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feat: various refactorings

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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto 2023-07-15 01:19:43 +02:00
parent f2f1d7fe72
commit 5dcfdbe51d
28 changed files with 2130 additions and 1933 deletions
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108
api/api.go
View File

@ -3,8 +3,13 @@ package api
import (
"errors"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/localai"
"github.com/go-skynet/LocalAI/api/openai"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/internal"
"github.com/go-skynet/LocalAI/pkg/assets"
"github.com/gofiber/fiber/v2"
"github.com/gofiber/fiber/v2/middleware/cors"
"github.com/gofiber/fiber/v2/middleware/logger"
@ -13,18 +18,18 @@ import (
"github.com/rs/zerolog/log"
)
func App(opts ...AppOption) (*fiber.App, error) {
options := newOptions(opts...)
func App(opts ...options.AppOption) (*fiber.App, error) {
options := options.NewOptions(opts...)
zerolog.SetGlobalLevel(zerolog.InfoLevel)
if options.debug {
if options.Debug {
zerolog.SetGlobalLevel(zerolog.DebugLevel)
}
// Return errors as JSON responses
app := fiber.New(fiber.Config{
BodyLimit: options.uploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
DisableStartupMessage: options.disableMessage,
BodyLimit: options.UploadLimitMB * 1024 * 1024, // this is the default limit of 4MB
DisableStartupMessage: options.DisableMessage,
// Override default error handler
ErrorHandler: func(ctx *fiber.Ctx, err error) error {
// Status code defaults to 500
@ -38,44 +43,44 @@ func App(opts ...AppOption) (*fiber.App, error) {
// Send custom error page
return ctx.Status(code).JSON(
ErrorResponse{
Error: &APIError{Message: err.Error(), Code: code},
openai.ErrorResponse{
Error: &openai.APIError{Message: err.Error(), Code: code},
},
)
},
})
if options.debug {
if options.Debug {
app.Use(logger.New(logger.Config{
Format: "[${ip}]:${port} ${status} - ${method} ${path}\n",
}))
}
log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.threads, options.loader.ModelPath)
log.Info().Msgf("Starting LocalAI using %d threads, with models path: %s", options.Threads, options.Loader.ModelPath)
log.Info().Msgf("LocalAI version: %s", internal.PrintableVersion())
cm := NewConfigMerger()
if err := cm.LoadConfigs(options.loader.ModelPath); err != nil {
cm := config.NewConfigLoader()
if err := cm.LoadConfigs(options.Loader.ModelPath); err != nil {
log.Error().Msgf("error loading config files: %s", err.Error())
}
if options.configFile != "" {
if err := cm.LoadConfigFile(options.configFile); err != nil {
if options.ConfigFile != "" {
if err := cm.LoadConfigFile(options.ConfigFile); err != nil {
log.Error().Msgf("error loading config file: %s", err.Error())
}
}
if options.debug {
if options.Debug {
for _, v := range cm.ListConfigs() {
cfg, _ := cm.GetConfig(v)
log.Debug().Msgf("Model: %s (config: %+v)", v, cfg)
}
}
if options.assetsDestination != "" {
if options.AssetsDestination != "" {
// Extract files from the embedded FS
err := assets.ExtractFiles(options.backendAssets, options.assetsDestination)
log.Debug().Msgf("Extracting backend assets files to %s", options.assetsDestination)
err := assets.ExtractFiles(options.BackendAssets, options.AssetsDestination)
log.Debug().Msgf("Extracting backend assets files to %s", options.AssetsDestination)
if err != nil {
log.Warn().Msgf("Failed extracting backend assets files: %s (might be required for some backends to work properly, like gpt4all)", err)
}
@ -84,31 +89,32 @@ func App(opts ...AppOption) (*fiber.App, error) {
// Default middleware config
app.Use(recover.New())
if options.preloadJSONModels != "" {
if err := ApplyGalleryFromString(options.loader.ModelPath, options.preloadJSONModels, cm, options.galleries); err != nil {
if options.PreloadJSONModels != "" {
if err := localai.ApplyGalleryFromString(options.Loader.ModelPath, options.PreloadJSONModels, cm, options.Galleries); err != nil {
return nil, err
}
}
if options.preloadModelsFromPath != "" {
if err := ApplyGalleryFromFile(options.loader.ModelPath, options.preloadModelsFromPath, cm, options.galleries); err != nil {
if options.PreloadModelsFromPath != "" {
if err := localai.ApplyGalleryFromFile(options.Loader.ModelPath, options.PreloadModelsFromPath, cm, options.Galleries); err != nil {
return nil, err
}
}
if options.cors {
if options.corsAllowOrigins == "" {
app.Use(cors.New())
if options.CORS {
var c func(ctx *fiber.Ctx) error
if options.CORSAllowOrigins == "" {
c = cors.New()
} else {
app.Use(cors.New(cors.Config{
AllowOrigins: options.corsAllowOrigins,
}))
c = cors.New(cors.Config{AllowOrigins: options.CORSAllowOrigins})
}
app.Use(c)
}
// LocalAI API endpoints
applier := newGalleryApplier(options.loader.ModelPath)
applier.start(options.context, cm)
galleryService := localai.NewGalleryService(options.Loader.ModelPath)
galleryService.Start(options.Context, cm)
app.Get("/version", func(c *fiber.Ctx) error {
return c.JSON(struct {
@ -116,43 +122,43 @@ func App(opts ...AppOption) (*fiber.App, error) {
}{Version: internal.PrintableVersion()})
})
app.Post("/models/apply", applyModelGallery(options.loader.ModelPath, cm, applier.C, options.galleries))
app.Get("/models/available", listModelFromGallery(options.galleries, options.loader.ModelPath))
app.Get("/models/jobs/:uuid", getOpStatus(applier))
app.Post("/models/apply", localai.ApplyModelGalleryEndpoint(options.Loader.ModelPath, cm, galleryService.C, options.Galleries))
app.Get("/models/available", localai.ListModelFromGalleryEndpoint(options.Galleries, options.Loader.ModelPath))
app.Get("/models/jobs/:uuid", localai.GetOpStatusEndpoint(galleryService))
// openAI compatible API endpoint
// chat
app.Post("/v1/chat/completions", chatEndpoint(cm, options))
app.Post("/chat/completions", chatEndpoint(cm, options))
app.Post("/v1/chat/completions", openai.ChatEndpoint(cm, options))
app.Post("/chat/completions", openai.ChatEndpoint(cm, options))
// edit
app.Post("/v1/edits", editEndpoint(cm, options))
app.Post("/edits", editEndpoint(cm, options))
app.Post("/v1/edits", openai.EditEndpoint(cm, options))
app.Post("/edits", openai.EditEndpoint(cm, options))
// completion
app.Post("/v1/completions", completionEndpoint(cm, options))
app.Post("/completions", completionEndpoint(cm, options))
app.Post("/v1/engines/:model/completions", completionEndpoint(cm, options))
app.Post("/v1/completions", openai.CompletionEndpoint(cm, options))
app.Post("/completions", openai.CompletionEndpoint(cm, options))
app.Post("/v1/engines/:model/completions", openai.CompletionEndpoint(cm, options))
// embeddings
app.Post("/v1/embeddings", embeddingsEndpoint(cm, options))
app.Post("/embeddings", embeddingsEndpoint(cm, options))
app.Post("/v1/engines/:model/embeddings", embeddingsEndpoint(cm, options))
app.Post("/v1/embeddings", openai.EmbeddingsEndpoint(cm, options))
app.Post("/embeddings", openai.EmbeddingsEndpoint(cm, options))
app.Post("/v1/engines/:model/embeddings", openai.EmbeddingsEndpoint(cm, options))
// audio
app.Post("/v1/audio/transcriptions", transcriptEndpoint(cm, options))
app.Post("/tts", ttsEndpoint(cm, options))
app.Post("/v1/audio/transcriptions", openai.TranscriptEndpoint(cm, options))
app.Post("/tts", localai.TTSEndpoint(cm, options))
// images
app.Post("/v1/images/generations", imageEndpoint(cm, options))
app.Post("/v1/images/generations", openai.ImageEndpoint(cm, options))
if options.imageDir != "" {
app.Static("/generated-images", options.imageDir)
if options.ImageDir != "" {
app.Static("/generated-images", options.ImageDir)
}
if options.audioDir != "" {
app.Static("/generated-audio", options.audioDir)
if options.AudioDir != "" {
app.Static("/generated-audio", options.AudioDir)
}
ok := func(c *fiber.Ctx) error {
@ -164,8 +170,8 @@ func App(opts ...AppOption) (*fiber.App, error) {
app.Get("/readyz", ok)
// models
app.Get("/v1/models", listModels(options.loader, cm))
app.Get("/models", listModels(options.loader, cm))
app.Get("/v1/models", openai.ListModelsEndpoint(options.Loader, cm))
app.Get("/models", openai.ListModelsEndpoint(options.Loader, cm))
return app, nil
}

