with sub-Describes
                              for GetConfig, PatchConfig, EditYAML
    state_test.go          — Describe("ConfigService.ToggleState")
    pinned_test.go         — Describe("ConfigService.TogglePinned")
    atomic_test.go         — Describe("writeFileAtomic")

  core/http/endpoints/mcp/
    localai_assistant_test.go — Describe("LocalAIAssistantHolder")

Each package gets a `*_suite_test.go` with the standard
`RegisterFailHandler(Fail) + RunSpecs(t, "...")` boilerplate. Helpers
that previously took *testing.T (newTestService, writeModelYAML,
readMap, sortedStrings, sortGalleries, etc.) drop the *T receiver and
use Gomega Expectations directly. tmp dirs come from GinkgoT().TempDir().

No semantic change to test coverage — every original assertion has a
direct Gomega counterpart. All suites pass with -race.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test+docs(assistant): drift detector for Tool ↔ REST route mapping

Honest gap from the audit: the parity_test.go suite only checks four
methods, and uses the same httpapi.Client for both sides — it asserts
stability of the DTO shapes, not equivalence between in-process and
HTTP. If a contributor adds an admin REST endpoint without an MCP tool,
or a tool without a matching httpapi route, both surfaces silently
diverge.

Add a coverage test plus stronger docs:

- pkg/mcp/localaitools/coverage_test.go introduces a hand-maintained
  toolToHTTPRoute map: every Tool* constant must list the REST endpoint
  the httpapi.Client hits (or "(none)" with a documented reason). Two
  Ginkgo specs assert the map and the published catalog stay in sync —
  one fails when a Tool is added without a route entry, the other fails
  when a route entry references a tool that no longer exists. Verified
  by removing the ToolDeleteModel entry locally; the test fired with a
  clear message pointing the contributor at the file.

  Deliberate non-test: we don't enumerate live admin REST routes from
  here. Walking the route registry requires booting Application;
  parsing core/http/routes/localai.go is brittle. The "new admin REST
  endpoint → MCP tool" direction stays a PR checklist item — see below.

- AGENTS.md gets a new Quick Reference bullet that calls out the rule
  and points at the test by name.

- .agents/api-endpoints-and-auth.md tightens the existing "Companion:
  MCP admin tool surface" subsection from "if useful, consider..." to
  "MUST be considered, with three concrete outcomes (tool added,
  deliberately skipped with documented reason, or forgot — which
  breaks the contract)". Adds a checklist item at the bottom of the
  file's authoritative checklist.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(assistant): drop duplicate DTOs, surface canonical types

Audit feedback: localaitools/dto.go reinvented several types that already
existed in the codebase. Replace the duplicates with the canonical types
so the LLM-visible wire format stays aligned with the rest of LocalAI by
construction (no parallel structs to keep in sync).

Removed (and the canonical type now used by the LocalAIClient interface):

  localaitools.Gallery          → config.Gallery
  localaitools.GalleryModelHit  → gallery.Metadata
  localaitools.VRAMEstimate     → vram.EstimateResult

Tightened scope:

  localaitools.Backend          → kept, but reduced to {Name, Installed}.
                                  ListKnownBackends now returns
                                  []schema.KnownBackend (the canonical
                                  type already used by REST /backends/known).

Kept with documented rationale:

  localaitools.JobStatus       — galleryop.OpStatus has Error error which
                                 marshals to "{}". JobStatus is the
                                 JSON-friendly mirror.
  localaitools.Node            — nodes.BackendNode carries gorm internals
                                 + token hash; we expose only the
                                 LLM-relevant fields.
  ImportModelURIRequest/Response — schema.ImportModelRequest and
                                   GalleryResponse are wire-shaped, mine
                                   are LLM-shaped (BackendPreference flat,
                                   AmbiguousBackend exposed).

Side wins:

  - Drop bytesPerMiB; vram.EstimateResult already carries human-readable
    display strings (size_display, vram_display) the LLM uses directly.
  - Drop the handler-private vramEstimateRequest in
    core/http/endpoints/localai/vram.go and bind directly into
    modeladmin.VRAMRequest (now JSON-tagged).

Both clients pass through these types now where possible (e.g.
ListGalleries in inproc.Client is a one-liner returning
AppConfig.Galleries; httpapi.Client.GallerySearch decodes straight into
[]gallery.Metadata).

All tests green with -race.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactor(assistant): extract REST route paths into named constants

httpapi.Client had 18 bare-string path sites scattered across methods.
Pull them into pkg/mcp/localaitools/httpapi/routes.go: static paths as
package-private constants, dynamic paths as small builders that handle
url.PathEscape on segment values.

No behaviour change. Drops the now-unused net/url import from client.go
since path escaping moved into routes.go alongside the path it applies to.

Local-only by design: the server-side registrations in
core/http/routes/localai.go remain bare strings. Sharing constants across
the pkg/ ↔ core/ boundary would invert the layering today; the existing
Tool↔REST drift-detector in coverage_test.go is the safety net for that
direction.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

* docs(assistant): align with shipped UI and dropped bootstrap env vars

The LocalAI Assistant doc still described the older iteration:

- The in-chat toggle was renamed from "Admin" to "Manage" (the badge is
  now "Manage mode" and the home page exposes a "Manage by chat" CTA).
- LOCALAI_ASSISTANT_BOOTSTRAP_MODEL / --localai-assistant-bootstrap-model
  and the bootstrap_default_model tool were removed — admins pick a model
  from the existing selector instead, no env-var configuration required.
- The shipped tool catalog includes import_model_uri but didn't appear in
  the doc; bootstrap_default_model appeared but no longer exists.
- The Settings → LocalAI Assistant runtime toggle wasn't mentioned as the
  preferred way to disable without restart.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude:claude-opus-4-7 [Claude Code]

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-28 19:29:27 +02:00
Ettore Di Giacinto
2da1a4d230 feat(distributed): per-node backend installation from the gallery
In distributed mode the Backends gallery used to fan every install out to
every worker — fine for auto-resolving (meta) backends like llama-cpp where
each node picks its own variant, but wrong for hardware-specific builds
like cpu-llama-cpp that would silently land on every GPU node.

Adds a node-targeted install path through the existing
POST /api/nodes/:id/backends/install plumbing, with two entry points:

- Backends gallery row gets a split-button in distributed mode. Auto-
  resolving keeps "Install on all nodes" as the primary; chevron menu
  opens the picker. Hardware-specific routes the primary directly to the
  picker — no fan-out path on the row.
- Nodes-page drawer gets a "+ Add backend" button that navigates to
  /app/backends?target=<node-id>; the gallery scopes itself to that node
  (banner, single per-row install button, Reinstall/Remove for already-
  installed). One gallery, two scopes — no second UI to maintain.

The picker (new NodeInstallPicker) shows a 3-state suitability column
(Compatible / Override / Installed), an auto-expanding variant override
disclosure that fires when selected nodes have no working GPU, parallel
per-node installs with inline status and Retry-failed-nodes, and a
mismatch confirm that names the consequence on the button itself.

A 409 fan-out guard on /api/backends/apply protects CLI/Terraform/script
users from the same footgun: hardware-specific installs in distributed
mode now return code "concrete_backend_requires_target" with a human-
readable error and a meta_alternative pointer.

The gallery list payload now surfaces capabilities, metaBackendFor and
per-row nodes (NodeBackendRef) so the picker and the new Nodes column
have everything they need without re-walking the gallery client-side.

GODEBUG=netdns=go is set on the compose services because the cgo DNS
resolver follows the container's nsswitch.conf to host systemd-resolved
(127.0.0.53), unreachable from inside the container; the pure-Go
resolver reads /etc/resolv.conf directly and uses Docker's embedded DNS.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Assisted-by: Claude Code:claude-opus-4-7[1m] [Edit] [Bash] [Read] [Write]
2026-04-26 22:05:18 +00:00
Ettore Di Giacinto
181ebb6df4 feat: voice recognition (#9500)
* 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
2026-04-23 12:07:14 +02:00
Ettore Di Giacinto
f0c92610a1 feat(importer): expand importer flow to almost all backends (#9466)
* docs(agents): require importer integration when adding backends

Document the importer registry workflow so contributors know that adding
a new backend also requires updating the /import-model dropdown source:
either a new importer in core/gallery/importers/, extending an existing
one for drop-in replacements, or the pref-only slice for backends with
no reliable auto-detect signal. Always covered by a table-driven test.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for Batch 0 primitives

Introduce failing tests that drive Batch 0 of the importer expansion:

- pkg/huggingface-api: assert GetModelDetails populates PipelineTag and
  LibraryName from /api/models/{repo}, and that a failing metadata
  endpoint still returns file details (best-effort fetch).
- core/gallery/importers/helpers_test.go: new table-driven coverage for
  HasFile, HasExtension, HasONNX, HasONNXConfigPair, HasGGMLFile.
- core/gallery/importers/importers_test.go: assert ErrAmbiguousImport
  sentinel exists and round-trips through errors.Is.
- core/gallery/importers/local_test.go: extend with detection cases for
  ggml-*.bin (whisper), silero_vad.onnx (silero-vad), and the piper
  .onnx + .onnx.json pair.
- core/http/endpoints/localai/import_model_test.go: assert
  ImportModelURIEndpoint returns HTTP 400 with a structured
  {error, detail, hint} body when ErrAmbiguousImport surfaces.

All tests fail in the expected places (missing fields, missing
helpers, missing sentinel, endpoint still wraps as 500).

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): Batch 0 foundation — helpers, sentinel, local detection

Implements the Batch 0 primitives that subsequent importer batches build on:

- pkg/huggingface-api: ModelDetails gains PipelineTag and LibraryName.
  GetModelDetails now layers a best-effort GET /api/models/{repo} fetch
  on top of ListFiles — a metadata outage leaves the fields empty but
  still returns full file details. Uses a dedicated response struct
  because the single-model endpoint uses snake_case keys while the list
  endpoint historically returned camelCase.

- core/gallery/importers/helpers.go: generic HasFile, HasExtension,
  HasONNX, HasONNXConfigPair, HasGGMLFile helpers working on
  []hfapi.ModelFile so per-backend importers can detect artefact
  patterns without duplicating string wrangling.

