⬆️ Update ggerganov/llama.cpp (#1655)

Signed-off-by: GitHub <noreply@github.com>
Co-authored-by: mudler <mudler@users.noreply.github.com>

Makefile

@@ -8,7 +8,7 @@ GOLLAMA_VERSION?=aeba71ee842819da681ea537e78846dc75949ac0
 
 GOLLAMA_STABLE_VERSION?=50cee7712066d9e38306eccadcfbb44ea87df4b7
 
-CPPLLAMA_VERSION?=6f9939d119b2d004c264952eb510bd106455531e
+CPPLLAMA_VERSION?=6db2b41a76ee78d5efdd5c3cddd5d7ad3f646855
 
 # gpt4all version
 GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all

api/api.go

@@ -37,7 +37,7 @@ func Startup(opts ...options.AppOption) (*options.Option, *config.ConfigLoader,
 	log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.Threads, options.Loader.ModelPath)
 	log.Info().Msgf("LocalAI version: %s", internal.PrintableVersion())
 
-	startup.PreloadModelsConfigurations(options.Loader.ModelPath, options.ModelsURL...)
+	startup.PreloadModelsConfigurations(options.ModelLibraryURL, options.Loader.ModelPath, options.ModelsURL...)
 
 	cl := config.NewConfigLoader()
 	if err := cl.LoadConfigs(options.Loader.ModelPath); err != nil {
@@ -216,6 +216,11 @@ func App(opts ...options.AppOption) (*fiber.App, error) {
 		}{Version: internal.PrintableVersion()})
 	})
 
+	// Make sure directories exists
+	os.MkdirAll(options.ImageDir, 0755)
+	os.MkdirAll(options.AudioDir, 0755)
+	os.MkdirAll(options.Loader.ModelPath, 0755)
+
 	modelGalleryService := localai.CreateModelGalleryService(options.Galleries, options.Loader.ModelPath, galleryService)
 	app.Post("/models/apply", auth, modelGalleryService.ApplyModelGalleryEndpoint())
 	app.Get("/models/available", auth, modelGalleryService.ListModelFromGalleryEndpoint())

api/backend/options.go

@@ -63,6 +63,8 @@ func gRPCModelOpts(c config.Config) *pb.ModelOptions {
 		F16Memory:      c.F16,
 		MLock:          c.MMlock,
 		RopeFreqBase:   c.RopeFreqBase,
+		RopeScaling:    c.RopeScaling,
+		Type:           c.ModelType,
 		RopeFreqScale:  c.RopeFreqScale,
 		NUMA:           c.NUMA,
 		Embeddings:     c.Embeddings,

api/config/config.go

@@ -128,7 +128,9 @@ type LLMConfig struct {
 	Quantization string  `yaml:"quantization"`
 	MMProj       string  `yaml:"mmproj"`
 
-	RopeScaling    string  `yaml:"rope_scaling"`
+	RopeScaling string `yaml:"rope_scaling"`
+	ModelType   string `yaml:"type"`
+
 	YarnExtFactor  float32 `yaml:"yarn_ext_factor"`
 	YarnAttnFactor float32 `yaml:"yarn_attn_factor"`
 	YarnBetaFast   float32 `yaml:"yarn_beta_fast"`

api/options/options.go

@@ -28,6 +28,8 @@ type Option struct {
 	ApiKeys                             []string
 	Metrics                             *metrics.Metrics
 
+	ModelLibraryURL string
+
 	Galleries []gallery.Gallery
 
 	BackendAssets     embed.FS
@@ -78,6 +80,12 @@ func WithCors(b bool) AppOption {
 	}
 }
 
+func WithModelLibraryURL(url string) AppOption {
+	return func(o *Option) {
+		o.ModelLibraryURL = url
+	}
+}
+
 var EnableWatchDog = func(o *Option) {
 	o.WatchDog = true
 }

backend/backend.proto

@@ -134,6 +134,8 @@ message ModelOptions {
   float YarnAttnFactor = 45;
   float YarnBetaFast = 46;
   float YarnBetaSlow = 47;
+
+  string Type = 49;
 }
 