12
api/api_test.go
View File

@ -13,6 +13,7 @@ import (
"runtime"
. "github.com/go-skynet/LocalAI/api"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/gallery"
"github.com/go-skynet/LocalAI/pkg/model"
"github.com/go-skynet/LocalAI/pkg/utils"
@ -154,9 +155,10 @@ var _ = Describe("API test", func() {
},
}
app, err = App(WithContext(c),
WithGalleries(galleries),
WithModelLoader(modelLoader), WithBackendAssets(backendAssets), WithBackendAssetsOutput(tmpdir))
app, err = App(
options.WithContext(c),
options.WithGalleries(galleries),
options.WithModelLoader(modelLoader), options.WithBackendAssets(backendAssets), options.WithBackendAssetsOutput(tmpdir))
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")
@ -342,7 +344,7 @@ var _ = Describe("API test", func() {
c, cancel = context.WithCancel(context.Background())
var err error
app, err = App(WithContext(c), WithModelLoader(modelLoader))
app, err = App(options.WithContext(c), options.WithModelLoader(modelLoader))
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")
@ -462,7 +464,7 @@ var _ = Describe("API test", func() {
c, cancel = context.WithCancel(context.Background())
var err error
app, err = App(WithContext(c), WithModelLoader(modelLoader), WithConfigFile(os.Getenv("CONFIG_FILE")))
app, err = App(options.WithContext(c), options.WithModelLoader(modelLoader), options.WithConfigFile(os.Getenv("CONFIG_FILE")))
Expect(err).ToNot(HaveOccurred())
go app.Listen("127.0.0.1:9090")

107
api/backend/embeddings.go Normal file
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@ -0,0 +1,107 @@
package backend
import (
"context"
"fmt"
"sync"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grpc"
model "github.com/go-skynet/LocalAI/pkg/model"
bert "github.com/go-skynet/go-bert.cpp"
)
func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.Config, o *options.Option) (func() ([]float32, error), error) {
if !c.Embeddings {
return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
}
modelFile := c.Model
grpcOpts := gRPCModelOpts(c)
var inferenceModel interface{}
var err error
opts := []model.Option{
model.WithLoadGRPCOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)),
model.WithAssetDir(o.AssetsDestination),
model.WithModelFile(modelFile),
}
if c.Backend == "" {
inferenceModel, err = loader.GreedyLoader(opts...)
} else {
opts = append(opts, model.WithBackendString(c.Backend))
inferenceModel, err = loader.BackendLoader(opts...)
}
if err != nil {
return nil, err
}
var fn func() ([]float32, error)
switch model := inferenceModel.(type) {
case *grpc.Client:
fn = func() ([]float32, error) {
predictOptions := gRPCPredictOpts(c, loader.ModelPath)
if len(tokens) > 0 {
embeds := []int32{}
for _, t := range tokens {
embeds = append(embeds, int32(t))
}
predictOptions.EmbeddingTokens = embeds
res, err := model.Embeddings(context.TODO(), predictOptions)
if err != nil {
return nil, err
}
return res.Embeddings, nil
}
predictOptions.Embeddings = s
res, err := model.Embeddings(context.TODO(), predictOptions)
if err != nil {
return nil, err
}
return res.Embeddings, nil
}
// bert embeddings
case *bert.Bert:
fn = func() ([]float32, error) {
if len(tokens) > 0 {
return model.TokenEmbeddings(tokens, bert.SetThreads(c.Threads))
}
return model.Embeddings(s, bert.SetThreads(c.Threads))
}
default:
fn = func() ([]float32, error) {
return nil, fmt.Errorf("embeddings not supported by the backend")
}
}
return func() ([]float32, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
l := Lock(modelFile)
defer l.Unlock()
embeds, err := fn()
if err != nil {
return embeds, err
}
// Remove trailing 0s
for i := len(embeds) - 1; i >= 0; i-- {
if embeds[i] == 0.0 {
embeds = embeds[:i]
} else {
break
}
}
return embeds, nil
}, nil
}

56
api/backend/image.go Normal file
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@ -0,0 +1,56 @@
package backend
import (
"fmt"
"sync"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/go-skynet/LocalAI/pkg/stablediffusion"
)
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
if c.Backend != model.StableDiffusionBackend {
return nil, fmt.Errorf("endpoint only working with stablediffusion models")
}
inferenceModel, err := loader.BackendLoader(
model.WithBackendString(c.Backend),
model.WithAssetDir(o.AssetsDestination),
model.WithThreads(uint32(c.Threads)),
model.WithModelFile(c.ImageGenerationAssets),
)
if err != nil {
return nil, err
}
var fn func() error
switch model := inferenceModel.(type) {
case *stablediffusion.StableDiffusion:
fn = func() error {
return model.GenerateImage(height, width, mode, step, seed, positive_prompt, negative_prompt, dst)
}
default:
fn = func() error {
return fmt.Errorf("creation of images not supported by the backend")
}
}
return func() error {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[c.Backend]
if !ok {
m := &sync.Mutex{}
mutexes[c.Backend] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
return fn()
}, nil
}

160
api/backend/llm.go Normal file
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@ -0,0 +1,160 @@
package backend
import (
"context"
"regexp"
"strings"
"sync"
"github.com/donomii/go-rwkv.cpp"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/grpc"
"github.com/go-skynet/LocalAI/pkg/langchain"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/go-skynet/bloomz.cpp"
)
func ModelInference(s string, loader *model.ModelLoader, c config.Config, o *options.Option, tokenCallback func(string) bool) (func() (string, error), error) {
supportStreams := false
modelFile := c.Model
grpcOpts := gRPCModelOpts(c)
var inferenceModel interface{}
var err error
opts := []model.Option{
model.WithLoadGRPCOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)), // GPT4all uses this
model.WithAssetDir(o.AssetsDestination),
model.WithModelFile(modelFile),
}
if c.Backend == "" {
inferenceModel, err = loader.GreedyLoader(opts...)
} else {
opts = append(opts, model.WithBackendString(c.Backend))
inferenceModel, err = loader.BackendLoader(opts...)
}
if err != nil {
return nil, err
}
var fn func() (string, error)
switch model := inferenceModel.(type) {
case *rwkv.RwkvState:
supportStreams = true
fn = func() (string, error) {
stopWord := "\n"
if len(c.StopWords) > 0 {
stopWord = c.StopWords[0]
}
if err := model.ProcessInput(s); err != nil {
return "", err
}
response := model.GenerateResponse(c.Maxtokens, stopWord, float32(c.Temperature), float32(c.TopP), tokenCallback)
return response, nil
}
case *bloomz.Bloomz:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []bloomz.PredictOption{
bloomz.SetTemperature(c.Temperature),
bloomz.SetTopP(c.TopP),
bloomz.SetTopK(c.TopK),
bloomz.SetTokens(c.Maxtokens),
bloomz.SetThreads(c.Threads),
}
if c.Seed != 0 {
predictOptions = append(predictOptions, bloomz.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *grpc.Client:
// in GRPC, the backend is supposed to answer to 1 single token if stream is not supported
supportStreams = true
fn = func() (string, error) {
opts := gRPCPredictOpts(c, loader.ModelPath)
opts.Prompt = s
if tokenCallback != nil {
ss := ""
err := model.PredictStream(context.TODO(), opts, func(s string) {
tokenCallback(s)
ss += s
})
return ss, err
} else {
reply, err := model.Predict(context.TODO(), opts)
return reply.Message, err
}
}
case *langchain.HuggingFace:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []langchain.PredictOption{
langchain.SetModel(c.Model),
langchain.SetMaxTokens(c.Maxtokens),
langchain.SetTemperature(c.Temperature),
langchain.SetStopWords(c.StopWords),
}
pred, er := model.PredictHuggingFace(s, predictOptions...)
if er != nil {
return "", er
}
return pred.Completion, nil
}
}
return func() (string, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
l := Lock(modelFile)
defer l.Unlock()
res, err := fn()
if tokenCallback != nil && !supportStreams {
tokenCallback(res)
}
return res, err
}, nil
}
var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
var mu sync.Mutex = sync.Mutex{}
func Finetune(config config.Config, input, prediction string) string {
if config.Echo {
prediction = input + prediction
}
for _, c := range config.Cutstrings {
mu.Lock()
reg, ok := cutstrings[c]
if !ok {
cutstrings[c] = regexp.MustCompile(c)
reg = cutstrings[c]
}
mu.Unlock()
prediction = reg.ReplaceAllString(prediction, "")
}
for _, c := range config.TrimSpace {
prediction = strings.TrimSpace(strings.TrimPrefix(prediction, c))
}
return prediction
}

