mirror of
https://github.com/mudler/LocalAI.git
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eed5706994
Refactor: channel based llm flow and services split --------- Signed-off-by: Dave Lee <dave@gray101.com>
76 lines
2.4 KiB
Go
76 lines
2.4 KiB
Go
package backend
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import (
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"context"
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"fmt"
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"github.com/go-skynet/LocalAI/core/config"
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"github.com/go-skynet/LocalAI/core/schema"
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"github.com/go-skynet/LocalAI/pkg/concurrency"
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"github.com/go-skynet/LocalAI/pkg/grpc/proto"
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"github.com/go-skynet/LocalAI/pkg/model"
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)
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type TranscriptionBackendService struct {
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ml *model.ModelLoader
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bcl *config.BackendConfigLoader
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appConfig *config.ApplicationConfig
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}
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func NewTranscriptionBackendService(ml *model.ModelLoader, bcl *config.BackendConfigLoader, appConfig *config.ApplicationConfig) *TranscriptionBackendService {
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return &TranscriptionBackendService{
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ml: ml,
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bcl: bcl,
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appConfig: appConfig,
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}
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}
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func (tbs *TranscriptionBackendService) Transcribe(request *schema.OpenAIRequest) <-chan concurrency.ErrorOr[*schema.TranscriptionResult] {
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responseChannel := make(chan concurrency.ErrorOr[*schema.TranscriptionResult])
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go func(request *schema.OpenAIRequest) {
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bc, request, err := tbs.bcl.LoadBackendConfigForModelAndOpenAIRequest(request.Model, request, tbs.appConfig)
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if err != nil {
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responseChannel <- concurrency.ErrorOr[*schema.TranscriptionResult]{Error: fmt.Errorf("failed reading parameters from request:%w", err)}
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close(responseChannel)
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return
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}
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tr, err := modelTranscription(request.File, request.Language, tbs.ml, bc, tbs.appConfig)
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if err != nil {
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responseChannel <- concurrency.ErrorOr[*schema.TranscriptionResult]{Error: err}
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close(responseChannel)
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return
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}
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responseChannel <- concurrency.ErrorOr[*schema.TranscriptionResult]{Value: tr}
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close(responseChannel)
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}(request)
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return responseChannel
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}
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func modelTranscription(audio, language string, ml *model.ModelLoader, backendConfig *config.BackendConfig, appConfig *config.ApplicationConfig) (*schema.TranscriptionResult, error) {
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opts := modelOpts(backendConfig, appConfig, []model.Option{
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model.WithBackendString(model.WhisperBackend),
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model.WithModel(backendConfig.Model),
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model.WithContext(appConfig.Context),
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model.WithThreads(uint32(*backendConfig.Threads)),
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model.WithAssetDir(appConfig.AssetsDestination),
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})
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whisperModel, err := ml.BackendLoader(opts...)
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if err != nil {
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return nil, err
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}
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if whisperModel == nil {
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return nil, fmt.Errorf("could not load whisper model")
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}
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return whisperModel.AudioTranscription(context.Background(), &proto.TranscriptRequest{
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Dst: audio,
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Language: language,
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Threads: uint32(*backendConfig.Threads),
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})
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}
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