 message Result {

backend/backend_grpc.pb.go

@@ -0,0 +1,457 @@
+// Code generated by protoc-gen-go-grpc. DO NOT EDIT.
+// versions:
+// - protoc-gen-go-grpc v1.2.0
+// - protoc             v4.23.4
+// source: backend/backend.proto
+
+package proto
+
+import (
+	context "context"
+	grpc "google.golang.org/grpc"
+	codes "google.golang.org/grpc/codes"
+	status "google.golang.org/grpc/status"
+)
+
+// This is a compile-time assertion to ensure that this generated file
+// is compatible with the grpc package it is being compiled against.
+// Requires gRPC-Go v1.32.0 or later.
+const _ = grpc.SupportPackageIsVersion7
+
+// BackendClient is the client API for Backend service.
+//
+// For semantics around ctx use and closing/ending streaming RPCs, please refer to https://pkg.go.dev/google.golang.org/grpc/?tab=doc#ClientConn.NewStream.
+type BackendClient interface {
+	Health(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*Reply, error)
+	Predict(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*Reply, error)
+	LoadModel(ctx context.Context, in *ModelOptions, opts ...grpc.CallOption) (*Result, error)
+	PredictStream(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (Backend_PredictStreamClient, error)
+	Embedding(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*EmbeddingResult, error)
+	GenerateImage(ctx context.Context, in *GenerateImageRequest, opts ...grpc.CallOption) (*Result, error)
+	AudioTranscription(ctx context.Context, in *TranscriptRequest, opts ...grpc.CallOption) (*TranscriptResult, error)
+	TTS(ctx context.Context, in *TTSRequest, opts ...grpc.CallOption) (*Result, error)
+	TokenizeString(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*TokenizationResponse, error)
+	Status(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*StatusResponse, error)
+}
+
+type backendClient struct {
+	cc grpc.ClientConnInterface
+}
+
+func NewBackendClient(cc grpc.ClientConnInterface) BackendClient {
+	return &backendClient{cc}
+}
+
+func (c *backendClient) Health(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*Reply, error) {
+	out := new(Reply)
+	err := c.cc.Invoke(ctx, "/backend.Backend/Health", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) Predict(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*Reply, error) {
+	out := new(Reply)
+	err := c.cc.Invoke(ctx, "/backend.Backend/Predict", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) LoadModel(ctx context.Context, in *ModelOptions, opts ...grpc.CallOption) (*Result, error) {
+	out := new(Result)
+	err := c.cc.Invoke(ctx, "/backend.Backend/LoadModel", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) PredictStream(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (Backend_PredictStreamClient, error) {
+	stream, err := c.cc.NewStream(ctx, &Backend_ServiceDesc.Streams[0], "/backend.Backend/PredictStream", opts...)
+	if err != nil {
+		return nil, err
+	}
+	x := &backendPredictStreamClient{stream}
+	if err := x.ClientStream.SendMsg(in); err != nil {
+		return nil, err
+	}
+	if err := x.ClientStream.CloseSend(); err != nil {
+		return nil, err
+	}
+	return x, nil
+}
+
+type Backend_PredictStreamClient interface {
+	Recv() (*Reply, error)
+	grpc.ClientStream
+}
+
+type backendPredictStreamClient struct {
+	grpc.ClientStream
+}
+
+func (x *backendPredictStreamClient) Recv() (*Reply, error) {
+	m := new(Reply)
+	if err := x.ClientStream.RecvMsg(m); err != nil {
+		return nil, err
+	}
+	return m, nil
+}
+
+func (c *backendClient) Embedding(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*EmbeddingResult, error) {
+	out := new(EmbeddingResult)
+	err := c.cc.Invoke(ctx, "/backend.Backend/Embedding", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) GenerateImage(ctx context.Context, in *GenerateImageRequest, opts ...grpc.CallOption) (*Result, error) {
+	out := new(Result)
+	err := c.cc.Invoke(ctx, "/backend.Backend/GenerateImage", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) AudioTranscription(ctx context.Context, in *TranscriptRequest, opts ...grpc.CallOption) (*TranscriptResult, error) {
+	out := new(TranscriptResult)
+	err := c.cc.Invoke(ctx, "/backend.Backend/AudioTranscription", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) TTS(ctx context.Context, in *TTSRequest, opts ...grpc.CallOption) (*Result, error) {
+	out := new(Result)
+	err := c.cc.Invoke(ctx, "/backend.Backend/TTS", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) TokenizeString(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*TokenizationResponse, error) {
+	out := new(TokenizationResponse)
+	err := c.cc.Invoke(ctx, "/backend.Backend/TokenizeString", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+func (c *backendClient) Status(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*StatusResponse, error) {
+	out := new(StatusResponse)
+	err := c.cc.Invoke(ctx, "/backend.Backend/Status", in, out, opts...)
+	if err != nil {
+		return nil, err
+	}
+	return out, nil
+}
+
+// BackendServer is the server API for Backend service.
+// All implementations must embed UnimplementedBackendServer
+// for forward compatibility
+type BackendServer interface {
+	Health(context.Context, *HealthMessage) (*Reply, error)
+	Predict(context.Context, *PredictOptions) (*Reply, error)
+	LoadModel(context.Context, *ModelOptions) (*Result, error)
+	PredictStream(*PredictOptions, Backend_PredictStreamServer) error
+	Embedding(context.Context, *PredictOptions) (*EmbeddingResult, error)
+	GenerateImage(context.Context, *GenerateImageRequest) (*Result, error)
+	AudioTranscription(context.Context, *TranscriptRequest) (*TranscriptResult, error)
+	TTS(context.Context, *TTSRequest) (*Result, error)
+	TokenizeString(context.Context, *PredictOptions) (*TokenizationResponse, error)
+	Status(context.Context, *HealthMessage) (*StatusResponse, error)
+	mustEmbedUnimplementedBackendServer()
+}
+
+// UnimplementedBackendServer must be embedded to have forward compatible implementations.
+type UnimplementedBackendServer struct {
+}
+
+func (UnimplementedBackendServer) Health(context.Context, *HealthMessage) (*Reply, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method Health not implemented")
+}
+func (UnimplementedBackendServer) Predict(context.Context, *PredictOptions) (*Reply, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method Predict not implemented")
+}
+func (UnimplementedBackendServer) LoadModel(context.Context, *ModelOptions) (*Result, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method LoadModel not implemented")
+}
+func (UnimplementedBackendServer) PredictStream(*PredictOptions, Backend_PredictStreamServer) error {
+	return status.Errorf(codes.Unimplemented, "method PredictStream not implemented")
+}
