mirror of
https://github.com/mudler/LocalAI.git
synced 2026-06-22 15:49:12 -04:00
* feat(ced): sketch sound-classification backend (CED audio tagger) Wires ced.cpp (CED, 527-class AudioSet sound-event tagger; baby cry, footsteps, glass, alarms, dog bark) into LocalAI as a Go/purego backend. SKETCH (backend skeleton real; core REST wiring + CI/gallery is a checklist in DESIGN.md): - backend/backend.proto: new SoundDetection rpc + SoundClass messages (run `make protogen-go` to regenerate pkg/grpc/proto). - backend/go/ced: main.go (purego dlopen libced.so + ced_capi.h), goced.go (Ced gRPC backend: Load + SoundDetection), Makefile (clone-at-pin CED_VERSION, ggml static-PIC shared build), run.sh, package.sh, .gitignore. - DESIGN.md: REST /v1/audio/classification wiring (handler/route/capability registration checklist), gallery/index + CI registration, and a scoping note for the realtime/websocket live-recognition path (sliding-window classify over the existing ws transport + voicegate; the ced C-API per-PCM entry point is already window-friendly). Backend code does not compile until protogen-go regenerates the pb types and a libced.so is built (Makefile clones+builds it). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): REST /v1/audio/classification endpoint + capability registration Wires the ced sound-event classification backend (AudioSet audio tagger) end to end through the REST surface, mirroring the transcription path. - Handler: core/http/endpoints/openai/sound_classification.go parses the multipart audio upload, temp-files it, resolves the model config and calls the SoundDetection RPC; returns {model, detections[]} JSON. - Backend wrapper: core/backend/sound_classification.go (ModelSoundDetection) loads the model and normalizes the proto response into schema types. - Schema: core/schema/sound_classification.go (SoundClassificationResult). - gRPC layer: SoundDetection wired through the LocalAI wrapper (interface, Backend client, Client, embed, server, base default) so the loader-typed client exposes the RPC; proto regenerated via make protogen-go. - Route: POST /v1/audio/classification (+ /audio/classification alias) with the audio/multipart default-model middleware in routes/openai.go. - Capability surfaces: swagger @Tags/@Router on the handler; FLAG_SOUND_ CLASSIFICATION usecase flag + UsecaseSoundClassification + UsecaseInfoMap + GuessUsecases + ModalityGroups + GetAllModelConfigUsecases; meta usecase option; /api/instructions audio area updated; auth RouteFeatureRegistry + FeatureAudioClassification (APIFeatures, default ON) + FeatureMetas; UI usecaseFilters, capabilities.js CAP_SOUND_CLASSIFICATION, Models.jsx filter + i18n; docs page features/audio-classification.md + whats-new + crosslink. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): realtime sound-event detection over the websocket API When a realtime pipeline configures a sound-classification model, each VAD-committed utterance (the same window the transcription path produces) is also run through the CED sound-event classifier and the scored AudioSet tags are emitted as a new server event. No new backend rpc is needed: the SoundDetection gRPC method already exists on this branch. - config: add Pipeline.SoundDetection (yaml/json sound_detection,omitempty) beside Transcription/VAD. - realtime: add Model.SoundDetection(ctx, audio, topK, threshold) to the ModelInterface; implement it on wrappedModel and transcriptOnlyModel by calling backend.ModelSoundDetection with the session's sound-classification model config (mirrors how Transcribe dispatches). Load the optional config in newModel / newTranscriptionOnlyModel; nil config keeps it additive. - types: add ConversationItemSoundDetectionEvent (item_id, content_index, detections[]{label,score,index}) with type conversation.item.sound_detection, its ServerEventType constant and MarshalJSON, mirroring the transcription completed event. - realtime: add emitSoundDetection (unary path: classify the committed window, build the event, t.SendEvent) and wire it at the utterance-commit hook right after emitTranscription; gated on session.SoundDetectionEnabled (resolved from Pipeline.SoundDetection at session setup, defaults top_k=5, threshold=0). Its error is logged via xlog but never aborts the turn. - test: Ginkgo specs for emitSoundDetection (tags emitted, empty detections, classifier error) plus a SoundDetection method on the fakeModel double. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(ced): implement SoundDetection in nodes backend test doubles The SoundDetection method added to the grpc backend interface left two test doubles (fakeBackendClient, fakeGRPCBackend) incomplete, so core/services/nodes failed to compile under `go vet`/`go test` (go build missed it: the doubles live in _test.go). Add the method to both, mirroring their existing Detect mock. Repairs CI for the nodes package. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): decouple realtime sound detection from VAD (sound-only sessions) Sound-event detection must activate on sounds, not speech, so it no longer runs through the voice VAD/transcription path. A sound-detection-only pipeline (sound_detection set, no transcription/LLM) now: - is accepted by prepareRealtimeConfig (sound_detection counts as a pipeline stage), - builds a lightweight model via newSoundDetectionOnlyModel (no VAD/STT/LLM/TTS loaded), and - defaults the session to turn_detection none (no VAD) with no transcription stage, so the client drives windowing via input_audio_buffer.commit (option A: client-side sliding window). The per-PCM C-API already supports arbitrary windows. commitUtterance gains a sound-only branch: it emits the conversation.item.sound_detection event (scored AudioSet tags) and stops - no transcription, no LLM response. generateResponse is now guarded on a transcription stage being present, so a sound-only turn never invokes the LLM. Existing transcription/VAD sessions are unchanged (additive). Added a commitUtterance sound-only Ginkgo spec asserting it emits the sound event and neither transcribes nor generates a response. go vet + golangci-lint (new-from-merge-base) clean; openai suite green. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): register sound-classification backend in gallery + CI Mechanical backend-image registration for the ced sound-event classifier, mirroring the parakeet-cpp Go/purego backend everywhere it is wired up. - .github/backend-matrix.yml: add the ced build matrix, field-for-field copies of the parakeet-cpp entries (cpu amd64/arm64, cublas cuda 12/13 amd64, l4t cuda-13 arm64, l4t-jetpack cuda-12 arm64, sycl f32/f16, vulkan amd64/arm64, rocm hipblas, and the metal darwin entry), changing only backend and tag-suffix. dockerfile stays ./backend/Dockerfile.golang. - backend/index.yaml: add the &ced meta anchor (capabilities map per platform) plus ced-development and the per-arch image entries, each uri/mirror tag-suffix matching the matrix exactly. The model gallery (GGUF) entry is intentionally deferred pending the HuggingFace publish (TODO note inline). - scripts/changed-backends.js: add an explicit item.backend === "ced" branch in inferBackendPath mapping to backend/go/ced/, same mechanism and ordering as the parakeet-cpp branch (before the generic golang fallthrough). - .github/workflows/bump_deps.yaml: register mudler/ced.cpp -> CED_VERSION in backend/go/ced/Makefile so the daily bot bumps the pin. - swagger/{docs.go,swagger.json,swagger.yaml}: regenerated via make swagger so the existing /v1/audio/classification annotations land in the generated spec. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): server-side windowing for realtime sound detection (option B) Adds an optional server-driven sliding-window classifier so a sound-only realtime client only has to stream audio (no input_audio_buffer.commit): - Pipeline.sound_detection_window_ms / sound_detection_hop_ms config knobs. When both > 0 on a sound-only session, the server classifies the last window of streamed audio every hop and emits a conversation.item.sound_ detection event; the input buffer is trimmed to one window so a long stream stays bounded. When unset, the session stays client-driven (option A). Runs independent of VAD (sound events are not speech). - handleSoundWindow (ticker) + classifySoundWindow (one tick, extracted so it is unit-testable) + writeWindowWAV, which declares the true InputSampleRate (NewWAVHeaderWithRate) so the classifier resamples correctly. Goroutine is started after toggleVAD and torn down with the session (close + wg.Wait). - Register pipeline.sound_detection (+window_ms/hop_ms) in the config meta registry; the earlier realtime commit added pipeline.sound_detection without a registry entry, failing TestAllFieldsHaveRegistryEntries. This fixes that and covers the two new knobs. Tests: classifySoundWindow emits an event + trims the buffer to one window, no-ops on too-little audio; writeWindowWAV declares the given sample rate. go build/vet + golangci-lint (new-from-merge-base) clean; config + openai suites green. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): add ced-base GGUF model gallery entries (f16 + q8_0) The ced-base weights are now published at mudler/ced-base-gguf (Apache-2.0, converted from mispeech/ced-base). Adds gallery/ced.yaml (backend: ced + known_usecases: sound_classification) and two gallery/index.yaml entries (ced-base-f16 default, ced-base-q8 smallest) with sha256-pinned files, and removes the now-resolved TODO from backend/index.yaml. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * feat(ced): add tiny/mini/small GGUF model gallery entries Publishes the rest of the CED family (same architecture, metadata-driven port verified end-to-end on ced-tiny) to mudler/ced-{tiny,mini,small}-gguf and adds their f16 + q8_0 gallery entries: ced-tiny (5.5M, edge/Pi-class) f16 11MB / q8_0 6MB ced-mini (9.6M) f16 19MB / q8_0 11MB ced-small (22M) f16 42MB / q8_0 23MB All sha256-pinned. ced-base remains the accuracy default. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(ced): point gallery entries at the consolidated mudler/ced-gguf repo All CED quantizations (tiny/mini/small/base, f16/q8_0) now live in a single HuggingFace repo, mudler/ced-gguf, instead of per-model repos. Repoint the 8 gallery model entries' urls + file uris accordingly. sha256 and filenames are unchanged. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(ced): bump CED_VERSION to the short-clip fix Pin the ced backend to ced.cpp 99c6ed3, which fixes a crash on any clip shorter than target_length (~10.11s): time_pos_embed was added at its full 63-frame grid instead of being sliced to the clip's actual time grid, tripping ggml_can_repeat in ggml_add. Surfaced by the live realtime e2e (sub-10s windows) and gated with a short-clip parity test upstream. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * docs(ced): list ced.cpp as a LocalAI-team engine + backend-guide directive - README.md: add ced.cpp to the "native C/C++/GGML engines developed and maintained by the LocalAI project" table. - docs/content/features/backends.md: add a Sound Classification backend category (sound-event classification / audio tagging) listing ced.cpp. - .agents/adding-backends.md: add a "Documenting the backend" section and two verification-checklist items requiring new backends to be documented in the backends.md category list, and in-house native engines to be added to the README maintained-engines table. This directive was missing. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * chore(ced): repin CED_VERSION to the v0.1.0 release commit ced.cpp history was squashed into a single release commit (tagged v0.1.0), so the previous pin (99c6ed3) no longer exists upstream. Pin to c04ac14, the v0.1.0 release commit, so the backend builds against a commit that exists. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> * fix(ced): silence gosec G304/G103 + govet unsafeptr on audited paths - sound_classification.go: os.Create(dst) where dst = temp dir + path.Base of the upload (no traversal). #nosec G304, matching the depth-anything-cpp handler. - goced.go: reading a NUL-terminated C string from a libced-owned buffer. #nosec G103 (gosec) + //nolint:govet (golangci-lint's unsafeptr check), since the uintptr is a C-owned malloc'd buffer, not Go-GC memory. Signed-off-by: Ettore Di Giacinto <mudler@localai.io> --------- Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
898 lines
22 KiB
Go
898 lines
22 KiB
Go
package grpc
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import (
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"context"
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"crypto/subtle"
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"errors"
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"fmt"
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"io"
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"log"
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"net"
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"os"
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"strings"
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pb "github.com/mudler/LocalAI/pkg/grpc/proto"
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"google.golang.org/grpc"
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"google.golang.org/grpc/codes"
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"google.golang.org/grpc/metadata"
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"google.golang.org/grpc/status"
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)
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// A GRPC Server that allows to run LLM inference.
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// It is used by the LLMServices to expose the LLM functionalities that are called by the client.
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// The GRPC Service is general, trying to encompass all the possible LLM options models.
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// It depends on the real implementer then what can be done or not.
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//
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// The server is implemented as a GRPC service, with the following methods:
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// - Predict: to run the inference with options
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// - PredictStream: to run the inference with options and stream the results
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// server is used to implement helloworld.GreeterServer.
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type server struct {
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pb.UnimplementedBackendServer
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llm AIModel
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}
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func (s *server) Health(ctx context.Context, in *pb.HealthMessage) (*pb.Reply, error) {
