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45 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
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4906cbad04 |
feat: add biometrics UI (#9524)
* feat(react-ui): add Face & Voice Recognition pages
Expose the face and voice biometrics endpoints
(/v1/face/*, /v1/voice/*) through the React UI. Each page has four
tabs driving the six endpoints per modality: Analyze (demographics
with bounding boxes / waveform segments), Compare (verify with a
match gauge and live threshold slider), Enrollment (register /
identify / forget with a top-K matches view), Embedding (raw
vector inspector with sparkline + copy).
MediaInput supports file upload plus live capture: webcam
snap-to-canvas for face, MediaRecorder -> AudioContext ->
16-bit PCM mono WAV transcode for voice (libsndfile on the
backend only handles WAV/FLAC/OGG natively).
Sidebar gets a new Biometrics section feature-gated on
face_recognition / voice_recognition; routes are wrapped in
<RequireFeature>. No new dependencies -- Font Awesome icons
picked from the Free set.
Assisted-by: Claude:Opus 4.7
* fix(localai): accept data URI prefixes with codec/charset params
Browser MediaRecorder produces data URIs like
data:audio/webm;codecs=opus;base64,...
so the pre-';base64,' section can carry multiple parameter
segments. The `^data:([^;]+);base64,` regex in pkg/utils/base64.go
and core/http/endpoints/localai/audio.go only matched exactly one
segment, so recordings straight from the React UI's live-capture
tab failed the strip and then tripped the base64 decoder on the
leading 'data:' literal, surfacing as
"invalid audio base64: illegal base64 data at input byte 4"
Widened both regexes to `^data:[^,]+?;base64,` so any number of
';param=value' segments between the mime type and ';base64,' are
tolerated. Added a regression test covering the MediaRecorder
shape.
Assisted-by: Claude:Opus 4.7
* fix(insightface): scope pack ONNX loading to known manifests
LocalAI's gallery extracts buffalo_* zips flat into the models
directory, which inevitably mixes with ONNX files from other
backends (opencv face engine, MiniFASNet antispoof, WeSpeaker
voice embedding) and older buffalo pack installs. Feeding those
foreign files into insightface's model_zoo.get_model() blows up
inside the router -- it assumes a 4-D NCHW input and indexes
`input_shape[2]` on tensors that aren't shaped like a face model,
raising IndexError mid-load and leaving the backend unusable.
The router's dispatch isn't amenable to per-file try/except alone
(first-file-wins picks det_10g.onnx from buffalo_l even when the
user asked for buffalo_sc -- alphabetical order happens to favour
the wrong pack). Instead, ship an explicit manifest of the
upstream v0.7 pack contents and scope the glob to that when the
requested pack is known. The manifest is small and stable; future
packs can be added alongside or fall through to the tolerance
loop, which also swallows any remaining IndexError / ValueError
from foreign files with a clear `[insightface] skipped` stderr
line for diagnostics.
Assisted-by: Claude:Opus 4.7
* fix(speaker-recognition): extract FBank features for rank-3 ONNX encoders
Pre-exported speaker-encoder ONNX graphs come in two shapes:
rank-2 [batch, samples] -- some 3D-Speaker exports,
take raw waveform directly.
rank-3 [batch, frames, n_mels] -- WeSpeaker and most Kaldi-
lineage encoders, expect
pre-computed Kaldi FBank.
OnnxDirectEngine unconditionally fed `audio.reshape(1, -1)` --
correct for rank-2, IndexError-on-input_shape[3] on rank-3, which
surfaced to the UI as
"Invalid rank for input: feats Got: 2 Expected: 3"
Detect the input rank at session init and run Kaldi FBank
(80-dim, 25ms/10ms frames, dither=0.0, per-utterance CMN) before
the forward pass when rank>=3. All knobs are configurable via
backend options for encoders that deviate from defaults.
torchaudio.compliance.kaldi is already in the backend's
requirements (SpeechBrain pulls torchaudio in), so no new
dependency.