+func (UnimplementedBackendServer) Embedding(context.Context, *PredictOptions) (*EmbeddingResult, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method Embedding not implemented")
+}
+func (UnimplementedBackendServer) GenerateImage(context.Context, *GenerateImageRequest) (*Result, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method GenerateImage not implemented")
+}
+func (UnimplementedBackendServer) AudioTranscription(context.Context, *TranscriptRequest) (*TranscriptResult, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method AudioTranscription not implemented")
+}
+func (UnimplementedBackendServer) TTS(context.Context, *TTSRequest) (*Result, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method TTS not implemented")
+}
+func (UnimplementedBackendServer) TokenizeString(context.Context, *PredictOptions) (*TokenizationResponse, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method TokenizeString not implemented")
+}
+func (UnimplementedBackendServer) Status(context.Context, *HealthMessage) (*StatusResponse, error) {
+	return nil, status.Errorf(codes.Unimplemented, "method Status not implemented")
+}
+func (UnimplementedBackendServer) mustEmbedUnimplementedBackendServer() {}
+
+// UnsafeBackendServer may be embedded to opt out of forward compatibility for this service.
+// Use of this interface is not recommended, as added methods to BackendServer will
+// result in compilation errors.
+type UnsafeBackendServer interface {
+	mustEmbedUnimplementedBackendServer()
+}
+
+func RegisterBackendServer(s grpc.ServiceRegistrar, srv BackendServer) {
+	s.RegisterService(&Backend_ServiceDesc, srv)
+}
+
+func _Backend_Health_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(HealthMessage)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).Health(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/Health",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).Health(ctx, req.(*HealthMessage))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_Predict_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(PredictOptions)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).Predict(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/Predict",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).Predict(ctx, req.(*PredictOptions))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_LoadModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(ModelOptions)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).LoadModel(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/LoadModel",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).LoadModel(ctx, req.(*ModelOptions))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_PredictStream_Handler(srv interface{}, stream grpc.ServerStream) error {
+	m := new(PredictOptions)
+	if err := stream.RecvMsg(m); err != nil {
+		return err
+	}
+	return srv.(BackendServer).PredictStream(m, &backendPredictStreamServer{stream})
+}
+
+type Backend_PredictStreamServer interface {
+	Send(*Reply) error
+	grpc.ServerStream
+}
+
+type backendPredictStreamServer struct {
+	grpc.ServerStream
+}
+
+func (x *backendPredictStreamServer) Send(m *Reply) error {
+	return x.ServerStream.SendMsg(m)
+}
+
+func _Backend_Embedding_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(PredictOptions)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).Embedding(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/Embedding",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).Embedding(ctx, req.(*PredictOptions))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_GenerateImage_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(GenerateImageRequest)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).GenerateImage(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/GenerateImage",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).GenerateImage(ctx, req.(*GenerateImageRequest))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_AudioTranscription_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(TranscriptRequest)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).AudioTranscription(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/AudioTranscription",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).AudioTranscription(ctx, req.(*TranscriptRequest))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_TTS_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(TTSRequest)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).TTS(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/TTS",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).TTS(ctx, req.(*TTSRequest))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_TokenizeString_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(PredictOptions)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).TokenizeString(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/TokenizeString",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).TokenizeString(ctx, req.(*PredictOptions))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+func _Backend_Status_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
+	in := new(HealthMessage)
+	if err := dec(in); err != nil {
+		return nil, err
+	}
+	if interceptor == nil {
+		return srv.(BackendServer).Status(ctx, in)
+	}
+	info := &grpc.UnaryServerInfo{
+		Server:     srv,
+		FullMethod: "/backend.Backend/Status",
+	}
+	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
+		return srv.(BackendServer).Status(ctx, req.(*HealthMessage))
+	}
+	return interceptor(ctx, in, info, handler)
+}
+
+// Backend_ServiceDesc is the grpc.ServiceDesc for Backend service.
+// It's only intended for direct use with grpc.RegisterService,
+// and not to be introspected or modified (even as a copy)
+var Backend_ServiceDesc = grpc.ServiceDesc{
+	ServiceName: "backend.Backend",
+	HandlerType: (*BackendServer)(nil),
+	Methods: []grpc.MethodDesc{
+		{
+			MethodName: "Health",
+			Handler:    _Backend_Health_Handler,
+		},
+		{
+			MethodName: "Predict",
+			Handler:    _Backend_Predict_Handler,
+		},
+		{
+			MethodName: "LoadModel",
+			Handler:    _Backend_LoadModel_Handler,
+		},
+		{
+			MethodName: "Embedding",
+			Handler:    _Backend_Embedding_Handler,
+		},
+		{
+			MethodName: "GenerateImage",
+			Handler:    _Backend_GenerateImage_Handler,
+		},
+		{
+			MethodName: "AudioTranscription",
+			Handler:    _Backend_AudioTranscription_Handler,
+		},
+		{
+			MethodName: "TTS",
+			Handler:    _Backend_TTS_Handler,
+		},
+		{
+			MethodName: "TokenizeString",
+			Handler:    _Backend_TokenizeString_Handler,
+		},
+		{
+			MethodName: "Status",
+			Handler:    _Backend_Status_Handler,
+		},
+	},
+	Streams: []grpc.StreamDesc{
+		{
+			StreamName:    "PredictStream",
+			Handler:       _Backend_PredictStream_Handler,
+			ServerStreams: true,
+		},
+	},
+	Metadata: "backend/backend.proto",
+}

