mirror of
https://github.com/mudler/LocalAI.git
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transformers: correctly load automodels (#1643)
* backends(transformers): use AutoModel with LLM types * examples: animagine-xl * Add codellama examples
This commit is contained in:
parent
3733250b3c
commit
cb7512734d
@ -63,6 +63,8 @@ func gRPCModelOpts(c config.Config) *pb.ModelOptions {
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F16Memory: c.F16,
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MLock: c.MMlock,
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RopeFreqBase: c.RopeFreqBase,
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RopeScaling: c.RopeScaling,
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Type: c.ModelType,
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RopeFreqScale: c.RopeFreqScale,
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NUMA: c.NUMA,
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Embeddings: c.Embeddings,
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@ -128,7 +128,9 @@ type LLMConfig struct {
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Quantization string `yaml:"quantization"`
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MMProj string `yaml:"mmproj"`
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RopeScaling string `yaml:"rope_scaling"`
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RopeScaling string `yaml:"rope_scaling"`
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ModelType string `yaml:"type"`
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YarnExtFactor float32 `yaml:"yarn_ext_factor"`
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YarnAttnFactor float32 `yaml:"yarn_attn_factor"`
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YarnBetaFast float32 `yaml:"yarn_beta_fast"`
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@ -134,6 +134,8 @@ message ModelOptions {
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float YarnAttnFactor = 45;
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float YarnBetaFast = 46;
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float YarnBetaSlow = 47;
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string Type = 49;
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}
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message Result {
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457
backend/backend_grpc.pb.go
Normal file
457
backend/backend_grpc.pb.go
Normal file
@ -0,0 +1,457 @@
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// Code generated by protoc-gen-go-grpc. DO NOT EDIT.
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// versions:
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// - protoc-gen-go-grpc v1.2.0
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// - protoc v4.23.4
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// source: backend/backend.proto
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package proto
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import (
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context "context"
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grpc "google.golang.org/grpc"
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codes "google.golang.org/grpc/codes"
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status "google.golang.org/grpc/status"
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)
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// This is a compile-time assertion to ensure that this generated file
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// is compatible with the grpc package it is being compiled against.
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// Requires gRPC-Go v1.32.0 or later.
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const _ = grpc.SupportPackageIsVersion7
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// BackendClient is the client API for Backend service.
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//
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// 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.
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type BackendClient interface {
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Health(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*Reply, error)
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Predict(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*Reply, error)
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LoadModel(ctx context.Context, in *ModelOptions, opts ...grpc.CallOption) (*Result, error)
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PredictStream(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (Backend_PredictStreamClient, error)
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Embedding(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*EmbeddingResult, error)
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GenerateImage(ctx context.Context, in *GenerateImageRequest, opts ...grpc.CallOption) (*Result, error)
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AudioTranscription(ctx context.Context, in *TranscriptRequest, opts ...grpc.CallOption) (*TranscriptResult, error)
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TTS(ctx context.Context, in *TTSRequest, opts ...grpc.CallOption) (*Result, error)
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TokenizeString(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*TokenizationResponse, error)
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Status(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*StatusResponse, error)
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}
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type backendClient struct {
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cc grpc.ClientConnInterface
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}
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func NewBackendClient(cc grpc.ClientConnInterface) BackendClient {
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return &backendClient{cc}
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}
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func (c *backendClient) Health(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*Reply, error) {
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out := new(Reply)
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err := c.cc.Invoke(ctx, "/backend.Backend/Health", in, out, opts...)
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if err != nil {
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return nil, err
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}
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return out, nil
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}
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func (c *backendClient) Predict(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*Reply, error) {
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out := new(Reply)
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err := c.cc.Invoke(ctx, "/backend.Backend/Predict", in, out, opts...)
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if err != nil {
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return nil, err
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}
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return out, nil
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}
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func (c *backendClient) LoadModel(ctx context.Context, in *ModelOptions, opts ...grpc.CallOption) (*Result, error) {
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out := new(Result)
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err := c.cc.Invoke(ctx, "/backend.Backend/LoadModel", in, out, opts...)