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return newReply("OK"), nil
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}
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func (s *server) Embedding(ctx context.Context, in *pb.PredictOptions) (*pb.EmbeddingResult, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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embeds, err := s.llm.Embeddings(in)
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if err != nil {
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return nil, err
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}
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return &pb.EmbeddingResult{Embeddings: embeds}, nil
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}
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func (s *server) LoadModel(ctx context.Context, in *pb.ModelOptions) (*pb.Result, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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err := s.llm.Load(in)
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if err != nil {
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return &pb.Result{Message: fmt.Sprintf("Error loading model: %s", err.Error()), Success: false}, err
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}
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return &pb.Result{Message: "Loading succeeded", Success: true}, nil
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}
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func (s *server) Predict(ctx context.Context, in *pb.PredictOptions) (*pb.Reply, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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if rich, ok := s.llm.(AIModelRich); ok {
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return rich.PredictRich(in)
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}
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result, err := s.llm.Predict(in)
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return newReply(result), err
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}
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func (s *server) GenerateImage(ctx context.Context, in *pb.GenerateImageRequest) (*pb.Result, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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err := s.llm.GenerateImage(in)
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if err != nil {
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return &pb.Result{Message: fmt.Sprintf("Error generating image: %s", err.Error()), Success: false}, err
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}
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return &pb.Result{Message: "Image generated", Success: true}, nil
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}
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func (s *server) GenerateVideo(ctx context.Context, in *pb.GenerateVideoRequest) (*pb.Result, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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err := s.llm.GenerateVideo(in)
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if err != nil {
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return &pb.Result{Message: fmt.Sprintf("Error generating video: %s", err.Error()), Success: false}, err
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}
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return &pb.Result{Message: "Video generated", Success: true}, nil
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}
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func (s *server) TTS(ctx context.Context, in *pb.TTSRequest) (*pb.Result, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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err := s.llm.TTS(in)
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if err != nil {
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return &pb.Result{Message: fmt.Sprintf("Error generating audio: %s", err.Error()), Success: false}, err
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}
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return &pb.Result{Message: "TTS audio generated", Success: true}, nil
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}
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func (s *server) TTSStream(in *pb.TTSRequest, stream pb.Backend_TTSStreamServer) error {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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audioChan := make(chan []byte)
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done := make(chan bool)
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go func() {
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for audioChunk := range audioChan {
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stream.Send(&pb.Reply{Audio: audioChunk})
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}
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done <- true
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}()
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err := s.llm.TTSStream(in, audioChan)
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<-done
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return err
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}
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func (s *server) SoundGeneration(ctx context.Context, in *pb.SoundGenerationRequest) (*pb.Result, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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err := s.llm.SoundGeneration(in)
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if err != nil {
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return &pb.Result{Message: fmt.Sprintf("Error generating audio: %s", err.Error()), Success: false}, err
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}
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return &pb.Result{Message: "Sound Generation audio generated", Success: true}, nil
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}
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func (s *server) Detect(ctx context.Context, in *pb.DetectOptions) (*pb.DetectResponse, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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res, err := s.llm.Detect(in)
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if err != nil {
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return nil, err
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}
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return &res, nil
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}
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func (s *server) Depth(ctx context.Context, in *pb.DepthRequest) (*pb.DepthResponse, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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res, err := s.llm.Depth(in)
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if err != nil {
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return nil, err
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}
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return &res, nil
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}
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func (s *server) FaceVerify(ctx context.Context, in *pb.FaceVerifyRequest) (*pb.FaceVerifyResponse, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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res, err := s.llm.FaceVerify(in)
