feat: backends improvements (#778)

.github/workflows/test.yml

@@ -29,6 +29,7 @@ jobs:
           
           sudo apt-get install -y ca-certificates cmake curl patch
           sudo apt-get install -y libopencv-dev && sudo ln -s /usr/include/opencv4/opencv2 /usr/include/opencv2
+          sudo pip install -r extra/requirements.txt
 
           sudo mkdir /build && sudo chmod -R 777 /build && cd /build && \
           curl -L "https://github.com/gabime/spdlog/archive/refs/tags/v1.11.0.tar.gz" | \
@@ -45,7 +46,6 @@ jobs:
           sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /lib64/ && \
           sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/lib/. /usr/lib/ && \
           sudo cp -rfv /build/lib/Linux-$(uname -m)/piper_phonemize/include/. /usr/include/
-    
       - name: Test
         run: |
           ESPEAK_DATA="/build/lib/Linux-$(uname -m)/piper_phonemize/lib/espeak-ng-data" GO_TAGS="tts stablediffusion" make test

.gitignore

@@ -3,9 +3,10 @@ go-llama
 /gpt4all
 go-stable-diffusion
 go-piper
+/go-bert
 go-ggllm
 /piper
-
+__pycache__/
 *.a
 get-sources
 

Dockerfile

@@ -11,10 +11,15 @@ ARG TARGETARCH
 ARG TARGETVARIANT
 
 ENV BUILD_TYPE=${BUILD_TYPE}
+ENV EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/build/extra/grpc/huggingface/huggingface.py"
 ARG GO_TAGS="stablediffusion tts"
 
 RUN apt-get update && \
-    apt-get install -y ca-certificates cmake curl patch
+    apt-get install -y ca-certificates cmake curl patch pip
+
+# Extras requirements
+COPY extra/requirements.txt /build/extra/requirements.txt
+RUN pip install -r /build/extra/requirements.txt && rm -rf /build/extra/requirements.txt
 
 # CuBLAS requirements
 RUN if [ "${BUILD_TYPE}" = "cublas" ]; then \

Makefile

@@ -310,7 +310,7 @@ test: prepare test-models/testmodel grpcs
 	@echo 'Running tests'
 	export GO_TAGS="tts stablediffusion"
 	$(MAKE) prepare-test
-	TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
+	HUGGINGFACE_GRPC=$(abspath ./)/extra/grpc/huggingface/huggingface.py TEST_DIR=$(abspath ./)/test-dir/ FIXTURES=$(abspath ./)/tests/fixtures CONFIG_FILE=$(abspath ./)/test-models/config.yaml MODELS_PATH=$(abspath ./)/test-models \
 	$(GOCMD) run github.com/onsi/ginkgo/v2/ginkgo --label-filter="!gpt4all && !llama" --flake-attempts 5 -v -r ./api ./pkg
 	$(MAKE) test-gpt4all
 	$(MAKE) test-llama
@@ -335,9 +335,7 @@ test-stablediffusion: prepare-test
 
 test-container:
 	docker build --target requirements -t local-ai-test-container .
-	docker run --name localai-tests -e GO_TAGS=$(GO_TAGS) -ti -v $(abspath ./):/build local-ai-test-container make test
+	docker run -ti --rm --entrypoint /bin/bash -ti -v $(abspath ./):/build local-ai-test-container
-	docker rm localai-tests
-	docker rmi local-ai-test-container
 
 ## Help:
 help: ## Show this help.
@@ -351,10 +349,15 @@ help: ## Show this help.
 		else if (/^## .*$$/) {printf "  ${CYAN}%s${RESET}\n", substr($$1,4)} \
 		}' $(MAKEFILE_LIST)
 
-protogen:
+protogen: protogen-go protogen-python
+
+protogen-go:
 	protoc --go_out=. --go_opt=paths=source_relative --go-grpc_out=. --go-grpc_opt=paths=source_relative \
     pkg/grpc/proto/backend.proto
 
+protogen-python:
+	python -m grpc_tools.protoc -Ipkg/grpc/proto/ --python_out=extra/grpc/huggingface/ --grpc_python_out=extra/grpc/huggingface/ pkg/grpc/proto/backend.proto
+
 ## GRPC
 
 backend-assets/grpc:

api/api_test.go

@@ -125,6 +125,11 @@ var _ = Describe("API test", func() {
 	var cancel context.CancelFunc
 	var tmpdir string
 
+	commonOpts := []options.AppOption{
+		options.WithDebug(true),
+		options.WithDisableMessage(true),
+	}
+
 	Context("API with ephemeral models", func() {
 		BeforeEach(func() {
 			var err error
@@ -143,7 +148,7 @@ var _ = Describe("API test", func() {
 					Name:            "bert2",
 					URL:             "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
 					Overrides:       map[string]interface{}{"foo": "bar"},
-					AdditionalFiles: []gallery.File{gallery.File{Filename: "foo.yaml", URI: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"}},
+					AdditionalFiles: []gallery.File{{Filename: "foo.yaml", URI: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"}},
 				},
 			}
 			out, err := yaml.Marshal(g)
@@ -159,9 +164,10 @@ var _ = Describe("API test", func() {
 			}
 
 			app, err = App(
+				append(commonOpts,
 					options.WithContext(c),
 					options.WithGalleries(galleries),
-				options.WithModelLoader(modelLoader), options.WithBackendAssets(backendAssets), options.WithBackendAssetsOutput(tmpdir))
+					options.WithModelLoader(modelLoader), options.WithBackendAssets(backendAssets), options.WithBackendAssetsOutput(tmpdir))...)
 			Expect(err).ToNot(HaveOccurred())
 			go app.Listen("127.0.0.1:9090")
 
@@ -400,13 +406,14 @@ var _ = Describe("API test", func() {
 			}
 
 			app, err = App(
+				append(commonOpts,
 					options.WithContext(c),
 					options.WithAudioDir(tmpdir),
 					options.WithImageDir(tmpdir),
 					options.WithGalleries(galleries),
 					options.WithModelLoader(modelLoader),
 					options.WithBackendAssets(backendAssets),
-				options.WithBackendAssetsOutput(tmpdir),
+					options.WithBackendAssetsOutput(tmpdir))...,
 			)
 			Expect(err).ToNot(HaveOccurred())
 			go app.Listen("127.0.0.1:9090")
@@ -500,7 +507,12 @@ var _ = Describe("API test", func() {
 			c, cancel = context.WithCancel(context.Background())
 
 			var err error
-			app, err = App(options.WithContext(c), options.WithModelLoader(modelLoader))
+			app, err = App(
+				append(commonOpts,
+					options.WithExternalBackend("huggingface", os.Getenv("HUGGINGFACE_GRPC")),
+					options.WithContext(c),
+					options.WithModelLoader(modelLoader),
+				)...)
 			Expect(err).ToNot(HaveOccurred())
 			go app.Listen("127.0.0.1:9090")
 
@@ -524,7 +536,7 @@ var _ = Describe("API test", func() {
 		It("returns the models list", func() {
 			models, err := client.ListModels(context.TODO())
 			Expect(err).ToNot(HaveOccurred())
-			Expect(len(models.Models)).To(Equal(10))
+			Expect(len(models.Models)).To(Equal(11))
 		})
 		It("can generate completions", func() {
 			resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", Prompt: "abcdedfghikl"})
@@ -555,7 +567,7 @@ var _ = Describe("API test", func() {
 		})
 
 		It("returns errors", func() {
-			backends := len(model.AutoLoadBackends)
+			backends := len(model.AutoLoadBackends) + 1 // +1 for huggingface
 			_, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "foomodel", Prompt: "abcdedfghikl"})
 			Expect(err).To(HaveOccurred())
 			Expect(err.Error()).To(ContainSubstring(fmt.Sprintf("error, status code: 500, message: could not load model - all backends returned error: %d errors occurred:", backends)))
@@ -602,6 +614,36 @@ var _ = Describe("API test", func() {
 			Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
 		})
 