backend/python/transformers/transformers_server.py

@@ -15,8 +15,8 @@ import backend_pb2_grpc
 
 import grpc
 import torch
-
-from transformers import AutoTokenizer, AutoModel
+import torch.cuda
+from transformers import AutoTokenizer, AutoModel, AutoModelForCausalLM, set_seed
 
 _ONE_DAY_IN_SECONDS = 60 * 60 * 24
 
@@ -68,16 +68,19 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         """
         model_name = request.Model
         try:
-            self.model = AutoModel.from_pretrained(model_name, trust_remote_code=True) # trust_remote_code is needed to use the encode method with embeddings models like jinai-v2
-            self.tokenizer = AutoTokenizer.from_pretrained(model_name)
+            if request.Type == "AutoModelForCausalLM":
+                self.model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
+            else:
+                self.model = AutoModel.from_pretrained(model_name, trust_remote_code=True)
 
-            if request.CUDA:
+            self.tokenizer = AutoTokenizer.from_pretrained(model_name)
+            self.CUDA = False
+
+            if request.CUDA or torch.cuda.is_available():
                 try:
-                    # TODO: also tensorflow, make configurable
-                    import torch.cuda
-                    if torch.cuda.is_available():
-                        print("Loading model", model_name, "to CUDA.", file=sys.stderr)
-                        self.model = self.model.to("cuda")
+                    print("Loading model", model_name, "to CUDA.", file=sys.stderr)
+                    self.model = self.model.to("cuda")
+                    self.CUDA = True
                 except Exception as err:
                     print("Not using CUDA:", err, file=sys.stderr)
         except Exception as err:
@@ -98,6 +101,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
             An EmbeddingResult object that contains the calculated embeddings.
         """
 
+        set_seed(request.Seed)
         # Tokenize input
         max_length = 512
         if request.Tokens != 0:
@@ -113,6 +117,51 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         print("Embeddings:", sentence_embeddings, file=sys.stderr)
         return backend_pb2.EmbeddingResult(embeddings=sentence_embeddings)
 
+    def Predict(self, request, context):
+        """
+        Generates text based on the given prompt and sampling parameters.
+
+        Args:
+            request: The predict request.
+            context: The gRPC context.
+
+        Returns:
+            backend_pb2.Reply: The predict result.
+        """
+        set_seed(request.Seed)
+        if request.TopP == 0:
+            request.TopP = 0.9
+
+        max_tokens = 200
+        if request.Tokens > 0:
+            max_tokens = request.Tokens
+
+        inputs = self.tokenizer(request.Prompt, return_tensors="pt").input_ids
+        if self.CUDA:
+            inputs = inputs.to("cuda")
+
+        outputs = self.model.generate(inputs,max_new_tokens=max_tokens, temperature=request.Temperature, top_p=request.TopP)
+
+        generated_text = self.tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
+        # Remove prompt from response if present
+        if request.Prompt in generated_text:
+            generated_text = generated_text.replace(request.Prompt, "")
+
+        return backend_pb2.Reply(message=bytes(generated_text, encoding='utf-8'))
+
+    def PredictStream(self, request, context):
+        """
+        Generates text based on the given prompt and sampling parameters, and streams the results.
+
+        Args:
+            request: The predict stream request.
+            context: The gRPC context.
+
+        Returns:
+            backend_pb2.Result: The predict stream result.
+        """
+        yield self.Predict(request, context)
+
 
 def serve(address):
     server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS))