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if err != nil {
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return nil, err
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}
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return out, nil
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}
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func (c *backendClient) PredictStream(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (Backend_PredictStreamClient, error) {
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stream, err := c.cc.NewStream(ctx, &Backend_ServiceDesc.Streams[0], "/backend.Backend/PredictStream", opts...)
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if err != nil {
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return nil, err
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}
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x := &backendPredictStreamClient{stream}
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if err := x.ClientStream.SendMsg(in); err != nil {
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return nil, err
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}
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if err := x.ClientStream.CloseSend(); err != nil {
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return nil, err
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}
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return x, nil
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}
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type Backend_PredictStreamClient interface {
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Recv() (*Reply, error)
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grpc.ClientStream
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}
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type backendPredictStreamClient struct {
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grpc.ClientStream
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}
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func (x *backendPredictStreamClient) Recv() (*Reply, error) {
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m := new(Reply)
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if err := x.ClientStream.RecvMsg(m); err != nil {
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return nil, err
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}
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return m, nil
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}
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func (c *backendClient) Embedding(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*EmbeddingResult, error) {
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out := new(EmbeddingResult)
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err := c.cc.Invoke(ctx, "/backend.Backend/Embedding", in, out, opts...)
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if err != nil {
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return nil, err
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}
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return out, nil
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}
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func (c *backendClient) GenerateImage(ctx context.Context, in *GenerateImageRequest, opts ...grpc.CallOption) (*Result, error) {
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out := new(Result)
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err := c.cc.Invoke(ctx, "/backend.Backend/GenerateImage", in, out, opts...)
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if err != nil {
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return nil, err
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}
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return out, nil
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}
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func (c *backendClient) AudioTranscription(ctx context.Context, in *TranscriptRequest, opts ...grpc.CallOption) (*TranscriptResult, error) {
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out := new(TranscriptResult)
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err := c.cc.Invoke(ctx, "/backend.Backend/AudioTranscription", in, out, opts...)
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if err != nil {
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return nil, err
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}
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return out, nil
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}
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func (c *backendClient) TTS(ctx context.Context, in *TTSRequest, opts ...grpc.CallOption) (*Result, error) {
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out := new(Result)
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err := c.cc.Invoke(ctx, "/backend.Backend/TTS", in, out, opts...)
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if err != nil {
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return nil, err
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}
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return out, nil
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}
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func (c *backendClient) TokenizeString(ctx context.Context, in *PredictOptions, opts ...grpc.CallOption) (*TokenizationResponse, error) {
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out := new(TokenizationResponse)
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err := c.cc.Invoke(ctx, "/backend.Backend/TokenizeString", in, out, opts...)
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if err != nil {
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return nil, err
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}
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return out, nil
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}
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func (c *backendClient) Status(ctx context.Context, in *HealthMessage, opts ...grpc.CallOption) (*StatusResponse, error) {
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out := new(StatusResponse)
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err := c.cc.Invoke(ctx, "/backend.Backend/Status", in, out, opts...)
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if err != nil {
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return nil, err
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}
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return out, nil
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}
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// BackendServer is the server API for Backend service.
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// All implementations must embed UnimplementedBackendServer
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// for forward compatibility
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type BackendServer interface {
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Health(context.Context, *HealthMessage) (*Reply, error)
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Predict(context.Context, *PredictOptions) (*Reply, error)
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LoadModel(context.Context, *ModelOptions) (*Result, error)
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PredictStream(*PredictOptions, Backend_PredictStreamServer) error
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Embedding(context.Context, *PredictOptions) (*EmbeddingResult, error)
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GenerateImage(context.Context, *GenerateImageRequest) (*Result, error)
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AudioTranscription(context.Context, *TranscriptRequest) (*TranscriptResult, error)
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TTS(context.Context, *TTSRequest) (*Result, error)
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TokenizeString(context.Context, *PredictOptions) (*TokenizationResponse, error)
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Status(context.Context, *HealthMessage) (*StatusResponse, error)
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mustEmbedUnimplementedBackendServer()
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}
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// UnimplementedBackendServer must be embedded to have forward compatible implementations.