- core/gallery/importers/importers.go: adds the ErrAmbiguousImport
  sentinel. DiscoverModelConfig now returns it (wrapped with
  fmt.Errorf("%w: ...")) when no importer matched AND the HF
  pipeline_tag falls in a whitelist of narrow modalities (ASR, TTS,
  sentence-similarity, text-classification, object-detection). The
  whitelist is intentionally narrow — unknown tags keep the previous
  "no importer matched" behaviour to avoid blocking rare repos.

- core/gallery/importers/local.go: three new local-path detections,
  inserted before the existing merged-transformers branch:
    * ggml-*.bin → whisper
    * silero*.onnx → silero-vad
    * *.onnx + *.onnx.json pair → piper

- core/http/endpoints/localai/import_model.go: ImportModelURIEndpoint
  surfaces ErrAmbiguousImport as HTTP 400 with
  {error, detail, hint} JSON, preserving existing behaviour for
  unrelated errors.

Green tests:
  go test ./core/gallery/importers/... ./pkg/huggingface-api/... \
          ./core/http/endpoints/localai/...

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(importers): red tests for KnownBackend endpoint and importer metadata

Add failing tests that drive Batch UI-Dropdown:

- importers_test.go: assert importers expose Name/Modality/AutoDetects
  and that LlamaCPPImporter advertises drop-in replacements via a new
  AdditionalBackendsProvider interface. A Registry() accessor is also
  expected.

- backend_test.go (new): assert GET /backends/known returns
  []schema.KnownBackend, covers every importer, exposes drop-in
  llama-cpp replacements, includes curated pref-only backends, has no
  duplicates, and is sorted by Modality+Name.

These tests fail at compile time against master; they are intentionally
red so the follow-up green commit is reviewable.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery): add /backends/known endpoint for importer-aware backend list

Extend the Importer interface with Name/Modality/AutoDetects so the
import system can self-describe its registry, and introduce the
AdditionalBackendsProvider interface so importers can advertise drop-in
replacements (llama-cpp advertises ik-llama-cpp and turboquant).

Expose the new GET /backends/known endpoint that merges:

- the importer registry (auto-detect supported),
- drop-in replacements hosted by importers (preference-only),
- a curated knownPrefOnlyBackends slice for backends with no dedicated
  importer (sglang, tinygrad, trl, mlx-vlm, whisperx, kokoros, Qwen TTS
  variants, sam3-cpp) — kept at the top of backend.go so contributors
  adding a new pref-only backend have one obvious place to edit,
- backends installed on disk but unknown to the importer (marked
  AutoDetect=false, empty Modality).

The endpoint deliberately does NOT filter by gallery membership or host
capability (unlike /backends/available): LocalAI may auto-install a
backend that is not yet present, so the import form dropdown must show
everything the importer knows about.

Response is deduplicated (importer wins over pref-only) and sorted by
Modality+Name for deterministic output.

Registered in core/http/routes/localai.go next to /backends/available
under the same admin middleware.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(ui): source import form backend dropdown from /backends/known

Replace the hard-coded BACKENDS constant in ImportModel.jsx with a
live fetch of /backends/known on mount. Users now see every backend
the importer layer knows about (including preference-only entries)
grouped by modality, not a stale subset.

Changes:

- config.js: add backendsKnown endpoint constant next to
  backendsAvailable.
- api.js: add backendsApi.listKnown() wrapper.
- ImportModel.jsx: remove BACKENDS constant, fetch the list via
  useEffect, and derive grouped options via buildBackendOptions.
  Preference-only entries render with a " (preference-only)" suffix.
  Loading state disables the dropdown with a "Loading backends…"
  placeholder; on fetch failure the form falls back to auto-detect
  only and surfaces a non-blocking toast.
- SearchableSelect.jsx: accept items flagged isHeader=true and render
  them as non-selectable section dividers. Keyboard navigation skips
  headers and search queries hide them so filtered output stays
  relevant.

Vitest is not set up in this project (devDependencies ship Playwright
only). Per the brief's guard-rail, no frontend test framework is
introduced; coverage is provided by the Go handler tests that assert
the /backends/known contract consumed by the React form.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for whisper importer

Asserts detection on ggerganov/whisper.cpp (via ggml-*.bin filename),
the preferences.backend=whisper override path for arbitrary URIs,
and the Importer interface metadata (name/modality/autodetect).

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add whisper importer

Recognises whisper.cpp GGML models by the "ggml-*.bin" filename
convention (direct URL or HF repo member) and by the explicit
preferences.backend="whisper" override. Emits backend: whisper with
the transcript use-case. Registered before llama-cpp so the narrow
filename signal wins before any generic GGUF match is attempted.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for moonshine importer

Asserts detection on UsefulSensors/moonshine-tiny via owner + ONNX
files, the preferences.backend=moonshine override for arbitrary URIs,
and the Importer interface metadata (name/modality/autodetect).

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add moonshine importer

Matches UsefulSensors-owned HF repos whose artefacts or metadata
identify them as ASR: on-disk .onnx files (the canonical Moonshine
packaging) OR pipeline_tag=automatic-speech-recognition (covers
transformers/safetensors-only sibling repos). preferences.backend=
moonshine overrides detection. Test uses the live moonshine-tiny
repo because the canonical UsefulSensors/moonshine repo currently
hits a recursive-subfolder bug in pkg/huggingface-api ListFiles.

Registered after WhisperImporter but before LlamaCPPImporter and
TransformersImporter so the narrower owner+ASR signal wins before
the generic tokenizer.json check routes the repo to transformers.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for nemo importer

Asserts detection on nvidia/parakeet-tdt-0.6b-v3 via owner + .nemo
file, the preferences.backend=nemo override for arbitrary URIs, and
the Importer interface metadata (name/modality/autodetect).

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add nemo importer

Matches nvidia-owned HF repos that ship a .nemo checkpoint archive,
the canonical NeMo ASR packaging. preferences.backend=nemo forces
detection. Registered between moonshine and llama-cpp so the narrow
owner + extension signal wins before any downstream generic matcher.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for faster-whisper importer

Asserts detection on Systran/faster-whisper-large-v3 (owner +
model.bin + config.json + ASR pipeline), the preferences.backend=
faster-whisper override for arbitrary URIs, and the Importer
interface metadata.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add faster-whisper importer

Recognises CTranslate2-packaged whisper checkpoints distributed for
the faster-whisper runtime: model.bin + config.json + ASR
pipeline_tag, narrowed to Systran-owned repos or repo names
containing "faster-whisper" to avoid falsely claiming vanilla
OpenAI whisper HF repos. preferences.backend=faster-whisper
overrides detection. Registered before llama-cpp and transformers
so the narrow signal wins before tokenizer.json routes the repo to
the generic transformers importer.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for qwen-asr importer

Asserts detection on Qwen/Qwen3-ASR-1.7B via owner + ASR substring
in the repo name, the preferences.backend=qwen-asr override for
arbitrary URIs, and the Importer interface metadata.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add qwen-asr importer

Matches Qwen-owned HF repos whose name contains "ASR"
(case-insensitive), routing them to the qwen-asr backend rather
than the generic transformers/vllm path. The substring check scans
the repo portion only so the owner field cannot leak a false match.
preferences.backend=qwen-asr forces detection. Registered before
llama-cpp and transformers so the narrow owner+name signal wins.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): ASR ambiguity surfaces ErrAmbiguousImport

Locks in the behaviour added in Batch 0: an HF repo whose pipeline_tag
marks it as automatic-speech-recognition but whose artefacts match no
ASR importer (and no generic importer) must fail with
ErrAmbiguousImport so callers know to pass preferences.backend rather
than silently guess. pyannote/voice-activity-detection is the fixture
— its file list is only config.yaml + README, leaving every importer's
artefact check negative.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for piper importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add piper importer

Detects piper TTS voices by the canonical <voice>.onnx + <voice>.onnx.json
pair packaging (via HasONNXConfigPair). Narrow enough to skip generic
ONNX repos used by other backends (Moonshine ASR, sentence-transformers).

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for bark importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add bark importer

Detects Suno's Bark TTS checkpoints by HF owner "suno" + repo name
prefix "bark". Adds HFOwnerRepoFromURI() helper so importers can fall
back to URI parsing when pkg/huggingface-api's recursive tree listing
errors on repos with nested subdirectories (suno/bark ships a
speaker_embeddings/v2 subtree that trips a pre-existing path-doubling
bug in the listFilesInPath recursion).

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for fish-speech importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add fish-speech importer

Detects Fish Audio TTS releases by HF owner "fishaudio" with a URI-based
fallback for repos whose tree recursion trips the pre-existing hfapi
path-doubling bug.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for outetts importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add outetts importer

Detects OuteAI's OuteTTS releases by HF owner "OuteAI" or a case-
insensitive "OuteTTS" substring in the repo name, with a URI-based
fallback for recursion-bugged repos.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for voxcpm importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add voxcpm importer

Detects OpenBMB's VoxCPM TTS family by repo-name substring (community
mirrors re-host the weights under many owners — mlx-community,
bluryar, callgg, etc).

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for kokoro importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add kokoro importer

Detects hexgrad's Kokoro TTS by the "Kokoro" repo-name substring paired
with a PyTorch .pth/.pt checkpoint — the pairing excludes ONNX-only
mirrors (handled by the pref-only `kokoros` Rust runtime) and GGUF
mirrors (handled by llama-cpp).

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for kitten-tts importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add kitten-tts importer

Detects KittenML's kitten-tts releases by owner or "kitten-tts" repo-name
substring, with URI-parsing fallback.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for neutts importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add neutts importer

Detects Neuphonic's NeuTTS releases by owner "neuphonic" or "neutts"
repo-name substring, with URI-parsing fallback.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for chatterbox importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add chatterbox importer

Detects Resemble AI's Chatterbox TTS by owner "ResembleAI" or
"chatterbox" repo-name substring, with URI-parsing fallback.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for vibevoice importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add vibevoice importer

Detects Microsoft's VibeVoice TTS by "vibevoice" repo-name substring
(case-insensitive) so community mirrors still route here.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for coqui importer

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add coqui importer

Detects Coqui AI's TTS releases (XTTS-v2, YourTTS, …) by the
authoritative `coqui` HF owner, with URI-parsing fallback.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): TTS ambiguity surfaces ErrAmbiguousImport

Adds a Ginkgo spec that imports nari-labs/Dia-1.6B — a real HF repo
carrying pipeline_tag="text-to-speech" whose artefacts (*.pth, one
safetensors shard, preprocessor_config.json, config.json) match none of
the Batch-2 TTS importers nor the generic text/image importers — and
asserts DiscoverModelConfig wraps ErrAmbiguousImport via errors.Is.