docs/content/docs/getting-started/customize-model.md

@@ -26,6 +26,8 @@ Here's an example to initiate the **phi-2** model:
 docker run -p 8080:8080 localai/localai:{{< version >}}-ffmpeg-core https://gist.githubusercontent.com/mudler/ad601a0488b497b69ec549150d9edd18/raw/a8a8869ef1bb7e3830bf5c0bae29a0cce991ff8d/phi-2.yaml
 ```
 
+You can also check all the embedded models configurations [here](https://github.com/mudler/LocalAI/tree/master/embedded/models).
+
 {{% alert icon="" %}}
 The model configurations used in the quickstart are accessible here: [https://github.com/mudler/LocalAI/tree/master/embedded/models](https://github.com/mudler/LocalAI/tree/master/embedded/models). Contributions are welcome; please feel free to submit a Pull Request.
 

docs/content/docs/getting-started/quickstart.md

@@ -40,7 +40,7 @@ There are different categories of models: [LLMs]({{%relref "docs/features/text-g
 
 {{% alert icon="💡" %}}
 
-To customize the models, see [Model customization]({{%relref "docs/getting-started/customize-model" %}}). For more model configurations, visit the [Examples Section](https://github.com/mudler/LocalAI/tree/master/examples/configurations).
+To customize the models, see [Model customization]({{%relref "docs/getting-started/customize-model" %}}). For more model configurations, visit the [Examples Section](https://github.com/mudler/LocalAI/tree/master/examples/configurations) and the configurations for the models below is available [here](https://github.com/mudler/LocalAI/tree/master/embedded/models).
 {{% /alert %}}
 
 {{< tabs tabTotal="3" >}}
@@ -64,6 +64,10 @@ To customize the models, see [Model customization]({{%relref "docs/getting-start
 | [tinyllama-chat](https://huggingface.co/TheBloke/TinyLlama-1.1B-Chat-v0.3-GGUF) [original model](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v0.3) | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 localai/localai:{{< version >}}-ffmpeg-core tinyllama-chat``` |
 | [dolphin-2.5-mixtral-8x7b](https://huggingface.co/TheBloke/dolphin-2.5-mixtral-8x7b-GGUF) | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 localai/localai:{{< version >}}-ffmpeg-core dolphin-2.5-mixtral-8x7b``` |
 | 🐍 [mamba](https://github.com/state-spaces/mamba) | [LLM]({{%relref "docs/features/text-generation" %}}) | GPU-only |
+| animagine-xl | [Text to Image]({{%relref "docs/features/image-generation" %}}) | GPU-only |
+| transformers-tinyllama | [LLM]({{%relref "docs/features/text-generation" %}}) | GPU-only |
+| [codellama-7b](https://huggingface.co/codellama/CodeLlama-7b-hf) (with transformers) | [LLM]({{%relref "docs/features/text-generation" %}}) | GPU-only |
+| [codellama-7b-gguf](https://huggingface.co/TheBloke/CodeLlama-7B-GGUF) (with llama.cpp) | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 localai/localai:{{< version >}}-ffmpeg-core codellama-7b-gguf``` |
 {{% /tab %}}
 {{% tab tabName="GPU (CUDA 11)" %}}
 
@@ -86,7 +90,10 @@ To customize the models, see [Model customization]({{%relref "docs/getting-start
 | [tinyllama-chat](https://huggingface.co/TheBloke/TinyLlama-1.1B-Chat-v0.3-GGUF) [original model](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v0.3) | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda11-core tinyllama-chat``` |
 | [dolphin-2.5-mixtral-8x7b](https://huggingface.co/TheBloke/dolphin-2.5-mixtral-8x7b-GGUF) | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda11-core dolphin-2.5-mixtral-8x7b``` |
 | 🐍 [mamba](https://github.com/state-spaces/mamba) | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda11 mamba-chat``` |
-
+| animagine-xl | [Text to Image]({{%relref "docs/features/image-generation" %}}) |  ```docker run -ti -p 8080:8080 -e COMPEL=0 --gpus all localai/localai:{{< version >}}-cublas-cuda11 animagine-xl``` |
+| transformers-tinyllama | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda11 transformers-tinyllama``` |
+| [codellama-7b](https://huggingface.co/codellama/CodeLlama-7b-hf) | [LLM]({{%relref "docs/features/text-generation" %}})  | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda11 codellama-7b``` |
+| [codellama-7b-gguf](https://huggingface.co/TheBloke/CodeLlama-7B-GGUF) | [LLM]({{%relref "docs/features/text-generation" %}})  | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda11-core codellama-7b-gguf``` |
 {{% /tab %}}
 
 
@@ -110,6 +117,10 @@ To customize the models, see [Model customization]({{%relref "docs/getting-start
 | [tinyllama-chat](https://huggingface.co/TheBloke/TinyLlama-1.1B-Chat-v0.3-GGUF) [original model](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v0.3) | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda12-core tinyllama-chat``` |