+		Context("External gRPC calls", func() {
+			It("calculate embeddings with huggingface", func() {
+				if runtime.GOOS != "linux" {
+					Skip("test supported only on linux")
+				}
+				resp, err := client.CreateEmbeddings(
+					context.Background(),
+					openai.EmbeddingRequest{
+						Model: openai.AdaCodeSearchCode,
+						Input: []string{"sun", "cat"},
+					},
+				)
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
+				Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
+
+				sunEmbedding := resp.Data[0].Embedding
+				resp2, err := client.CreateEmbeddings(
+					context.Background(),
+					openai.EmbeddingRequest{
+						Model: openai.AdaCodeSearchCode,
+						Input: []string{"sun"},
+					},
+				)
+				Expect(err).ToNot(HaveOccurred())
+				Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
+				Expect(resp2.Data[0].Embedding).ToNot(Equal(resp.Data[1].Embedding))
+			})
+		})
+
 		Context("backends", func() {
 			It("runs rwkv completion", func() {
 				if runtime.GOOS != "linux" {
@@ -674,7 +716,12 @@ var _ = Describe("API test", func() {
 			c, cancel = context.WithCancel(context.Background())
 
 			var err error
-			app, err = App(options.WithContext(c), options.WithModelLoader(modelLoader), options.WithConfigFile(os.Getenv("CONFIG_FILE")))
+			app, err = App(
+				append(commonOpts,
+					options.WithContext(c),
+					options.WithModelLoader(modelLoader),
+					options.WithConfigFile(os.Getenv("CONFIG_FILE")))...,
+			)
 			Expect(err).ToNot(HaveOccurred())
 			go app.Listen("127.0.0.1:9090")
 
@@ -696,7 +743,7 @@ var _ = Describe("API test", func() {
 		It("can generate chat completions from config file", func() {
 			models, err := client.ListModels(context.TODO())
 			Expect(err).ToNot(HaveOccurred())
-			Expect(len(models.Models)).To(Equal(12))
+			Expect(len(models.Models)).To(Equal(13))
 		})
 		It("can generate chat completions from config file", func() {
 			resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "abcdedfghikl"}}})

api/backend/embeddings.go

@@ -30,6 +30,10 @@ func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.
 		model.WithContext(o.Context),
 	}
 
+	for k, v := range o.ExternalGRPCBackends {
+		opts = append(opts, model.WithExternalBackend(k, v))
+	}
+
 	if c.Backend == "" {
 		inferenceModel, err = loader.GreedyLoader(opts...)
 	} else {

api/backend/image.go

@@ -15,12 +15,20 @@ func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negat
 		return nil, fmt.Errorf("endpoint only working with stablediffusion models")
 	}
 
-	inferenceModel, err := loader.BackendLoader(
+	opts := []model.Option{
 		model.WithBackendString(c.Backend),
 		model.WithAssetDir(o.AssetsDestination),
 		model.WithThreads(uint32(c.Threads)),
 		model.WithContext(o.Context),
 		model.WithModelFile(c.ImageGenerationAssets),
+	}
+
+	for k, v := range o.ExternalGRPCBackends {
+		opts = append(opts, model.WithExternalBackend(k, v))
+	}
+
+	inferenceModel, err := loader.BackendLoader(
+		opts...,
 	)
 	if err != nil {
 		return nil, err

api/backend/llm.go

@@ -1,14 +1,17 @@
 package backend
 
 import (
+	"os"
 	"regexp"
 	"strings"
 	"sync"
 
 	config "github.com/go-skynet/LocalAI/api/config"
 	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/pkg/gallery"
 	"github.com/go-skynet/LocalAI/pkg/grpc"
 	model "github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/go-skynet/LocalAI/pkg/utils"
 )
 
 func ModelInference(s string, loader *model.ModelLoader, c config.Config, o *options.Option, tokenCallback func(string) bool) (func() (string, error), error) {
@@ -27,12 +30,32 @@ func ModelInference(s string, loader *model.ModelLoader, c config.Config, o *opt
 		model.WithContext(o.Context),
 	}
 
+	for k, v := range o.ExternalGRPCBackends {
+		opts = append(opts, model.WithExternalBackend(k, v))
+	}
+
+	if c.Backend != "" {
+		opts = append(opts, model.WithBackendString(c.Backend))
+	}
+
+	// Check if the modelFile exists, if it doesn't try to load it from the gallery
+	if o.AutoloadGalleries { // experimental
+		if _, err := os.Stat(modelFile); os.IsNotExist(err) {
+			utils.ResetDownloadTimers()
+			// if we failed to load the model, we try to download it
+			err := gallery.InstallModelFromGalleryByName(o.Galleries, modelFile, loader.ModelPath, gallery.GalleryModel{}, utils.DisplayDownloadFunction)
+			if err != nil {
+				return nil, err
+			}
+		}
+	}
+
 	if c.Backend == "" {
 		inferenceModel, err = loader.GreedyLoader(opts...)
 	} else {
-		opts = append(opts, model.WithBackendString(c.Backend))
 		inferenceModel, err = loader.BackendLoader(opts...)
 	}
+
 	if err != nil {
 		return nil, err
 	}
@@ -50,6 +73,9 @@ func ModelInference(s string, loader *model.ModelLoader, c config.Config, o *opt
 			return ss, err
 		} else {
 			reply, err := inferenceModel.Predict(o.Context, opts)
+			if err != nil {
+				return "", err
+			}
 			return reply.Message, err
 		}
 	}

api/backend/transcript.go

@@ -0,0 +1,42 @@
+package backend
+
+import (
+	"context"
+	"fmt"
+
+	config "github.com/go-skynet/LocalAI/api/config"
+
+	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
+	"github.com/go-skynet/LocalAI/pkg/grpc/whisper/api"
+	model "github.com/go-skynet/LocalAI/pkg/model"
+)
+
+func ModelTranscription(audio, language string, loader *model.ModelLoader, c config.Config, o *options.Option) (*api.Result, error) {
+	opts := []model.Option{
+		model.WithBackendString(model.WhisperBackend),
+		model.WithModelFile(c.Model),
+		model.WithContext(o.Context),
+		model.WithThreads(uint32(c.Threads)),
+		model.WithAssetDir(o.AssetsDestination),
+	}
+
+	for k, v := range o.ExternalGRPCBackends {
+		opts = append(opts, model.WithExternalBackend(k, v))
+	}
+
+	whisperModel, err := o.Loader.BackendLoader(opts...)
+	if err != nil {
+		return nil, err
+	}
+
+	if whisperModel == nil {
+		return nil, fmt.Errorf("could not load whisper model")
+	}
+
+	return whisperModel.AudioTranscription(context.Background(), &proto.TranscriptRequest{
+		Dst:      audio,
+		Language: language,
+		Threads:  uint32(c.Threads),
+	})
+}