Also pivots the endpoint-level ambiguity fixture from hexgrad/Kokoro-82M
to nari-labs/Dia-1.6B. Batch 2 added a dedicated kokoro importer that
now claims the original fixture; Dia remains genuinely unclaimed and
so exercises the same ambiguity code path at the HTTP layer.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for stablediffusion-ggml importer

Covers HF repo detection (city96/FLUX.1-dev-gguf), raw .gguf URL matching on
filename arch tokens, preference override, and Importer interface metadata.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add stablediffusion-ggml importer

Detects GGUF-packed Stable Diffusion and FLUX checkpoints (leejet owner,
city96 FLUX mirrors, second-state SD dumps, raw .gguf URLs with arch
tokens) and routes them to the stablediffusion-ggml backend. Registered
BEFORE LlamaCPPImporter so .gguf image checkpoints are not stolen by
llama-cpp's generic .gguf match. Reuses HFOwnerRepoFromURI for the
hfapi-recursion-bug fallback. preferences.backend overrides detection.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for ace-step importer

Covers HF repo-name detection (ACE-Step/ACE-Step-v1-3.5B), preference
override, and Importer interface metadata.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add ace-step importer

Routes ACE-Step music generation checkpoints (ACE-Step/ACE-Step-v1-3.5B,
ACE-Step/Ace-Step1.5, community mirrors) to the ace-step backend.
Matching is case-insensitive on the "ace-step" repo-name substring and
owner, with an HFOwnerRepoFromURI fallback for the hfapi recursion bug.
KnownUsecaseStrings mirrors the gallery's ace-step-turbo entry
(sound_generation, tts). preferences.backend overrides.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): surface ErrAmbiguousImport on text-to-image misses

Adds text-to-image to ambiguousModalities whitelist and covers the
h94/IP-Adapter-FaceID case — pipeline_tag=text-to-image but ships only
.bin/.safetensors so diffusers, stablediffusion-ggml, llama-cpp,
transformers, vllm, mlx, and ace-step all miss. DiscoverModelConfig now
surfaces ErrAmbiguousImport for that shape instead of the opaque
"no importer matched" error.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for vllm-omni importer

Introduces the test surface for the forthcoming VLLMOmniImporter:
detection via preferences.backend, Qwen owner + Omni repo token,
URI-only fallback, negative cases (plain Qwen, random OmniX repo), and
Import() emitting backend: vllm-omni with chat + multimodal usecases.

Includes a registration-order assertion via DiscoverModelConfig to pin
the requirement that vllm-omni wins over vllm for Qwen Omni repos
(tokenizer files are usually present too).

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add vllm-omni importer

Adds VLLMOmniImporter for Qwen Omni-style multimodal checkpoints
(Qwen3-Omni, Qwen2.5-Omni, …). Detection is narrow: HF owner "Qwen"
combined with "omni" in the repo name, or a repo name matching the
-Omni-/Omni- naming pattern. preferences.backend="vllm-omni" always
wins; HFOwnerRepoFromURI provides a URI-only fallback for the hfapi
recursion-bug edge case.

Emitted YAML sets backend: vllm-omni and known_usecases: [chat,
multimodal], matching the gallery/index.yaml vllm-omni entries. The
importer is registered ahead of VLLMImporter so Qwen Omni repos —
which also carry tokenizer files — route to vllm-omni rather than the
plain vllm backend.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for llama-cpp drop-in preferences

Pins the expected drop-in replacement behaviour: preferences.backend
of ik-llama-cpp or turboquant must swap the emitted YAML backend
field while keeping the llama-cpp file layout identical. Also covers
the unknown-backend case (must stay llama-cpp) and re-asserts
AdditionalBackends() returns the two curated entries with non-empty
descriptions.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): llama-cpp honours ik-llama-cpp and turboquant drop-in preferences

preferences.backend set to ik-llama-cpp or turboquant now swaps the
emitted YAML backend field while leaving the file layout, model path,
mmproj handling and everything else in the llama-cpp Import pipeline
untouched. Unknown values are ignored and fall back to backend:
llama-cpp so arbitrary input can't leak into the config.

Aligns the AdditionalBackends() descriptions with the user-facing
naming conventions surfaced via /backends/known. No changes to the
pref-only curated list in endpoints/localai/backend.go: the two
drop-in names have always lived on the importer side via
AdditionalBackends.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for silero-vad importer

Add the SileroVADImporter test fixtures covering metadata, preference
overrides, snakers4 + onnx detection, silero_vad.onnx canonical filename,
URI fallback, and live HF discovery. Implementation follows in the next
commit.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add silero-vad importer

Recognise the Silero VAD ONNX packaging: the canonical silero_vad.onnx
filename or any ONNX file under the snakers4 owner. Emits a
backend: silero-vad config with the vad known_usecase, and attaches the
canonical file entry when present so the weights download on import.

Registered before the generic importers so the unique-filename signal
takes precedence over any downstream tokenizer-based matcher.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for rerankers importer

Cover the RerankersImporter contract: interface metadata, preference
override, cross-encoder owner detection, case-insensitive 'reranker'
substring match (BAAI/bge-reranker, Alibaba-NLP/gte-reranker), URI
fallback, and the full-discovery ordering check that a BAAI reranker
repo must route to the rerankers importer rather than transformers.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add rerankers importer

Recognise reranker repositories — cross-encoder owner or any repo whose
name contains 'reranker' (case-insensitive). Emits backend: rerankers
with reranking: true and the rerank known_usecase.

Registered ahead of sentencetransformers and transformers so reranker
repos that happen to ship tokenizer.json or modules.json still route
here.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for sentencetransformers importer

Cover the SentenceTransformersImporter contract: interface metadata,
preference override, modules.json marker file, sentence_bert_config.json
marker file, sentence-transformers owner, URI fallback, and the
full-discovery ordering check that ensures a sentence-transformers HF
URI routes here rather than transformers.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add sentencetransformers importer

Recognise sentence-transformers embedding repos by modules.json,
sentence_bert_config.json, or the sentence-transformers owner. Emits
backend: sentencetransformers with embeddings: true and the embeddings
known_usecase.

Registered ahead of transformers so ST repos that carry tokenizer.json
still route here.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): add failing tests for rfdetr importer

Cover the RFDetrImporter contract: interface metadata, preference
override, case-insensitive rf-detr and rfdetr substring matches, URI
fallback, and negative cases. Implementation follows in the next
commit.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(gallery/importers): add rfdetr importer

Recognise RF-DETR object-detection repositories by a case-insensitive
'rf-detr' / 'rfdetr' substring in the repo name. Emits backend: rfdetr
with the detection known_usecase.

Registered ahead of transformers so RF-DETR repos with tokenizer
artefacts still route here.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(gallery/importers): surface ErrAmbiguousImport on sentence-similarity misses

Add an ambiguity fixture covering the embeddings/rerankers modality.
Qdrant/bm25 carries pipeline_tag=sentence-similarity but ships only
config.json + stopword .txt files — none of the Batch 5 importers
(silero-vad, rerankers, sentencetransformers, rfdetr) or the generic
vllm/transformers/llama-cpp/mlx/diffusers importers match. Because the
modality is in the ambiguous whitelist, DiscoverModelConfig must
surface ErrAmbiguousImport.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(localai/backend): red tests for KnownBackend.Installed flag

Extend the /backends/known suite with three failing cases that pin down
the forthcoming Installed field: JSON field presence on every entry,
flipping to true when an importer-registered backend is also present on
disk (and staying false for non-installed pref-only entries), and
surfacing system-only backends with empty modality and AutoDetect=false.

A small writeFakeSystemBackend helper plants a run.sh under the backends
dir so gallery.ListSystemBackends recognises the fixture.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(schema,localai/backend): add Installed flag to KnownBackend

Add an Installed bool to schema.KnownBackend and populate it from the
/backends/known handler so the React import form can warn users that
picking a not-yet-installed backend will trigger an automatic download
on submit.

Computation: after merging the importer registry, additional backends
provider entries and the curated pref-only slice, the handler walks
gallery.ListSystemBackends(systemState) and either flips the existing
map entry's Installed flag to true (preserving modality / autodetect /
description metadata) or inserts a bare {Installed:true} entry for
system-only backends the importer layer doesn't know about.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(localai/import_model): structured ambiguous-import response

Add red tests covering the extended ambiguity shape the React import
form needs:

- ImportModelURIEndpoint must return an HTTP 400 body that exposes the
  detected `modality` (normalised to the importer modality key, e.g.
  "tts" for pipeline_tag=text-to-speech) and a list of `candidates`
  (backend names filtered by modality, excluding text-LLM backends).
- The importers package must surface a typed AmbiguousImportError so
  HTTP consumers can read Modality + Candidates without parsing the
  error string. errors.Is against the existing sentinel keeps working.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(localai/import_model): structured ambiguity response with modality + candidates

DiscoverModelConfig now returns a typed AmbiguousImportError that
carries the importer modality key, candidate backend names, the
original URI, and the raw HF pipeline_tag. Its Is() preserves
errors.Is(err, ErrAmbiguousImport) for legacy callers.

The importer modality is pre-mapped from the HF pipeline_tag
(automatic-speech-recognition → asr, text-to-speech → tts, etc) via
PipelineTagToModality — surfaced as an exported helper so downstream
consumers can avoid duplicating the table. CandidatesForModality
filters the default importer registry plus AdditionalBackendsProvider
drop-ins by modality, sorts deterministically, and is the single
source of truth used by ImportModelURIEndpoint.