22
api/backend/lock.go Normal file
View File

@ -0,0 +1,22 @@
package backend
import "sync"
// mutex still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
var mutexMap sync.Mutex
var mutexes map[string]*sync.Mutex = make(map[string]*sync.Mutex)
func Lock(s string) *sync.Mutex {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[s]
if !ok {
m := &sync.Mutex{}
mutexes[s] = m
l = m
}
mutexMap.Unlock()
l.Lock()
return l
}

98
api/backend/options.go Normal file
View File

@ -0,0 +1,98 @@
package backend
import (
"os"
"path/filepath"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/pkg/langchain"
"github.com/go-skynet/bloomz.cpp"
)
func langchainOptions(c config.Config) []langchain.PredictOption {
return []langchain.PredictOption{
langchain.SetModel(c.Model),
langchain.SetMaxTokens(c.Maxtokens),
langchain.SetTemperature(c.Temperature),
langchain.SetStopWords(c.StopWords),
}
}
func bloomzOptions(c config.Config) []bloomz.PredictOption {
// Generate the prediction using the language model
predictOptions := []bloomz.PredictOption{
bloomz.SetTemperature(c.Temperature),
bloomz.SetTopP(c.TopP),
bloomz.SetTopK(c.TopK),
bloomz.SetTokens(c.Maxtokens),
bloomz.SetThreads(c.Threads),
}
if c.Seed != 0 {
predictOptions = append(predictOptions, bloomz.SetSeed(c.Seed))
}
return predictOptions
}
func gRPCModelOpts(c config.Config) *pb.ModelOptions {
b := 512
if c.Batch != 0 {
b = c.Batch
}
return &pb.ModelOptions{
ContextSize: int32(c.ContextSize),
Seed: int32(c.Seed),
NBatch: int32(b),
F16Memory: c.F16,
MLock: c.MMlock,
NUMA: c.NUMA,
Embeddings: c.Embeddings,
LowVRAM: c.LowVRAM,
NGPULayers: int32(c.NGPULayers),
MMap: c.MMap,
MainGPU: c.MainGPU,
Threads: int32(c.Threads),
TensorSplit: c.TensorSplit,
}
}
func gRPCPredictOpts(c config.Config, modelPath string) *pb.PredictOptions {
promptCachePath := ""
if c.PromptCachePath != "" {
p := filepath.Join(modelPath, c.PromptCachePath)
os.MkdirAll(filepath.Dir(p), 0755)
promptCachePath = p
}
return &pb.PredictOptions{
Temperature: float32(c.Temperature),
TopP: float32(c.TopP),
TopK: int32(c.TopK),
Tokens: int32(c.Maxtokens),
Threads: int32(c.Threads),
PromptCacheAll: c.PromptCacheAll,
PromptCacheRO: c.PromptCacheRO,
PromptCachePath: promptCachePath,
F16KV: c.F16,
DebugMode: c.Debug,
Grammar: c.Grammar,
Mirostat: int32(c.Mirostat),
MirostatETA: float32(c.MirostatETA),
MirostatTAU: float32(c.MirostatTAU),
Debug: c.Debug,
StopPrompts: c.StopWords,
Repeat: int32(c.RepeatPenalty),
NKeep: int32(c.Keep),
Batch: int32(c.Batch),
IgnoreEOS: c.IgnoreEOS,
Seed: int32(c.Seed),
FrequencyPenalty: float32(c.FrequencyPenalty),
MLock: c.MMlock,
MMap: c.MMap,
MainGPU: c.MainGPU,
TensorSplit: c.TensorSplit,
TailFreeSamplingZ: float32(c.TFZ),
TypicalP: float32(c.TypicalP),
}
}