api/backend/tts.go

@@ -0,0 +1,72 @@
+package backend
+
+import (
+	"context"
+	"fmt"
+	"os"
+	"path/filepath"
+
+	"github.com/go-skynet/LocalAI/api/options"
+	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
+	model "github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/go-skynet/LocalAI/pkg/utils"
+)
+
+func generateUniqueFileName(dir, baseName, ext string) string {
+	counter := 1
+	fileName := baseName + ext
+
+	for {
+		filePath := filepath.Join(dir, fileName)
+		_, err := os.Stat(filePath)
+		if os.IsNotExist(err) {
+			return fileName
+		}
+
+		counter++
+		fileName = fmt.Sprintf("%s_%d%s", baseName, counter, ext)
+	}
+}
+
+func ModelTTS(text, modelFile string, loader *model.ModelLoader, o *options.Option) (string, *proto.Result, error) {
+	opts := []model.Option{
+		model.WithBackendString(model.PiperBackend),
+		model.WithModelFile(modelFile),
+		model.WithContext(o.Context),
+		model.WithAssetDir(o.AssetsDestination),
+	}
+
+	for k, v := range o.ExternalGRPCBackends {
+		opts = append(opts, model.WithExternalBackend(k, v))
+	}
+
+	piperModel, err := o.Loader.BackendLoader(opts...)
+	if err != nil {
+		return "", nil, err
+	}
+
+	if piperModel == nil {
+		return "", nil, fmt.Errorf("could not load piper model")
+	}
+
+	if err := os.MkdirAll(o.AudioDir, 0755); err != nil {
+		return "", nil, fmt.Errorf("failed creating audio directory: %s", err)
+	}
+
+	fileName := generateUniqueFileName(o.AudioDir, "piper", ".wav")
+	filePath := filepath.Join(o.AudioDir, fileName)
+
+	modelPath := filepath.Join(o.Loader.ModelPath, modelFile)
+
+	if err := utils.VerifyPath(modelPath, o.Loader.ModelPath); err != nil {
+		return "", nil, err
+	}
+
+	res, err := piperModel.TTS(context.Background(), &proto.TTSRequest{
+		Text:  text,
+		Model: modelPath,
+		Dst:   filePath,
+	})
+
+	return filePath, res, err
+}

api/localai/gallery.go

@@ -4,13 +4,15 @@ import (
 	"context"
 	"fmt"
 	"os"
+	"strings"
 	"sync"
-	"time"
 
 	json "github.com/json-iterator/go"
 
 	config "github.com/go-skynet/LocalAI/api/config"
 	"github.com/go-skynet/LocalAI/pkg/gallery"
+	"github.com/go-skynet/LocalAI/pkg/utils"
+
 	"github.com/gofiber/fiber/v2"
 	"github.com/google/uuid"
 	"github.com/rs/zerolog/log"
@@ -80,6 +82,8 @@ func (g *galleryApplier) Start(c context.Context, cm *config.ConfigLoader) {
 			case <-c.Done():
 				return
 			case op := <-g.C:
+				utils.ResetDownloadTimers()
+
 				g.updateStatus(op.id, &galleryOpStatus{Message: "processing", Progress: 0})
 
 				// updates the status with an error
@@ -90,13 +94,17 @@ func (g *galleryApplier) Start(c context.Context, cm *config.ConfigLoader) {
 				// displayDownload displays the download progress
 				progressCallback := func(fileName string, current string, total string, percentage float64) {
 					g.updateStatus(op.id, &galleryOpStatus{Message: "processing", Progress: percentage, TotalFileSize: total, DownloadedFileSize: current})
-					displayDownload(fileName, current, total, percentage)
+					utils.DisplayDownloadFunction(fileName, current, total, percentage)
 				}
 
 				var err error
 				// if the request contains a gallery name, we apply the gallery from the gallery list
 				if op.galleryName != "" {
+					if strings.Contains(op.galleryName, "@") {
 						err = gallery.InstallModelFromGallery(op.galleries, op.galleryName, g.modelPath, op.req, progressCallback)
+					} else {
+						err = gallery.InstallModelFromGalleryByName(op.galleries, op.galleryName, g.modelPath, op.req, progressCallback)
+					}
 				} else {
 					err = prepareModel(g.modelPath, op.req, cm, progressCallback)
 				}
@@ -119,31 +127,6 @@ func (g *galleryApplier) Start(c context.Context, cm *config.ConfigLoader) {
 	}()
 }
 
-var lastProgress time.Time = time.Now()
-var startTime time.Time = time.Now()
-
-func displayDownload(fileName string, current string, total string, percentage float64) {
-	currentTime := time.Now()
-
-	if currentTime.Sub(lastProgress) >= 5*time.Second {
-
-		lastProgress = currentTime
-
-		// calculate ETA based on percentage and elapsed time
-		var eta time.Duration
-		if percentage > 0 {
-			elapsed := currentTime.Sub(startTime)
-			eta = time.Duration(float64(elapsed)*(100/percentage) - float64(elapsed))
-		}
-
-		if total != "" {
-			log.Debug().Msgf("Downloading %s: %s/%s (%.2f%%) ETA: %s", fileName, current, total, percentage, eta)
-		} else {
-			log.Debug().Msgf("Downloading: %s", current)
-		}
-	}
-}
-
 type galleryModel struct {
 	gallery.GalleryModel
 	ID string `json:"id"`
@@ -165,10 +148,11 @@ func ApplyGalleryFromString(modelPath, s string, cm *config.ConfigLoader, galler
 	}
 
 	for _, r := range requests {
+		utils.ResetDownloadTimers()
 		if r.ID == "" {
-			err = prepareModel(modelPath, r.GalleryModel, cm, displayDownload)
+			err = prepareModel(modelPath, r.GalleryModel, cm, utils.DisplayDownloadFunction)
 		} else {
-			err = gallery.InstallModelFromGallery(galleries, r.ID, modelPath, r.GalleryModel, displayDownload)
+			err = gallery.InstallModelFromGallery(galleries, r.ID, modelPath, r.GalleryModel, utils.DisplayDownloadFunction)
 		}
 	}
 

api/localai/localai.go

@@ -1,17 +1,10 @@
 package localai
 
 import (
-	"context"
+	"github.com/go-skynet/LocalAI/api/backend"
-	"fmt"
-	"os"
-	"path/filepath"
-
 	config "github.com/go-skynet/LocalAI/api/config"
 
 	"github.com/go-skynet/LocalAI/api/options"
-	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
-	model "github.com/go-skynet/LocalAI/pkg/model"
-	"github.com/go-skynet/LocalAI/pkg/utils"
 	"github.com/gofiber/fiber/v2"
 )
 
@@ -20,22 +13,6 @@ type TTSRequest struct {
 	Input string `json:"input" yaml:"input"`
 }
 
-func generateUniqueFileName(dir, baseName, ext string) string {
-	counter := 1
-	fileName := baseName + ext
-
-	for {
-		filePath := filepath.Join(dir, fileName)
-		_, err := os.Stat(filePath)
-		if os.IsNotExist(err) {
-			return fileName
-		}
-
-		counter++
-		fileName = fmt.Sprintf("%s_%d%s", baseName, counter, ext)
-	}
-}
-
 func TTSEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
 	return func(c *fiber.Ctx) error {
 
@@ -45,40 +22,10 @@ func TTSEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx)
 			return err
 		}
 
-		piperModel, err := o.Loader.BackendLoader(
+		filePath, _, err := backend.ModelTTS(input.Input, input.Model, o.Loader, o)
-			model.WithBackendString(model.PiperBackend),
-			model.WithModelFile(input.Model),
-			model.WithContext(o.Context),
-			model.WithAssetDir(o.AssetsDestination))
 		if err != nil {
 			return err
 		}
-
-		if piperModel == nil {
-			return fmt.Errorf("could not load piper model")
-		}
-
-		if err := os.MkdirAll(o.AudioDir, 0755); err != nil {
-			return fmt.Errorf("failed creating audio directory: %s", err)
-		}
-
-		fileName := generateUniqueFileName(o.AudioDir, "piper", ".wav")
-		filePath := filepath.Join(o.AudioDir, fileName)
-
-		modelPath := filepath.Join(o.Loader.ModelPath, input.Model)
-
-		if err := utils.VerifyPath(modelPath, o.Loader.ModelPath); err != nil {
-			return err
-		}
-
-		if _, err := piperModel.TTS(context.Background(), &proto.TTSRequest{
-			Text:  input.Input,
-			Model: modelPath,
-			Dst:   filePath,
-		}); err != nil {
-			return err
-		}
-
 		return c.Download(filePath)
 	}
 }

api/openai/transcription.go

@@ -1,7 +1,6 @@
 package openai
 
 import (
-	"context"
 	"fmt"
 	"io"
 	"net/http"
@@ -9,10 +8,9 @@ import (
 	"path"
 	"path/filepath"
 