ImportModelURIEndpoint now returns HTTP 400 with
  { error, detail, modality, candidates, hint }
when ambiguity fires, letting the React form render a modality-scoped
picker inline instead of a generic toast.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(ui/import): manual pick badge + tooltip

Red Playwright coverage for the preference-only → manual pick rename:

- The Backend dropdown renders a "manual pick" badge on every option
  whose KnownBackend.auto_detect is false.
- The badge carries a title attribute with hover-tooltip copy that
  explains auto-detect won't route to this backend.
- Auto-detectable backends must NOT carry the badge.
- The legacy " (preference-only)" suffix is gone from every label.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* ui(import): replace preference-only suffix with manual pick badge

SearchableSelect option rows now support an optional badge field — a
muted pill rendered to the right of the label with an optional title
attribute for native hover tooltips. Plain text so screen readers read
it alongside the option name.

buildBackendOptions in ImportModel stops appending " (preference-only)"
to the label and instead sets badge="manual pick" plus a descriptive
tooltip on every option whose auto_detect is false. The Backend help
text explains what "manual pick" means so users aren't left wondering
about the badge.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(ui/import): inline ambiguity picker

Red Playwright coverage for Batch A2 — when the server returns a 400
ambiguity body, the form must render an inline alert instead of a
toast, expose one clickable chip per candidate backend, and support
both auto-resubmit on pick and silent dismiss.

- Mocks /api/models/import-uri with the structured ambiguity body
  (error, detail, modality, candidates, hint).
- On first click of Import, the alert is visible, carries
  modality-specific copy, and shows a chip per candidate.
- Clicking a chip clears the alert, sets the Backend dropdown, and
  triggers a second POST to /api/models/import-uri.
- Dismissing the alert leaves the Backend dropdown on Auto-detect —
  no implicit backend assignment.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(ui/import): inline ambiguity alert with candidate chips

Adds AmbiguityAlert — a soft, info-coloured card rendered above the URI
input when the server returns a structured 400 with { modality,
candidates }. Message is modality-aware (tts/asr/embeddings/image/
reranker/detection get purpose-written copy, everything else falls back
to a generic template). Each candidate is a clickable chip that shows a
download icon when /backends/known marks the backend as not yet
installed, so users aren't surprised by an implicit install.

ImportModel wires the alert to handleSimpleImport's error path:
- api.handleResponse now attaches { status, body } to the thrown Error
  so pages can pattern-match on structured responses instead of string
  error messages.
- handleSimpleImport detects `status === 400 && body.error === 'ambiguous
  import'` and flips into the inline-picker mode instead of toasting.
- Clicking a chip sets prefs.backend and auto-resubmits (passing the
  picked backend as an override so setPrefs's asynchrony doesn't leak
  a stale value).
- Dismissing clears the alert; changing the URI or the backend also
  clears it so a stale alert never sticks around.

Test fixtures mock GET /backends/known + POST /models/import-uri so the
Playwright specs don't depend on real network reachability.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(ui/import): auto-install warning

Red Playwright coverage for Batch A3 — when the user picks a backend
whose KnownBackend.installed is false, the form must render a muted
inline note under the Backend dropdown warning that submitting will
download the backend first. Picking an installed backend or leaving
Auto-detect selected must keep the note hidden.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(ui/import): auto-install warning under backend dropdown

When the user picks a backend whose KnownBackend.installed is false,
render a muted inline note under the Backend dropdown's help text
warning that submitting will download the backend first. The note
lives inside the same form-group so it lines up with the existing
hint text; it's hidden when Auto-detect is selected (the selected
backend is unknowable at that point) or when the chosen backend is
already on disk.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* ui(import): drop redundant section header, adjust icons, rename HF shortcut

- Remove the "Import from URI" card-level <h2> — the page title already
  says "Import New Model" one row up, so the secondary header was
  duplicating information.
- Swap the fa-star on "Common Preferences" for fa-sliders (stars imply
  favourites/ratings; this is just a preferences block) and move the
  Custom Preferences fa-sliders-h to fa-plus-circle so the two blocks
  read as distinct rather than as two sliders.
- Rename the HF shortcut from "Search GGUF on HF" → "Browse models on
  HF" and drop the `search=gguf` filter on the linked URL. The import
  form now supports ~40 backends; hard-coding GGUF in the copy no
  longer matches the form's actual reach.
- Pure polish — no behaviour change, covered by the existing Batch A
  Playwright suite.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(ui/import): batch B — simple/power switch, options, tabs, dialog

Adds a failing Playwright suite covering the full Batch B surface ahead
of implementation:

- B1: SimplePowerSwitch segmented control renders, toggles, persists to
  localStorage across reloads.
- B2: Simple-mode Options disclosure is collapsed by default; expanding
  exposes only Backend, Model Name, Description (no quantizations,
  mmproj, model type, or custom prefs).
- B3: Power mode has Preferences and YAML tabs with a persistent
  selection across reloads; URI/name/description typed in Simple carry
  over to Power; YAML tab swaps the primary action to Create.
- B4: Switching Power -> Simple with a custom preference set triggers
  the 3-button confirmation dialog (Keep / Discard / Cancel) with the
  documented semantics.

Tests fail against master — implementation lands in the following
commits.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(ui/import): add SimplePowerSwitch segmented control

Replaces the previous "Advanced Mode / Simple Mode" toggle button in the
page header with a two-segment control that flips between Simple and
Power. The control reuses the existing .segmented CSS shared with the
Sound page for visual consistency.

Mode state is persisted to localStorage under `import-form-mode` so
reloads land on the same view (default: simple). The boolean alias
`isAdvancedMode` is retained internally to minimise diff — subsequent
commits reshape the Simple and Power surfaces independently.

Closes B1 from the Batch B Playwright suite.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(ui/import): simple mode collapsible options, power tabs, switch dialog

Completes the Batch B surface in a single structural pass so Simple and
Power mode can evolve independently:

Simple mode
  - URI input + Ambiguity alert + Import button, plus a collapsible
    "Options" disclosure that exposes ONLY Backend, Model Name,
    Description. Quantizations / MMProj / Model Type / Diffusers fields
    / Custom Preferences are no longer rendered in Simple mode.

Power mode
  - In-page segmented "Preferences · YAML" tab strip. Active tab
    persists to localStorage under `import-form-power-tab`.
  - Preferences tab = the full existing preferences + custom prefs
    panel (no progressive disclosure yet — that's Batch D).
  - YAML tab = the existing CodeEditor. Primary button reads "Create"
    here, "Import Model" everywhere else.

Switch dialog
  - Power -> Simple with non-default prefs (advanced pref keys set,
    any custom-pref key non-empty, or YAML edited away from the
    template) opens a 3-button dialog: Keep & switch / Discard &
    switch / Cancel.
  - Keep preserves all state. Discard resets prefs + customPrefs + YAML
    to defaults. Cancel leaves the user in Power mode.

Page subtitle reflects the current surface (Simple, Power/Preferences,
Power/YAML). Estimate banner renders everywhere except Power/YAML.

Closes B2/B3/B4 from the Batch B Playwright suite.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(ui/import): expand Options disclosure in Batch A tests

Batch B hid the Backend dropdown behind a collapsible Options disclosure
in Simple mode. The Batch A tests that exercise the dropdown directly
(manual-pick badge, ambiguity chip sets the selected backend, auto-
install warning) now click the disclosure toggle before asserting on
dropdown contents. Test intent is unchanged.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* ui(import): strip decorative icons from field labels

The preference panel had 12 Font Awesome icons decorating field labels
(Backend, Model Name, Description, Quantizations, MMProj Quantizations,
Model Type, Pipeline Type, Scheduler Type, Enable Parameters, Embeddings,
CUDA, plus fa-link on Model URI). Every label screamed equally, flattening
the visual hierarchy.

Remove them. Keep icons where they carry meaning: page-level section
headers, URI format guide entries, primary buttons, the Simple-mode
Options disclosure, the ambiguity alert's fa-lightbulb, the auto-install
note's fa-download, and the Estimated-requirements banner's
fa-memory / fa-microchip / fa-download.

No new behaviour, no layout / spacing changes beyond removing the
orphaned icon margin. Playwright suite green.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(ui/import): progressive disclosure of preference fields

Cover the Batch D visibility matrix for Power > Preferences: Quantizations,
MMProj Quantizations, and Model Type each render only for the backends that
can consume them, stay visible when the backend is unset, and preserve any
value the user already typed when toggled off and back on. Also pin the
shrunk Description textarea at rows=2.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(ui/import): progressive disclosure + shorter description textarea

Gate Quantizations, MMProj Quantizations, and Model Type in the Power >
Preferences tab so each field only renders for the backends that can
actually consume it. Backend unset keeps everything visible. Hidden
fields' state is preserved (the JSX wrapper is guarded, not the
underlying prefs state) so users flipping backends back and forth don't
lose input.

Also shrink the Description textarea from rows=3 to rows=2 — it's
shared between Simple Options and Power Preferences so the change
applies to both.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(ui/import): enter-to-submit in Simple mode

Red test for Batch F3 — pressing Enter in the URI input must POST
/models/import-uri, and Enter in the Description textarea must insert
a newline without submitting the form.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(ui/import): enter-to-submit in Simple mode

Wrap the Simple-mode URI input + ambiguity alert + Options disclosure
in a <form> whose onSubmit calls handleSimpleImport. Pressing Enter in
the URI input (or any Simple-mode text input) now submits the import
without having to move the mouse to the header button. The Description
textarea keeps its native behaviour — Enter inserts a newline.

A hidden submit button is included because the visible Import button
lives outside the form in the page header; some browsers only fire
implicit Enter-submit when the form contains a submit-capable element.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* ui(import,SearchableSelect,components): aria-hidden on decorative icons

Every Font Awesome icon in the import form is decorative — its meaning
is already conveyed by adjacent visible text. Adding aria-hidden="true"
prevents screen readers from announcing the unicode glyph point as
content. Covers ImportModel.jsx (all remaining <i> glyphs) and
SearchableSelect.jsx (the trigger chevron).

AmbiguityAlert and SimplePowerSwitch already set aria-hidden on their
icons when the components landed in Batches A and B — no change needed
there.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* ui(SearchableSelect): responsive dropdown maxHeight + hover focus guard

F2 — replace fixed pixel heights with min(pixel, vh) so the dropdown
and its inner scroll region don't overflow short viewports. Outer
container: 260px -> min(260px, 60vh); inner listbox: 200px ->
min(200px, 50vh). Tall viewports still get the original pixel caps.

