mirror of https://github.com/mudler/LocalAI.git
488 lines
14 KiB
Go
488 lines
14 KiB
Go
package main
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import (
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"context"
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"encoding/json"
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"errors"
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"fmt"
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"os"
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"os/signal"
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"path/filepath"
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"strings"
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"syscall"
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"time"
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api "github.com/go-skynet/LocalAI/api"
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"github.com/go-skynet/LocalAI/api/backend"
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config "github.com/go-skynet/LocalAI/api/config"
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"github.com/go-skynet/LocalAI/api/options"
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"github.com/go-skynet/LocalAI/internal"
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"github.com/go-skynet/LocalAI/metrics"
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"github.com/go-skynet/LocalAI/pkg/gallery"
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model "github.com/go-skynet/LocalAI/pkg/model"
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"github.com/rs/zerolog"
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"github.com/rs/zerolog/log"
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progressbar "github.com/schollz/progressbar/v3"
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"github.com/urfave/cli/v2"
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)
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func main() {
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log.Logger = log.Output(zerolog.ConsoleWriter{Out: os.Stderr})
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// clean up process
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go func() {
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c := make(chan os.Signal, 1) // we need to reserve to buffer size 1, so the notifier are not blocked
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signal.Notify(c, os.Interrupt, syscall.SIGTERM)
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<-c
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os.Exit(1)
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}()
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path, err := os.Getwd()
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if err != nil {
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log.Error().Msgf("error: %s", err.Error())
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os.Exit(1)
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}
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app := &cli.App{
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Name: "LocalAI",
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Version: internal.PrintableVersion(),
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Usage: "OpenAI compatible API for running LLaMA/GPT models locally on CPU with consumer grade hardware.",
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Flags: []cli.Flag{
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&cli.BoolFlag{
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Name: "f16",
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EnvVars: []string{"F16"},
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},
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&cli.BoolFlag{
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Name: "autoload-galleries",
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EnvVars: []string{"AUTOLOAD_GALLERIES"},
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},
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&cli.BoolFlag{
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Name: "debug",
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EnvVars: []string{"DEBUG"},
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},
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&cli.BoolFlag{
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Name: "single-active-backend",
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EnvVars: []string{"SINGLE_ACTIVE_BACKEND"},
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Usage: "Allow only one backend to be running.",
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},
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&cli.BoolFlag{
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Name: "parallel-requests",
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EnvVars: []string{"PARALLEL_REQUESTS"},
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Usage: "Enable backends to handle multiple requests in parallel. This is for backends that supports multiple requests in parallel, like llama.cpp or vllm",
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},
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&cli.BoolFlag{
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Name: "cors",
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EnvVars: []string{"CORS"},
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},
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&cli.StringFlag{
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Name: "cors-allow-origins",
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EnvVars: []string{"CORS_ALLOW_ORIGINS"},
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},
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&cli.IntFlag{
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Name: "threads",
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Usage: "Number of threads used for parallel computation. Usage of the number of physical cores in the system is suggested.",
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EnvVars: []string{"THREADS"},
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Value: 4,
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},
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&cli.StringFlag{
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Name: "models-path",
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Usage: "Path containing models used for inferencing",
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EnvVars: []string{"MODELS_PATH"},
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Value: filepath.Join(path, "models"),
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},
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&cli.StringFlag{
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Name: "galleries",
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Usage: "JSON list of galleries",
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EnvVars: []string{"GALLERIES"},
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},
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&cli.StringFlag{
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Name: "preload-models",
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Usage: "A List of models to apply in JSON at start",
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EnvVars: []string{"PRELOAD_MODELS"},
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},