Assisted-by: Claude:Opus 4.7
* fix(biometrics): isolate face and voice vector stores
Face (ArcFace, 512-D) and voice (ECAPA-TDNN 192-D / WeSpeaker
256-D) biometric embeddings were colliding inside a single
in-memory local-store instance. Enrolling one after the other
failed with
"Try to add key with length N when existing length is M"
because local-store correctly refuses to mix dimensions in one
keyspace.
The registries were constructed with `storeName=""`, which in
StoreBackend() is just a WithModel() call. But ModelLoader's
cache is keyed on `modelID`, not `model` -- so both registries
collapsed to the same `modelID=""` slot and reused the same
backend process despite looking isolated on paper.
Three complementary fixes:
1. application.go -- give each registry a distinct default
namespace ("localai-face-biometrics" /
"localai-voice-biometrics"). The comment claimed
isolation, now it's actually enforced.
2. stores.go -- pass the storeName as both WithModelID and
WithModel so the ModelLoader cache key separates
namespaces and the loader spawns distinct processes.
3. local-store/store.go -- drop the Load() `opts.Model != ""`
guard. It was there to prevent generic model-loading loops
from picking up local-store by accident, but that auto-load
path is being retired; the guard now just blocks legitimate
namespace isolation. opts.Model is treated as a tag; the
per-tuple process isolation upstream handles discrimination.
Assisted-by: Claude:Opus 4.7
* fix(gallery): stale-file cleanup and upgrade-tmp directory safety
Two related robustness fixes for backend install/upgrade:
pkg/downloader/uri.go
OCI downloads passed through
if filepath.Ext(filePath) != "" ...
filePath = filepath.Dir(filePath)
which was intended to redirect file-shaped download targets
into their parent directory for OCI extraction. The heuristic
misfires on directory-shaped paths with a dot-suffix --
gallery.UpgradeBackend uses
tmpPath = "<backendsPath>/<name>.upgrade-tmp"
and Go's filepath.Ext treats ".upgrade-tmp" as an extension.
The rewrite landed the extraction at "<backendsPath>/", which
then **overwrote the real install** (backends/<name>/) with a
flat-layout file and left a stray run.sh at the top level. The
tmp dir itself stayed empty, so the validation step that
checked "<tmpPath>/run.sh" predictably failed with
"upgrade validation failed: run.sh not found in new backend"
Every manual upgrade silently corrupted the backends tree this
way. Guard the rewrite behind "target isn't already an existing
directory" -- InstallBackend / UpgradeBackend both pre-create
the target as a directory, so they get the correct behaviour;
existing file-path callers with a genuine dot-extension still
get the parent redirect.
core/gallery/backends.go
InstallBackend's MkdirAll returned ENOTDIR when something at
the target path was already a file (legacy dev builds dropped
golang backend binaries directly at `<backendsPath>/<name>`
instead of nesting them under their own subdir). That
permanently blocked reinstall and upgrade for anyone carrying
that state, since every retry hit the same error. Detect a
pre-existing non-directory, warn, and remove it before the
MkdirAll so the fresh install can write the correct nested
layout with metadata.json + run.sh.
Assisted-by: Claude:Opus 4.7
* fix(galleryop): refresh upgrade cache after backend ops
UpgradeChecker caches the last upgrade-check result and only
refreshes on the 6-hour tick or after an auto-upgrade cycle.
Manual upgrades (POST /api/backends/upgrade/:name) go through
the async galleryop worker, which completes the upgrade
correctly but never tells UpgradeChecker to re-check -- so
/api/backends/upgrades continued to list a just-upgraded backend
as upgradeable, indistinguishable from a failed upgrade, for up
to six hours.
Add an optional `OnBackendOpCompleted func()` hook on
GalleryService that fires after every successful install /
upgrade / delete on the backend channel (async, so a slow
callback doesn't stall the queue). startup.go wires it to
UpgradeChecker.TriggerCheck after both services exist. Result:
the upgrade banner clears within milliseconds of the worker
finishing.
Assisted-by: Claude:Opus 4.7
* build: prepend GOPATH/bin to PATH for protogen-go
install-go-tools runs `go install` for protoc-gen-go and
protoc-gen-go-grpc, which writes them into `go env GOPATH`/bin.
