mirror of
https://github.com/mudler/LocalAI.git
synced 2026-04-29 03:24:49 -04:00
* 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
307 lines
10 KiB
Go
307 lines
10 KiB
Go
package application
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import (
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"context"
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"math/rand/v2"
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"sync"
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"sync/atomic"
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"time"
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corebackend "github.com/mudler/LocalAI/core/backend"
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"github.com/mudler/LocalAI/core/config"
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mcpTools "github.com/mudler/LocalAI/core/http/endpoints/mcp"
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"github.com/mudler/LocalAI/core/services/agentpool"
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"github.com/mudler/LocalAI/core/services/facerecognition"
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"github.com/mudler/LocalAI/core/services/galleryop"
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"github.com/mudler/LocalAI/core/services/nodes"
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"github.com/mudler/LocalAI/core/services/voicerecognition"
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"github.com/mudler/LocalAI/core/templates"
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pkggrpc "github.com/mudler/LocalAI/pkg/grpc"
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"github.com/mudler/LocalAI/pkg/model"
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"github.com/mudler/xlog"
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"gorm.io/gorm"
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)
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// faceEmbeddingDim is the expected dimension for face embeddings.
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// Set to 0 so the Registry accepts whatever dim the loaded recognizer
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// produces — ArcFace R50 is 512-d, MBF is 512-d, SFace is 128-d, and
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// the insightface backend can load any of them via LoadModel options.
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// Locking this to a specific value would force a single recognizer
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// family per deployment; we keep the door open instead.
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const faceEmbeddingDim = 0
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// voiceEmbeddingDim is the expected dimension for speaker embeddings.
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// 0 so the Registry accepts whatever dim the loaded recognizer
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// produces — ECAPA-TDNN is 192, WeSpeaker ResNet34 is 256, 3D-Speaker
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// ERes2Net is 192, CAM++ is 512.
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const voiceEmbeddingDim = 0
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type Application struct {
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backendLoader *config.ModelConfigLoader
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modelLoader *model.ModelLoader
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applicationConfig *config.ApplicationConfig
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startupConfig *config.ApplicationConfig // Stores original config from env vars (before file loading)
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templatesEvaluator *templates.Evaluator
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galleryService *galleryop.GalleryService
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agentJobService *agentpool.AgentJobService
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agentPoolService atomic.Pointer[agentpool.AgentPoolService]
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faceRegistry facerecognition.Registry
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voiceRegistry voicerecognition.Registry
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authDB *gorm.DB
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watchdogMutex sync.Mutex
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watchdogStop chan bool
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p2pMutex sync.Mutex
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p2pCtx context.Context
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p2pCancel context.CancelFunc
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agentJobMutex sync.Mutex
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// Distributed mode services (nil when not in distributed mode)
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distributed *DistributedServices
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// Upgrade checker (background service for detecting backend upgrades)
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upgradeChecker *UpgradeChecker
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}
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func newApplication(appConfig *config.ApplicationConfig) *Application {
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ml := model.NewModelLoader(appConfig.SystemState)
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// Close MCP sessions when a model is unloaded (watchdog eviction, manual shutdown, etc.)
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ml.OnModelUnload(func(modelName string) {
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mcpTools.CloseMCPSessions(modelName)
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})
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app := &Application{
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backendLoader: config.NewModelConfigLoader(appConfig.SystemState.Model.ModelsPath),
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modelLoader: ml,
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applicationConfig: appConfig,
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templatesEvaluator: templates.NewEvaluator(appConfig.SystemState.Model.ModelsPath),
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}
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// Face-recognition registry backed by LocalAI's built-in vector store.
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// The resolver closes over the ModelLoader so the Registry stays
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// decoupled from loader plumbing; swapping in a postgres-backed
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// implementation later is a single construction change here.
