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package cli |
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import ( |
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"context" |
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"errors" |
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"fmt" |
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"github.com/mudler/LocalAI/core/backend" |
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cliContext "github.com/mudler/LocalAI/core/cli/context" |
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"github.com/mudler/LocalAI/core/config" |
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"github.com/mudler/LocalAI/pkg/model" |
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"github.com/rs/zerolog/log" |
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) |
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type TranscriptCMD struct { |
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Filename string `arg:""` |
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Backend string `short:"b" default:"whisper" help:"Backend to run the transcription model"` |
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Model string `short:"m" required:"" help:"Model name to run the TTS"` |
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Language string `short:"l" help:"Language of the audio file"` |
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Translate bool `short:"c" help:"Translate the transcription to english"` |
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Threads int `short:"t" default:"1" help:"Number of threads used for parallel computation"` |
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ModelsPath string `env:"LOCALAI_MODELS_PATH,MODELS_PATH" type:"path" default:"${basepath}/models" help:"Path containing models used for inferencing" group:"storage"` |
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BackendAssetsPath string `env:"LOCALAI_BACKEND_ASSETS_PATH,BACKEND_ASSETS_PATH" type:"path" default:"/tmp/localai/backend_data" help:"Path used to extract libraries that are required by some of the backends in runtime" group:"storage"` |
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} |
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func (t *TranscriptCMD) Run(ctx *cliContext.Context) error { |
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opts := &config.ApplicationConfig{ |
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ModelPath: t.ModelsPath, |
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Context: context.Background(), |
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AssetsDestination: t.BackendAssetsPath, |
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} |
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cl := config.NewBackendConfigLoader(t.ModelsPath) |
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ml := model.NewModelLoader(opts.ModelPath) |
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if err := cl.LoadBackendConfigsFromPath(t.ModelsPath); err != nil { |
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return err |
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} |
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c, exists := cl.GetBackendConfig(t.Model) |
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if !exists { |
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return errors.New("model not found") |
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} |
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c.Threads = &t.Threads |
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defer func() { |
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err := ml.StopAllGRPC() |
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if err != nil { |
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log.Error().Err(err).Msg("unable to stop all grpc processes") |
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} |
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}() |
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tr, err := backend.ModelTranscription(t.Filename, t.Language, t.Translate, ml, c, opts) |
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if err != nil { |
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return err |
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} |
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for _, segment := range tr.Segments { |
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fmt.Println(segment.Start.String(), "-", segment.Text) |
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} |
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return nil |
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} |
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