F5 — short-circuit onMouseEnter when the hovered row is already the
focused row. Avoids queueing a setFocusIndex call (and a render) for
every mousemove inside the same item — the state would be identical.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* ui(import): aria-label on custom preference rows

The Key / Value inputs and trash button in each Custom Preferences row
previously relied on placeholder text alone. Placeholders are not
accessible names — they vanish on input and screen readers do not
announce them consistently. Add row-indexed aria-labels so assistive
tech can distinguish "Preference key for row 1" from "row 2", and give
the trash button an explicit "Remove this preference" label.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* test(ui/import): modality chip row

Red tests for Batch E — a horizontal modality chip row that filters the
Backend dropdown by modality. Covers visibility in Simple-mode Options
and Power/Preferences (and absence in Power/YAML), filter behaviour,
mismatched-backend clearing with toast, ambiguity-alert auto-selection,
and radiogroup keyboard navigation.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* feat(ui/import): add ModalityChips component + filter integration

Horizontal chip row (Any, Text, Speech, TTS, Image, Embeddings,
Rerankers, Detection, VAD) filters the Backend dropdown options to the
selected modality. Default is Any — no filter, current behaviour.

- New ModalityChips component (radiogroup pattern, roving tabindex,
  arrow-key navigation, Home/End).
- buildBackendOptions now accepts an optional modalityFilter so grouped
  output is narrowed before rendering.
- Chips render inside Simple-mode Options disclosure and Power >
  Preferences tab. Power > YAML stays unaffected.
- Switching the filter drops a mismatched backend selection and
  surfaces a toast so the auto-clear is visible.
- Ambiguity alerts auto-activate the matching chip so users see only
  relevant backends even if they dismiss the alert.

Tightens the Batch E tests' option-matching to the label <span> so the
"↵" keybind hint on the focused row doesn't break accessible-name
lookups.

Assisted-by: Claude:claude-opus-4-7[1m] [Agent]

* fix(ui/import): rename Power to Advanced + stop URI-formats toggle from submitting form

The "Supported URI Formats" disclosure button inside the Simple-mode form
lacked an explicit type attribute, so it defaulted to type="submit". Every
click triggered the form's onSubmit and surfaced the empty-URI validation
toast ("Please enter a model URI"). Marking it type="button" lets it
behave as a pure toggle.

While here, rename the user-visible "Power" label to "Advanced" in the
mode switch (button text + tooltip) and the Power-mode tab's aria-label,
matching the term users actually expect. The internal mode key stays
'power' so tests, localStorage, and data-testid selectors are untouched.

Assisted-by: Claude:claude-opus-4-7

* fix(system): fall back to cpu when meta backend lacks default capability

Meta backends like vllm and sglang enumerate concrete variants for
nvidia/amd/intel/cpu but omit a default: catch-all entry. On a no-GPU
host the reported capability is "default", so the previous Capability()
returned "default" unconditionally on a miss — IsCompatibleWith then saw
no "default" key and filtered the meta out of AvailableBackends. The
import flow's auto-install step then failed with "no backend found with
name <meta>", contradicting the UI's promise that the backend would be
downloaded on demand.

Try the explicit "default" key first, then fall back to "cpu" before
giving up. vllm now resolves to cpu-vllm on CPU-only Linux without
touching the gallery YAML.

Assisted-by: Claude:claude-opus-4-7
2026-04-22 22:42:37 +02:00
Ettore Di Giacinto
20baec77ab feat(face-recognition): add insightface/onnx backend for 1:1 verify, 1:N identify, embedding, detection, analysis (#9480)
* feat(face-recognition): add insightface backend for 1:1 verify, 1:N identify, embedding, detection, analysis

Adds face recognition as a new first-class capability in LocalAI via the
`insightface` Python backend, with a pluggable two-engine design so
non-commercial (insightface model packs) and commercial-safe
(OpenCV Zoo YuNet + SFace) models share the same gRPC/HTTP surface.

New gRPC RPCs (backend/backend.proto):
  * FaceVerify(FaceVerifyRequest) returns FaceVerifyResponse
  * FaceAnalyze(FaceAnalyzeRequest) returns FaceAnalyzeResponse

Existing Embedding and Detect RPCs are reused (face image in
PredictOptions.Images / DetectOptions.src) for face embedding and
face detection respectively.

New HTTP endpoints under /v1/face/:
  * verify     — 1:1 image pair same-person decision
  * analyze    — per-face age + gender (emotion/race reserved)
  * register   — 1:N enrollment; stores embedding in vector store
  * identify   — 1:N recognition; detect → embed → StoresFind
  * forget     — remove a registered face by opaque ID

Service layer (core/services/facerecognition/) introduces a
`Registry` interface with one in-memory `storeRegistry` impl backed
by LocalAI's existing local-store gRPC vector backend. HTTP handlers
depend on the interface, not on StoresSet/StoresFind directly, so a
persistent PostgreSQL/pgvector implementation can be slotted in via a
single constructor change in core/application (TODO marker in the
package doc).

New usecase flag FLAG_FACE_RECOGNITION; insightface is also wired
into FLAG_DETECTION so /v1/detection works for face bounding boxes.

Gallery (backend/index.yaml) ships three entries:
  * insightface-buffalo-l   — SCRFD-10GF + ArcFace R50 + genderage
                              (~326MB pre-baked; non-commercial research use only)
  * insightface-opencv      — YuNet + SFace (~40MB pre-baked; Apache 2.0)
  * insightface-buffalo-s   — SCRFD-500MF + MBF (runtime download; non-commercial)

Python backend (backend/python/insightface/):
  * engines.py — FaceEngine protocol with InsightFaceEngine and
    OnnxDirectEngine; resolves model paths relative to the backend
    directory so the same gallery config works in docker-scratch and
    in the e2e-backends rootfs-extraction harness.
  * backend.py — gRPC servicer implementing Health, LoadModel, Status,
    Embedding, Detect, FaceVerify, FaceAnalyze.
  * install.sh — pre-bakes buffalo_l + OpenCV YuNet/SFace inside the
    backend directory so first-run is offline-clean (the final scratch
    image only preserves files under /<backend>/).
  * test.py — parametrized unit tests over both engines.

Tests:
  * Registry unit tests (go test -race ./core/services/facerecognition/...)
    — in-memory fake grpc.Backend, table-driven, covers register/
    identify/forget/error paths + concurrent access.
  * tests/e2e-backends/backend_test.go extended with face caps
    (face_detect, face_embed, face_verify, face_analyze); relative
    ordering + configurable verifyCeiling per engine.
  * Makefile targets: test-extra-backend-insightface-buffalo-l,
    -opencv, and the -all aggregate.
  * CI: .github/workflows/test-extra.yml gains tests-insightface-grpc,
    auto-triggered by changes under backend/python/insightface/.

Docs:
  * docs/content/features/face-recognition.md — feature page with
    license table, quickstart (defaults to the commercial-safe model),
    models matrix, API reference, 1:N workflow, storage caveats.
  * Cross-refs in object-detection.md, stores.md, embeddings.md, and
    whats-new.md.
  * Contributor README at backend/python/insightface/README.md.

Verified end-to-end:
  * buffalo_l: 6/6 specs (health, load, face_detect, face_embed,
    face_verify, face_analyze).
  * opencv: 5/5 specs (same minus face_analyze — SFace has no
    demographic head; correctly skipped via BACKEND_TEST_CAPS).

Assisted-by: Claude:claude-opus-4-7

* fix(face-recognition): move engine selection to model gallery, collapse backend entries

The previous commit put engine/model_pack options on backend gallery
entries (`backend/index.yaml`). That was wrong — `GalleryBackend`
(core/gallery/backend_types.go:32) has no `options` field, so the
YAML decoder silently dropped those keys and all three "different
insightface-*" backend entries resolved to the same container image
with no distinguishing configuration.

Correct split:

  * `backend/index.yaml` now has ONE `insightface` backend entry
    shipping the CPU + CUDA 12 container images. The Python backend
    bundles both the non-commercial insightface model packs
    (buffalo_l / buffalo_s) and the commercial-safe OpenCV Zoo
    weights (YuNet + SFace); the active engine is selected at
    LoadModel time via `options: ["engine:..."]`.

  * `gallery/index.yaml` gains three model entries —
    `insightface-buffalo-l`, `insightface-opencv`,
    `insightface-buffalo-s` — each setting the appropriate
    `overrides.backend` + `overrides.options` so installing one
    actually gives the user the intended engine. This matches how
    `rfdetr-base` lives in the model gallery against the `rfdetr`
    backend.

The earlier e2e tests passed despite this bug because the Makefile
targets pass `BACKEND_TEST_OPTIONS` directly to LoadModel via gRPC,
bypassing any gallery resolution entirely. No code changes needed.

Assisted-by: Claude:claude-opus-4-7

* feat(face-recognition): cover all supported models in the gallery + drop weight baking

Follows up on the model-gallery split: adds entries for every model
configuration either engine actually supports, and switches weight
delivery from image-baked to LocalAI's standard gallery mechanism.

Gallery now has seven `insightface-*` model entries (gallery/index.yaml):

  insightface (family)  — non-commercial research use
    • buffalo-l   (326MB)  — SCRFD-10GF + ResNet50 + genderage, default
    • buffalo-m   (313MB)  — SCRFD-2.5GF + ResNet50 + genderage
    • buffalo-s   (159MB)  — SCRFD-500MF + MBF + genderage
    • buffalo-sc  (16MB)   — SCRFD-500MF + MBF, recognition only
                             (no landmarks, no demographics — analyze
                             returns empty attributes)
    • antelopev2  (407MB)  — SCRFD-10GF + ResNet100@Glint360K + genderage

  OpenCV Zoo family — Apache 2.0 commercial-safe
    • opencv       — YuNet + SFace fp32 (~40MB)
    • opencv-int8  — YuNet + SFace int8 (~12MB, ~3x smaller, faster on CPU)

Model weights are no longer baked into the backend image. The image
now ships only the Python runtime + libraries (~275MB content size,
~1.18GB disk vs ~1.21GB when weights were baked). Weights flow through
LocalAI's gallery mechanism:

  * OpenCV variants list `files:` with ONNX URIs + SHA-256, so
    `local-ai models install insightface-opencv` pulls them into the
    models directory exactly like any other gallery-managed model.

  * insightface packs (upstream distributes .zip archives only, not
    individual ONNX files) auto-download on first LoadModel via
    FaceAnalysis' built-in machinery, rooted at the LocalAI models
    directory so they live alongside everything else — same pattern
    `rfdetr` uses with `inference.get_model()`.