That directory isn't on every dev's PATH, and protoc resolves
its code-gen plugins via PATH, so the immediately-following
protoc invocation fails with
"protoc-gen-go: program not found"
which in turn blocks `make build` and any
`make backends/%` target that depends on build.
Prepend `go env GOPATH`/bin to PATH for the protoc invocation
so the freshly-installed plugins are found without requiring a
shell-profile change.
Assisted-by: Claude:Opus 4.7
* refactor(ui-api): non-blocking backend upgrade handler with opcache
POST /api/backends/upgrade/:name used to send the ManagementOp
directly onto the unbuffered BackendGalleryChannel, which blocked
the HTTP request whenever the galleryop worker was busy with a
prior operation. The op also didn't show up in /api/operations,
so the Backends UI couldn't reflect upgrade progress on the
affected row.
Register the op in opcache immediately, wrap it in a cancellable
context, store the cancellation function on the GalleryService,
and push onto the channel from a goroutine so the handler
returns right away. Response gains a `jobID` field and a
`message` string so clients have a consistent handle regardless
of whether the op is queued or running.
Pairs with the OnBackendOpCompleted hook added in the galleryop
commit — together the UI sees the upgrade start, watches
progress via /api/operations, and drops the "upgradeable" flag
the moment the worker finishes.
Assisted-by: Claude:Opus 4.7
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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
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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]
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75a63f87d8 |
feat(distributed): sync state with frontends, better backend management reporting (#9426)
* fix(distributed): detect backend upgrades across worker nodes
Before this change `DistributedBackendManager.CheckUpgrades` delegated to the
local manager, which read backends from the frontend filesystem. In
distributed deployments the frontend has no backends installed locally —
they live on workers — so the upgrade-detection loop never ran and the UI
silently never surfaced upgrades even when the gallery advertised newer
versions or digests.
Worker-side: NATS backend.list reply now carries Version, URI and Digest
for each installed backend (read from metadata.json).
Frontend-side: DistributedBackendManager.ListBackends aggregates per-node
refs (name, status, version, digest) instead of deduping, and CheckUpgrades
feeds that aggregation into gallery.CheckUpgradesAgainst — a new entrypoint
factored out of CheckBackendUpgrades so both paths share the same core
logic.
Cluster drift policy: when per-node version/digest tuples disagree, the
backend is flagged upgradeable regardless of whether any single node
matches the gallery, and UpgradeInfo.NodeDrift enumerates the outliers so
operators can see *why* it is out of sync. The next upgrade-all realigns
the cluster.
Tests cover: drift detection, unanimous-match (no upgrade), and the
empty-installed-version path that the old distributed code silently
missed.
* feat(ui): surface backend upgrades in the System page
The System page (Manage.jsx) only showed updates as a tiny inline arrow,
so operators routinely missed them. Port the Backend Gallery's upgrade UX
so System speaks the same visual language:
- Yellow banner at the top of the Backends tab when upgrades are pending,
with an "Upgrade all" button (serial fan-out, matches the gallery) and a
"Updates only" filter toggle.
- Warning pill (↑ N) next to the tab label so the count is glanceable even
when the banner is scrolled out of view.
- Per-row labeled "Upgrade to vX.Y" button (replaces the icon-only button
that silently flipped semantics between Reinstall and Upgrade), plus an
"Update available" badge in the new Version column.
- New columns: Version (with upgrade + drift chips), Nodes (per-node
attribution badges for distributed mode, degrading to a compact
"on N nodes · M offline" chip above three nodes), Installed (relative
time).
- System backends render a "Protected" chip instead of a bare "—" so rows
still align and the reason is obvious.
- Delete uses the softer btn-danger-ghost so rows don't scream red; the
ConfirmDialog still owns the "are you sure".
The upgrade checker also needed the same per-worker fix as the previous
commit: NewUpgradeChecker now takes a BackendManager getter so its
periodic runs call the distributed CheckUpgrades (which asks workers)
instead of the empty frontend filesystem. Without this the /api/backends/
upgrades endpoint stayed empty in distributed mode even with the protocol
change in place.