401
api/config.go
View File

@ -1,401 +0,0 @@
package api
import (
"encoding/json"
"fmt"
"io/fs"
"os"
"path/filepath"
"strings"
"sync"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"gopkg.in/yaml.v3"
)
type Config struct {
OpenAIRequest `yaml:"parameters"`
Name string `yaml:"name"`
StopWords []string `yaml:"stopwords"`
Cutstrings []string `yaml:"cutstrings"`
TrimSpace []string `yaml:"trimspace"`
ContextSize int `yaml:"context_size"`
F16 bool `yaml:"f16"`
NUMA bool `yaml:"numa"`
Threads int `yaml:"threads"`
Debug bool `yaml:"debug"`
Roles map[string]string `yaml:"roles"`
Embeddings bool `yaml:"embeddings"`
Backend string `yaml:"backend"`
TemplateConfig TemplateConfig `yaml:"template"`
MirostatETA float64 `yaml:"mirostat_eta"`
MirostatTAU float64 `yaml:"mirostat_tau"`
Mirostat int `yaml:"mirostat"`
NGPULayers int `yaml:"gpu_layers"`
MMap bool `yaml:"mmap"`
MMlock bool `yaml:"mmlock"`
LowVRAM bool `yaml:"low_vram"`
TensorSplit string `yaml:"tensor_split"`
MainGPU string `yaml:"main_gpu"`
ImageGenerationAssets string `yaml:"asset_dir"`
PromptCachePath string `yaml:"prompt_cache_path"`
PromptCacheAll bool `yaml:"prompt_cache_all"`
PromptCacheRO bool `yaml:"prompt_cache_ro"`
Grammar string `yaml:"grammar"`
FunctionsConfig Functions `yaml:"function"`
PromptStrings, InputStrings []string
InputToken [][]int
functionCallString, functionCallNameString string
}
type Functions struct {
DisableNoAction bool `yaml:"disable_no_action"`
NoActionFunctionName string `yaml:"no_action_function_name"`
NoActionDescriptionName string `yaml:"no_action_description_name"`
}
type TemplateConfig struct {
Completion string `yaml:"completion"`
Functions string `yaml:"function"`
Chat string `yaml:"chat"`
Edit string `yaml:"edit"`
}
type ConfigMerger struct {
configs map[string]Config
sync.Mutex
}
func defaultConfig(modelFile string) *Config {
return &Config{
OpenAIRequest: defaultRequest(modelFile),
}
}
func NewConfigMerger() *ConfigMerger {
return &ConfigMerger{
configs: make(map[string]Config),
}
}
func ReadConfigFile(file string) ([]*Config, error) {
c := &[]*Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return *c, nil
}
func ReadConfig(file string) (*Config, error) {
c := &Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return c, nil
}
func (cm *ConfigMerger) LoadConfigFile(file string) error {
cm.Lock()
defer cm.Unlock()
c, err := ReadConfigFile(file)
if err != nil {
return fmt.Errorf("cannot load config file: %w", err)
}
for _, cc := range c {
cm.configs[cc.Name] = *cc
}
return nil
}
func (cm *ConfigMerger) LoadConfig(file string) error {
cm.Lock()
defer cm.Unlock()
c, err := ReadConfig(file)
if err != nil {
return fmt.Errorf("cannot read config file: %w", err)
}
cm.configs[c.Name] = *c
return nil
}
func (cm *ConfigMerger) GetConfig(m string) (Config, bool) {
cm.Lock()
defer cm.Unlock()
v, exists := cm.configs[m]
return v, exists
}
func (cm *ConfigMerger) ListConfigs() []string {
cm.Lock()
defer cm.Unlock()
var res []string
for k := range cm.configs {
res = append(res, k)
}
return res
}
func (cm *ConfigMerger) LoadConfigs(path string) error {
cm.Lock()
defer cm.Unlock()
entries, err := os.ReadDir(path)
if err != nil {
return err
}
files := make([]fs.FileInfo, 0, len(entries))
for _, entry := range entries {
info, err := entry.Info()
if err != nil {
return err
}
files = append(files, info)
}
for _, file := range files {
// Skip templates, YAML and .keep files
if !strings.Contains(file.Name(), ".yaml") {
continue
}
c, err := ReadConfig(filepath.Join(path, file.Name()))
if err == nil {
cm.configs[c.Name] = *c
}
}
return nil
}
func updateConfig(config *Config, input *OpenAIRequest) {
if input.Echo {
config.Echo = input.Echo
}
if input.TopK != 0 {
config.TopK = input.TopK
}
if input.TopP != 0 {
config.TopP = input.TopP
}
if input.Grammar != "" {
config.Grammar = input.Grammar
}
if input.Temperature != 0 {
config.Temperature = input.Temperature
}
if input.Maxtokens != 0 {
config.Maxtokens = input.Maxtokens
}
switch stop := input.Stop.(type) {
case string:
if stop != "" {
config.StopWords = append(config.StopWords, stop)
}
case []interface{}:
for _, pp := range stop {
if s, ok := pp.(string); ok {
config.StopWords = append(config.StopWords, s)
}
}
}
if input.RepeatPenalty != 0 {
config.RepeatPenalty = input.RepeatPenalty
}
if input.Keep != 0 {
config.Keep = input.Keep
}
if input.Batch != 0 {
config.Batch = input.Batch
}
if input.F16 {
config.F16 = input.F16
}
if input.IgnoreEOS {
config.IgnoreEOS = input.IgnoreEOS
}
if input.Seed != 0 {
config.Seed = input.Seed
}
if input.Mirostat != 0 {
config.Mirostat = input.Mirostat
}
if input.MirostatETA != 0 {
config.MirostatETA = input.MirostatETA
}
if input.MirostatTAU != 0 {
config.MirostatTAU = input.MirostatTAU
}
if input.TypicalP != 0 {
config.TypicalP = input.TypicalP
}
switch inputs := input.Input.(type) {
case string:
if inputs != "" {
config.InputStrings = append(config.InputStrings, inputs)
}
case []interface{}:
for _, pp := range inputs {
switch i := pp.(type) {
case string:
config.InputStrings = append(config.InputStrings, i)
case []interface{}:
tokens := []int{}
for _, ii := range i {
tokens = append(tokens, int(ii.(float64)))
}
config.InputToken = append(config.InputToken, tokens)
}
}
}
// Can be either a string or an object
switch fnc := input.FunctionCall.(type) {
case string:
if fnc != "" {
config.functionCallString = fnc
}
case map[string]interface{}:
var name string
n, exists := fnc["name"]
if exists {
nn, e := n.(string)
if e {
name = nn
}
}
config.functionCallNameString = name
}
switch p := input.Prompt.(type) {
case string:
config.PromptStrings = append(config.PromptStrings, p)
case []interface{}:
for _, pp := range p {
if s, ok := pp.(string); ok {
config.PromptStrings = append(config.PromptStrings, s)
}
}
}
}
func readInput(c *fiber.Ctx, loader *model.ModelLoader, randomModel bool) (string, *OpenAIRequest, error) {
input := new(OpenAIRequest)
// Get input data from the request body
if err := c.BodyParser(input); err != nil {
return "", nil, err
}
modelFile := input.Model
if c.Params("model") != "" {
modelFile = c.Params("model")
}
received, _ := json.Marshal(input)
log.Debug().Msgf("Request received: %s", string(received))
// Set model from bearer token, if available
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
// If no model was specified, take the first available
if modelFile == "" && !bearerExists && randomModel {
models, _ := loader.ListModels()
if len(models) > 0 {
modelFile = models[0]
log.Debug().Msgf("No model specified, using: %s", modelFile)
} else {
log.Debug().Msgf("No model specified, returning error")
return "", nil, fmt.Errorf("no model specified")
}
}
// If a model is found in bearer token takes precedence
if bearerExists {
log.Debug().Msgf("Using model from bearer token: %s", bearer)
modelFile = bearer
}
return modelFile, input, nil
}
func readConfig(modelFile string, input *OpenAIRequest, cm *ConfigMerger, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*Config, *OpenAIRequest, error) {
// Load a config file if present after the model name
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
var config *Config
defaults := func() {
config = defaultConfig(modelFile)
config.ContextSize = ctx
config.Threads = threads
config.F16 = f16
config.Debug = debug
}
cfg, exists := cm.GetConfig(modelFile)
if !exists {
if _, err := os.Stat(modelConfig); err == nil {
if err := cm.LoadConfig(modelConfig); err != nil {
return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
}
cfg, exists = cm.GetConfig(modelFile)
if exists {
config = &cfg
} else {
defaults()
}
} else {
defaults()
}
} else {
config = &cfg
}
// Set the parameters for the language model prediction
updateConfig(config, input)
// Don't allow 0 as setting
if config.Threads == 0 {
if threads != 0 {
config.Threads = threads
} else {
config.Threads = 4
}
}
// Enforce debug flag if passed from CLI
if debug {
config.Debug = true
}
return config, input, nil
}

209
api/config/config.go Normal file
View File

@ -0,0 +1,209 @@
package api_config
import (
"fmt"
"io/fs"
"os"
"path/filepath"
"strings"
"sync"
"gopkg.in/yaml.v3"
)
type Config struct {
PredictionOptions `yaml:"parameters"`
Name string `yaml:"name"`
StopWords []string `yaml:"stopwords"`
Cutstrings []string `yaml:"cutstrings"`
TrimSpace []string `yaml:"trimspace"`
ContextSize int `yaml:"context_size"`
F16 bool `yaml:"f16"`
NUMA bool `yaml:"numa"`
Threads int `yaml:"threads"`
Debug bool `yaml:"debug"`
Roles map[string]string `yaml:"roles"`
Embeddings bool `yaml:"embeddings"`
Backend string `yaml:"backend"`
TemplateConfig TemplateConfig `yaml:"template"`
MirostatETA float64 `yaml:"mirostat_eta"`
MirostatTAU float64 `yaml:"mirostat_tau"`
Mirostat int `yaml:"mirostat"`
NGPULayers int `yaml:"gpu_layers"`
MMap bool `yaml:"mmap"`
MMlock bool `yaml:"mmlock"`
LowVRAM bool `yaml:"low_vram"`
TensorSplit string `yaml:"tensor_split"`
MainGPU string `yaml:"main_gpu"`
ImageGenerationAssets string `yaml:"asset_dir"`
PromptCachePath string `yaml:"prompt_cache_path"`
PromptCacheAll bool `yaml:"prompt_cache_all"`
PromptCacheRO bool `yaml:"prompt_cache_ro"`
Grammar string `yaml:"grammar"`
PromptStrings, InputStrings []string
InputToken [][]int
functionCallString, functionCallNameString string
FunctionsConfig Functions `yaml:"function"`
}
type Functions struct {
DisableNoAction bool `yaml:"disable_no_action"`
NoActionFunctionName string `yaml:"no_action_function_name"`
NoActionDescriptionName string `yaml:"no_action_description_name"`
}
type TemplateConfig struct {
Completion string `yaml:"completion"`
Functions string `yaml:"function"`
Chat string `yaml:"chat"`
Edit string `yaml:"edit"`
}
type ConfigLoader struct {
configs map[string]Config
sync.Mutex
}
func (c *Config) SetFunctionCallString(s string) {
c.functionCallString = s
}
func (c *Config) SetFunctionCallNameString(s string) {
c.functionCallNameString = s
}
func (c *Config) ShouldUseFunctions() bool {
return ((c.functionCallString != "none" || c.functionCallString == "") || c.ShouldCallSpecificFunction())
}
func (c *Config) ShouldCallSpecificFunction() bool {
return len(c.functionCallNameString) > 0
}
func (c *Config) FunctionToCall() string {
return c.functionCallNameString
}
func defaultPredictOptions(modelFile string) PredictionOptions {
return PredictionOptions{
TopP: 0.7,
TopK: 80,
Maxtokens: 512,
Temperature: 0.9,
Model: modelFile,
}
}
func DefaultConfig(modelFile string) *Config {
return &Config{
PredictionOptions: defaultPredictOptions(modelFile),
}
}
func NewConfigLoader() *ConfigLoader {
return &ConfigLoader{
configs: make(map[string]Config),
}
}
func ReadConfigFile(file string) ([]*Config, error) {
c := &[]*Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return *c, nil
}
func ReadConfig(file string) (*Config, error) {
c := &Config{}
f, err := os.ReadFile(file)
if err != nil {
return nil, fmt.Errorf("cannot read config file: %w", err)
}
if err := yaml.Unmarshal(f, c); err != nil {
return nil, fmt.Errorf("cannot unmarshal config file: %w", err)
}
return c, nil
}
func (cm *ConfigLoader) LoadConfigFile(file string) error {
cm.Lock()
defer cm.Unlock()
c, err := ReadConfigFile(file)
if err != nil {
return fmt.Errorf("cannot load config file: %w", err)
}
for _, cc := range c {
cm.configs[cc.Name] = *cc
}
return nil
}
func (cm *ConfigLoader) LoadConfig(file string) error {
cm.Lock()
defer cm.Unlock()
c, err := ReadConfig(file)
if err != nil {
return fmt.Errorf("cannot read config file: %w", err)
}
cm.configs[c.Name] = *c
return nil
}
func (cm *ConfigLoader) GetConfig(m string) (Config, bool) {
cm.Lock()
defer cm.Unlock()
v, exists := cm.configs[m]
return v, exists
}
func (cm *ConfigLoader) ListConfigs() []string {
cm.Lock()
defer cm.Unlock()
var res []string
for k := range cm.configs {
res = append(res, k)
}
return res
}
func (cm *ConfigLoader) LoadConfigs(path string) error {
cm.Lock()
defer cm.Unlock()
entries, err := os.ReadDir(path)
if err != nil {
return err
}
files := make([]fs.FileInfo, 0, len(entries))
for _, entry := range entries {
info, err := entry.Info()
if err != nil {
return err
}
files = append(files, info)
}
for _, file := range files {
// Skip templates, YAML and .keep files
if !strings.Contains(file.Name(), ".yaml") {
continue
}
c, err := ReadConfig(filepath.Join(path, file.Name()))
if err == nil {
cm.configs[c.Name] = *c
}
}
return nil
}