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&cli.StringSliceFlag{
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Name: "models",
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Usage: "A List of models URLs configurations.",
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EnvVars: []string{"MODELS"},
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},
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&cli.StringFlag{
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Name: "preload-models-config",
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Usage: "A List of models to apply at startup. Path to a YAML config file",
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EnvVars: []string{"PRELOAD_MODELS_CONFIG"},
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},
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&cli.StringFlag{
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Name: "config-file",
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Usage: "Config file",
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EnvVars: []string{"CONFIG_FILE"},
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},
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&cli.StringFlag{
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Name: "address",
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Usage: "Bind address for the API server.",
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EnvVars: []string{"ADDRESS"},
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Value: ":8080",
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},
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&cli.StringFlag{
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Name: "image-path",
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Usage: "Image directory",
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EnvVars: []string{"IMAGE_PATH"},
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Value: "/tmp/generated/images",
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},
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&cli.StringFlag{
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Name: "audio-path",
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Usage: "audio directory",
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EnvVars: []string{"AUDIO_PATH"},
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Value: "/tmp/generated/audio",
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},
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&cli.StringFlag{
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Name: "backend-assets-path",
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Usage: "Path used to extract libraries that are required by some of the backends in runtime.",
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EnvVars: []string{"BACKEND_ASSETS_PATH"},
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Value: "/tmp/localai/backend_data",
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},
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&cli.StringSliceFlag{
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Name: "external-grpc-backends",
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Usage: "A list of external grpc backends",
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EnvVars: []string{"EXTERNAL_GRPC_BACKENDS"},
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},
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&cli.IntFlag{
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Name: "context-size",
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Usage: "Default context size of the model",
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EnvVars: []string{"CONTEXT_SIZE"},
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Value: 512,
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},
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&cli.IntFlag{
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Name: "upload-limit",
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Usage: "Default upload-limit. MB",
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EnvVars: []string{"UPLOAD_LIMIT"},
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Value: 15,
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},
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&cli.StringSliceFlag{
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Name: "api-keys",
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Usage: "List of API Keys to enable API authentication. When this is set, all the requests must be authenticated with one of these API keys.",
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EnvVars: []string{"API_KEY"},
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},
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&cli.BoolFlag{
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Name: "enable-watchdog-idle",
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Usage: "Enable watchdog for stopping idle backends. This will stop the backends if are in idle state for too long.",
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EnvVars: []string{"WATCHDOG_IDLE"},
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Value: false,
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},
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&cli.BoolFlag{
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Name: "enable-watchdog-busy",
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Usage: "Enable watchdog for stopping busy backends that exceed a defined threshold.",
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EnvVars: []string{"WATCHDOG_BUSY"},
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Value: false,
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},
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&cli.StringFlag{
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Name: "watchdog-busy-timeout",
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Usage: "Watchdog timeout. This will restart the backend if it crashes.",
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EnvVars: []string{"WATCHDOG_BUSY_TIMEOUT"},
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Value: "5m",
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},
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&cli.StringFlag{
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Name: "watchdog-idle-timeout",
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Usage: "Watchdog idle timeout. This will restart the backend if it crashes.",
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EnvVars: []string{"WATCHDOG_IDLE_TIMEOUT"},
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Value: "15m",
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},
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&cli.BoolFlag{
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Name: "preload-backend-only",
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Usage: "If set, the api is NOT launched, and only the preloaded models / backends are started. This is intended for multi-node setups.",
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EnvVars: []string{"PRELOAD_BACKEND_ONLY"},
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Value: false,
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},
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},
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Description: `
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LocalAI is a drop-in replacement OpenAI API which runs inference locally.