+	"github.com/go-skynet/LocalAI/api/backend"
 	config "github.com/go-skynet/LocalAI/api/config"
 	"github.com/go-skynet/LocalAI/api/options"
-	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
-	model "github.com/go-skynet/LocalAI/pkg/model"
 
 	"github.com/gofiber/fiber/v2"
 	"github.com/rs/zerolog/log"
@@ -61,25 +59,7 @@ func TranscriptEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fibe
 
 		log.Debug().Msgf("Audio file copied to: %+v", dst)
 
-		whisperModel, err := o.Loader.BackendLoader(
+		tr, err := backend.ModelTranscription(dst, input.Language, o.Loader, *config, o)
-			model.WithBackendString(model.WhisperBackend),
-			model.WithModelFile(config.Model),
-			model.WithContext(o.Context),
-			model.WithThreads(uint32(config.Threads)),
-			model.WithAssetDir(o.AssetsDestination))
-		if err != nil {
-			return err
-		}
-
-		if whisperModel == nil {
-			return fmt.Errorf("could not load whisper model")
-		}
-
-		tr, err := whisperModel.AudioTranscription(context.Background(), &proto.TranscriptRequest{
-			Dst:      dst,
-			Language: input.Language,
-			Threads:  uint32(config.Threads),
-		})
 		if err != nil {
 			return err
 		}

api/options/options.go

@@ -28,6 +28,10 @@ type Option struct {
 
 	BackendAssets     embed.FS
 	AssetsDestination string
+
+	ExternalGRPCBackends map[string]string
+
+	AutoloadGalleries bool
 }
 
 type AppOption func(*Option)
@@ -53,6 +57,19 @@ func WithCors(b bool) AppOption {
 	}
 }
 
+var EnableGalleriesAutoload = func(o *Option) {
+	o.AutoloadGalleries = true
+}
+
+func WithExternalBackend(name string, uri string) AppOption {
+	return func(o *Option) {
+		if o.ExternalGRPCBackends == nil {
+			o.ExternalGRPCBackends = make(map[string]string)
+		}
+		o.ExternalGRPCBackends[name] = uri
+	}
+}
+
 func WithCorsAllowOrigins(b string) AppOption {
 	return func(o *Option) {
 		o.CORSAllowOrigins = b

extra/grpc/huggingface/backend_pb2.py

@@ -0,0 +1,49 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: backend.proto
+"""Generated protocol buffer code."""
+from google.protobuf import descriptor as _descriptor
+from google.protobuf import descriptor_pool as _descriptor_pool
+from google.protobuf import symbol_database as _symbol_database
+from google.protobuf.internal import builder as _builder
+# @@protoc_insertion_point(imports)
+
+_sym_db = _symbol_database.Default()
+
+
+
+
+DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\rbackend.proto\x12\x07\x62\x61\x63kend\"\x0f\n\rHealthMessage\"\xa4\x05\n\x0ePredictOptions\x12\x0e\n\x06Prompt\x18\x01 \x01(\t\x12\x0c\n\x04Seed\x18\x02 \x01(\x05\x12\x0f\n\x07Threads\x18\x03 \x01(\x05\x12\x0e\n\x06Tokens\x18\x04 \x01(\x05\x12\x0c\n\x04TopK\x18\x05 \x01(\x05\x12\x0e\n\x06Repeat\x18\x06 \x01(\x05\x12\r\n\x05\x42\x61tch\x18\x07 \x01(\x05\x12\r\n\x05NKeep\x18\x08 \x01(\x05\x12\x13\n\x0bTemperature\x18\t \x01(\x02\x12\x0f\n\x07Penalty\x18\n \x01(\x02\x12\r\n\x05\x46\x31\x36KV\x18\x0b \x01(\x08\x12\x11\n\tDebugMode\x18\x0c \x01(\x08\x12\x13\n\x0bStopPrompts\x18\r \x03(\t\x12\x11\n\tIgnoreEOS\x18\x0e \x01(\x08\x12\x19\n\x11TailFreeSamplingZ\x18\x0f \x01(\x02\x12\x10\n\x08TypicalP\x18\x10 \x01(\x02\x12\x18\n\x10\x46requencyPenalty\x18\x11 \x01(\x02\x12\x17\n\x0fPresencePenalty\x18\x12 \x01(\x02\x12\x10\n\x08Mirostat\x18\x13 \x01(\x05\x12\x13\n\x0bMirostatETA\x18\x14 \x01(\x02\x12\x13\n\x0bMirostatTAU\x18\x15 \x01(\x02\x12\x12\n\nPenalizeNL\x18\x16 \x01(\x08\x12\x11\n\tLogitBias\x18\x17 \x01(\t\x12\r\n\x05MLock\x18\x19 \x01(\x08\x12\x0c\n\x04MMap\x18\x1a \x01(\x08\x12\x16\n\x0ePromptCacheAll\x18\x1b \x01(\x08\x12\x15\n\rPromptCacheRO\x18\x1c \x01(\x08\x12\x0f\n\x07Grammar\x18\x1d \x01(\t\x12\x0f\n\x07MainGPU\x18\x1e \x01(\t\x12\x13\n\x0bTensorSplit\x18\x1f \x01(\t\x12\x0c\n\x04TopP\x18  \x01(\x02\x12\x17\n\x0fPromptCachePath\x18! \x01(\t\x12\r\n\x05\x44\x65\x62ug\x18\" \x01(\x08\x12\x17\n\x0f\x45mbeddingTokens\x18# \x03(\x05\x12\x12\n\nEmbeddings\x18$ \x01(\t\"\x18\n\x05Reply\x12\x0f\n\x07message\x18\x01 \x01(\t\"\xac\x02\n\x0cModelOptions\x12\r\n\x05Model\x18\x01 \x01(\t\x12\x13\n\x0b\x43ontextSize\x18\x02 \x01(\x05\x12\x0c\n\x04Seed\x18\x03 \x01(\x05\x12\x0e\n\x06NBatch\x18\x04 \x01(\x05\x12\x11\n\tF16Memory\x18\x05 \x01(\x08\x12\r\n\x05MLock\x18\x06 \x01(\x08\x12\x0c\n\x04MMap\x18\x07 \x01(\x08\x12\x11\n\tVocabOnly\x18\x08 \x01(\x08\x12\x0f\n\x07LowVRAM\x18\t \x01(\x08\x12\x12\n\nEmbeddings\x18\n \x01(\x08\x12\x0c\n\x04NUMA\x18\x0b \x01(\x08\x12\x12\n\nNGPULayers\x18\x0c \x01(\x05\x12\x0f\n\x07MainGPU\x18\r \x01(\t\x12\x13\n\x0bTensorSplit\x18\x0e \x01(\t\x12\x0f\n\x07Threads\x18\x0f \x01(\x05\x12\x19\n\x11LibrarySearchPath\x18\x10 \x01(\t\"*\n\x06Result\x12\x0f\n\x07message\x18\x01 \x01(\t\x12\x0f\n\x07success\x18\x02 \x01(\x08\"%\n\x0f\x45mbeddingResult\x12\x12\n\nembeddings\x18\x01 \x03(\x02\"C\n\x11TranscriptRequest\x12\x0b\n\x03\x64st\x18\x02 \x01(\t\x12\x10\n\x08language\x18\x03 \x01(\t\x12\x0f\n\x07threads\x18\x04 \x01(\r\"N\n\x10TranscriptResult\x12,\n\x08segments\x18\x01 \x03(\x0b\x32\x1a.backend.TranscriptSegment\x12\x0c\n\x04text\x18\x02 \x01(\t\"Y\n\x11TranscriptSegment\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05start\x18\x02 \x01(\x03\x12\x0b\n\x03\x65nd\x18\x03 \x01(\x03\x12\x0c\n\x04text\x18\x04 \x01(\t\x12\x0e\n\x06tokens\x18\x05 \x03(\x05\"\x9e\x01\n\x14GenerateImageRequest\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x0c\n\x04mode\x18\x03 \x01(\x05\x12\x0c\n\x04step\x18\x04 \x01(\x05\x12\x0c\n\x04seed\x18\x05 \x01(\x05\x12\x17\n\x0fpositive_prompt\x18\x06 \x01(\t\x12\x17\n\x0fnegative_prompt\x18\x07 \x01(\t\x12\x0b\n\x03\x64st\x18\x08 \x01(\t\"6\n\nTTSRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\r\n\x05model\x18\x02 \x01(\t\x12\x0b\n\x03\x64st\x18\x03 \x01(\t2\xeb\x03\n\x07\x42\x61\x63kend\x12\x32\n\x06Health\x12\x16.backend.HealthMessage\x1a\x0e.backend.Reply\"\x00\x12\x34\n\x07Predict\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x12\x35\n\tLoadModel\x12\x15.backend.ModelOptions\x1a\x0f.backend.Result\"\x00\x12<\n\rPredictStream\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x30\x01\x12@\n\tEmbedding\x12\x17.backend.PredictOptions\x1a\x18.backend.EmbeddingResult\"\x00\x12\x41\n\rGenerateImage\x12\x1d.backend.GenerateImageRequest\x1a\x0f.backend.Result\"\x00\x12M\n\x12\x41udioTranscription\x12\x1a.backend.TranscriptRequest\x1a\x19.backend.TranscriptResult\"\x00\x12-\n\x03TTS\x12\x13.backend.TTSRequest\x1a\x0f.backend.Result\"\x00\x42Z\n\x19io.skynet.localai.backendB\x0eLocalAIBackendP\x01Z+github.com/go-skynet/LocalAI/pkg/grpc/protob\x06proto3')
+
+_globals = globals()
+_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
+_builder.BuildTopDescriptorsAndMessages(DESCRIPTOR, 'backend_pb2', _globals)
+if _descriptor._USE_C_DESCRIPTORS == False:
+
+  DESCRIPTOR._options = None
+  DESCRIPTOR._serialized_options = b'\n\031io.skynet.localai.backendB\016LocalAIBackendP\001Z+github.com/go-skynet/LocalAI/pkg/grpc/proto'
+  _globals['_HEALTHMESSAGE']._serialized_start=26
+  _globals['_HEALTHMESSAGE']._serialized_end=41
+  _globals['_PREDICTOPTIONS']._serialized_start=44
+  _globals['_PREDICTOPTIONS']._serialized_end=720
+  _globals['_REPLY']._serialized_start=722
+  _globals['_REPLY']._serialized_end=746
+  _globals['_MODELOPTIONS']._serialized_start=749
+  _globals['_MODELOPTIONS']._serialized_end=1049
+  _globals['_RESULT']._serialized_start=1051
+  _globals['_RESULT']._serialized_end=1093
+  _globals['_EMBEDDINGRESULT']._serialized_start=1095
+  _globals['_EMBEDDINGRESULT']._serialized_end=1132
+  _globals['_TRANSCRIPTREQUEST']._serialized_start=1134
+  _globals['_TRANSCRIPTREQUEST']._serialized_end=1201
+  _globals['_TRANSCRIPTRESULT']._serialized_start=1203
+  _globals['_TRANSCRIPTRESULT']._serialized_end=1281
+  _globals['_TRANSCRIPTSEGMENT']._serialized_start=1283
+  _globals['_TRANSCRIPTSEGMENT']._serialized_end=1372
+  _globals['_GENERATEIMAGEREQUEST']._serialized_start=1375
+  _globals['_GENERATEIMAGEREQUEST']._serialized_end=1533
+  _globals['_TTSREQUEST']._serialized_start=1535
+  _globals['_TTSREQUEST']._serialized_end=1589
+  _globals['_BACKEND']._serialized_start=1592
+  _globals['_BACKEND']._serialized_end=2083
+# @@protoc_insertion_point(module_scope)