24
api/config_test.go → api/config/config_test.go
View File

@ -1,8 +1,10 @@
package api
package api_config_test
import (
"os"
. "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/pkg/model"
. "github.com/onsi/ginkgo/v2"
. "github.com/onsi/gomega"
@ -26,29 +28,29 @@ var _ = Describe("Test cases for config related functions", func() {
})
It("Test LoadConfigs", func() {
cm := NewConfigMerger()
options := newOptions()
cm := NewConfigLoader()
opts := options.NewOptions()
modelLoader := model.NewModelLoader(os.Getenv("MODELS_PATH"))
WithModelLoader(modelLoader)(options)
options.WithModelLoader(modelLoader)(opts)
err := cm.LoadConfigs(options.loader.ModelPath)
err := cm.LoadConfigs(opts.Loader.ModelPath)
Expect(err).To(BeNil())
Expect(cm.configs).ToNot(BeNil())
Expect(cm.ListConfigs()).ToNot(BeNil())
// config should includes gpt4all models's api.config
Expect(cm.configs).To(HaveKey("gpt4all"))
Expect(cm.ListConfigs()).To(ContainElements("gpt4all"))
// config should includes gpt2 models's api.config
Expect(cm.configs).To(HaveKey("gpt4all-2"))
Expect(cm.ListConfigs()).To(ContainElements("gpt4all-2"))
// config should includes text-embedding-ada-002 models's api.config
Expect(cm.configs).To(HaveKey("text-embedding-ada-002"))
Expect(cm.ListConfigs()).To(ContainElements("text-embedding-ada-002"))
// config should includes rwkv_test models's api.config
Expect(cm.configs).To(HaveKey("rwkv_test"))
Expect(cm.ListConfigs()).To(ContainElements("rwkv_test"))
// config should includes whisper-1 models's api.config
Expect(cm.configs).To(HaveKey("whisper-1"))
Expect(cm.ListConfigs()).To(ContainElements("whisper-1"))
})
})
})

37
api/config/prediction.go Normal file
View File

@ -0,0 +1,37 @@
package api_config
type PredictionOptions struct {
// Also part of the OpenAI official spec
Model string `json:"model" yaml:"model"`
// Also part of the OpenAI official spec
Language string `json:"language"`
// Also part of the OpenAI official spec. use it for returning multiple results
N int `json:"n"`
// Common options between all the API calls, part of the OpenAI spec
TopP float64 `json:"top_p" yaml:"top_p"`
TopK int `json:"top_k" yaml:"top_k"`
Temperature float64 `json:"temperature" yaml:"temperature"`
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
Echo bool `json:"echo"`
// Custom parameters - not present in the OpenAI API
Batch int `json:"batch" yaml:"batch"`
F16 bool `json:"f16" yaml:"f16"`
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
Keep int `json:"n_keep" yaml:"n_keep"`
MirostatETA float64 `json:"mirostat_eta" yaml:"mirostat_eta"`
MirostatTAU float64 `json:"mirostat_tau" yaml:"mirostat_tau"`
Mirostat int `json:"mirostat" yaml:"mirostat"`
FrequencyPenalty float64 `json:"frequency_penalty" yaml:"frequency_penalty"`
TFZ float64 `json:"tfz" yaml:"tfz"`
TypicalP float64 `json:"typical_p" yaml:"typical_p"`
Seed int `json:"seed" yaml:"seed"`
}

21
api/gallery.go → api/localai/gallery.go
View File

@ -1,4 +1,4 @@
package api
package localai
import (
"context"
@ -9,6 +9,7 @@ import (
json "github.com/json-iterator/go"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/pkg/gallery"
"github.com/gofiber/fiber/v2"
"github.com/google/uuid"
@ -38,7 +39,7 @@ type galleryApplier struct {
statuses map[string]*galleryOpStatus
}
func newGalleryApplier(modelPath string) *galleryApplier {
func NewGalleryService(modelPath string) *galleryApplier {
return &galleryApplier{
modelPath: modelPath,
C: make(chan galleryOp),
@ -47,7 +48,7 @@ func newGalleryApplier(modelPath string) *galleryApplier {
}
// prepareModel applies a
func prepareModel(modelPath string, req gallery.GalleryModel, cm *ConfigMerger, downloadStatus func(string, string, string, float64)) error {
func prepareModel(modelPath string, req gallery.GalleryModel, cm *config.ConfigLoader, downloadStatus func(string, string, string, float64)) error {
config, err := gallery.GetGalleryConfigFromURL(req.URL)
if err != nil {
@ -72,7 +73,7 @@ func (g *galleryApplier) getStatus(s string) *galleryOpStatus {
return g.statuses[s]
}
func (g *galleryApplier) start(c context.Context, cm *ConfigMerger) {
func (g *galleryApplier) Start(c context.Context, cm *config.ConfigLoader) {
go func() {
for {
select {
@ -148,7 +149,7 @@ type galleryModel struct {
ID string `json:"id"`
}
func ApplyGalleryFromFile(modelPath, s string, cm *ConfigMerger, galleries []gallery.Gallery) error {
func ApplyGalleryFromFile(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery) error {
dat, err := os.ReadFile(s)
if err != nil {
return err
@ -156,7 +157,7 @@ func ApplyGalleryFromFile(modelPath, s string, cm *ConfigMerger, galleries []gal
return ApplyGalleryFromString(modelPath, string(dat), cm, galleries)
}
func ApplyGalleryFromString(modelPath, s string, cm *ConfigMerger, galleries []gallery.Gallery) error {
func ApplyGalleryFromString(modelPath, s string, cm *config.ConfigLoader, galleries []gallery.Gallery) error {
var requests []galleryModel
err := json.Unmarshal([]byte(s), &requests)
if err != nil {
@ -174,7 +175,9 @@ func ApplyGalleryFromString(modelPath, s string, cm *ConfigMerger, galleries []g
return err
}
func getOpStatus(g *galleryApplier) func(c *fiber.Ctx) error {
/// Endpoints
func GetOpStatusEndpoint(g *galleryApplier) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
status := g.getStatus(c.Params("uuid"))
@ -191,7 +194,7 @@ type GalleryModel struct {
gallery.GalleryModel
}
func applyModelGallery(modelPath string, cm *ConfigMerger, g chan galleryOp, galleries []gallery.Gallery) func(c *fiber.Ctx) error {
func ApplyModelGalleryEndpoint(modelPath string, cm *config.ConfigLoader, g chan galleryOp, galleries []gallery.Gallery) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
input := new(GalleryModel)
// Get input data from the request body
@ -216,7 +219,7 @@ func applyModelGallery(modelPath string, cm *ConfigMerger, g chan galleryOp, gal
}
}
func listModelFromGallery(galleries []gallery.Gallery, basePath string) func(c *fiber.Ctx) error {
func ListModelFromGalleryEndpoint(galleries []gallery.Gallery, basePath string) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
log.Debug().Msgf("Listing models from galleries: %+v", galleries)