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Some of the models compatible are:
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- Vicuna
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- Koala
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- GPT4ALL
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- GPT4ALL-J
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- Cerebras
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- Alpaca
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- StableLM (ggml quantized)
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For a list of compatible model, check out: https://localai.io/model-compatibility/index.html
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`,
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UsageText: `local-ai [options]`,
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Copyright: "Ettore Di Giacinto",
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Action: func(ctx *cli.Context) error {
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opts := []options.AppOption{
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options.WithConfigFile(ctx.String("config-file")),
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options.WithJSONStringPreload(ctx.String("preload-models")),
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options.WithYAMLConfigPreload(ctx.String("preload-models-config")),
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options.WithModelLoader(model.NewModelLoader(ctx.String("models-path"))),
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options.WithContextSize(ctx.Int("context-size")),
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options.WithDebug(ctx.Bool("debug")),
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options.WithImageDir(ctx.String("image-path")),
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options.WithAudioDir(ctx.String("audio-path")),
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options.WithF16(ctx.Bool("f16")),
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options.WithStringGalleries(ctx.String("galleries")),
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options.WithDisableMessage(false),
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options.WithCors(ctx.Bool("cors")),
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options.WithCorsAllowOrigins(ctx.String("cors-allow-origins")),
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options.WithThreads(ctx.Int("threads")),
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options.WithBackendAssets(backendAssets),
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options.WithBackendAssetsOutput(ctx.String("backend-assets-path")),
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options.WithUploadLimitMB(ctx.Int("upload-limit")),
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options.WithApiKeys(ctx.StringSlice("api-keys")),
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options.WithModelsURL(append(ctx.StringSlice("models"), ctx.Args().Slice()...)...),
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}
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idleWatchDog := ctx.Bool("enable-watchdog-idle")
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busyWatchDog := ctx.Bool("enable-watchdog-busy")
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if idleWatchDog || busyWatchDog {
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opts = append(opts, options.EnableWatchDog)
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if idleWatchDog {
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opts = append(opts, options.EnableWatchDogIdleCheck)
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dur, err := time.ParseDuration(ctx.String("watchdog-idle-timeout"))
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if err != nil {
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return err
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}
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opts = append(opts, options.SetWatchDogIdleTimeout(dur))
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}
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if busyWatchDog {
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opts = append(opts, options.EnableWatchDogBusyCheck)
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dur, err := time.ParseDuration(ctx.String("watchdog-busy-timeout"))
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if err != nil {
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return err
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}
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opts = append(opts, options.SetWatchDogBusyTimeout(dur))
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}
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}
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if ctx.Bool("parallel-requests") {
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opts = append(opts, options.EnableParallelBackendRequests)
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}
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if ctx.Bool("single-active-backend") {
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opts = append(opts, options.EnableSingleBackend)
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}
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externalgRPC := ctx.StringSlice("external-grpc-backends")
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// split ":" to get backend name and the uri
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for _, v := range externalgRPC {
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backend := v[:strings.IndexByte(v, ':')]
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uri := v[strings.IndexByte(v, ':')+1:]
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opts = append(opts, options.WithExternalBackend(backend, uri))
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}
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if ctx.Bool("autoload-galleries") {
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opts = append(opts, options.EnableGalleriesAutoload)
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}
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if ctx.Bool("preload-backend-only") {
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_, _, err := api.Startup(opts...)
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return err
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}
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metrics, err := metrics.SetupMetrics()
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if err != nil {
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return err
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}
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opts = append(opts, options.WithMetrics(metrics))
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app, err := api.App(opts...)
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if err != nil {
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return err
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}
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return app.Listen(ctx.String("address"))
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},
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Commands: []*cli.Command{
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{
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Name: "models",
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Usage: "List or install models",
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Subcommands: []*cli.Command{
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{
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Name: "list",
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Usage: "List the models avaiable in your galleries",
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Action: func(ctx *cli.Context) error {
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var galleries []gallery.Gallery
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if err := json.Unmarshal([]byte(ctx.String("galleries")), &galleries); err != nil {
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log.Error().Msgf("unable to load galleries: %s", err.Error())
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}
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models, err := gallery.AvailableGalleryModels(galleries, ctx.String("models-path"))
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if err != nil {
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return err
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}
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for _, model := range models {
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if model.Installed {
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fmt.Printf(" * %s@%s (installed)\n", model.Gallery.Name, model.Name)
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} else {
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fmt.Printf(" - %s@%s\n", model.Gallery.Name, model.Name)
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}
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}
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return nil
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},
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},
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{
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Name: "install",
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Usage: "Install a model from the gallery",
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Action: func(ctx *cli.Context) error {
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modelName := ctx.Args().First()
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var galleries []gallery.Gallery
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if err := json.Unmarshal([]byte(ctx.String("galleries")), &galleries); err != nil {
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log.Error().Msgf("unable to load galleries: %s", err.Error())
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}
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progressBar := progressbar.NewOptions(
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1000,