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if err != nil {
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return nil, err
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}
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return &res, nil
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}
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func (s *server) FaceAnalyze(ctx context.Context, in *pb.FaceAnalyzeRequest) (*pb.FaceAnalyzeResponse, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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res, err := s.llm.FaceAnalyze(in)
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if err != nil {
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return nil, err
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}
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return &res, nil
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}
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func (s *server) VoiceVerify(ctx context.Context, in *pb.VoiceVerifyRequest) (*pb.VoiceVerifyResponse, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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res, err := s.llm.VoiceVerify(in)
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if err != nil {
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return nil, err
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}
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return &res, nil
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}
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func (s *server) VoiceAnalyze(ctx context.Context, in *pb.VoiceAnalyzeRequest) (*pb.VoiceAnalyzeResponse, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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res, err := s.llm.VoiceAnalyze(in)
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if err != nil {
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return nil, err
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}
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return &res, nil
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}
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func (s *server) VoiceEmbed(ctx context.Context, in *pb.VoiceEmbedRequest) (*pb.VoiceEmbedResponse, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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res, err := s.llm.VoiceEmbed(in)
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if err != nil {
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return nil, err
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}
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return &res, nil
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}
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func (s *server) AudioTranscription(ctx context.Context, in *pb.TranscriptRequest) (*pb.TranscriptResult, error) {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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result, err := s.llm.AudioTranscription(ctx, in)
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if err != nil {
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return nil, err
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}
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tresult := &pb.TranscriptResult{}
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for _, s := range result.Segments {
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tks := []int32{}
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for _, t := range s.Tokens {
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tks = append(tks, int32(t))
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}
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words := make([]*pb.TranscriptWord, 0, len(s.Words))
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for _, w := range s.Words {
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words = append(words, &pb.TranscriptWord{
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Start: int64(w.Start),
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End: int64(w.End),
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Text: w.Text,
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})
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}
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tresult.Segments = append(tresult.Segments,
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&pb.TranscriptSegment{
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Text: s.Text,
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Id: int32(s.Id),
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Start: int64(s.Start),
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End: int64(s.End),
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Tokens: tks,
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Speaker: s.Speaker,
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Words: words,
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})
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}
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tresult.Text = result.Text
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tresult.Language = result.Language
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tresult.Duration = result.Duration
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return tresult, nil
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}
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func (s *server) AudioTranscriptionStream(in *pb.TranscriptRequest, stream pb.Backend_AudioTranscriptionStreamServer) error {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
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}
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resultChan := make(chan *pb.TranscriptStreamResponse)
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done := make(chan bool)
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go func() {
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for chunk := range resultChan {
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stream.Send(chunk)
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}
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done <- true
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}()
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err := s.llm.AudioTranscriptionStream(stream.Context(), in, resultChan)
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<-done
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return err
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}
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func (s *server) PredictStream(in *pb.PredictOptions, stream pb.Backend_PredictStreamServer) error {
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if s.llm.Locking() {
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s.llm.Lock()
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defer s.llm.Unlock()
|
|
}
|
|
|
|
if rich, ok := s.llm.(AIModelRich); ok {
|
|
replyChan := make(chan *pb.Reply)
|
|
done := make(chan bool)
|
|
go func() {
|
|
for reply := range replyChan {
|
|
// Send errors here mean the client disconnected;
|
|
// drain the rest of the channel so the producer
|
|
// (PredictStreamRich) doesn't block on the next
|
|
// reply forever.