extra/grpc/huggingface/backend_pb2_grpc.py

@@ -0,0 +1,297 @@
+# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
+"""Client and server classes corresponding to protobuf-defined services."""
+import grpc
+
+import backend_pb2 as backend__pb2
+
+
+class BackendStub(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def __init__(self, channel):
+        """Constructor.
+
+        Args:
+            channel: A grpc.Channel.
+        """
+        self.Health = channel.unary_unary(
+                '/backend.Backend/Health',
+                request_serializer=backend__pb2.HealthMessage.SerializeToString,
+                response_deserializer=backend__pb2.Reply.FromString,
+                )
+        self.Predict = channel.unary_unary(
+                '/backend.Backend/Predict',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.Reply.FromString,
+                )
+        self.LoadModel = channel.unary_unary(
+                '/backend.Backend/LoadModel',
+                request_serializer=backend__pb2.ModelOptions.SerializeToString,
+                response_deserializer=backend__pb2.Result.FromString,
+                )
+        self.PredictStream = channel.unary_stream(
+                '/backend.Backend/PredictStream',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.Reply.FromString,
+                )
+        self.Embedding = channel.unary_unary(
+                '/backend.Backend/Embedding',
+                request_serializer=backend__pb2.PredictOptions.SerializeToString,
+                response_deserializer=backend__pb2.EmbeddingResult.FromString,
+                )
+        self.GenerateImage = channel.unary_unary(
+                '/backend.Backend/GenerateImage',
+                request_serializer=backend__pb2.GenerateImageRequest.SerializeToString,
+                response_deserializer=backend__pb2.Result.FromString,
+                )
+        self.AudioTranscription = channel.unary_unary(
+                '/backend.Backend/AudioTranscription',
+                request_serializer=backend__pb2.TranscriptRequest.SerializeToString,
+                response_deserializer=backend__pb2.TranscriptResult.FromString,
+                )
+        self.TTS = channel.unary_unary(
+                '/backend.Backend/TTS',
+                request_serializer=backend__pb2.TTSRequest.SerializeToString,
+                response_deserializer=backend__pb2.Result.FromString,
+                )
+
+
+class BackendServicer(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def Health(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def Predict(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def LoadModel(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def PredictStream(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def Embedding(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def GenerateImage(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def AudioTranscription(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def TTS(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+
+def add_BackendServicer_to_server(servicer, server):
+    rpc_method_handlers = {
+            'Health': grpc.unary_unary_rpc_method_handler(
+                    servicer.Health,
+                    request_deserializer=backend__pb2.HealthMessage.FromString,
+                    response_serializer=backend__pb2.Reply.SerializeToString,
+            ),
+            'Predict': grpc.unary_unary_rpc_method_handler(
+                    servicer.Predict,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.Reply.SerializeToString,
+            ),
+            'LoadModel': grpc.unary_unary_rpc_method_handler(
+                    servicer.LoadModel,
+                    request_deserializer=backend__pb2.ModelOptions.FromString,
+                    response_serializer=backend__pb2.Result.SerializeToString,
+            ),
+            'PredictStream': grpc.unary_stream_rpc_method_handler(
+                    servicer.PredictStream,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.Reply.SerializeToString,
+            ),
+            'Embedding': grpc.unary_unary_rpc_method_handler(
+                    servicer.Embedding,
+                    request_deserializer=backend__pb2.PredictOptions.FromString,
+                    response_serializer=backend__pb2.EmbeddingResult.SerializeToString,
+            ),
+            'GenerateImage': grpc.unary_unary_rpc_method_handler(
+                    servicer.GenerateImage,
+                    request_deserializer=backend__pb2.GenerateImageRequest.FromString,
+                    response_serializer=backend__pb2.Result.SerializeToString,
+            ),
+            'AudioTranscription': grpc.unary_unary_rpc_method_handler(
+                    servicer.AudioTranscription,
+                    request_deserializer=backend__pb2.TranscriptRequest.FromString,
+                    response_serializer=backend__pb2.TranscriptResult.SerializeToString,
+            ),
+            'TTS': grpc.unary_unary_rpc_method_handler(
+                    servicer.TTS,
+                    request_deserializer=backend__pb2.TTSRequest.FromString,
+                    response_serializer=backend__pb2.Result.SerializeToString,
+            ),
+    }
+    generic_handler = grpc.method_handlers_generic_handler(
+            'backend.Backend', rpc_method_handlers)
+    server.add_generic_rpc_handlers((generic_handler,))
+
+
+ # This class is part of an EXPERIMENTAL API.
+class Backend(object):
+    """Missing associated documentation comment in .proto file."""
+
+    @staticmethod
+    def Health(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Health',
+            backend__pb2.HealthMessage.SerializeToString,
+            backend__pb2.Reply.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def Predict(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Predict',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.Reply.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def LoadModel(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/LoadModel',
+            backend__pb2.ModelOptions.SerializeToString,
+            backend__pb2.Result.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def PredictStream(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_stream(request, target, '/backend.Backend/PredictStream',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.Reply.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def Embedding(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/Embedding',
+            backend__pb2.PredictOptions.SerializeToString,
+            backend__pb2.EmbeddingResult.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def GenerateImage(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/GenerateImage',
+            backend__pb2.GenerateImageRequest.SerializeToString,
+            backend__pb2.Result.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def AudioTranscription(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/AudioTranscription',
+            backend__pb2.TranscriptRequest.SerializeToString,
+            backend__pb2.TranscriptResult.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def TTS(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/backend.Backend/TTS',
+            backend__pb2.TTSRequest.SerializeToString,
+            backend__pb2.Result.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)