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type UnimplementedBackendServer struct {
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}
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func (UnimplementedBackendServer) Health(context.Context, *HealthMessage) (*Reply, error) {
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return nil, status.Errorf(codes.Unimplemented, "method Health not implemented")
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}
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func (UnimplementedBackendServer) Predict(context.Context, *PredictOptions) (*Reply, error) {
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return nil, status.Errorf(codes.Unimplemented, "method Predict not implemented")
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}
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func (UnimplementedBackendServer) LoadModel(context.Context, *ModelOptions) (*Result, error) {
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return nil, status.Errorf(codes.Unimplemented, "method LoadModel not implemented")
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}
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func (UnimplementedBackendServer) PredictStream(*PredictOptions, Backend_PredictStreamServer) error {
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return status.Errorf(codes.Unimplemented, "method PredictStream not implemented")
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}
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func (UnimplementedBackendServer) Embedding(context.Context, *PredictOptions) (*EmbeddingResult, error) {
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return nil, status.Errorf(codes.Unimplemented, "method Embedding not implemented")
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}
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func (UnimplementedBackendServer) GenerateImage(context.Context, *GenerateImageRequest) (*Result, error) {
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return nil, status.Errorf(codes.Unimplemented, "method GenerateImage not implemented")
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}
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func (UnimplementedBackendServer) AudioTranscription(context.Context, *TranscriptRequest) (*TranscriptResult, error) {
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return nil, status.Errorf(codes.Unimplemented, "method AudioTranscription not implemented")
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}
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func (UnimplementedBackendServer) TTS(context.Context, *TTSRequest) (*Result, error) {
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return nil, status.Errorf(codes.Unimplemented, "method TTS not implemented")
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}
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func (UnimplementedBackendServer) TokenizeString(context.Context, *PredictOptions) (*TokenizationResponse, error) {
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return nil, status.Errorf(codes.Unimplemented, "method TokenizeString not implemented")
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}
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func (UnimplementedBackendServer) Status(context.Context, *HealthMessage) (*StatusResponse, error) {
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return nil, status.Errorf(codes.Unimplemented, "method Status not implemented")
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}
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func (UnimplementedBackendServer) mustEmbedUnimplementedBackendServer() {}
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// UnsafeBackendServer may be embedded to opt out of forward compatibility for this service.
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// Use of this interface is not recommended, as added methods to BackendServer will
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// result in compilation errors.
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type UnsafeBackendServer interface {
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mustEmbedUnimplementedBackendServer()
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}
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func RegisterBackendServer(s grpc.ServiceRegistrar, srv BackendServer) {
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s.RegisterService(&Backend_ServiceDesc, srv)
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}
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func _Backend_Health_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
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in := new(HealthMessage)
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if err := dec(in); err != nil {
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return nil, err
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}
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if interceptor == nil {
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return srv.(BackendServer).Health(ctx, in)
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}
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info := &grpc.UnaryServerInfo{
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Server: srv,
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FullMethod: "/backend.Backend/Health",
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}
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handler := func(ctx context.Context, req interface{}) (interface{}, error) {
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return srv.(BackendServer).Health(ctx, req.(*HealthMessage))
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}
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return interceptor(ctx, in, info, handler)
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}
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func _Backend_Predict_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
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in := new(PredictOptions)
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if err := dec(in); err != nil {
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return nil, err
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}
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if interceptor == nil {
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return srv.(BackendServer).Predict(ctx, in)
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}
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info := &grpc.UnaryServerInfo{
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Server: srv,
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FullMethod: "/backend.Backend/Predict",
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}
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handler := func(ctx context.Context, req interface{}) (interface{}, error) {
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return srv.(BackendServer).Predict(ctx, req.(*PredictOptions))
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}