21
api/localai.go → api/localai/localai.go
View File

@ -1,10 +1,13 @@
package api
package localai
import (
"fmt"
"os"
"path/filepath"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/go-skynet/LocalAI/pkg/tts"
"github.com/go-skynet/LocalAI/pkg/utils"
@ -32,7 +35,7 @@ func generateUniqueFileName(dir, baseName, ext string) string {
}
}
func ttsEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
func TTSEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
input := new(TTSRequest)
@ -41,10 +44,10 @@ func ttsEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return err
}
piperModel, err := o.loader.BackendLoader(
piperModel, err := o.Loader.BackendLoader(
model.WithBackendString(model.PiperBackend),
model.WithModelFile(input.Model),
model.WithAssetDir(o.assetsDestination))
model.WithAssetDir(o.AssetsDestination))
if err != nil {
return err
}
@ -58,16 +61,16 @@ func ttsEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return fmt.Errorf("loader returned non-piper object %+v", w)
}
if err := os.MkdirAll(o.audioDir, 0755); err != nil {
if err := os.MkdirAll(o.AudioDir, 0755); err != nil {
return err
}
fileName := generateUniqueFileName(o.audioDir, "piper", ".wav")
filePath := filepath.Join(o.audioDir, fileName)
fileName := generateUniqueFileName(o.AudioDir, "piper", ".wav")
filePath := filepath.Join(o.AudioDir, fileName)
modelPath := filepath.Join(o.loader.ModelPath, input.Model)
modelPath := filepath.Join(o.Loader.ModelPath, input.Model)
if err := utils.VerifyPath(modelPath, o.loader.ModelPath); err != nil {
if err := utils.VerifyPath(modelPath, o.Loader.ModelPath); err != nil {
return err
}