extra/grpc/huggingface/huggingface.py

@@ -0,0 +1,67 @@
+#!/usr/bin/env python3
+import grpc
+from concurrent import futures
+import time
+import backend_pb2
+import backend_pb2_grpc
+import argparse
+import signal
+import sys
+import os
+from sentence_transformers import SentenceTransformer
+
+_ONE_DAY_IN_SECONDS = 60 * 60 * 24
+
+# Implement the BackendServicer class with the service methods
+class BackendServicer(backend_pb2_grpc.BackendServicer):
+    def Health(self, request, context):
+        return backend_pb2.Reply(message="OK")
+    def LoadModel(self, request, context):
+        model_name = request.Model
+        model_name = os.path.basename(model_name)
+        try:
+            self.model = SentenceTransformer(model_name)
+        except Exception as err:
+            return backend_pb2.Result(success=False, message=f"Unexpected {err=}, {type(err)=}")
+        # Implement your logic here for the LoadModel service
+        # Replace this with your desired response
+        return backend_pb2.Result(message="Model loaded successfully", success=True)
+    def Embedding(self, request, context):
+        # Implement your logic here for the Embedding service
+        # Replace this with your desired response
+        print("Calculated embeddings for: " + request.Embeddings, file=sys.stderr)
+        sentence_embeddings = self.model.encode(request.Embeddings)
+        return backend_pb2.EmbeddingResult(embeddings=sentence_embeddings)
+
+
+def serve(address):
+    server = grpc.server(futures.ThreadPoolExecutor(max_workers=10))
+    backend_pb2_grpc.add_BackendServicer_to_server(BackendServicer(), server)
+    server.add_insecure_port(address)
+    server.start()
+    print("Server started. Listening on: " + address, file=sys.stderr)
+
+    # Define the signal handler function
+    def signal_handler(sig, frame):
+        print("Received termination signal. Shutting down...")
+        server.stop(0)
+        sys.exit(0)
+
+    # Set the signal handlers for SIGINT and SIGTERM
+    signal.signal(signal.SIGINT, signal_handler)
+    signal.signal(signal.SIGTERM, signal_handler)
+
+    try:
+        while True:
+            time.sleep(_ONE_DAY_IN_SECONDS)
+    except KeyboardInterrupt:
+        server.stop(0)
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Run the gRPC server.")
+    parser.add_argument(
+        "--addr", default="localhost:50051", help="The address to bind the server to."
+    )
+    args = parser.parse_args()
+
+    serve(args.addr)

extra/requirements.txt

@@ -0,0 +1,4 @@
+sentence_transformers
+grpcio
+google
+protobuf

main.go

@@ -4,6 +4,7 @@ import (
 	"os"
 	"os/signal"
 	"path/filepath"
+	"strings"
 	"syscall"
 
 	api "github.com/go-skynet/LocalAI/api"
@@ -40,6 +41,10 @@ func main() {
 				Name:    "f16",
 				EnvVars: []string{"F16"},
 			},
+			&cli.BoolFlag{
+				Name:    "autoload-galleries",
+				EnvVars: []string{"AUTOLOAD_GALLERIES"},
+			},
 			&cli.BoolFlag{
 				Name:    "debug",
 				EnvVars: []string{"DEBUG"},
@@ -108,6 +113,11 @@ func main() {
 				EnvVars: []string{"BACKEND_ASSETS_PATH"},
 				Value:   "/tmp/localai/backend_data",
 			},
+			&cli.StringSliceFlag{
+				Name:    "external-grpc-backends",
+				Usage:   "A list of external grpc backends",
+				EnvVars: []string{"EXTERNAL_GRPC_BACKENDS"},
+			},
 			&cli.IntFlag{
 				Name:    "context-size",
 				Usage:   "Default context size of the model",
@@ -138,7 +148,8 @@ For a list of compatible model, check out: https://localai.io/model-compatibilit
 		UsageText: `local-ai [options]`,
 		Copyright: "Ettore Di Giacinto",
 		Action: func(ctx *cli.Context) error {
-			app, err := api.App(
+
+			opts := []options.AppOption{
 				options.WithConfigFile(ctx.String("config-file")),
 				options.WithJSONStringPreload(ctx.String("preload-models")),
 				options.WithYAMLConfigPreload(ctx.String("preload-models-config")),
@@ -155,7 +166,22 @@ For a list of compatible model, check out: https://localai.io/model-compatibilit
 				options.WithThreads(ctx.Int("threads")),
 				options.WithBackendAssets(backendAssets),
 				options.WithBackendAssetsOutput(ctx.String("backend-assets-path")),
-				options.WithUploadLimitMB(ctx.Int("upload-limit")))
+				options.WithUploadLimitMB(ctx.Int("upload-limit")),
+			}
+
+			externalgRPC := ctx.StringSlice("external-grpc-backends")
+			// split ":" to get backend name and the uri
+			for _, v := range externalgRPC {
+				backend := v[:strings.IndexByte(v, ':')]
+				uri := v[strings.IndexByte(v, ':')+1:]
+				opts = append(opts, options.WithExternalBackend(backend, uri))
+			}
+
+			if ctx.Bool("autoload-galleries") {
+				opts = append(opts, options.EnableGalleriesAutoload)
+			}
+
+			app, err := api.App(opts...)
 			if err != nil {
 				return err
 			}

pkg/gallery/gallery.go

@@ -18,23 +18,15 @@ type Gallery struct {
 
 // Installs a model from the gallery (galleryname@modelname)
 func InstallModelFromGallery(galleries []Gallery, name string, basePath string, req GalleryModel, downloadStatus func(string, string, string, float64)) error {
-
-	// os.PathSeparator is not allowed in model names. Replace them with "__" to avoid conflicts with file paths.
-	name = strings.ReplaceAll(name, string(os.PathSeparator), "__")
-
-	models, err := AvailableGalleryModels(galleries, basePath)
-	if err != nil {
-		return err
-	}
-
 	applyModel := func(model *GalleryModel) error {
 		config, err := GetGalleryConfigFromURL(model.URL)
 		if err != nil {
 			return err
 		}
 
