LocalAI/main.go
Jesús Espino e91f660eb1
feat(metrics): Adding initial support for prometheus metrics ()
* feat(metrics): Adding initial support for prometheus metrics

* Fixing CI

* run go mod tidy
2023-10-17 18:22:53 +02:00

428 lines
12 KiB
Go

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