|
|
_ = stream.Send(reply)
|
|
}
|
|
done <- true
|
|
}()
|
|
// Server-side close: PredictStreamRich implementations send into
|
|
// the channel and return when finished; closing is the host's
|
|
// concern so impls don't have to remember `defer close(...)`.
|
|
err := rich.PredictStreamRich(in, replyChan)
|
|
close(replyChan)
|
|
<-done
|
|
return err
|
|
}
|
|
|
|
resultChan := make(chan string)
|
|
done := make(chan bool)
|
|
go func() {
|
|
for result := range resultChan {
|
|
stream.Send(newReply(result))
|
|
}
|
|
done <- true
|
|
}()
|
|
|
|
err := s.llm.PredictStream(in, resultChan)
|
|
<-done
|
|
|
|
return err
|
|
}
|
|
|
|
func (s *server) TokenizeString(ctx context.Context, in *pb.PredictOptions) (*pb.TokenizationResponse, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.TokenizeString(in)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
|
|
castTokens := make([]int32, len(res.Tokens))
|
|
for i, v := range res.Tokens {
|
|
castTokens[i] = int32(v)
|
|
}
|
|
|
|
return &pb.TokenizationResponse{
|
|
Length: int32(res.Length),
|
|
Tokens: castTokens,
|
|
}, err
|
|
}
|
|
|
|
func (s *server) Status(ctx context.Context, in *pb.HealthMessage) (*pb.StatusResponse, error) {
|
|
res, err := s.llm.Status()
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
|
|
return &res, nil
|
|
}
|
|
|
|
func (s *server) StoresSet(ctx context.Context, in *pb.StoresSetOptions) (*pb.Result, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
err := s.llm.StoresSet(in)
|
|
if err != nil {
|
|
return &pb.Result{Message: fmt.Sprintf("Error setting entry: %s", err.Error()), Success: false}, err
|
|
}
|
|
return &pb.Result{Message: "Set key", Success: true}, nil
|
|
}
|
|
|
|
func (s *server) StoresDelete(ctx context.Context, in *pb.StoresDeleteOptions) (*pb.Result, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
err := s.llm.StoresDelete(in)
|
|
if err != nil {
|
|
return &pb.Result{Message: fmt.Sprintf("Error deleting entry: %s", err.Error()), Success: false}, err
|
|
}
|
|
return &pb.Result{Message: "Deleted key", Success: true}, nil
|
|
}
|
|
|
|
func (s *server) StoresGet(ctx context.Context, in *pb.StoresGetOptions) (*pb.StoresGetResult, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.StoresGet(in)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return &res, nil
|
|
}
|
|
|
|
func (s *server) StoresFind(ctx context.Context, in *pb.StoresFindOptions) (*pb.StoresFindResult, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.StoresFind(in)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return &res, nil
|
|
}
|
|
|
|
func (s *server) VAD(ctx context.Context, in *pb.VADRequest) (*pb.VADResponse, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.VAD(in)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return &res, nil
|
|
}
|
|
|
|
func (s *server) Diarize(ctx context.Context, in *pb.DiarizeRequest) (*pb.DiarizeResponse, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.Diarize(in)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return &res, nil
|
|
}
|
|
|
|
func (s *server) SoundDetection(ctx context.Context, in *pb.SoundDetectionRequest) (*pb.SoundDetectionResponse, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
return s.llm.SoundDetection(ctx, in)
|
|
}
|
|
|
|
func (s *server) AudioEncode(ctx context.Context, in *pb.AudioEncodeRequest) (*pb.AudioEncodeResult, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.AudioEncode(in)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return res, nil
|
|
}
|
|
|
|
func (s *server) AudioDecode(ctx context.Context, in *pb.AudioDecodeRequest) (*pb.AudioDecodeResult, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.AudioDecode(in)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return res, nil
|
|
}
|
|
|
|
func (s *server) AudioTransform(ctx context.Context, in *pb.AudioTransformRequest) (*pb.AudioTransformResult, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.AudioTransform(in)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return res, nil
|
|
}
|
|
|
|
func (s *server) AudioTransformStream(stream pb.Backend_AudioTransformStreamServer) error {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
|
|
in := make(chan *pb.AudioTransformFrameRequest, 4)
|
|
out := make(chan *pb.AudioTransformFrameResponse, 4)
|
|
|
|
// Pump incoming frames from the gRPC stream into `in`. EOF closes the
|
|
// channel, which signals the backend that the client is done sending.