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return interceptor(ctx, in, info, handler)
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}
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func _Backend_LoadModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
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in := new(ModelOptions)
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if err := dec(in); err != nil {
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return nil, err
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}
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if interceptor == nil {
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return srv.(BackendServer).LoadModel(ctx, in)
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}
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info := &grpc.UnaryServerInfo{
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Server: srv,
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FullMethod: "/backend.Backend/LoadModel",
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}
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handler := func(ctx context.Context, req interface{}) (interface{}, error) {
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return srv.(BackendServer).LoadModel(ctx, req.(*ModelOptions))
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}
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return interceptor(ctx, in, info, handler)
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}
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func _Backend_PredictStream_Handler(srv interface{}, stream grpc.ServerStream) error {
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m := new(PredictOptions)
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if err := stream.RecvMsg(m); err != nil {
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return err
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}
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return srv.(BackendServer).PredictStream(m, &backendPredictStreamServer{stream})
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}
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type Backend_PredictStreamServer interface {
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Send(*Reply) error
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grpc.ServerStream
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}
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type backendPredictStreamServer struct {
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grpc.ServerStream
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}
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func (x *backendPredictStreamServer) Send(m *Reply) error {
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return x.ServerStream.SendMsg(m)
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}
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func _Backend_Embedding_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
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in := new(PredictOptions)
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if err := dec(in); err != nil {
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return nil, err
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}
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if interceptor == nil {
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return srv.(BackendServer).Embedding(ctx, in)
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}
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info := &grpc.UnaryServerInfo{
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Server: srv,
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FullMethod: "/backend.Backend/Embedding",
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}
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handler := func(ctx context.Context, req interface{}) (interface{}, error) {
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return srv.(BackendServer).Embedding(ctx, req.(*PredictOptions))
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}
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return interceptor(ctx, in, info, handler)
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}
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func _Backend_GenerateImage_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
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in := new(GenerateImageRequest)
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if err := dec(in); err != nil {
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return nil, err
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}
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if interceptor == nil {
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return srv.(BackendServer).GenerateImage(ctx, in)
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}
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info := &grpc.UnaryServerInfo{
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Server: srv,
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FullMethod: "/backend.Backend/GenerateImage",
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}
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handler := func(ctx context.Context, req interface{}) (interface{}, error) {
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return srv.(BackendServer).GenerateImage(ctx, req.(*GenerateImageRequest))
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}
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return interceptor(ctx, in, info, handler)
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}
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func _Backend_AudioTranscription_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
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in := new(TranscriptRequest)
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if err := dec(in); err != nil {
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return nil, err
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}
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if interceptor == nil {
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return srv.(BackendServer).AudioTranscription(ctx, in)
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}
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info := &grpc.UnaryServerInfo{
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Server: srv,
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FullMethod: "/backend.Backend/AudioTranscription",
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}
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handler := func(ctx context.Context, req interface{}) (interface{}, error) {
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return srv.(BackendServer).AudioTranscription(ctx, req.(*TranscriptRequest))
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}
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return interceptor(ctx, in, info, handler)
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}
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func _Backend_TTS_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