 | [dolphin-2.5-mixtral-8x7b](https://huggingface.co/TheBloke/dolphin-2.5-mixtral-8x7b-GGUF) | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda12-core dolphin-2.5-mixtral-8x7b``` |
 | 🐍 [mamba](https://github.com/state-spaces/mamba) | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda12 mamba-chat``` |
+| animagine-xl | [Text to Image]({{%relref "docs/features/image-generation" %}}) | ```docker run -ti -p 8080:8080 -e COMPEL=0 --gpus all localai/localai:{{< version >}}-cublas-cuda12 animagine-xl``` |
+| transformers-tinyllama | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda12 transformers-tinyllama``` |
+| [codellama-7b](https://huggingface.co/codellama/CodeLlama-7b-hf) | [LLM]({{%relref "docs/features/text-generation" %}}) | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda12 codellama-7b``` |
+| [codellama-7b-gguf](https://huggingface.co/TheBloke/CodeLlama-7B-GGUF) | [LLM]({{%relref "docs/features/text-generation" %}})  | ```docker run -ti -p 8080:8080 --gpus all localai/localai:{{< version >}}-cublas-cuda12-core codellama-7b-gguf``` |
 {{% /tab %}}
 
 {{< /tabs >}}

docs/data/version.json

@@ -1,3 +1,3 @@
 {
-  "version": "v2.6.0"
+  "version": "v2.6.1"
 }

embedded/embedded.go

@@ -6,6 +6,8 @@ import (
 	"slices"
 	"strings"
 
+	"github.com/go-skynet/LocalAI/pkg/downloader"
+
 	"github.com/go-skynet/LocalAI/pkg/assets"
 	"gopkg.in/yaml.v3"
 )
@@ -30,6 +32,19 @@ func init() {
 	yaml.Unmarshal(modelLibrary, &modelShorteners)
 }
 
+func GetRemoteLibraryShorteners(url string) (map[string]string, error) {
+	remoteLibrary := map[string]string{}
+
+	err := downloader.GetURI(url, func(_ string, i []byte) error {
+		return yaml.Unmarshal(i, &remoteLibrary)
+	})
+	if err != nil {
+		return nil, fmt.Errorf("error downloading remote library: %s", err.Error())
+	}
+
+	return remoteLibrary, err
+}
+
 // ExistsInModelsLibrary checks if a model exists in the embedded models library
 func ExistsInModelsLibrary(s string) bool {
 	f := fmt.Sprintf("%s.yaml", s)

embedded/models/animagine-xl.yaml

@@ -0,0 +1,17 @@
+name: animagine-xl
+parameters:
+  model: Linaqruf/animagine-xl
+backend: diffusers
+f16: true
+diffusers:
+  scheduler_type: euler_a
+
+usage: |
+        curl http://localhost:8080/v1/images/generations \
+          -H "Content-Type: application/json" \
+          -d '{
+            "prompt": "<positive prompt>|<negative prompt>",
+            "model": "animagine-xl",
+            "step": 51,
+            "size": "1024x1024"
+          }'

embedded/models/codellama-7b-gguf.yaml

@@ -0,0 +1,16 @@
+name: codellama-7b-gguf
+backend: transformers
+parameters:
+  model: huggingface://TheBloke/CodeLlama-7B-GGUF/codellama-7b.Q4_K_M.gguf
+  temperature: 0.2
+  top_k: 40
+  seed: -1
+  top_p: 0.95
+context_size: 4096
+f16: true
+gpu_layers: 90
+usage: |
+      curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
+          "model": "codellama-7b-gguf",
+          "prompt": "import socket\n\ndef ping_exponential_backoff(host: str):"
+      }'

embedded/models/codellama-7b.yaml

@@ -0,0 +1,13 @@
+name: codellama-7b
+backend: transformers
+parameters:
+  model: codellama/CodeLlama-7b-hf
+  temperature: 0.2
+  top_k: 40
+  top_p: 0.95
+
+usage: |
+      curl http://localhost:8080/v1/completions -H "Content-Type: application/json" -d '{
+          "model": "codellama-7b",
+          "prompt": "import socket\n\ndef ping_exponential_backoff(host: str):"
+      }'

embedded/models/dolphin-2.5-mixtral-8x7b.yaml

@@ -1,10 +1,11 @@
 name: dolphin-mixtral-8x7b
 mmap: true
 parameters:
-  model: huggingface://TheBloke/dolphin-2.5-mixtral-8x7b-GGUF/blob/main/dolphin-2.5-mixtral-8x7b.Q2_K.gguf
+  model: huggingface://TheBloke/dolphin-2.5-mixtral-8x7b-GGUF/dolphin-2.5-mixtral-8x7b.Q2_K.gguf
   temperature: 0.2
   top_k: 40
   top_p: 0.95
+  seed: -1
 template:
   chat_message: |
     <|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "user"}}user{{end}}

embedded/models/llava.yaml

@@ -17,6 +17,7 @@ parameters:
   temperature: 0.2
   top_k: 40
   top_p: 0.95
+  seed: -1
 
 template:
   chat: |

embedded/models/mistral-openorca.yaml

@@ -5,6 +5,7 @@ parameters:
   temperature: 0.2
   top_k: 40
   top_p: 0.95
+  seed: -1
 template:
   chat_message: |
     <|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "user"}}user{{end}}

embedded/models/mixtral-instruct.yaml

@@ -4,6 +4,7 @@ parameters:
   model: huggingface://TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF/mixtral-8x7b-instruct-v0.1.Q2_K.gguf
   temperature: 0.2
   top_k: 40
+  seed: -1
   top_p: 0.95
 template:
   chat: &chat |

embedded/models/tinyllama-chat.yaml

@@ -4,6 +4,7 @@ parameters:
   model: huggingface://TheBloke/TinyLlama-1.1B-Chat-v0.3-GGUF/tinyllama-1.1b-chat-v0.3.Q8_0.gguf
   temperature: 0.2
   top_k: 40