|
|
recvErrCh := make(chan error, 1)
|
|
go func() {
|
|
defer close(in)
|
|
for {
|
|
req, err := stream.Recv()
|
|
if err != nil {
|
|
if errors.Is(err, io.EOF) {
|
|
recvErrCh <- nil
|
|
return
|
|
}
|
|
recvErrCh <- err
|
|
return
|
|
}
|
|
select {
|
|
case in <- req:
|
|
case <-stream.Context().Done():
|
|
recvErrCh <- stream.Context().Err()
|
|
return
|
|
}
|
|
}
|
|
}()
|
|
|
|
// Pump outgoing frames from `out` to the gRPC stream. The backend closes
|
|
// `out` on completion.
|
|
sendDone := make(chan error, 1)
|
|
go func() {
|
|
for resp := range out {
|
|
if err := stream.Send(resp); err != nil {
|
|
sendDone <- err
|
|
// Drain `out` so the backend can finish.
|
|
for range out {
|
|
}
|
|
return
|
|
}
|
|
}
|
|
sendDone <- nil
|
|
}()
|
|
|
|
backendErr := s.llm.AudioTransformStream(in, out)
|
|
sendErr := <-sendDone
|
|
recvErr := <-recvErrCh
|
|
|
|
if backendErr != nil {
|
|
return backendErr
|
|
}
|
|
if sendErr != nil {
|
|
return sendErr
|
|
}
|
|
return recvErr
|
|
}
|
|
|
|
// AudioToAudioStream is the bidirectional any-to-any S2S handler. The
|
|
// shape mirrors AudioTransformStream exactly (recv → in chan, out chan →
|
|
// send) so backends can implement either via the same goroutine idiom.
|
|
func (s *server) AudioToAudioStream(stream pb.Backend_AudioToAudioStreamServer) error {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
|
|
in := make(chan *pb.AudioToAudioRequest, 8)
|
|
out := make(chan *pb.AudioToAudioResponse, 8)
|
|
|
|
recvErrCh := make(chan error, 1)
|
|
go func() {
|
|
defer close(in)
|
|
for {
|
|
req, err := stream.Recv()
|
|
if err != nil {
|
|
if errors.Is(err, io.EOF) {
|
|
recvErrCh <- nil
|
|
return
|
|
}
|
|
recvErrCh <- err
|
|
return
|
|
}
|
|
select {
|
|
case in <- req:
|
|
case <-stream.Context().Done():
|
|
recvErrCh <- stream.Context().Err()
|
|
return
|
|
}
|
|
}
|
|
}()
|
|
|
|
sendDone := make(chan error, 1)
|
|
go func() {
|
|
for resp := range out {
|
|
if err := stream.Send(resp); err != nil {
|
|
sendDone <- err
|
|
for range out {
|
|
}
|
|
return
|
|
}
|
|
}
|
|
sendDone <- nil
|
|
}()
|
|
|
|
backendErr := s.llm.AudioToAudioStream(in, out)
|
|
sendErr := <-sendDone
|
|
recvErr := <-recvErrCh
|
|
|
|
if backendErr != nil {
|
|
return backendErr
|
|
}
|
|
if sendErr != nil {
|
|
return sendErr
|
|
}
|
|
return recvErr
|
|
}
|
|
|
|
// Forward is the bidi-stream handler for the cloud-proxy backend's
|
|
// passthrough mode. Same recv→in / out→send goroutine idiom as
|
|
// AudioTransformStream / AudioToAudioStream above. Buffer size 8 to
|
|
// keep SSE token streams flowing — at 4, a half-RTT slow gRPC client
|
|
// makes the body-read goroutine in the backend block on out<- after
|
|
// every few token frames.