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//
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// `faceStoreName` is the default namespace passed to StoreBackend when
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// the request doesn't override it. Face and voice MUST use distinct
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// namespaces — the local-store gRPC surface rejects mixed dimensions
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// inside one namespace ("Try to add key with length N when existing
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// length is M"). ArcFace buffalo_l produces 512-dim embeddings while
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// ECAPA-TDNN produces 192-dim; enrolling one after the other into a
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// shared namespace is exactly how we hit that error.
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const (
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faceStoreName = "localai-face-biometrics"
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voiceStoreName = "localai-voice-biometrics"
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)
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faceStoreResolver := func(_ context.Context, storeName string) (pkggrpc.Backend, error) {
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return corebackend.StoreBackend(ml, appConfig, storeName, "")
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}
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app.faceRegistry = facerecognition.NewStoreRegistry(faceStoreResolver, faceStoreName, faceEmbeddingDim)
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// Voice (speaker) recognition registry — same plumbing, separate
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// namespace so embedding spaces stay isolated (a face vector and a
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// speaker vector are not comparable and differ in dimensionality).
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voiceStoreResolver := func(_ context.Context, storeName string) (pkggrpc.Backend, error) {
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return corebackend.StoreBackend(ml, appConfig, storeName, "")
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}
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app.voiceRegistry = voicerecognition.NewStoreRegistry(voiceStoreResolver, voiceStoreName, voiceEmbeddingDim)
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return app
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}
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func (a *Application) ModelConfigLoader() *config.ModelConfigLoader {
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return a.backendLoader
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}
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func (a *Application) ModelLoader() *model.ModelLoader {
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return a.modelLoader
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}
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func (a *Application) ApplicationConfig() *config.ApplicationConfig {
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return a.applicationConfig
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}
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func (a *Application) TemplatesEvaluator() *templates.Evaluator {
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return a.templatesEvaluator
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}
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func (a *Application) GalleryService() *galleryop.GalleryService {
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return a.galleryService
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}
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func (a *Application) AgentJobService() *agentpool.AgentJobService {
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return a.agentJobService
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}
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func (a *Application) UpgradeChecker() *UpgradeChecker {
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return a.upgradeChecker
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}
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// distributedDB returns the PostgreSQL database for distributed coordination,
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// or nil in standalone mode.
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func (a *Application) distributedDB() *gorm.DB {
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if a.distributed != nil {
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return a.authDB
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}
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return nil
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}
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func (a *Application) AgentPoolService() *agentpool.AgentPoolService {
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return a.agentPoolService.Load()
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}
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// FaceRegistry returns the face-recognition registry used for 1:N
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// identification. The current implementation is backed by the
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// in-memory local-store backend; see core/services/facerecognition
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// for the interface and the postgres TODO.
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func (a *Application) FaceRegistry() facerecognition.Registry {
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return a.faceRegistry
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}
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// VoiceRegistry returns the voice (speaker) recognition registry used
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// for 1:N identification. Same in-memory local-store backing as
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// FaceRegistry but a separate instance — voice embeddings live in
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// their own vector space.
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func (a *Application) VoiceRegistry() voicerecognition.Registry {
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return a.voiceRegistry
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}
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// AuthDB returns the auth database connection, or nil if auth is not enabled.
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func (a *Application) AuthDB() *gorm.DB {
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return a.authDB
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}
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// StartupConfig returns the original startup configuration (from env vars, before file loading)
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func (a *Application) StartupConfig() *config.ApplicationConfig {
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return a.startupConfig
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}
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// Distributed returns the distributed services, or nil if not in distributed mode.
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func (a *Application) Distributed() *DistributedServices {
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return a.distributed
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}
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// IsDistributed returns true if the application is running in distributed mode.
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func (a *Application) IsDistributed() bool {
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return a.distributed != nil
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}
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// waitForHealthyWorker blocks until at least one healthy backend worker is registered.
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// This prevents the agent pool from failing during startup when workers haven't connected yet.