+  seed: -1
   top_p: 0.95
 template:
   chat_message: |

embedded/models/transformers-tinyllama.yaml

@@ -0,0 +1,31 @@
+name: tinyllama-chat
+backend: transformers
+type: AutoModelForCausalLM
+
+parameters:
+  model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
+  temperature: 0.2
+  top_k: 40
+  top_p: 0.95
+  max_tokens: 4096
+
+template:
+  chat_message: |
+    <|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "user"}}user{{end}}
+    {{if .Content}}{{.Content}}{{end}}<|im_end|>
+  chat: |
+    {{.Input}}
+    <|im_start|>assistant
+    
+  completion: |
+    {{.Input}}
+
+stopwords:
+- <|im_end|>
+
+usage: |
+      curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
+        "model": "tinyllama-chat",
+        "messages": [{"role": "user", "content": "Say this is a test!"}],
+        "temperature": 0.7
+      }'

examples/configurations/phi-2.yaml

@@ -10,8 +10,16 @@ parameters:
   temperature: 0.2
   top_k: 40
   top_p: 0.95
+  seed: -1
 template:
   chat: &template |
     Instruct: {{.Input}}
     Output:
-  completion: *template
+  completion: *template
+
+usage: |
+      To use this model, interact with the API (in another terminal) with curl for instance:
+      curl http://localhost:8080/v1/chat/completions -H "Content-Type: application/json" -d '{
+          "model": "phi-2",
+          "messages": [{"role": "user", "content": "How are you doing?", "temperature": 0.1}]
+      }'

main.go

@@ -26,6 +26,10 @@ import (
 	"github.com/urfave/cli/v2"
 )
 
+const (
+	remoteLibraryURL = "https://raw.githubusercontent.com/mudler/LocalAI/master/embedded/model_library.yaml"
+)
+
 func main() {
 	log.Logger = log.Output(zerolog.ConsoleWriter{Out: os.Stderr})
 	// clean up process
@@ -94,6 +98,12 @@ func main() {
 				Usage:   "JSON list of galleries",
 				EnvVars: []string{"GALLERIES"},
 			},
+			&cli.StringFlag{
+				Name:    "remote-library",
+				Usage:   "A LocalAI remote library URL",
+				EnvVars: []string{"REMOTE_LIBRARY"},
+				Value:   remoteLibraryURL,
+			},
 			&cli.StringFlag{
 				Name:    "preload-models",
 				Usage:   "A List of models to apply in JSON at start",
@@ -219,6 +229,7 @@ For a list of compatible model, check out: https://localai.io/model-compatibilit
 				options.WithAudioDir(ctx.String("audio-path")),
 				options.WithF16(ctx.Bool("f16")),
 				options.WithStringGalleries(ctx.String("galleries")),
+				options.WithModelLibraryURL(ctx.String("remote-library")),
 				options.WithDisableMessage(false),
 				options.WithCors(ctx.Bool("cors")),
 				options.WithCorsAllowOrigins(ctx.String("cors-allow-origins")),

pkg/grpc/proto/backend.pb.go

@@ -1,7 +1,7 @@
 // Code generated by protoc-gen-go. DO NOT EDIT.
 // versions:
-// 	protoc-gen-go v1.28.1
-// 	protoc        v3.6.1
+// 	protoc-gen-go v1.26.0
+// 	protoc        v4.23.4
 // source: backend.proto
 
 package proto
@@ -567,8 +567,7 @@ type ModelOptions struct {
 	CLIPSubfolder string  `protobuf:"bytes,32,opt,name=CLIPSubfolder,proto3" json:"CLIPSubfolder,omitempty"`
 	CLIPSkip      int32   `protobuf:"varint,33,opt,name=CLIPSkip,proto3" json:"CLIPSkip,omitempty"`
 	ControlNet    string  `protobuf:"bytes,48,opt,name=ControlNet,proto3" json:"ControlNet,omitempty"`
-	// RWKV
-	Tokenizer string `protobuf:"bytes,34,opt,name=Tokenizer,proto3" json:"Tokenizer,omitempty"`
+	Tokenizer     string  `protobuf:"bytes,34,opt,name=Tokenizer,proto3" json:"Tokenizer,omitempty"`
 	// LLM (llama.cpp)
 	LoraBase    string  `protobuf:"bytes,35,opt,name=LoraBase,proto3" json:"LoraBase,omitempty"`
 	LoraAdapter string  `protobuf:"bytes,36,opt,name=LoraAdapter,proto3" json:"LoraAdapter,omitempty"`
@@ -584,6 +583,7 @@ type ModelOptions struct {
 	YarnAttnFactor float32 `protobuf:"fixed32,45,opt,name=YarnAttnFactor,proto3" json:"YarnAttnFactor,omitempty"`
 	YarnBetaFast   float32 `protobuf:"fixed32,46,opt,name=YarnBetaFast,proto3" json:"YarnBetaFast,omitempty"`
 	YarnBetaSlow   float32 `protobuf:"fixed32,47,opt,name=YarnBetaSlow,proto3" json:"YarnBetaSlow,omitempty"`
+	Type           string  `protobuf:"bytes,49,opt,name=Type,proto3" json:"Type,omitempty"`
 }
 
 func (x *ModelOptions) Reset() {
@@ -954,6 +954,13 @@ func (x *ModelOptions) GetYarnBetaSlow() float32 {
 	return 0
 }
 
+func (x *ModelOptions) GetType() string {
+	if x != nil {
+		return x.Type
+	}
+	return ""
+}
+
 type Result struct {
 	state         protoimpl.MessageState
 	sizeCache     protoimpl.SizeCache
@@ -1696,7 +1703,7 @@ var file_backend_proto_rawDesc = []byte{
 	0x65, 0x73, 0x18, 0x2a, 0x20, 0x03, 0x28, 0x09, 0x52, 0x06, 0x49, 0x6d, 0x61, 0x67, 0x65, 0x73,
 	0x22, 0x21, 0x0a, 0x05, 0x52, 0x65, 0x70, 0x6c, 0x79, 0x12, 0x18, 0x0a, 0x07, 0x6d, 0x65, 0x73,
 	0x73, 0x61, 0x67, 0x65, 0x18, 0x01, 0x20, 0x01, 0x28, 0x0c, 0x52, 0x07, 0x6d, 0x65, 0x73, 0x73,