+		installName := model.Name
 		if req.Name != "" {
-			model.Name = req.Name
+			installName = req.Name
 		}
 
 		config.Files = append(config.Files, req.AdditionalFiles...)
@@ -45,20 +37,58 @@ func InstallModelFromGallery(galleries []Gallery, name string, basePath string,
 			return err
 		}
 
-		if err := InstallModel(basePath, model.Name, &config, model.Overrides, downloadStatus); err != nil {
+		if err := InstallModel(basePath, installName, &config, model.Overrides, downloadStatus); err != nil {
 			return err
 		}
 
 		return nil
 	}
 
+	models, err := AvailableGalleryModels(galleries, basePath)
+	if err != nil {
+		return err
+	}
+
+	model, err := FindGallery(models, name)
+	if err != nil {
+		return err
+	}
+
+	return applyModel(model)
+}
+
+func FindGallery(models []*GalleryModel, name string) (*GalleryModel, error) {
+	// os.PathSeparator is not allowed in model names. Replace them with "__" to avoid conflicts with file paths.
+	name = strings.ReplaceAll(name, string(os.PathSeparator), "__")
+
 	for _, model := range models {
 		if name == fmt.Sprintf("%s@%s", model.Gallery.Name, model.Name) {
-			return applyModel(model)
+			return model, nil
+		}
+	}
+	return nil, fmt.Errorf("no gallery found with name %q", name)
+}
+
+// InstallModelFromGalleryByName loads a model from the gallery by specifying only the name (first match wins)
+func InstallModelFromGalleryByName(galleries []Gallery, name string, basePath string, req GalleryModel, downloadStatus func(string, string, string, float64)) error {
+	models, err := AvailableGalleryModels(galleries, basePath)
+	if err != nil {
+		return err
+	}
+
+	name = strings.ReplaceAll(name, string(os.PathSeparator), "__")
+	var model *GalleryModel
+	for _, m := range models {
+		if name == m.Name {
+			model = m
 		}
 	}
 
+	if model == nil {
 		return fmt.Errorf("no model found with name %q", name)
+	}
+
+	return InstallModelFromGallery(galleries, fmt.Sprintf("%s@%s", model.Gallery.Name, model.Name), basePath, req, downloadStatus)
 }
 
 // List available models

pkg/grpc/tts/piper.go

@@ -3,7 +3,9 @@ package tts
 // This is a wrapper to statisfy the GRPC service interface
 // It is meant to be used by the main executable that is the server for the specific backend type (falcon, gpt3, etc)
 import (
+	"fmt"
 	"os"
+	"path/filepath"
 
 	"github.com/go-skynet/LocalAI/pkg/grpc/base"
 	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
@@ -16,6 +18,9 @@ type Piper struct {
 }
 
 func (sd *Piper) Load(opts *pb.ModelOptions) error {
+	if filepath.Ext(opts.Model) != ".onnx" {
+		return fmt.Errorf("unsupported model type %s (should end with .onnx)", opts.Model)
+	}
 	var err error
 	// Note: the Model here is a path to a directory containing the model files
 	sd.piper, err = New(opts.LibrarySearchPath)

pkg/model/initializers.go

@@ -19,8 +19,6 @@ import (
 	process "github.com/mudler/go-processmanager"
 )
 
-const tokenizerSuffix = ".tokenizer.json"
-
 const (
 	LlamaBackend        = "llama"
 	BloomzBackend       = "bloomz"
@@ -45,7 +43,6 @@ const (
 	StableDiffusionBackend = "stablediffusion"
 	PiperBackend           = "piper"
 	LCHuggingFaceBackend   = "langchain-huggingface"
-	//GGLLMFalconBackend     = "falcon"
 )
 
 var AutoLoadBackends []string = []string{
@@ -62,6 +59,11 @@ var AutoLoadBackends []string = []string{
 	MPTBackend,
 	ReplitBackend,
 	StarcoderBackend,
+	BloomzBackend,
+	RwkvBackend,
+	WhisperBackend,
+	StableDiffusionBackend,
+	PiperBackend,
 }
 
 func (ml *ModelLoader) StopGRPC() {
@@ -70,45 +72,28 @@ func (ml *ModelLoader) StopGRPC() {
 	}
 }
 
-// starts the grpcModelProcess for the backend, and returns a grpc client
+func (ml *ModelLoader) startProcess(grpcProcess, id string, serverAddress string) error {
-// It also loads the model
-func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc.Client, error) {
-	return func(s string) (*grpc.Client, error) {
-		log.Debug().Msgf("Loading GRPC Model", backend, *o)
-
-		grpcProcess := filepath.Join(o.assetDir, "backend-assets", "grpc", backend)
-
-		// Check if the file exists
-		if _, err := os.Stat(grpcProcess); os.IsNotExist(err) {
-			return nil, fmt.Errorf("grpc process not found: %s. some backends(stablediffusion, tts) require LocalAI compiled with GO_TAGS", grpcProcess)
-		}
-
 	// Make sure the process is executable
 	if err := os.Chmod(grpcProcess, 0755); err != nil {
-			return nil, err
+		return err
 	}
 
 	log.Debug().Msgf("Loading GRPC Process", grpcProcess)
-		port, err := freeport.GetFreePort()
-		if err != nil {
-			return nil, err
-		}
 
-		serverAddress := fmt.Sprintf("localhost:%d", port)
+	log.Debug().Msgf("GRPC Service for %s will be running at: '%s'", id, serverAddress)
-
-		log.Debug().Msgf("GRPC Service for '%s' (%s) will be running at: '%s'", backend, o.modelFile, serverAddress)
 
 	grpcControlProcess := process.New(
 		process.WithTemporaryStateDir(),
 		process.WithName(grpcProcess),
 		process.WithArgs("--addr", serverAddress))
 
-		ml.grpcProcesses[o.modelFile] = grpcControlProcess
+	ml.grpcProcesses[id] = grpcControlProcess
 
 	if err := grpcControlProcess.Run(); err != nil {
-			return nil, err
+		return err
 	}
 
+	log.Debug().Msgf("GRPC Service state dir: %s", grpcControlProcess.StateDir())
 	// clean up process
 	go func() {
 		c := make(chan os.Signal, 1)
@@ -123,7 +108,7 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc
 			log.Debug().Msgf("Could not tail stderr")
 		}
 		for line := range t.Lines {
-				log.Debug().Msgf("GRPC(%s): stderr %s", strings.Join([]string{backend, o.modelFile, serverAddress}, "-"), line.Text)
+			log.Debug().Msgf("GRPC(%s): stderr %s", strings.Join([]string{id, serverAddress}, "-"), line.Text)
 		}
 	}()
 	go func() {
@@ -132,13 +117,71 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc
 			log.Debug().Msgf("Could not tail stdout")
 		}
 		for line := range t.Lines {
-				log.Debug().Msgf("GRPC(%s): stderr %s", strings.Join([]string{backend, o.modelFile, serverAddress}, "-"), line.Text)
+			log.Debug().Msgf("GRPC(%s): stdout %s", strings.Join([]string{id, serverAddress}, "-"), line.Text)
 		}
 	}()
 
+	return nil
+}
+
+// starts the grpcModelProcess for the backend, and returns a grpc client
+// It also loads the model
+func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc.Client, error) {
+	return func(s string) (*grpc.Client, error) {
+		log.Debug().Msgf("Loading GRPC Model", backend, *o)
+
+		var client *grpc.Client
+
+		getFreeAddress := func() (string, error) {
+			port, err := freeport.GetFreePort()
+			if err != nil {
+				return "", fmt.Errorf("failed allocating free ports: %s", err.Error())
+			}
+			return fmt.Sprintf("127.0.0.1:%d", port), nil
+		}
+
+		// Check if the backend is provided as external
+		if uri, ok := o.externalBackends[backend]; ok {
+			log.Debug().Msgf("Loading external backend: %s", uri)
+			// check if uri is a file or a address
+			if _, err := os.Stat(uri); err == nil {
+				serverAddress, err := getFreeAddress()
+				if err != nil {
+					return nil, fmt.Errorf("failed allocating free ports: %s", err.Error())
+				}
+				// Make sure the process is executable
+				if err := ml.startProcess(uri, o.modelFile, serverAddress); err != nil {
+					return nil, err
+				}
+
 				log.Debug().Msgf("GRPC Service Started")
 