New CSS primitives — .upgrade-banner, .tab-pill, .badge-row, .cell-stack,
.cell-mono, .cell-muted, .row-actions, .btn-danger-ghost — all live in
App.css so other pages can adopt them without duplicating styles.
* feat(ui): polish the Nodes page so it reads like a product
The Nodes page was the biggest visual liability in distributed mode.
Rework the main dashboard surfaces in place without changing behavior:
StatCards: uniform height (96px min), left accent bar colored by the
metric's semantic (success/warning/error/primary), icon lives in a
36x36 soft-tinted chip top-right, value is left-aligned and large.
Grid auto-fills so the row doesn't collapse on narrow viewports. This
replaces the previous thin-bordered boxes with inconsistent heights.
Table rows: expandable rows now show a chevron cue on the left (rotates
on expand) so users know rows open. Status cell became a dedicated chip
with an LED-style halo dot instead of a bare bullet. Action buttons gained
labels — "Approve", "Resume", "Drain" — so the icons aren't doing all
the semantic work; the destructive remove action uses the softer
btn-danger-ghost variant so rows don't scream red, with the ConfirmDialog
still owning the real "are you sure". Applied cell-mono/cell-muted
utility classes so label chips and addresses share one spacing/font
grammar instead of re-declaring inline styles everywhere.
Expanded drawer: empty states for Loaded Models and Installed Backends
now render as a proper drawer-empty card (dashed border, icon, one-line
hint) instead of a plain muted string that read like broken formatting.
Tabs: three inline-styled buttons became the shared .tab class so they
inherit focus ring, hover state, and the rest of the design system —
matches the System page.
"Add more workers" toggle turned into a .nodes-add-worker dashed-border
button labelled "Register a new worker" (action voice) instead of a
chevron + muted link that operators kept mistaking for broken text.
New shared CSS primitives carry over to other pages:
.stat-grid + .stat-card, .row-chevron, .node-status, .drawer-empty,
.nodes-add-worker.
* feat(distributed): durable backend fan-out + state reconciliation
Two connected problems handled together:
1) Backend delete/install/upgrade used to silently skip non-healthy nodes,
so a delete during an outage left a zombie on the offline node once it
returned. The fan-out now records intent in a new pending_backend_ops
table before attempting the NATS round-trip. Currently-healthy nodes
get an immediate attempt; everyone else is queued. Unique index on
(node_id, backend, op) means reissuing the same operation refreshes
next_retry_at instead of stacking duplicates.
2) Loaded-model state could drift from reality: a worker OOM'd, got
killed, or restarted a backend process would leave a node_models row
claiming the model was still loaded, feeding ghost entries into the
/api/nodes/models listing and the router's scheduling decisions.
The existing ReplicaReconciler gains two new passes that run under a
fresh KeyStateReconciler advisory lock (non-blocking, so one wedged
frontend doesn't freeze the cluster):
- drainPendingBackendOps: retries queued ops whose next_retry_at has
passed on currently-healthy nodes. Success deletes the row; failure
bumps attempts and pushes next_retry_at out with exponential backoff
(30s → 15m cap). ErrNoResponders also marks the node unhealthy.
- probeLoadedModels: gRPC-HealthChecks addresses the DB thinks are
loaded but hasn't seen touched in the last probeStaleAfter (2m).
Unreachable addresses are removed from the registry. A pluggable
ModelProber lets tests substitute a fake without standing up gRPC.
DistributedBackendManager exposes DeleteBackendDetailed so the HTTP
handler can surface per-node outcomes ("2 succeeded, 1 queued") to the
UI in a follow-up commit; the existing DeleteBackend still returns
error-only for callers that don't care about node breakdown.
Multi-frontend safety: the state pass uses advisorylock.TryWithLockCtx
on a new key so N frontends coordinate — the same pattern the health
monitor and replica reconciler already rely on. Single-node mode runs
both passes inline (adapter is nil, state drain is a no-op).
Tests cover the upsert semantics, backoff math, the probe removing an
unreachable model but keeping a reachable one, and filtering by
probeStaleAfter.