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progressbar.OptionSetDescription(fmt.Sprintf("downloading model %s", modelName)),
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progressbar.OptionShowBytes(false),
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progressbar.OptionClearOnFinish(),
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)
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progressCallback := func(fileName string, current string, total string, percentage float64) {
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progressBar.Set(int(percentage * 10))
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}
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err = gallery.InstallModelFromGallery(galleries, modelName, ctx.String("models-path"), gallery.GalleryModel{}, progressCallback)
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if err != nil {
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return err
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}
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return nil
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},
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},
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},
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},
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{
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Name: "tts",
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Usage: "Convert text to speech",
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Flags: []cli.Flag{
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&cli.StringFlag{
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Name: "backend",
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Value: "piper",
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Aliases: []string{"b"},
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Usage: "Backend to run the TTS model",
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},
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&cli.StringFlag{
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Name: "model",
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Aliases: []string{"m"},
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Usage: "Model name to run the TTS",
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Required: true,
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},
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&cli.StringFlag{
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Name: "output-file",
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Aliases: []string{"o"},
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Usage: "The path to write the output wav file",
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},
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},
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Action: func(ctx *cli.Context) error {
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modelOption := ctx.String("model")
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if modelOption == "" {
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return errors.New("--model parameter is required")
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}
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backendOption := ctx.String("backend")
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if backendOption == "" {
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backendOption = "piper"
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}
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outputFile := ctx.String("output-file")
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outputDir := ctx.String("backend-assets-path")
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if outputFile != "" {
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outputDir = filepath.Dir(outputFile)
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}
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text := strings.Join(ctx.Args().Slice(), " ")
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opts := &options.Option{
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Loader: model.NewModelLoader(ctx.String("models-path")),
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Context: context.Background(),
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AudioDir: outputDir,
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AssetsDestination: ctx.String("backend-assets-path"),
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}
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defer opts.Loader.StopAllGRPC()
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filePath, _, err := backend.ModelTTS(backendOption, text, modelOption, opts.Loader, opts)
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if err != nil {
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return err
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}
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if outputFile != "" {
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if err := os.Rename(filePath, outputFile); err != nil {
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return err
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}
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fmt.Printf("Generate file %s\n", outputFile)
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} else {
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fmt.Printf("Generate file %s\n", filePath)
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}
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return nil
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},
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},
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{
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Name: "transcript",
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Usage: "Convert audio to text",
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Flags: []cli.Flag{
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&cli.StringFlag{
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Name: "backend",
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Value: "whisper",
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Aliases: []string{"b"},
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Usage: "Backend to run the transcription model",
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},
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&cli.StringFlag{
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Name: "model",
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Aliases: []string{"m"},
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Usage: "Model name to run the transcription",
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},
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&cli.StringFlag{
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Name: "language",
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Aliases: []string{"l"},
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Usage: "Language of the audio file",
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},
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&cli.IntFlag{
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Name: "threads",
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Aliases: []string{"t"},
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Usage: "Threads to use",
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Value: 1,
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},
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&cli.StringFlag{
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Name: "output-file",
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Aliases: []string{"o"},
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Usage: "The path to write the output wav file",
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},
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},
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Action: func(ctx *cli.Context) error {
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modelOption := ctx.String("model")
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filename := ctx.Args().First()
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language := ctx.String("language")
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threads := ctx.Int("threads")
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opts := &options.Option{
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Loader: model.NewModelLoader(ctx.String("models-path")),
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Context: context.Background(),
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AssetsDestination: ctx.String("backend-assets-path"),
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}
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cl := config.NewConfigLoader()
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if err := cl.LoadConfigs(ctx.String("models-path")); err != nil {
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return err
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}
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c, exists := cl.GetConfig(modelOption)
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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 = threads
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defer opts.Loader.StopAllGRPC()
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tr, err := backend.ModelTranscription(filename, language, opts.Loader, 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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},
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},
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}
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err = app.Run(os.Args)
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if err != nil {
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log.Error().Msgf("error: %s", err.Error())
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os.Exit(1)
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}
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}
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