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in := new(TTSRequest)
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if err := dec(in); err != nil {
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return nil, err
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}
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if interceptor == nil {
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return srv.(BackendServer).TTS(ctx, in)
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}
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info := &grpc.UnaryServerInfo{
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Server: srv,
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FullMethod: "/backend.Backend/TTS",
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}
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handler := func(ctx context.Context, req interface{}) (interface{}, error) {
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return srv.(BackendServer).TTS(ctx, req.(*TTSRequest))
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}
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return interceptor(ctx, in, info, handler)
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}
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func _Backend_TokenizeString_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
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in := new(PredictOptions)
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if err := dec(in); err != nil {
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return nil, err
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}
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if interceptor == nil {
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return srv.(BackendServer).TokenizeString(ctx, in)
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}
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info := &grpc.UnaryServerInfo{
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Server: srv,
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FullMethod: "/backend.Backend/TokenizeString",
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}
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handler := func(ctx context.Context, req interface{}) (interface{}, error) {
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return srv.(BackendServer).TokenizeString(ctx, req.(*PredictOptions))
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}
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return interceptor(ctx, in, info, handler)
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}
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func _Backend_Status_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
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in := new(HealthMessage)
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if err := dec(in); err != nil {
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return nil, err
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}
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if interceptor == nil {
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return srv.(BackendServer).Status(ctx, in)
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}
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info := &grpc.UnaryServerInfo{
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Server: srv,
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FullMethod: "/backend.Backend/Status",
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}
|
||||
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",
|
||||
}
|
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@ -16,7 +16,7 @@ import backend_pb2_grpc
|
||||
import grpc
|
||||
import torch
|
||||
import torch.cuda
|
||||
from transformers import AutoTokenizer, AutoModel
|
||||
from transformers import AutoTokenizer, AutoModel, AutoModelForCausalLM, set_seed
|
||||
|
||||
_ONE_DAY_IN_SECONDS = 60 * 60 * 24
|
||||
|
||||
@ -68,12 +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
|
||||
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)
|
||||
|
||||
self.tokenizer = AutoTokenizer.from_pretrained(model_name)
|
||||
self.CUDA = False
|
||||
|
||||
if request.CUDA or torch.cuda.is_available():
|
||||
try:
|
||||
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:
|
||||
@ -94,6 +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:
|
||||
@ -120,6 +128,7 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
|
||||
Returns:
|
||||
backend_pb2.Reply: The predict result.
|
||||
"""
|
||||
set_seed(request.Seed)
|
||||
if request.TopP == 0:
|
||||
request.TopP = 0.9
|
||||
|
||||
@ -127,10 +136,13 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
|
||||
if request.Tokens > 0:
|
||||
max_tokens = request.Tokens
|
||||
|
||||
inputs = self.tokenizer.tokenizer(request.Prompt, return_tensors="pt").input_ids
|
||||
outputs = self.model.generate(inputs,max_tokens=max_tokens, temperature=request.Temperature, top_p=request.TopP)
|
||||
inputs = self.tokenizer(request.Prompt, return_tensors="pt").input_ids
|
||||
if self.CUDA:
|
||||
inputs = inputs.to("cuda")
|
||||
|
||||
generated_text = self.tokenizer.tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
|
||||
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, "")
|
||||
|
File diff suppressed because one or more lines are too long
File diff suppressed because one or more lines are too long
@ -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.
|
||||
|
||||
|
@ -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" %}}) | GPU-only | ```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" %}}) | GPU-only | ```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 >}}
|
||||
|
17
embedded/models/animagine-xl.yaml
Normal file
17
embedded/models/animagine-xl.yaml
Normal file
@ -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"
|
||||
}'
|
16
embedded/models/codellama-7b-gguf.yaml
Normal file
16
embedded/models/codellama-7b-gguf.yaml
Normal file
@ -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):"
|
||||
}'
|
14
embedded/models/codellama-7b.yaml
Normal file
14
embedded/models/codellama-7b.yaml
Normal file
@ -0,0 +1,14 @@
|
||||
name: codellama-7b
|
||||
backend: transformers
|
||||
parameters:
|
||||
model: codellama/CodeLlama-7b-hf
|
||||
temperature: 0.2
|
||||
top_k: 40
|
||||
seed: -1
|
||||
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):"
|
||||
}'
|
@ -1,7 +1,7 @@
|
||||
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
|
||||
|
32
embedded/models/transformers-tinyllama.yaml
Normal file
32
embedded/models/transformers-tinyllama.yaml
Normal file
@ -0,0 +1,32 @@
|
||||
name: tinyllama-chat
|
||||
backend: transformers
|
||||
type: AutoModelForCausalLM
|
||||
|
||||
parameters:
|
||||
model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
|
||||
temperature: 0.2
|
||||
top_k: 40
|
||||
seed: -1
|
||||
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
|
||||
}'
|
@ -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,
|
||||
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|
||||
}
|
||||
|
||||
var (
|
||||
|
@ -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
|
||||
|
Loading…
Reference in New Issue
Block a user