* feat(ui): show cluster distribution of models in the System page
When a frontend restarted in distributed mode, models that workers had
already loaded weren't visible until the operator clicked into each node
manually — the /api/models/capabilities endpoint only knew about
configs on the frontend's filesystem, not the registry-backed truth.
/api/models/capabilities now joins in ListAllLoadedModels() when the
registry is active, returning loaded_on[] with node id/name/state/status
for each model. Models that live in the registry but lack a local config
(the actual ghosts, not recovered from the frontend's file cache) still
surface with source="registry-only" so operators can see and persist
them; without that emission they'd be invisible to this frontend.
Manage → Models replaces the old Running/Idle pill with a distribution
cell that lists the first three nodes the model is loaded on as chips
colored by state (green loaded, blue loading, amber anything else). On
wider clusters the remaining count collapses into a +N chip with a
title-attribute breakdown. Disabled / single-node behavior unchanged.
Adopted models get an extra "Adopted" ghost-icon chip with hover copy
explaining what it means and how to make it permanent.
Distributed mode also enables a 10s auto-refresh and a "Last synced Xs
ago" indicator next to the Update button so ghost rows drop off within
one reconcile tick after their owning process dies. Non-distributed
mode is untouched — no polling, no cell-stack, same old Running/Idle.
* feat(ui): NodeDistributionChip — shared per-node attribution component
Large clusters were going to break the Manage → Backends Nodes column:
the old inline logic rendered every node as a badge and would shred the
layout at >10 workers, plus the Manage → Models distribution cell had
copy-pasted its own slightly-different version.
NodeDistributionChip handles any cluster size with two render modes:
- small (≤3 nodes): inline chips of node names, colored by health.
- large: a single "on N nodes · M offline · K drift" summary chip;
clicking opens a Popover with a per-node table (name, status,
version, digest for backends; name, status, state for models).
Drift counting mirrors the backend's summarizeNodeDrift so the UI
number matches UpgradeInfo.NodeDrift. Digests are truncated to the
docker-style 12-char form with the full value preserved in the title.
Popover is a new general-purpose primitive: fixed positioning anchored
to the trigger, flips above when there's no room below, closes on
outside-click or Escape, returns focus to the trigger. Uses .card as
its surface so theming is inherited. Also useful for a future
labels-editor popup and the user menu.
Manage.jsx drops its duplicated inline Nodes-column + loaded_on cell
and uses the shared chip with context="backends" / "models"
respectively. Delete code removes ~40 lines of ad-hoc logic.
* feat(ui): shared FilterBar across the System page tabs
The Backends gallery had a nice search + chip + toggle strip; the System
page had nothing, so the two surfaces felt like different apps. Lift the
pattern into a reusable FilterBar and wire both System tabs through it.
New component core/http/react-ui/src/components/FilterBar.jsx renders a
search input, a role="tablist" chip row (aria-selected for a11y), and
optional toggles / right slot. Chips support an optional `count` which
the System page uses to show "User 3", "Updates 1" etc.
System Models tab: search by id or backend; chips for
All/Running/Idle/Disabled/Pinned plus a conditional Distributed chip in
distributed mode. "Last synced" + Update button live in the right slot.
System Backends tab: search by name/alias/meta-backend-for; chips for
All/User/System/Meta plus conditional Updates / Offline-nodes chips
when relevant. The old ad-hoc "Updates only" toggle from the upgrade
banner folded into the Updates chip — one source of truth for that
filter. Offline chip only appears in distributed mode when at least
one backend has an unhealthy node, so the chip row stays quiet on
healthy clusters.
Filter state persists in URL query params (mq/mf/bq/bf) so deep links
and tab switches keep the operator's filter context instead of
resetting every time.
Also adds an "Adopted" distribution path: when a model in
/api/models/capabilities carries source="registry-only" (discovered on
a worker but not configured locally), the Models tab shows a ghost chip
labelled "Adopted" with hover copy explaining how to persist it — this
is what closes the loop on the ghost-model story end-to-end.