Backend changes (backend/python/insightface/):

  * backend.py — LoadModel propagates `ModelOptions.ModelPath` (the
    LocalAI models directory) to engines via a `_model_dir` hint.
    This replaces the earlier ModelFile-dirname approach; ModelPath
    is the canonical "models directory" variable set by the Go loader
    (pkg/model/initializers.go:144) and is always populated.

  * engines.py::_resolve_model_path — picks up `model_dir` and searches
    it (plus basename-in-model-dir) before falling back to the dev
    script-dir. This is how OnnxDirectEngine finds gallery-downloaded
    YuNet/SFace files by filename only.

  * engines.py::_flatten_insightface_pack — new helper that works
    around an upstream packaging inconsistency: buffalo_l/s/sc zips
    expand flat, but buffalo_m and antelopev2 zips wrap their ONNX
    files in a redundant `<name>/` directory. insightface's own
    loader looks one level too shallow and fails. We call
    `ensure_available()` explicitly, flatten if nested, then hand to
    FaceAnalysis.

  * engines.py::InsightFaceEngine.prepare — root-resolution order now
    includes the `_model_dir` hint so packs download into the LocalAI
    models directory by default.

  * install.sh — no longer pre-downloads any weights. Everything is
    gallery-managed now.

  * smoke.py (new) — parametrized smoke test that iterates over every
    gallery configuration, simulating the LocalAI install flow
    (creates a models dir, fetches OpenCV files with checksum
    verification, lets insightface auto-download its packs), then
    runs detect + embed + verify (+ analyze where supported) through
    the in-process BackendServicer.

  * test.py — OnnxDirectEngineTest no longer hardcodes `/models/opencv/`
    paths; downloads ONNX files to a temp dir at setUpClass time and
    passes ModelPath accordingly.

Registry change (core/services/facerecognition/store_registry.go):

  * `dim=0` in NewStoreRegistry now means "accept whatever dimension
    arrives" — needed because the backend supports 512-d ArcFace/MBF
    and 128-d SFace via the same Registry. A non-zero dim still fails
    fast with ErrDimensionMismatch.

  * core/application plumbs `faceEmbeddingDim = 0`, explaining the
    rationale in the comment.

Backend gallery description updated to reflect that the image carries
no weights — it's just Python + engines.

Smoke-tested all 7 configurations against the rebuilt image (with the
flatten fix applied), exit 0:

    PASS: insightface-buffalo-l    faces=6 dim=512 same-dist=0.000
    PASS: insightface-buffalo-sc   faces=6 dim=512 same-dist=0.000
    PASS: insightface-buffalo-s    faces=6 dim=512 same-dist=0.000
    PASS: insightface-buffalo-m    faces=6 dim=512 same-dist=0.000
    PASS: insightface-antelopev2   faces=6 dim=512 same-dist=0.000
    PASS: insightface-opencv       faces=6 dim=128 same-dist=0.000
    PASS: insightface-opencv-int8  faces=6 dim=128 same-dist=0.000
    7/7 passed

Assisted-by: Claude:claude-opus-4-7

* fix(face-recognition): pre-fetch OpenCV ONNX for e2e target; drop stale pre-baked claim

CI regression from the previous commit: I moved OpenCV Zoo weight
delivery to LocalAI's gallery `files:` mechanism, but the
test-extra-backend-insightface-opencv target was still passing
relative paths `detector_onnx:models/opencv/yunet.onnx` in
BACKEND_TEST_OPTIONS. The e2e suite drives LoadModel directly over
gRPC without going through the gallery, so those relative paths
resolved to nothing and OpenCV's ONNXImporter failed:

    LoadModel failed: Failed to load face engine:
    OpenCV(4.13.0) ... Can't read ONNX file: models/opencv/yunet.onnx

Fix: add an `insightface-opencv-models` prerequisite target that
fetches the two ONNX files (YuNet + SFace) to a deterministic host
cache at /tmp/localai-insightface-opencv-cache/, verifies SHA-256,
and skips the download on re-runs. The opencv test target depends on
it and passes absolute paths in BACKEND_TEST_OPTIONS, so the backend
finds the files via its normal absolute-path resolution branch.

Also refresh the buffalo_l comment: it no longer says "pre-baked"
(nothing is — the pack auto-downloads from upstream's GitHub release
on first LoadModel, same as in CI).

Locally verified: `make test-extra-backend-insightface-opencv` passes
5/5 specs (health, load, face_detect, face_embed, face_verify).

Assisted-by: Claude:claude-opus-4-7

* feat(face-recognition): add POST /v1/face/embed + correct /v1/embeddings docs

The docs promised that /v1/embeddings returns face vectors when you
send an image data-URI. That was never true: /v1/embeddings is
OpenAI-compatible and text-only by contract — its handler goes
through `core/backend/embeddings.go::ModelEmbedding`, which sets
`predictOptions.Embeddings = s` (a string of TEXT to embed) and never
populates `predictOptions.Images[]`. The Python backend's Embedding
gRPC method does handle Images[] (that's how /v1/face/register reaches
it internally via `backend.FaceEmbed`), but the HTTP embeddings
endpoint wasn't wired to populate it.

Rather than overload /v1/embeddings with image-vs-text detection —
messy, and the endpoint is OpenAI-compatible by design — add a
dedicated /v1/face/embed endpoint that wraps `backend.FaceEmbed`
(already used internally by /v1/face/register and /v1/face/identify).

Matches LocalAI's convention of a dedicated path per non-standard flow
(/v1/rerank, /v1/detection, /v1/face/verify etc.).

Response:

    {
      "embedding": [<dim> floats, L2-normed],
      "dim": int,           // 512 for ArcFace R50 / MBF, 128 for SFace
      "model": "<name>"
    }

Live-tested on the opencv engine: returns a 128-d L2-normalized vector
(sum(x^2) = 1.0000). Sentinel in docs updated to note /v1/embeddings
is text-only and point image users at /v1/face/embed instead.

Assisted-by: Claude:claude-opus-4-7

* fix(http): map malformed image input + gRPC status codes to proper 4xx

Image-input failures on LocalAI's single-image endpoints (/v1/detection,
/v1/face/{verify,analyze,embed,register,identify}) have historically
returned 500 — even when the client was the one who sent garbage.
Classic example: you POST an "image" that isn't a URL, isn't a
data-URI, and isn't a valid JPEG/PNG — the server shouldn't claim
that's its fault.

Two helpers land in core/http/endpoints/localai/images.go and every
single-image handler is switched over:

  * decodeImageInput(s)
      Wraps utils.GetContentURIAsBase64 and turns any failure
      (invalid URL, not a data-URI, download error, etc.) into
      echo.NewHTTPError(400, "invalid image input: ...").

  * mapBackendError(err)
      Inspects the gRPC status on a backend call error and maps:
        INVALID_ARGUMENT     → 400 Bad Request
        NOT_FOUND            → 404 Not Found
        FAILED_PRECONDITION  → 412 Precondition Failed
        Unimplemented        → 501 Not Implemented
      All other codes fall through unchanged (still 500).

Before, my 1×1 PNG error-path test returned:
    HTTP 500 "rpc error: code = InvalidArgument desc = failed to decode one or both images"
After:
    HTTP 400 "failed to decode one or both images"

Scope-limited to the LocalAI single-image endpoints. The multi-modal
paths (middleware/request.go, openresponses/responses.go,
openai/realtime.go) intentionally log-and-skip individual media parts
when decoding fails — different design intent (graceful degradation
of a multi-part message), not a 400-worthy failure. Left untouched.

Live-verified: every error case in /tmp/face_errors.py now returns
4xx with a meaningful message; the "image with no face (1x1 PNG)"
case specifically went from 500 → 400.

Assisted-by: Claude:claude-opus-4-7

* refactor(face-recognition): insightface packs go through gallery files:, drop FaceAnalysis

Follows up on the discovery that LocalAI's gallery `files:` mechanism
handles archives (zip, tar.gz, …) via mholt/archiver/v3 — the rhasspy
piper voices use exactly this pattern. Insightface packs are zip
archives, so we can now deliver them the same way every other
gallery-managed model gets delivered: declaratively, checksum-verified,
through LocalAI's standard download+extract pipeline.

Two changes:

1. Gallery (gallery/index.yaml) — every insightface-* entry gains a
   `files:` list with the pack zip's URI + SHA-256. `local-ai models
   install insightface-buffalo-l` now fetches the zip, verifies the
   hash, and extracts it into the models directory. No more reliance
   on insightface's library-internal `ensure_available()` auto-download
   or its hardcoded `BASE_REPO_URL`.

2. InsightFaceEngine (backend/python/insightface/engines.py) — drops
   the FaceAnalysis wrapper and drives insightface's `model_zoo`
   directly. The ~50 lines FaceAnalysis provides — glob ONNX files,
   route each through `model_zoo.get_model()`, build a
   `{taskname: model}` dict, loop per-face at inference — are
   reimplemented in `InsightFaceEngine`. The actual inference classes
   (RetinaFace, ArcFaceONNX, Attribute, Landmark) are still
   insightface's — we only replicate the glue, so drift risk against
   upstream is minimal.

   Why drop FaceAnalysis: it hard-codes a `<root>/models/<name>/*.onnx`
   layout that doesn't match what LocalAI's zip extraction produces.
   LocalAI unpacks archives flat into `<models_dir>`. Upstream packs
   are inconsistent — buffalo_l/s/sc ship ONNX at the zip root (lands
   at `<models_dir>/*.onnx`), buffalo_m/antelopev2 wrap in a redundant
   `<name>/` dir (lands at `<models_dir>/<name>/*.onnx`). The new
   `_locate_insightface_pack` helper searches both locations plus
   legacy paths and returns whichever has ONNX files. Replaces the
   earlier `_flatten_insightface_pack` helper (which tried to fight
   FaceAnalysis's layout expectations; now we just find the files
   wherever they are).

Net effect for users: install once via LocalAI's managed flow,
weights live alongside every other model, progress shows in the
jobs endpoint, no first-load network call. Same API surface,
cleaner plumbing.

Assisted-by: Claude:claude-opus-4-7

* fix(face-recognition): CI's insightface e2e path needs the pack pre-fetched

The e2e suite drives LoadModel over gRPC without going through LocalAI's
gallery flow, so the engine's `_model_dir` option (normally populated
from ModelPath) is empty. Previously the insightface target relied on
FaceAnalysis auto-download to paper over this, but we dropped
FaceAnalysis in favor of direct model_zoo calls — so the buffalo_l
target started failing at LoadModel with "no insightface pack found".