|
|
func (s *server) Forward(stream pb.Backend_ForwardServer) error {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
|
|
in := make(chan *pb.ForwardRequest, 8)
|
|
out := make(chan *pb.ForwardReply, 8)
|
|
|
|
recvErrCh := make(chan error, 1)
|
|
go func() {
|
|
defer close(in)
|
|
for {
|
|
req, err := stream.Recv()
|
|
if err != nil {
|
|
if errors.Is(err, io.EOF) {
|
|
recvErrCh <- nil
|
|
return
|
|
}
|
|
recvErrCh <- err
|
|
return
|
|
}
|
|
select {
|
|
case in <- req:
|
|
case <-stream.Context().Done():
|
|
recvErrCh <- stream.Context().Err()
|
|
return
|
|
}
|
|
}
|
|
}()
|
|
|
|
sendDone := make(chan error, 1)
|
|
go func() {
|
|
for resp := range out {
|
|
if err := stream.Send(resp); err != nil {
|
|
sendDone <- err
|
|
for range out {
|
|
}
|
|
return
|
|
}
|
|
}
|
|
sendDone <- nil
|
|
}()
|
|
|
|
backendErr := s.llm.Forward(stream.Context(), in, out)
|
|
sendErr := <-sendDone
|
|
recvErr := <-recvErrCh
|
|
|
|
if backendErr != nil {
|
|
return backendErr
|
|
}
|
|
if sendErr != nil {
|
|
return sendErr
|
|
}
|
|
return recvErr
|
|
}
|
|
|
|
func (s *server) StartFineTune(ctx context.Context, in *pb.FineTuneRequest) (*pb.FineTuneJobResult, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.StartFineTune(in)
|
|
if err != nil {
|
|
return &pb.FineTuneJobResult{Success: false, Message: fmt.Sprintf("Error starting fine-tune: %s", err.Error())}, err
|
|
}
|
|
return res, nil
|
|
}
|
|
|
|
func (s *server) FineTuneProgress(in *pb.FineTuneProgressRequest, stream pb.Backend_FineTuneProgressServer) error {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
updateChan := make(chan *pb.FineTuneProgressUpdate)
|
|
|
|
done := make(chan bool)
|
|
go func() {
|
|
for update := range updateChan {
|
|
stream.Send(update)
|
|
}
|
|
done <- true
|
|
}()
|
|
|
|
err := s.llm.FineTuneProgress(in, updateChan)
|
|
<-done
|
|
|
|
return err
|
|
}
|
|
|
|
func (s *server) StopFineTune(ctx context.Context, in *pb.FineTuneStopRequest) (*pb.Result, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
err := s.llm.StopFineTune(in)
|
|
if err != nil {
|
|
return &pb.Result{Message: fmt.Sprintf("Error stopping fine-tune: %s", err.Error()), Success: false}, err
|
|
}
|
|
return &pb.Result{Message: "Fine-tune stopped", Success: true}, nil
|
|
}
|
|
|
|
func (s *server) ListCheckpoints(ctx context.Context, in *pb.ListCheckpointsRequest) (*pb.ListCheckpointsResponse, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.ListCheckpoints(in)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return res, nil
|
|
}
|
|
|
|
func (s *server) ExportModel(ctx context.Context, in *pb.ExportModelRequest) (*pb.Result, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
err := s.llm.ExportModel(in)
|
|
if err != nil {
|
|
return &pb.Result{Message: fmt.Sprintf("Error exporting model: %s", err.Error()), Success: false}, err
|
|
}
|
|
return &pb.Result{Message: "Model exported", Success: true}, nil
|
|
}
|
|
|
|
func (s *server) StartQuantization(ctx context.Context, in *pb.QuantizationRequest) (*pb.QuantizationJobResult, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.StartQuantization(in)
|
|
if err != nil {
|
|
return &pb.QuantizationJobResult{Success: false, Message: fmt.Sprintf("Error starting quantization: %s", err.Error())}, err
|
|
}
|
|
return res, nil
|
|
}
|
|
|
|
func (s *server) QuantizationProgress(in *pb.QuantizationProgressRequest, stream pb.Backend_QuantizationProgressServer) error {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
updateChan := make(chan *pb.QuantizationProgressUpdate)
|
|
|
|
done := make(chan bool)
|
|
go func() {
|
|
for update := range updateChan {
|
|
stream.Send(update)
|
|
}
|
|
done <- true
|
|
}()
|
|
|
|
err := s.llm.QuantizationProgress(in, updateChan)
|
|
<-done
|
|
|
|
return err
|
|
}
|
|
|
|
func (s *server) StopQuantization(ctx context.Context, in *pb.QuantizationStopRequest) (*pb.Result, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
err := s.llm.StopQuantization(in)
|
|
if err != nil {
|
|
return &pb.Result{Message: fmt.Sprintf("Error stopping quantization: %s", err.Error()), Success: false}, err
|
|
}
|
|
return &pb.Result{Message: "Quantization stopped", Success: true}, nil
|
|
}
|
|
|
|
func (s *server) ModelMetadata(ctx context.Context, in *pb.ModelOptions) (*pb.ModelMetadataResponse, error) {
|
|
if s.llm.Locking() {
|
|
s.llm.Lock()
|
|
defer s.llm.Unlock()
|
|
}
|
|
res, err := s.llm.ModelMetadata(in)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
return res, nil
|
|
}
|
|
|
|
func (s *server) Free(ctx context.Context, in *pb.HealthMessage) (*pb.Result, error) {
|
|
if err := s.llm.Free(); err != nil {
|
|
return &pb.Result{Success: false, Message: err.Error()}, nil
|
|
}
|
|
return &pb.Result{Success: true}, nil
|
|
}
|
|
|
|
// NewBackendServer creates a pb.BackendServer.