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func (a *Application) waitForHealthyWorker() {
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maxWait := a.applicationConfig.Distributed.WorkerWaitTimeoutOrDefault()
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const basePoll = 2 * time.Second
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xlog.Info("Waiting for at least one healthy backend worker before starting agent pool")
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deadline := time.Now().Add(maxWait)
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for time.Now().Before(deadline) {
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registered, err := a.distributed.Registry.List(context.Background())
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if err == nil {
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for _, n := range registered {
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if n.NodeType == nodes.NodeTypeBackend && n.Status == nodes.StatusHealthy {
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xlog.Info("Healthy backend worker found", "node", n.Name)
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return
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}
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}
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}
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// Add 0-1s jitter to prevent thundering-herd on the node registry
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jitter := time.Duration(rand.Int64N(int64(time.Second)))
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select {
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case <-a.applicationConfig.Context.Done():
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return
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case <-time.After(basePoll + jitter):
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}
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}
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xlog.Warn("No healthy backend worker found after waiting, proceeding anyway")
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}
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// InstanceID returns the unique identifier for this frontend instance.
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func (a *Application) InstanceID() string {
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return a.applicationConfig.Distributed.InstanceID
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}
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func (a *Application) start() error {
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galleryService := galleryop.NewGalleryService(a.ApplicationConfig(), a.ModelLoader())
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err := galleryService.Start(a.ApplicationConfig().Context, a.ModelConfigLoader(), a.ApplicationConfig().SystemState)
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if err != nil {
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return err
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}
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a.galleryService = galleryService
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// Initialize agent job service (Start() is deferred to after distributed wiring)
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agentJobService := agentpool.NewAgentJobService(
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a.ApplicationConfig(),
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a.ModelLoader(),
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a.ModelConfigLoader(),
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a.TemplatesEvaluator(),
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)
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a.agentJobService = agentJobService
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return nil
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}
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// StartAgentPool initializes and starts the agent pool service (LocalAGI integration).
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// This must be called after the HTTP server is listening, because backends like
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// PostgreSQL need to call the embeddings API during collection initialization.
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func (a *Application) StartAgentPool() {
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if !a.applicationConfig.AgentPool.Enabled {
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return
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}
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// Build options struct from available dependencies
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opts := agentpool.AgentPoolOptions{
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AuthDB: a.authDB,
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}
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if d := a.Distributed(); d != nil {
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if d.DistStores != nil && d.DistStores.Skills != nil {
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opts.SkillStore = d.DistStores.Skills
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}
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opts.NATSClient = d.Nats
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opts.EventBridge = d.AgentBridge
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opts.AgentStore = d.AgentStore
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}
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aps, err := agentpool.NewAgentPoolService(a.applicationConfig, opts)
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if err != nil {
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xlog.Error("Failed to create agent pool service", "error", err)
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return
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}
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// Wire distributed mode components
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if d := a.Distributed(); d != nil {
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// Wait for at least one healthy backend worker before starting the agent pool.
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// Collections initialization calls embeddings which require a worker.
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if d.Registry != nil {
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a.waitForHealthyWorker()
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}
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}
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if err := aps.Start(a.applicationConfig.Context); err != nil {
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xlog.Error("Failed to start agent pool", "error", err)
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return
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}
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// Wire per-user scoped services so collections, skills, and jobs are isolated per user
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usm := agentpool.NewUserServicesManager(
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aps.UserStorage(),
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a.applicationConfig,
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a.modelLoader,
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a.backendLoader,
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a.templatesEvaluator,
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)
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// Wire distributed backends to per-user job services
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if a.agentJobService != nil {
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if d := a.agentJobService.Dispatcher(); d != nil {
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usm.SetJobDispatcher(d)
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}
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if s := a.agentJobService.DBStore(); s != nil {
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usm.SetJobDBStore(s)
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}
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}
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aps.SetUserServicesManager(usm)
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a.agentPoolService.Store(aps)
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}
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