Mirror the opencv target's pre-fetch pattern: download buffalo_sc.zip
(same SHA as the gallery entry), extract it on the host, and pass
`root:<dir>` so the engine locates the pack without needing
ModelPath. Switched to buffalo_sc (smallest pack, ~16MB) to keep CI
fast; it covers the same insightface engine code path as buffalo_l.

Face analyze cap dropped since buffalo_sc has no age/gender head.

Assisted-by: Claude:claude-opus-4-7[1m]

* feat(face-recognition): surface face-recognition in advertised feature maps

The six /v1/face/* endpoints were missing from every place LocalAI
advertises its feature surface to clients:

  * api_instructions — the machine-readable capability index at
    GET /api/instructions. Added `face-recognition` as a dedicated
    instruction area with an intro that calls out the in-memory
    registry caveat and the /v1/face/embed vs /v1/embeddings split.
  * auth/permissions — added FeatureFaceRecognition constant, routed
    all six face endpoints through it so admins can gate them per-user
    like any other API feature. Default ON (matches the other API
    features).
  * React UI capabilities — CAP_FACE_RECOGNITION symbol mapped to
    FLAG_FACE_RECOGNITION. Declared only for now; the Face page is a
    follow-up (noted in the plan).

Instruction count bumped 9 → 10; test updated.

Assisted-by: Claude:claude-opus-4-7[1m]

* docs(agents): capture advertising-surface steps in the endpoint guide

Before this change, adding a new /v1/* endpoint reliably missed one or
more of: the swagger @Tags annotation, the /api/instructions registry,
the auth RouteFeatureRegistry, and the React UI CAP_* symbol. The
endpoint would work but be invisible to API consumers, admins, and the
UI — and nothing in the existing docs said to look in those places.

Extend .agents/api-endpoints-and-auth.md with a new "Advertising
surfaces" section covering all four surfaces (swagger tags, /api/
instructions, capabilities.js, docs/), and expand the closing checklist
so it's impossible to ship a feature without visiting each one. Hoist a
one-liner reminder into AGENTS.md's Quick Reference so agents skim it
before diving in.

Assisted-by: Claude:claude-opus-4-7[1m]
2026-04-22 21:55:41 +02:00
Ettore Di Giacinto
8ab0744458 feat: backend versioning, upgrade detection and auto-upgrade (#9315)
* feat: add backend versioning data model foundation

Add Version, URI, and Digest fields to BackendMetadata for tracking
installed backend versions and enabling upgrade detection. Add Version
field to GalleryBackend. Add UpgradeAvailable/AvailableVersion fields
to SystemBackend. Implement GetImageDigest() for lightweight OCI digest
lookups via remote.Head. Record version, URI, and digest at install time
in InstallBackend() and propagate version through meta backends.

* feat: add backend upgrade detection and execution logic

Add CheckBackendUpgrades() to compare installed backend versions/digests
against gallery entries, and UpgradeBackend() to perform atomic upgrades
with backup-based rollback on failure. Includes Agent A's data model
changes (Version/URI/Digest fields, GetImageDigest).

* feat: add AutoUpgradeBackends config and runtime settings

Add configuration and runtime settings for backend auto-upgrade:
- RuntimeSettings field for dynamic config via API/JSON
- ApplicationConfig field, option func, and roundtrip conversion
- CLI flag with LOCALAI_AUTO_UPGRADE_BACKENDS env var
- Config file watcher support for runtime_settings.json
- Tests for ToRuntimeSettings, ApplyRuntimeSettings, and roundtrip

* feat(ui): add backend version display and upgrade support

- Add upgrade check/trigger API endpoints to config and api module
- Backends page: version badge, upgrade indicator, upgrade button
- Manage page: version in metadata, context-aware upgrade/reinstall button
- Settings page: auto-upgrade backends toggle

* feat: add upgrade checker service, API endpoints, and CLI command

- UpgradeChecker background service: checks every 6h, auto-upgrades when enabled
- API endpoints: GET /backends/upgrades, POST /backends/upgrades/check, POST /backends/upgrade/:name
- CLI: `localai backends upgrade` command, version display in `backends list`
- BackendManager interface: add UpgradeBackend and CheckUpgrades methods
- Wire upgrade op through GalleryService backend handler
- Distributed mode: fan-out upgrade to worker nodes via NATS

* fix: use advisory lock for upgrade checker in distributed mode

In distributed mode with multiple frontend instances, use PostgreSQL
advisory lock (KeyBackendUpgradeCheck) so only one instance runs
periodic upgrade checks and auto-upgrades. Prevents duplicate
upgrade operations across replicas.

Standalone mode is unchanged (simple ticker loop).

* test: add e2e tests for backend upgrade API

- Test GET /api/backends/upgrades returns 200 (even with no upgrade checker)
- Test POST /api/backends/upgrade/:name accepts request and returns job ID
- Test full upgrade flow: trigger upgrade via API, wait for job completion,
  verify run.sh updated to v2 and metadata.json has version 2.0.0
- Test POST /api/backends/upgrades/check returns 200
- Fix nil check for applicationInstance in upgrade API routes
2026-04-11 22:31:15 +02:00
Ettore Di Giacinto
5c35e85fe2 feat: allow to pin models and skip from reaping (#9309)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-04-11 08:38:17 +02:00
Leigh Phillips
062e0d0d00 feat: Add toggle mechanism to enable/disable models from loading on demand (#9304)
* feat: add toggle mechanism to enable/disable models from loading on demand

Implements #9303 - Adds ability to disable models from being auto-loaded
while keeping them in the collection.

Backend changes:
- Add Disabled field to ModelConfig struct with IsDisabled() getter
- New ToggleModelEndpoint handler (PUT /models/toggle/:name/:action)
- Request middleware returns 403 when disabled model is requested
- Capabilities endpoint exposes disabled status

Frontend changes:
- Toggle switch in System > Models table Actions column
- Visual indicators: dimmed row, red Disabled badge, muted icons
- Tooltip describes toggle function on hover
- Loading state while API call is in progress

* fix: remove extra closing brace causing syntax error in request middleware

* refactor: reorder Actions column - Stop button before toggle switch

* refactor: migrate from toggle to toggle-state per PR review feedback
2026-04-10 18:17:41 +02:00
Richard Palethorpe
557d0f0f04 feat(api): Allow coding agents to interactively discover how to control and configure LocalAI (#9084)
Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-04-04 15:14:35 +02:00
Ettore Di Giacinto
59108fbe32 feat: add distributed mode (#9124)
* feat: add distributed mode (experimental)

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix data races, mutexes, transactions

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactorings

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fixups

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix events and tool stream in agent chat

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* use ginkgo

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactoring and consolidation

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactoring and consolidation

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactoring and consolidation

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactoring and consolidation

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactoring and consolidation

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactoring and consolidation

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactoring and consolidation

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactoring and consolidation

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(cron): compute correctly time boundaries avoiding re-triggering

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* enhancements, refactorings

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* do not flood of healthy checks

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* do not list obvious backends as text backends

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* tests fixups

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* refactoring and consolidation

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Drop redundant healthcheck

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* enhancements, refactorings

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-03-30 00:47:27 +02:00
Ettore Di Giacinto
f7e8d9e791 feat(quantization): add quantization backend (#9096)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-03-22 00:56:34 +01:00
Ettore Di Giacinto
d9c1db2b87 feat: add (experimental) fine-tuning support with TRL (#9088)
* feat: add fine-tuning endpoint

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(experimental): add fine-tuning endpoint and TRL support

This changeset defines new GRPC signatues for Fine tuning backends, and
add TRL backend as initial fine-tuning engine. This implementation also
supports exporting to GGUF and automatically importing it to LocalAI
after fine-tuning.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* commit TRL backend, stop by killing process

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* move fine-tune to generic features

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* add evals, reorder menu

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fix tests

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-03-21 02:08:02 +01:00
Ettore Di Giacinto
aea21951a2 feat: add users and authentication support (#9061)
* feat(ui): add users and authentication support

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat: allow the admin user to impersonificate users

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore: ui improvements, disable 'Users' button in navbar when no auth is configured

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat: add OIDC support

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix: gate models

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore: cache requests to optimize speed

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* small UI enhancements

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(ui): style improvements

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix: cover other paths by auth

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore: separate local auth, refactor

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* security hardening, approval mode

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix: fix tests and expectations

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore: update localagi/localrecall

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-03-19 21:40:51 +01:00
Richard Palethorpe
e832efeb9e fix(ui): Refresh model list on deletion (#9059)
Signed-off-by: Richard Palethorpe <io@richiejp.com>
2026-03-18 14:07:45 +01:00
Ettore Di Giacinto
6c11c54a3b fix: avoid race condition
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-03-12 18:46:22 +00:00
Ettore Di Giacinto
8818452d85 feat(ui): MCP Apps, mcp streaming and client-side support (#8947)
* Revert "fix: Add timeout-based wait for model deletion completion (#8756)"

This reverts commit 9e1b0d0c82.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat: add mcp prompts and resources

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ui): add client-side MCP

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ui): allow to authenticate MCP servers

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ui): add MCP Apps

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore: update AGENTS

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore: allow to collapse navbar, save state in storage

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(ui): add MCP button also to home page

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(chat): populate string content

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-03-11 07:30:49 +01:00
Ettore Di Giacinto
ac48867b7d feat: add agentic management (#8820)
* feat: add standalone and agentic functionalities

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* expose agents via responses api

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-03-07 00:03:08 +01:00
LocalAI [bot]
ab315f2725 feat: Add LOCALAI_DISABLE_MCP environment variable to disable MCP support (#8816)
* feat: Add LOCALAI_DISABLE_MCP environment variable to disable MCP support

- Added DisableMCP field to RunCMD struct in core/cli/run.go
- Added LOCALAI_DISABLE_MCP environment variable support
- Added DisableMCP field to ApplicationConfig struct
- Added DisableMCP AppOption function
- Updated MCP endpoint routing to check appConfig.DisableMCP
- When LOCALAI_DISABLE_MCP is set to true/1/yes, MCP endpoints are not registered

When set, all MCP functionality is disabled and appropriate error messages
are returned to users.