-	0x61, 0x67, 0x65, 0x22, 0xcc, 0x0b, 0x0a, 0x0c, 0x4d, 0x6f, 0x64, 0x65, 0x6c, 0x4f, 0x70, 0x74,
+	0x61, 0x67, 0x65, 0x22, 0xe0, 0x0b, 0x0a, 0x0c, 0x4d, 0x6f, 0x64, 0x65, 0x6c, 0x4f, 0x70, 0x74,
 	0x69, 0x6f, 0x6e, 0x73, 0x12, 0x14, 0x0a, 0x05, 0x4d, 0x6f, 0x64, 0x65, 0x6c, 0x18, 0x01, 0x20,
 	0x01, 0x28, 0x09, 0x52, 0x05, 0x4d, 0x6f, 0x64, 0x65, 0x6c, 0x12, 0x20, 0x0a, 0x0b, 0x43, 0x6f,
 	0x6e, 0x74, 0x65, 0x78, 0x74, 0x53, 0x69, 0x7a, 0x65, 0x18, 0x02, 0x20, 0x01, 0x28, 0x05, 0x52,
@@ -1789,131 +1796,132 @@ var file_backend_proto_rawDesc = []byte{
 	0x52, 0x0c, 0x59, 0x61, 0x72, 0x6e, 0x42, 0x65, 0x74, 0x61, 0x46, 0x61, 0x73, 0x74, 0x12, 0x22,
 	0x0a, 0x0c, 0x59, 0x61, 0x72, 0x6e, 0x42, 0x65, 0x74, 0x61, 0x53, 0x6c, 0x6f, 0x77, 0x18, 0x2f,
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-	0x6f, 0x77, 0x22, 0x3c, 0x0a, 0x06, 0x52, 0x65, 0x73, 0x75, 0x6c, 0x74, 0x12, 0x18, 0x0a, 0x07,
-	0x6d, 0x65, 0x73, 0x73, 0x61, 0x67, 0x65, 0x18, 0x01, 0x20, 0x01, 0x28, 0x09, 0x52, 0x07, 0x6d,
-	0x65, 0x73, 0x73, 0x61, 0x67, 0x65, 0x12, 0x18, 0x0a, 0x07, 0x73, 0x75, 0x63, 0x63, 0x65, 0x73,
-	0x73, 0x18, 0x02, 0x20, 0x01, 0x28, 0x08, 0x52, 0x07, 0x73, 0x75, 0x63, 0x63, 0x65, 0x73, 0x73,
-	0x22, 0x31, 0x0a, 0x0f, 0x45, 0x6d, 0x62, 0x65, 0x64, 0x64, 0x69, 0x6e, 0x67, 0x52, 0x65, 0x73,
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-	0x6e, 0x67, 0x73, 0x22, 0x5b, 0x0a, 0x11, 0x54, 0x72, 0x61, 0x6e, 0x73, 0x63, 0x72, 0x69, 0x70,
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+	0x6f, 0x62, 0x06, 0x70, 0x72, 0x6f, 0x74, 0x6f, 0x33,
 }
 
 var (

pkg/grpc/proto/backend_grpc.pb.go

@@ -1,7 +1,7 @@
 // Code generated by protoc-gen-go-grpc. DO NOT EDIT.
 // versions:
 // - protoc-gen-go-grpc v1.2.0
-// - protoc             v3.6.1
+// - protoc             v4.23.4
 // source: backend.proto
 
 package proto

pkg/startup/model_preload.go

@@ -14,10 +14,22 @@ import (
 // PreloadModelsConfigurations will preload models from the given list of URLs
 // It will download the model if it is not already present in the model path
 // It will also try to resolve if the model is an embedded model YAML configuration
-func PreloadModelsConfigurations(modelPath string, models ...string) {
+func PreloadModelsConfigurations(modelLibraryURL string, modelPath string, models ...string) {
 	for _, url := range models {
-		url = embedded.ModelShortURL(url)
 
+		// As a best effort, try to resolve the model from the remote library
+		// if it's not resolved we try with the other method below
+		if modelLibraryURL != "" {
+			lib, err := embedded.GetRemoteLibraryShorteners(modelLibraryURL)
+			if err == nil {
+				if lib[url] != "" {
+					log.Debug().Msgf("[startup] model configuration is defined remotely: %s (%s)", url, lib[url])
+					url = lib[url]
+				}
+			}
+		}
+
+		url = embedded.ModelShortURL(url)
 		switch {
 		case embedded.ExistsInModelsLibrary(url):
 			modelYAML, err := embedded.ResolveContent(url)

pkg/startup/model_preload_test.go

@@ -15,13 +15,29 @@ import (
 var _ = Describe("Preload test", func() {
 
 	Context("Preloading from strings", func() {
+		It("loads from remote url", func() {
+			tmpdir, err := os.MkdirTemp("", "")
+			Expect(err).ToNot(HaveOccurred())
+			libraryURL := "https://raw.githubusercontent.com/mudler/LocalAI/master/embedded/model_library.yaml"
+			fileName := fmt.Sprintf("%s.yaml", "1701d57f28d47552516c2b6ecc3cc719")
+
+			PreloadModelsConfigurations(libraryURL, tmpdir, "phi-2")
+
+			resultFile := filepath.Join(tmpdir, fileName)
+
+			content, err := os.ReadFile(resultFile)
+			Expect(err).ToNot(HaveOccurred())
+
+			Expect(string(content)).To(ContainSubstring("name: phi-2"))
+		})
+
 		It("loads from embedded full-urls", func() {
 			tmpdir, err := os.MkdirTemp("", "")
 			Expect(err).ToNot(HaveOccurred())
 			url := "https://raw.githubusercontent.com/mudler/LocalAI/master/examples/configurations/phi-2.yaml"
 			fileName := fmt.Sprintf("%s.yaml", utils.MD5(url))
 
-			PreloadModelsConfigurations(tmpdir, url)
+			PreloadModelsConfigurations("", tmpdir, url)
 
 			resultFile := filepath.Join(tmpdir, fileName)
 
@@ -35,7 +51,7 @@ var _ = Describe("Preload test", func() {
 			Expect(err).ToNot(HaveOccurred())
 			url := "phi-2"
 
-			PreloadModelsConfigurations(tmpdir, url)
+			PreloadModelsConfigurations("", tmpdir, url)
 
 			entry, err := os.ReadDir(tmpdir)
 			Expect(err).ToNot(HaveOccurred())
@@ -53,7 +69,7 @@ var _ = Describe("Preload test", func() {
 			url := "mistral-openorca"
 			fileName := fmt.Sprintf("%s.yaml", utils.MD5(url))
 
-			PreloadModelsConfigurations(tmpdir, url)
+			PreloadModelsConfigurations("", tmpdir, url)
 
 			resultFile := filepath.Join(tmpdir, fileName)