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2865f0f8d3 |
feat(ux): backend management enhancement (#9325)
* feat: add PreferDevelopmentBackends setting, expose isMeta/isDevelopment in API - Add PreferDevelopmentBackends config field, CLI flag, runtime setting - Add IsDevelopment() method to GalleryBackend - Use AvailableBackendsUnfiltered in UI API to show all backends - Expose isMeta, isDevelopment, preferDevelopmentBackends in backend API response * feat: upgrade banner with Upgrade All button, detect pre-existing backends - Add upgrade banner on Backends page showing count and Upgrade All button - Fix upgrade detection for backends installed before version tracking: flag as upgradeable when gallery has a version but installed has none - Fix OCI digest check to flag backends with no stored digest as upgradeable |
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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 |
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5c35e85fe2 |
feat: allow to pin models and skip from reaping (#9309)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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8862e3ce60 |
feat: add node reconciler, allow to schedule to group of nodes, min/max autoscaler (#9186)
* always enable parallel requests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat: add node reconciler, allow to schedule to group of nodes, min/max autoscaler Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore: move tests to ginkgo Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(smart router): order by available vram Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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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> |
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2b12875302 |
fix: Add tracing settings loading from runtime_settings.json (#9081)
Tracing settings (EnableTracing and TracingMaxItems) were not being loaded from runtime_settings.json on startup, causing tracing settings configured via WebUI to be lost after service restart. This fix adds proper loading of tracing settings in loadRuntimeSettingsFromFile function in core/application/startup.go. Fixes #9072 Co-authored-by: localai-bot <localai-bot@localai.io> |
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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> |
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35d509d8e7 |
feat(ui): Per model backend logs and various fixes (#9028)
* feat(gallery): Switch to expandable box instead of pop-over and display model files Signed-off-by: Richard Palethorpe <io@richiejp.com> * feat(ui, backends): Add individual backend logging Signed-off-by: Richard Palethorpe <io@richiejp.com> * fix(ui): Set the context settings from the model config Signed-off-by: Richard Palethorpe <io@richiejp.com> --------- Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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e4c1c39727 |
fix(conf): Don't overwrite env provided galleries with runtime conf (#8994)
Signed-off-by: Richard Palethorpe <io@richiejp.com> |
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6c11c54a3b |
fix: avoid race condition
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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13bd0d9944 |
fix(collections): start agent pool after http server (#8981)
Otherwise if using collections with postgresql we create a deadlock, as we need embeddings to be up Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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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
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a026277ab9 |
feat(mlx-distributed): add new MLX-distributed backend (#8801)
* feat(mlx-distributed): add new MLX-distributed backend Add new MLX distributed backend with support for both TCP and RDMA for model sharding. This implementation ties in the discovery implementation already in place, and re-uses the same P2P mechanism for the TCP MLX-distributed inferencing. The Auto-parallel implementation is inspired by Exo's ones (who have been added to acknowledgement for the great work!) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * expose a CLI to facilitate backend starting Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat: make manual rank0 configurable via model configs Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add missing features from mlx backend Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Apply suggestion from @mudler Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Signed-off-by: Ettore Di Giacinto <mudler@users.noreply.github.com> |
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d200401e86 |
feat: Add --data-path CLI flag for persistent data separation (#8888)
feat: add --data-path CLI flag for persistent data separation - Add LOCALAI_DATA_PATH environment variable and --data-path CLI flag - Default data path: /data (separate from configuration directory) - Automatic migration on startup: moves agent_tasks.json, agent_jobs.json, collections/, and assets/ from old config dir to new data path - Backward compatible: preserves old behavior if LOCALAI_DATA_PATH is not set - Agent state and job directories now use DataPath with proper fallback chain - Update documentation with new flag and docker-compose example This separates mutable persistent data (collectiondb, agents, assets, skills) from configuration files, enabling better volume mounting and data persistence in containerized deployments. Signed-off-by: localai-bot <localai-bot@noreply.github.com> Co-authored-by: localai-bot <localai-bot@noreply.github.com> |
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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> |
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09ddaf94b2 |
feat(ui): move to React for frontend (#8772)
* feat(ui): move to React Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add import model Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * syntax highlight Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Minor fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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ecba23d44e |
fix: improve watchdown logics (#8591)
* fix: ensure proper watchdog shutdown and state passing between restarts Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix: add missing watchdog settings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix: untrack model if we shut it down successfully Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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c844b7ac58 |
feat: disable force eviction (#7725)