973
api/openai.go
View File

@ -1,973 +0,0 @@
package api
import (
"bufio"
"bytes"
"encoding/base64"
"encoding/json"
"errors"
"fmt"
"io"
"io/ioutil"
"net/http"
"os"
"path"
"path/filepath"
"strconv"
"strings"
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
"github.com/go-skynet/LocalAI/pkg/grammar"
model "github.com/go-skynet/LocalAI/pkg/model"
whisperutil "github.com/go-skynet/LocalAI/pkg/whisper"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
// APIError provides error information returned by the OpenAI API.
type APIError struct {
Code any `json:"code,omitempty"`
Message string `json:"message"`
Param *string `json:"param,omitempty"`
Type string `json:"type"`
}
type ErrorResponse struct {
Error *APIError `json:"error,omitempty"`
}
type OpenAIUsage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
TotalTokens int `json:"total_tokens"`
}
type Item struct {
Embedding []float32 `json:"embedding"`
Index int `json:"index"`
Object string `json:"object,omitempty"`
// Images
URL string `json:"url,omitempty"`
B64JSON string `json:"b64_json,omitempty"`
}
type OpenAIResponse struct {
Created int `json:"created,omitempty"`
Object string `json:"object,omitempty"`
ID string `json:"id,omitempty"`
Model string `json:"model,omitempty"`
Choices []Choice `json:"choices,omitempty"`
Data []Item `json:"data,omitempty"`
Usage OpenAIUsage `json:"usage"`
}
type Choice struct {
Index int `json:"index,omitempty"`
FinishReason string `json:"finish_reason,omitempty"`
Message *Message `json:"message,omitempty"`
Delta *Message `json:"delta,omitempty"`
Text string `json:"text,omitempty"`
}
type Message struct {
// The message role
Role string `json:"role,omitempty" yaml:"role"`
// The message content
Content *string `json:"content" yaml:"content"`
// A result of a function call
FunctionCall interface{} `json:"function_call,omitempty" yaml:"function_call,omitempty"`
}
type OpenAIModel struct {
ID string `json:"id"`
Object string `json:"object"`
}
type OpenAIRequest struct {
Model string `json:"model" yaml:"model"`
// whisper
File string `json:"file" validate:"required"`
Language string `json:"language"`
//whisper/image
ResponseFormat string `json:"response_format"`
// image
Size string `json:"size"`
// Prompt is read only by completion/image API calls
Prompt interface{} `json:"prompt" yaml:"prompt"`
// Edit endpoint
Instruction string `json:"instruction" yaml:"instruction"`
Input interface{} `json:"input" yaml:"input"`
Stop interface{} `json:"stop" yaml:"stop"`
// Messages is read only by chat/completion API calls
Messages []Message `json:"messages" yaml:"messages"`
// A list of available functions to call
Functions []grammar.Function `json:"functions" yaml:"functions"`
FunctionCall interface{} `json:"function_call" yaml:"function_call"` // might be a string or an object
Stream bool `json:"stream"`
Echo bool `json:"echo"`
// Common options between all the API calls
TopP float64 `json:"top_p" yaml:"top_p"`
TopK int `json:"top_k" yaml:"top_k"`
Temperature float64 `json:"temperature" yaml:"temperature"`
Maxtokens int `json:"max_tokens" yaml:"max_tokens"`
N int `json:"n"`
// Custom parameters - not present in the OpenAI API
Batch int `json:"batch" yaml:"batch"`
F16 bool `json:"f16" yaml:"f16"`
IgnoreEOS bool `json:"ignore_eos" yaml:"ignore_eos"`
RepeatPenalty float64 `json:"repeat_penalty" yaml:"repeat_penalty"`
Keep int `json:"n_keep" yaml:"n_keep"`
MirostatETA float64 `json:"mirostat_eta" yaml:"mirostat_eta"`
MirostatTAU float64 `json:"mirostat_tau" yaml:"mirostat_tau"`
Mirostat int `json:"mirostat" yaml:"mirostat"`
FrequencyPenalty float64 `json:"frequency_penalty" yaml:"frequency_penalty"`
TFZ float64 `json:"tfz" yaml:"tfz"`
Seed int `json:"seed" yaml:"seed"`
// Image (not supported by OpenAI)
Mode int `json:"mode"`
Step int `json:"step"`
// A grammar to constrain the LLM output
Grammar string `json:"grammar" yaml:"grammar"`
// A grammar object
JSONFunctionGrammarObject *grammar.JSONFunctionStructure `json:"grammar_json_functions" yaml:"grammar_json_functions"`
TypicalP float64 `json:"typical_p" yaml:"typical_p"`
}
func defaultRequest(modelFile string) OpenAIRequest {
return OpenAIRequest{
TopP: 0.7,
TopK: 80,
Maxtokens: 512,
Temperature: 0.9,
Model: modelFile,
}
}
// https://platform.openai.com/docs/api-reference/completions
func completionEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
ComputeChoices(s, req, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
Index: 0,
Text: s,
},
},
Object: "text_completion",
}
log.Debug().Msgf("Sending goroutine: %s", s)
responses <- resp
return true
})
close(responses)
}
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("`input`: %+v", input)
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
if input.Stream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
//c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
templateFile := config.Model
if config.TemplateConfig.Completion != "" {
templateFile = config.TemplateConfig.Completion
}
if input.Stream {
if len(config.PromptStrings) > 1 {
return errors.New("cannot handle more than 1 `PromptStrings` when Streaming")
}
predInput := config.PromptStrings[0]
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
Input string
}{
Input: predInput,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
responses := make(chan OpenAIResponse)
go process(predInput, input, config, o.loader, responses)
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
log.Debug().Msgf("Sending chunk: %s", buf.String())
fmt.Fprintf(w, "data: %v\n", buf.String())
w.Flush()
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
Index: 0,
FinishReason: "stop",
},
},
Object: "text_completion",
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.WriteString("data: [DONE]\n\n")
w.Flush()
}))
return nil
}
var result []Choice
for _, i := range config.PromptStrings {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
Input string
}{
Input: i,
})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input, config, o, o.loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
result = append(result, r...)
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "text_completion",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
// https://platform.openai.com/docs/api-reference/embeddings
func embeddingsEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
items := []Item{}
for i, s := range config.InputToken {
// get the model function to call for the result
embedFn, err := ModelEmbedding("", s, o.loader, *config, o)
if err != nil {
return err
}
embeddings, err := embedFn()
if err != nil {
return err
}
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
}
for i, s := range config.InputStrings {
// get the model function to call for the result
embedFn, err := ModelEmbedding(s, []int{}, o.loader, *config, o)
if err != nil {
return err
}
embeddings, err := embedFn()
if err != nil {
return err
}
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Data: items,
Object: "list",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
func isEOS(s string) bool {
if s == "<|endoftext|>" {
return true
}
return false
}
func chatEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
process := func(s string, req *OpenAIRequest, config *Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
initialMessage := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Role: "assistant"}}},
Object: "chat.completion.chunk",
}
responses <- initialMessage
ComputeChoices(s, req, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Content: &s}, Index: 0}},
Object: "chat.completion.chunk",
}
log.Debug().Msgf("Sending goroutine: %s", s)
if s != "" && !isEOS(s) {
responses <- resp
}
return true
})
close(responses)
}
return func(c *fiber.Ctx) error {
processFunctions := false
funcs := grammar.Functions{}
model, input, err := readInput(c, o.loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Configuration read: %+v", config)
// Allow the user to set custom actions via config file
// to be "embedded" in each model
noActionName := "answer"
noActionDescription := "use this action to answer without performing any action"
if config.FunctionsConfig.NoActionFunctionName != "" {
noActionName = config.FunctionsConfig.NoActionFunctionName
}
if config.FunctionsConfig.NoActionDescriptionName != "" {
noActionDescription = config.FunctionsConfig.NoActionDescriptionName
}
// process functions if we have any defined or if we have a function call string
if len(input.Functions) > 0 &&
((config.functionCallString != "none" || config.functionCallString == "") || len(config.functionCallNameString) > 0) {
log.Debug().Msgf("Response needs to process functions")
processFunctions = true
noActionGrammar := grammar.Function{
Name: noActionName,
Description: noActionDescription,
Parameters: map[string]interface{}{
"properties": map[string]interface{}{
"message": map[string]interface{}{
"type": "string",
"description": "The message to reply the user with",
}},
},
}
// Append the no action function
funcs = append(funcs, input.Functions...)
if !config.FunctionsConfig.DisableNoAction {
funcs = append(funcs, noActionGrammar)
}
// Force picking one of the functions by the request
if config.functionCallNameString != "" {
funcs = funcs.Select(config.functionCallNameString)
}
// Update input grammar
jsStruct := funcs.ToJSONStructure()
config.Grammar = jsStruct.Grammar("")
} else if input.JSONFunctionGrammarObject != nil {
config.Grammar = input.JSONFunctionGrammarObject.Grammar("")
}
// functions are not supported in stream mode (yet?)
toStream := input.Stream && !processFunctions
log.Debug().Msgf("Parameters: %+v", config)
var predInput string
mess := []string{}
for _, i := range input.Messages {
var content string
role := i.Role
// if function call, we might want to customize the role so we can display better that the "assistant called a json action"
// if an "assistant_function_call" role is defined, we use it, otherwise we use the role that is passed by in the request
if i.FunctionCall != nil && i.Role == "assistant" {
roleFn := "assistant_function_call"
r := config.Roles[roleFn]
if r != "" {
role = roleFn
}
}
r := config.Roles[role]
contentExists := i.Content != nil && *i.Content != ""
if r != "" {
if contentExists {
content = fmt.Sprint(r, " ", *i.Content)
}
if i.FunctionCall != nil {
j, err := json.Marshal(i.FunctionCall)
if err == nil {
if contentExists {
content += "\n" + fmt.Sprint(r, " ", string(j))
} else {
content = fmt.Sprint(r, " ", string(j))
}
}
}
} else {
if contentExists {
content = fmt.Sprint(*i.Content)
}
if i.FunctionCall != nil {
j, err := json.Marshal(i.FunctionCall)
if err == nil {
if contentExists {
content += "\n" + string(j)
} else {
content = string(j)
}
}
}
}
mess = append(mess, content)
}
predInput = strings.Join(mess, "\n")
log.Debug().Msgf("Prompt (before templating): %s", predInput)
if toStream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
// c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
templateFile := config.Model
if config.TemplateConfig.Chat != "" && !processFunctions {
templateFile = config.TemplateConfig.Chat
}
if config.TemplateConfig.Functions != "" && processFunctions {
templateFile = config.TemplateConfig.Functions
}
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
Input string
Functions []grammar.Function
}{
Input: predInput,
Functions: funcs,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
} else {
log.Debug().Msgf("Template failed loading: %s", err.Error())
}
log.Debug().Msgf("Prompt (after templating): %s", predInput)
if processFunctions {
log.Debug().Msgf("Grammar: %+v", config.Grammar)
}
if toStream {
responses := make(chan OpenAIResponse)
go process(predInput, input, config, o.loader, responses)
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
log.Debug().Msgf("Sending chunk: %s", buf.String())
fmt.Fprintf(w, "data: %v\n", buf.String())
w.Flush()
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
FinishReason: "stop",
Index: 0,
Delta: &Message{},
}},
Object: "chat.completion.chunk",
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.WriteString("data: [DONE]\n\n")
w.Flush()
}))
return nil
}
result, err := ComputeChoices(predInput, input, config, o, o.loader, func(s string, c *[]Choice) {
if processFunctions {
// As we have to change the result before processing, we can't stream the answer (yet?)
ss := map[string]interface{}{}
json.Unmarshal([]byte(s), &ss)
log.Debug().Msgf("Function return: %s %+v", s, ss)
// The grammar defines the function name as "function", while OpenAI returns "name"
func_name := ss["function"]
// Similarly, while here arguments is a map[string]interface{}, OpenAI actually want a stringified object
args := ss["arguments"] // arguments needs to be a string, but we return an object from the grammar result (TODO: fix)
d, _ := json.Marshal(args)
ss["arguments"] = string(d)
ss["name"] = func_name
// if do nothing, reply with a message
if func_name == noActionName {
log.Debug().Msgf("nothing to do, computing a reply")
// If there is a message that the LLM already sends as part of the JSON reply, use it
arguments := map[string]interface{}{}
json.Unmarshal([]byte(d), &arguments)
m, exists := arguments["message"]
if exists {
switch message := m.(type) {
case string:
if message != "" {
log.Debug().Msgf("Reply received from LLM: %s", message)
message = Finetune(*config, predInput, message)
log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &message}})
return
}
}
}
log.Debug().Msgf("No action received from LLM, without a message, computing a reply")
// Otherwise ask the LLM to understand the JSON output and the context, and return a message
// Note: This costs (in term of CPU) another computation
config.Grammar = ""
predFunc, err := ModelInference(predInput, o.loader, *config, o, nil)
if err != nil {
log.Error().Msgf("inference error: %s", err.Error())
return
}
prediction, err := predFunc()
if err != nil {
log.Error().Msgf("inference error: %s", err.Error())
return
}
prediction = Finetune(*config, predInput, prediction)
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &prediction}})
} else {
// otherwise reply with the function call
*c = append(*c, Choice{
FinishReason: "function_call",
Message: &Message{Role: "assistant", FunctionCall: ss},
})
}
return
}
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &s}})
}, nil)
if err != nil {
return err
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "chat.completion",
}
respData, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", respData)
// Return the prediction in the response body
return c.JSON(resp)
}
}
func editEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
templateFile := config.Model
if config.TemplateConfig.Edit != "" {
templateFile = config.TemplateConfig.Edit
}
var result []Choice
for _, i := range config.InputStrings {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.loader.TemplatePrefix(templateFile, struct {
Input string
Instruction string
}{Input: i})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input, config, o, o.loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
result = append(result, r...)
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "edit",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
// https://platform.openai.com/docs/api-reference/images/create
/*
*
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "A cute baby sea otter",
"n": 1,
"size": "512x512"
}'
*
*/
func imageEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
m, input, err := readInput(c, o.loader, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
if m == "" {
m = model.StableDiffusionBackend
}
log.Debug().Msgf("Loading model: %+v", m)
config, input, err := readConfig(m, input, cm, o.loader, o.debug, 0, 0, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
// XXX: Only stablediffusion is supported for now
if config.Backend == "" {
config.Backend = model.StableDiffusionBackend
}
sizeParts := strings.Split(input.Size, "x")
if len(sizeParts) != 2 {
return fmt.Errorf("Invalid value for 'size'")
}
width, err := strconv.Atoi(sizeParts[0])
if err != nil {
return fmt.Errorf("Invalid value for 'size'")
}
height, err := strconv.Atoi(sizeParts[1])
if err != nil {
return fmt.Errorf("Invalid value for 'size'")
}
b64JSON := false
if input.ResponseFormat == "b64_json" {
b64JSON = true
}
var result []Item
for _, i := range config.PromptStrings {
n := input.N
if input.N == 0 {
n = 1
}
for j := 0; j < n; j++ {
prompts := strings.Split(i, "|")
positive_prompt := prompts[0]
negative_prompt := ""
if len(prompts) > 1 {
negative_prompt = prompts[1]
}
mode := 0
step := 15
if input.Mode != 0 {
mode = input.Mode
}
if input.Step != 0 {
step = input.Step
}
tempDir := ""
if !b64JSON {
tempDir = o.imageDir
}
// Create a temporary file
outputFile, err := ioutil.TempFile(tempDir, "b64")
if err != nil {
return err
}
outputFile.Close()
output := outputFile.Name() + ".png"
// Rename the temporary file
err = os.Rename(outputFile.Name(), output)
if err != nil {
return err
}
baseURL := c.BaseURL()
fn, err := ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, o.loader, *config, o)
if err != nil {
return err
}
if err := fn(); err != nil {
return err
}
item := &Item{}
if b64JSON {
defer os.RemoveAll(output)
data, err := os.ReadFile(output)
if err != nil {
return err
}
item.B64JSON = base64.StdEncoding.EncodeToString(data)
} else {
base := filepath.Base(output)
item.URL = baseURL + "/generated-images/" + base
}
result = append(result, *item)
}
}
resp := &OpenAIResponse{
Data: result,
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}
// https://platform.openai.com/docs/api-reference/audio/create
func transcriptEndpoint(cm *ConfigMerger, o *Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
m, input, err := readInput(c, o.loader, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(m, input, cm, o.loader, o.debug, o.threads, o.ctxSize, o.f16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
// retrieve the file data from the request
file, err := c.FormFile("file")
if err != nil {
return err
}
f, err := file.Open()
if err != nil {
return err
}
defer f.Close()
dir, err := os.MkdirTemp("", "whisper")
if err != nil {
return err
}
defer os.RemoveAll(dir)
dst := filepath.Join(dir, path.Base(file.Filename))
dstFile, err := os.Create(dst)
if err != nil {
return err
}
if _, err := io.Copy(dstFile, f); err != nil {
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
return err
}
log.Debug().Msgf("Audio file copied to: %+v", dst)
whisperModel, err := o.loader.BackendLoader(
model.WithBackendString(model.WhisperBackend),
model.WithModelFile(config.Model),
model.WithThreads(uint32(config.Threads)),
model.WithAssetDir(o.assetsDestination))
if err != nil {
return err
}
if whisperModel == nil {
return fmt.Errorf("could not load whisper model")
}
w, ok := whisperModel.(whisper.Model)
if !ok {
return fmt.Errorf("loader returned non-whisper object")
}
tr, err := whisperutil.Transcript(w, dst, input.Language, uint(config.Threads))
if err != nil {
return err
}
log.Debug().Msgf("Trascribed: %+v", tr)
// TODO: handle different outputs here
return c.Status(http.StatusOK).JSON(tr)
}
}
func listModels(loader *model.ModelLoader, cm *ConfigMerger) func(ctx *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
models, err := loader.ListModels()
if err != nil {
return err
}
var mm map[string]interface{} = map[string]interface{}{}
dataModels := []OpenAIModel{}
for _, m := range models {
mm[m] = nil
dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
}
for _, k := range cm.ListConfigs() {
if _, exists := mm[k]; !exists {
dataModels = append(dataModels, OpenAIModel{ID: k, Object: "model"})
}
}
return c.JSON(struct {
Object string `json:"object"`
Data []OpenAIModel `json:"data"`
}{
Object: "list",
Data: dataModels,
})
}
}