|
|
func NewBackendServer(model AIModel) pb.BackendServer {
|
|
return &server{llm: model}
|
|
}
|
|
|
|
// AuthTokenEnvVar is the environment variable used to configure gRPC bearer token auth.
|
|
const AuthTokenEnvVar = "LOCALAI_GRPC_AUTH_TOKEN"
|
|
|
|
// validateToken extracts the bearer token from gRPC metadata and validates it.
|
|
func validateToken(ctx context.Context, expected string) error {
|
|
md, ok := metadata.FromIncomingContext(ctx)
|
|
if !ok {
|
|
return status.Error(codes.Unauthenticated, "missing metadata")
|
|
}
|
|
values := md.Get("authorization")
|
|
if len(values) == 0 {
|
|
return status.Error(codes.Unauthenticated, "missing authorization header")
|
|
}
|
|
raw := values[0]
|
|
if !strings.HasPrefix(raw, "Bearer ") {
|
|
return status.Error(codes.Unauthenticated, "authorization must use Bearer scheme")
|
|
}
|
|
token := strings.TrimPrefix(raw, "Bearer ")
|
|
if subtle.ConstantTimeCompare([]byte(token), []byte(expected)) != 1 {
|
|
return status.Error(codes.Unauthenticated, "invalid token")
|
|
}
|
|
return nil
|
|
}
|
|
|
|
func tokenUnaryInterceptor(token string) grpc.UnaryServerInterceptor {
|
|
return func(ctx context.Context, req any, info *grpc.UnaryServerInfo, handler grpc.UnaryHandler) (any, error) {
|
|
if err := validateToken(ctx, token); err != nil {
|
|
return nil, err
|
|
}
|
|
return handler(ctx, req)
|
|
}
|
|
}
|
|
|
|
func tokenStreamInterceptor(token string) grpc.StreamServerInterceptor {
|
|
return func(srv any, ss grpc.ServerStream, info *grpc.StreamServerInfo, handler grpc.StreamHandler) error {
|
|
if err := validateToken(ss.Context(), token); err != nil {
|
|
return err
|
|
}
|
|
return handler(srv, ss)
|
|
}
|
|
}
|
|
|
|
// serverOpts returns the common gRPC server options, including auth interceptors
|
|
// when LOCALAI_GRPC_AUTH_TOKEN is set.
|
|
func serverOpts() []grpc.ServerOption {
|
|
opts := []grpc.ServerOption{
|
|
grpc.MaxRecvMsgSize(maxGRPCMessageSize),
|
|
grpc.MaxSendMsgSize(maxGRPCMessageSize),
|
|
}
|
|
if token := os.Getenv(AuthTokenEnvVar); token != "" {
|
|
opts = append(opts,
|
|
grpc.UnaryInterceptor(tokenUnaryInterceptor(token)),
|
|
grpc.StreamInterceptor(tokenStreamInterceptor(token)),
|
|
)
|
|
log.Printf("gRPC auth enabled via %s", AuthTokenEnvVar)
|
|
}
|
|
return opts
|
|
}
|
|
|
|
func StartServer(address string, model AIModel) error {
|
|
lis, err := net.Listen("tcp", address)
|
|
if err != nil {
|
|
return err
|
|
}
|
|
s := grpc.NewServer(serverOpts()...)
|
|
pb.RegisterBackendServer(s, &server{llm: model})
|
|
log.Printf("gRPC Server listening at %v", lis.Addr())
|
|
if err := s.Serve(lis); err != nil {
|
|
return err
|
|
}
|
|
|
|
return nil
|
|
}
|
|
|
|
func RunServer(address string, model AIModel) (func() error, error) {
|
|
lis, err := net.Listen("tcp", address)
|
|
if err != nil {
|
|
return nil, err
|
|
}
|
|
s := grpc.NewServer(serverOpts()...)
|
|
pb.RegisterBackendServer(s, &server{llm: model})
|
|
log.Printf("gRPC Server listening at %v", lis.Addr())
|
|
if err = s.Serve(lis); err != nil {
|
|
return func() error {
|
|
return lis.Close()
|
|
}, err
|
|
}
|
|
|
|
return func() error {
|
|
s.GracefulStop()
|
|
return nil
|
|
}, nil
|
|
}
|