LocalAI/main.go

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package main
import (
"encoding/json"
"fmt"
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"os"
"path/filepath"
api "github.com/go-skynet/LocalAI/api"
"github.com/go-skynet/LocalAI/internal"
"github.com/go-skynet/LocalAI/pkg/gallery"
model "github.com/go-skynet/LocalAI/pkg/model"
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"github.com/rs/zerolog"
"github.com/rs/zerolog/log"
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"github.com/urfave/cli/v2"
)
func main() {
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log.Logger = log.Output(zerolog.ConsoleWriter{Out: os.Stderr})
path, err := os.Getwd()
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if err != nil {
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log.Error().Msgf("error: %s", err.Error())
os.Exit(1)
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}
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"},
},
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&cli.BoolFlag{
Name: "debug",
EnvVars: []string{"DEBUG"},
},
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&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,
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},
&cli.StringFlag{
Name: "models-path",
Usage: "Path containing models used for inferencing",
EnvVars: []string{"MODELS_PATH"},
Value: filepath.Join(path, "models"),
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},
&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"},
},
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&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.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,
},
},
Description: `
LocalAI is a drop-in replacement OpenAI API which runs inference locally.
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Some of the models compatible are:
- Vicuna
- Koala
- GPT4ALL
- GPT4ALL-J
- Cerebras
- Alpaca
- StableLM (ggml quantized)
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It uses llama.cpp, ggml and gpt4all as backend with golang c bindings.
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`,
UsageText: `local-ai [options]`,
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Copyright: "go-skynet authors",
Action: func(ctx *cli.Context) error {
fmt.Printf("Starting LocalAI using %d threads, with models path: %s\n", ctx.Int("threads"), ctx.String("models-path"))
galls := ctx.String("galleries")
var galleries []gallery.Gallery
err := json.Unmarshal([]byte(galls), &galleries)
fmt.Println(err)
app, err := api.App(
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api.WithConfigFile(ctx.String("config-file")),
api.WithGalleries(galleries),
api.WithJSONStringPreload(ctx.String("preload-models")),
api.WithYAMLConfigPreload(ctx.String("preload-models-config")),
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api.WithModelLoader(model.NewModelLoader(ctx.String("models-path"))),
api.WithContextSize(ctx.Int("context-size")),
api.WithDebug(ctx.Bool("debug")),
api.WithImageDir(ctx.String("image-path")),
api.WithAudioDir(ctx.String("audio-path")),
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api.WithF16(ctx.Bool("f16")),
api.WithDisableMessage(false),
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api.WithCors(ctx.Bool("cors")),
api.WithCorsAllowOrigins(ctx.String("cors-allow-origins")),
api.WithThreads(ctx.Int("threads")),
api.WithBackendAssets(backendAssets),
api.WithBackendAssetsOutput(ctx.String("backend-assets-path")),
api.WithUploadLimitMB(ctx.Int("upload-limit")))
if err != nil {
return err
}
return app.Listen(ctx.String("address"))
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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)
}
}