-		client := grpc.NewClient(serverAddress)
+				client = grpc.NewClient(serverAddress)
+			} else {
+				// address
+				client = grpc.NewClient(uri)
+			}
+		} else {
+			grpcProcess := filepath.Join(o.assetDir, "backend-assets", "grpc", backend)
+			// Check if the file exists
+			if _, err := os.Stat(grpcProcess); os.IsNotExist(err) {
+				return nil, fmt.Errorf("grpc process not found: %s. some backends(stablediffusion, tts) require LocalAI compiled with GO_TAGS", grpcProcess)
+			}
+
+			serverAddress, err := getFreeAddress()
+			if err != nil {
+				return nil, fmt.Errorf("failed allocating free ports: %s", err.Error())
+			}
+
+			// Make sure the process is executable
+			if err := ml.startProcess(grpcProcess, o.modelFile, serverAddress); err != nil {
+				return nil, err
+			}
+
+			log.Debug().Msgf("GRPC Service Started")
+
+			client = grpc.NewClient(serverAddress)
+		}
 
 		// Wait for the service to start up
 		ready := false
@@ -153,11 +196,6 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc
 
 		if !ready {
 			log.Debug().Msgf("GRPC Service NOT ready")
-			log.Debug().Msgf("Alive: ", grpcControlProcess.IsAlive())
-			log.Debug().Msgf(fmt.Sprintf("GRPC Service Exitcode:"))
-
-			log.Debug().Msgf(grpcControlProcess.ExitCode())
-
 			return nil, fmt.Errorf("grpc service not ready")
 		}
 
@@ -168,10 +206,10 @@ func (ml *ModelLoader) grpcModel(backend string, o *Options) func(string) (*grpc
 
 		res, err := client.LoadModel(o.context, &options)
 		if err != nil {
-			return nil, err
+			return nil, fmt.Errorf("could not load model: %w", err)
 		}
 		if !res.Success {
-			return nil, fmt.Errorf("could not load model: %s", res.Message)
+			return nil, fmt.Errorf("could not load model (no success): %s", res.Message)
 		}
 
 		return client, nil
@@ -184,6 +222,13 @@ func (ml *ModelLoader) BackendLoader(opts ...Option) (model *grpc.Client, err er
 	log.Debug().Msgf("Loading model %s from %s", o.backendString, o.modelFile)
 
 	backend := strings.ToLower(o.backendString)
+
+	// if an external backend is provided, use it
+	_, externalBackendExists := o.externalBackends[backend]
+	if externalBackendExists {
+		return ml.LoadModel(o.modelFile, ml.grpcModel(backend, o))
+	}
+
 	switch backend {
 	case LlamaBackend, LlamaGrammarBackend, GPTJBackend, DollyBackend,
 		MPTBackend, Gpt2Backend, FalconBackend,
@@ -204,8 +249,6 @@ func (ml *ModelLoader) BackendLoader(opts ...Option) (model *grpc.Client, err er
 func (ml *ModelLoader) GreedyLoader(opts ...Option) (*grpc.Client, error) {
 	o := NewOptions(opts...)
 
-	log.Debug().Msgf("Loading model '%s' greedly", o.modelFile)
-
 	// Is this really needed? BackendLoader already does this
 	ml.mu.Lock()
 	if m := ml.checkIsLoaded(o.modelFile); m != nil {
@@ -216,16 +259,29 @@ func (ml *ModelLoader) GreedyLoader(opts ...Option) (*grpc.Client, error) {
 	ml.mu.Unlock()
 	var err error
 
-	for _, b := range AutoLoadBackends {
+	// autoload also external backends
-		log.Debug().Msgf("[%s] Attempting to load", b)
+	allBackendsToAutoLoad := []string{}
+	allBackendsToAutoLoad = append(allBackendsToAutoLoad, AutoLoadBackends...)
+	for _, b := range o.externalBackends {
+		allBackendsToAutoLoad = append(allBackendsToAutoLoad, b)
+	}
+	log.Debug().Msgf("Loading model '%s' greedly from all the available backends: %s", o.modelFile, strings.Join(allBackendsToAutoLoad, ", "))
 
-		model, modelerr := ml.BackendLoader(
+	for _, b := range allBackendsToAutoLoad {
+		log.Debug().Msgf("[%s] Attempting to load", b)
+		options := []Option{
 			WithBackendString(b),
 			WithModelFile(o.modelFile),
 			WithLoadGRPCLLMModelOpts(o.gRPCOptions),
 			WithThreads(o.threads),
 			WithAssetDir(o.assetDir),
-		)
+		}
+
+		for k, v := range o.externalBackends {
+			options = append(options, WithExternalBackend(k, v))
+		}
+
+		model, modelerr := ml.BackendLoader(options...)
 		if modelerr == nil && model != nil {
 			log.Debug().Msgf("[%s] Loads OK", b)
 			return model, nil
@@ -233,7 +289,7 @@ func (ml *ModelLoader) GreedyLoader(opts ...Option) (*grpc.Client, error) {
 			err = multierror.Append(err, modelerr)
 			log.Debug().Msgf("[%s] Fails: %s", b, modelerr.Error())
 		} else if model == nil {
-			err = multierror.Append(err, modelerr)
+			err = multierror.Append(err, fmt.Errorf("backend returned no usable model"))
 			log.Debug().Msgf("[%s] Fails: %s", b, "backend returned no usable model")
 		}
 	}

pkg/model/options.go

@@ -14,10 +14,21 @@ type Options struct {
 	context       context.Context
 
 	gRPCOptions *pb.ModelOptions
+
+	externalBackends map[string]string
 }
 
 type Option func(*Options)
 
+func WithExternalBackend(name string, uri string) Option {
+	return func(o *Options) {
+		if o.externalBackends == nil {
+			o.externalBackends = make(map[string]string)
+		}
+		o.externalBackends[name] = uri
+	}
+}
+
 func WithBackendString(backend string) Option {
 	return func(o *Options) {
 		o.backendString = backend

pkg/utils/logging.go

@@ -0,0 +1,37 @@
+package utils
+
+import (
+	"time"
+
+	"github.com/rs/zerolog/log"
+)
+
+var lastProgress time.Time = time.Now()
+var startTime time.Time = time.Now()
+
+func ResetDownloadTimers() {
+	lastProgress = time.Now()
+	startTime = time.Now()
+}
+
+func DisplayDownloadFunction(fileName string, current string, total string, percentage float64) {
+	currentTime := time.Now()
+
+	if currentTime.Sub(lastProgress) >= 5*time.Second {
+
+		lastProgress = currentTime
+
+		// calculate ETA based on percentage and elapsed time
+		var eta time.Duration
+		if percentage > 0 {
+			elapsed := currentTime.Sub(startTime)
+			eta = time.Duration(float64(elapsed)*(100/percentage) - float64(elapsed))
+		}
+
+		if total != "" {
+			log.Debug().Msgf("Downloading %s: %s/%s (%.2f%%) ETA: %s", fileName, current, total, percentage, eta)
+		} else {
+			log.Debug().Msgf("Downloading: %s", current)
+		}
+	}
+}

tests/models_fixtures/grpc.yaml

@@ -0,0 +1,5 @@
+name: code-search-ada-code-001
+backend: huggingface
+embeddings: true
+parameters:
+  model: all-MiniLM-L6-v2