* feat: allow to set forcing backends eviction while requests are in flight Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat: try to make the request sit and retry if eviction couldn't be done Otherwise calls that in order to pass would need to shutdown other backends would just fail. In this way instead we make the request sit and retry eviction until it succeeds. The thresholds can be configured by the user. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * add tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * expose settings to CLI Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Update docs Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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c37785b78c |
chore(refactor): move logging to common package based on slog (#7668)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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f3c70a96ba |
chore(memory-reclaimer): use saner defaults
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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878c9d46d5 |
fix: improve ram estimation (#7603)
* fix: default to 10seconds of watchdog if runtime setting is malformed Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix: use gosigar for RAM estimation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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50f9c9a058 |
feat(watchdog): add Memory resource reclaimer (#7583)
* feat(watchdog): add GPU reclaimer Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Handle vram calculation for unified memory devices Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Support RAM eviction, set watchdog interval from runtime settings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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e1874cdb54 |
feat(ui): add mask to install custom backends (#7559)
* feat: allow to install backends from URL in the WebUI and API Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * trace backends installations Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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fc5b9ebfcc |
feat(loader): enhance single active backend to support LRU eviction (#7535)
* feat(loader): refactor single active backend support to LRU This changeset introduces LRU management of loaded backends. Users can set now a maximum number of models to be loaded concurrently, and, when setting LocalAI in single active backend mode we set LRU to 1 for backward compatibility. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore: add tests Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Update docs Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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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> |
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2dd42292dc |
feat(ui): runtime settings (#7320)
* feat(ui): add watchdog settings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Do not re-read env Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Some refactor, move other settings to runtime (p2p) Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Add API Keys handling Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Allow to disable runtime settings Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Documentation Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Small fixups Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * show MCP toggle in index Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Drop context default Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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735ca757fa |
feat(ui): allow to cancel ops (#7264)
* feat(ui): allow to cancel ops Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Improve progress text Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Cancel queued ops, don't show up message cancellation always Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix: fixup displaying of total progress over multiple files Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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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> |
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79a41a5e07 |
fix: register backends to model-loader during installation (#6159)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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9c7f92c81f |
feat(p2p): automatically sync installed models between instances (#6108)
* feat(p2p): sync models between federated nodes This change makes sure that between federated nodes all the models are synced with each other. Note: this works exclusively with models belonging to a gallery. It does not sync files between the nodes, but rather it synces the node setup. E.g. All the nodes needs to have configured the same galleries and install models without any local editing. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Make nodes stable Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * Fixups on syncing Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * ui: improve p2p view Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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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> |
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05757e2738 |
feat(backends install): allow to specify name and alias during manual installation (#5971)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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b3c2a3c257 |
fix: untangle pkg and core (#5896)
* migrate core/system to pkg/system - it has no dependencies FROM core, and IS USED in pkg Signed-off-by: Dave Lee <dave@gray101.com> * move pkg/templates up to core/templates -- nothing in pkg references it, but it does reference core. Signed-off-by: Dave Lee <dave@gray101.com> * remove extra check, len of nil is 0 Signed-off-by: Dave Lee <dave@gray101.com> * move pkg/startup to core/startup -- it does have important and unfixable dependencies on core Signed-off-by: Dave Lee <dave@gray101.com> --------- Signed-off-by: Dave Lee <dave@gray101.com> |
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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> |
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bb54f2da2b |
feat(gallery): automatically install missing backends along models (#5736)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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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> |
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2c9279a542 |
feat(video-gen): add endpoint for video generation (#5247)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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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> |
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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> |
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72e52c4f6a |
chore: drop embedded models (#4715)
Since the remote gallery was introduced this is now completely superseded by it. In order to keep the code clean and remove redudant parts let's simplify the usage. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> |
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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> |