Use Cases:
- Security-conscious deployments where MCP is not needed
- Reducing attack surface
- Compliance requirements that prohibit certain protocol support

Environment variable: LOCALAI_DISABLE_MCP=true

Signed-off-by: localai-bot <localai-bot@users.noreply.github.com>

* docs: Add documentation for LOCALAI_DISABLE_MCP environment variable

- Add section explaining how to disable MCP support using environment variable
- Document use cases for disabling MCP
- Provide examples for CLI and Docker usage

Signed-off-by: localai-bot <localai-bot@users.noreply.github.com>

---------

Signed-off-by: localai-bot <localai-bot@users.noreply.github.com>
Co-authored-by: localai-bot <localai-bot@users.noreply.github.com>
2026-03-06 20:44:03 +01:00
LocalAI [bot]
1027c487a6 fix: reload model after editing YAML config (issue #8647) (#8652)
fix: reload model configuration after editing (issue #8647)

- Add *model.ModelLoader parameter to EditModelEndpoint
- Call ml.ShutdownModel() after saving config to unload the running model
- Model will be reloaded on next inference request with new settings (e.g., context_size)
- Update route registration to pass ml to EditModelEndpoint

Signed-off-by: localai-bot <localai-bot@users.noreply.github.com>
Co-authored-by: localai-bot <localai-bot@users.noreply.github.com>
2026-02-25 22:18:42 +01:00
Ettore Di Giacinto
352b8aaa1b fix(ui): pass by needed values to unbreak model editor
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-02-20 09:06:17 +01:00
lif
4cd95b8a9d fix: Highly inconsistent agent response to cogito agent calling MCP server - Body "Invalid http method" (#7790)
* fix: resolve duplicate MCP route registration causing 50% failure rate

Fixes #7772

The issue was caused by duplicate registration of the MCP endpoint
/mcp/v1/chat/completions in both openai.go and localai.go, leading
to a race condition where requests would randomly hit different
handlers with incompatible behaviors.

Changes:
- Removed duplicate MCP route registration from openai.go
- Kept the localai.MCPStreamEndpoint as the canonical handler
- Added all three MCP route patterns for backward compatibility:
  * /v1/mcp/chat/completions
  * /mcp/v1/chat/completions
  * /mcp/chat/completions
- Added comments to clarify route ownership and prevent future conflicts
- Fixed formatting in ui_api.go

The localai.MCPStreamEndpoint handler is more feature-complete as it
supports both streaming and non-streaming modes, while the removed
openai.MCPCompletionEndpoint only supported synchronous requests.

This eliminates the ~50% failure rate where the cogito library would
receive "Invalid http method" errors when internal HTTP requests were
routed to the wrong handler.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Signed-off-by: majiayu000 <1835304752@qq.com>

* Address feedback from review

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: majiayu000 <1835304752@qq.com>
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Claude Sonnet 4.5 <noreply@anthropic.com>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-01-03 15:43:23 +01:00
Ettore Di Giacinto
53e5b2d6be feat: agent jobs panel (#7390)
* feat(agent): agent jobs

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Multiple webhooks, simplify

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Do not use cron with seconds

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Create separate pages for details

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Detect if no models have MCP configuration, show wizard

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Make services test to run

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-11-28 23:05:39 +01:00
Ettore Di Giacinto
47b546afdc feat(mcp): add LocalAI endpoint to stream live results of the agent (#7274)
* feat(mcp): add LocalAI endpoint to stream live results of the agent

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* wip

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Refactoring

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* MCP UX integration

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Enhance UX

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Support also non-SSE

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-11-15 17:38:00 +01:00
Ettore Di Giacinto
1cdcaf0152 feat: migrate to echo and enable cancellation of non-streaming requests (#7270)
* WIP: migrate to echo

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* tests

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-11-14 22:57:53 +01:00
Ettore Di Giacinto
3728552e94 feat: import models via URI (#7245)
* feat: initial hook to install elements directly

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* WIP: ui changes

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Move HF api client to pkg

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add simple importer for gguf files

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add opcache

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* wire importers to CLI

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add omitempty to config fields

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fix tests

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add MLX importer

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Small refactors to star to use HF for discovery

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add tests

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Common preferences

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add support to bare HF repos

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(importer/llama.cpp): add support for mmproj files

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* add mmproj quants to common preferences

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fix vlm usage in tokenizer mode with llama.cpp

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-11-12 20:48:56 +01:00
Matt Cowger
df6a80b38d feat: Add a model refresh button to manually refresh on-disk yaml (#6150)
Add a model refresh button
2025-08-27 09:44:40 +02:00
Ettore Di Giacinto
7050c9f69d feat(webui): add import/edit model page (#6050)
* feat(webui): add import/edit model page

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Convert to a YAML editor

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Pass by the baseurl

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fixups

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add tests

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Simplify

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Improve visibility of the yaml editor

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add test file

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Make reset work

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Emit error only if we can't delete the model yaml file

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-08-14 23:48:09 +02:00
Ettore Di Giacinto
089efe05fd feat(backends): add system backend, refactor (#6059)
- Add a system backend path
- Refactor and consolidate system information in system state
- Use system state in all the components to figure out the system paths
  to used whenever needed
- Refactor BackendConfig -> ModelConfig. This was otherway misleading as
  now we do have a backend configuration which is not the model config.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-08-14 19:38:26 +02:00
Ettore Di Giacinto
949e5b9be8 feat(rfdetr): add object detection API (#5923)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-27 22:02:51 +02:00
Ettore Di Giacinto
ee625fc34e fix(backends gallery): pass-by backend galleries to the model service (#5906)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-25 16:38:09 +02:00
Ettore Di Giacinto
98e5291afc feat: refactor build process, drop embedded backends (#5875)
* feat: split remaining backends and drop embedded backends

- Drop silero-vad, huggingface, and stores backend from embedded
  binaries
- Refactor Makefile and Dockerfile to avoid building grpc backends
- Drop golang code that was used to embed backends
- Simplify building by using goreleaser

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(gallery): be specific with llama-cpp backend templates

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(docs): update

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(ci): minor fixes

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore: drop all ffmpeg references

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix: run protogen-go

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Always enable p2p mode

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Update gorelease file

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(stores): do not always load

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fix linting issues

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Simplify

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Mac OS fixup

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-07-22 16:31:04 +02:00
Ettore Di Giacinto
2d64269763 feat: Add backend gallery (#5607)
* feat: Add backend gallery

This PR add support to manage backends as similar to models. There is
now available a backend gallery which can be used to install and remove
extra backends.
The backend gallery can be configured similarly as a model gallery, and
API calls allows to install and remove new backends in runtime, and as
well during the startup phase of LocalAI.

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add backends docs

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* wip: Backend Dockerfile for python backends

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat: drop extras images, build python backends separately

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fixup on all backends

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* test CI

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Tweaks

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Drop old backends leftovers

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fixup CI

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Move dockerfile upper

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fix proto

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Feature dropped for consistency - we prefer model galleries

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add missing packages in the build image

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* exllama is ponly available on cublas

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* pin torch on chatterbox

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Fixups to index

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* CI

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Debug CI

* Install accellerators deps

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Add target arch

* Add cuda minor version

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Use self-hosted runners

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* ci: use quay for test images

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fixups for vllm and chatterbox

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Small fixups on CI

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chatterbox is only available for nvidia

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Simplify CI builds

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Adapt test, use qwen3

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(model gallery): add jina-reranker-v1-tiny-en-gguf

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(gguf-parser): recover from potential panics that can happen while reading ggufs with gguf-parser

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Use reranker from llama.cpp in AIO images

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Limit concurrent jobs

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2025-06-15 14:56:52 +02:00
Ettore Di Giacinto
2c9279a542 feat(video-gen): add endpoint for video generation (#5247)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-04-26 18:05:01 +02:00
Ettore Di Giacinto
2c425e9c69 feat(loader): enhance single active backend by treating as singleton (#5107)
feat(loader): enhance single active backend by treating at singleton

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2025-04-01 20:58:11 +02:00
Dave
3cddf24747 feat: Centralized Request Processing middleware (#3847)
* squash past, centralize request middleware PR

Signed-off-by: Dave Lee <dave@gray101.com>

* migrate bruno request files to examples repo

Signed-off-by: Dave Lee <dave@gray101.com>

* fix

Signed-off-by: Dave Lee <dave@gray101.com>

* Update tests/e2e-aio/e2e_test.go

Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>

---------

Signed-off-by: Dave Lee <dave@gray101.com>
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2025-02-10 12:06:16 +01:00
Ettore Di Giacinto
cea5a0ea42 feat(template): read jinja templates from gguf files (#4332)
* Read jinja templates as fallback

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Move templating out of model loader

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Test TemplateMessages

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Set role and content from transformers

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Tests: be more flexible

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* More jinja

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Small refactoring and adaptations

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2024-12-08 13:50:33 +01:00
Ettore Di Giacinto
b1ea9318e6 feat(silero): add Silero-vad backend (#4204)
* feat(vad): add silero-vad backend (WIP)

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(vad): add API endpoint

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(vad): correctly place the onnxruntime libs

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* chore(vad): hook silero-vad to binary and container builds

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* feat(gRPC): register VAD Server

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(Makefile): consume ONNX_OS consistently

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(Makefile): handle macOS

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
2024-11-20 14:48:40 +01:00
Ettore Di Giacinto
8737a65760 feat: allow to disable '/metrics' endpoints for local stats (#3945)
Seem the "/metrics" endpoint that is source of confusion as people tends
to believe we collect telemetry data just because we import
"opentelemetry", however it is still a good idea to allow to disable
even local metrics if not really required.

See also: https://github.com/mudler/LocalAI/issues/3942

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2024-10-23 15:34:32 +02:00
Shraddha
5488fc3bc1 feat: tokenization endpoint (#3710)
endpoint to access the tokenizer

Signed-off-by: shraddhazpy <shraddha@shraddhafive.in>
Co-authored-by: Ettore Di Giacinto <mudler@users.noreply.github.com>
Co-authored-by: Dave <dave@gray101.com>
2024-10-02 08:56:18 +02:00
Ettore Di Giacinto
0893d3cbbe fix(health): do not require auth for /healthz and /readyz (#3656)
* fix(health): do not require auth for /healthz and /readyz

Fixes: #3655

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* Comment so I don’t forget

Adding a reminder here...

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Dave <dave@gray101.com>
2024-09-24 18:25:59 +00:00