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api/openai/api.go Normal file
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package openai
import (
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/pkg/grammar"
)
// APIError provides error information returned by the OpenAI API.
type APIError struct {
Code any `json:"code,omitempty"`
Message string `json:"message"`
Param *string `json:"param,omitempty"`
Type string `json:"type"`
}
type ErrorResponse struct {
Error *APIError `json:"error,omitempty"`
}
type OpenAIUsage struct {
PromptTokens int `json:"prompt_tokens"`
CompletionTokens int `json:"completion_tokens"`
TotalTokens int `json:"total_tokens"`
}
type Item struct {
Embedding []float32 `json:"embedding"`
Index int `json:"index"`
Object string `json:"object,omitempty"`
// Images
URL string `json:"url,omitempty"`
B64JSON string `json:"b64_json,omitempty"`
}
type OpenAIResponse struct {
Created int `json:"created,omitempty"`
Object string `json:"object,omitempty"`
ID string `json:"id,omitempty"`
Model string `json:"model,omitempty"`
Choices []Choice `json:"choices,omitempty"`
Data []Item `json:"data,omitempty"`
Usage OpenAIUsage `json:"usage"`
}
type Choice struct {
Index int `json:"index,omitempty"`
FinishReason string `json:"finish_reason,omitempty"`
Message *Message `json:"message,omitempty"`
Delta *Message `json:"delta,omitempty"`
Text string `json:"text,omitempty"`
}
type Message struct {
// The message role
Role string `json:"role,omitempty" yaml:"role"`
// The message content
Content *string `json:"content" yaml:"content"`
// A result of a function call
FunctionCall interface{} `json:"function_call,omitempty" yaml:"function_call,omitempty"`
}
type OpenAIModel struct {
ID string `json:"id"`
Object string `json:"object"`
}
type OpenAIRequest struct {
config.PredictionOptions
// whisper
File string `json:"file" validate:"required"`
//whisper/image
ResponseFormat string `json:"response_format"`
// image
Size string `json:"size"`
// Prompt is read only by completion/image API calls
Prompt interface{} `json:"prompt" yaml:"prompt"`
// Edit endpoint
Instruction string `json:"instruction" yaml:"instruction"`
Input interface{} `json:"input" yaml:"input"`
Stop interface{} `json:"stop" yaml:"stop"`
// Messages is read only by chat/completion API calls
Messages []Message `json:"messages" yaml:"messages"`
// A list of available functions to call
Functions []grammar.Function `json:"functions" yaml:"functions"`
FunctionCall interface{} `json:"function_call" yaml:"function_call"` // might be a string or an object
Stream bool `json:"stream"`
// Image (not supported by OpenAI)
Mode int `json:"mode"`
Step int `json:"step"`
// A grammar to constrain the LLM output
Grammar string `json:"grammar" yaml:"grammar"`
JSONFunctionGrammarObject *grammar.JSONFunctionStructure `json:"grammar_json_functions" yaml:"grammar_json_functions"`
}

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package openai
import (
"bufio"
"bytes"
"encoding/json"
"fmt"
"strings"
"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/pkg/grammar"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
func ChatEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
process := func(s string, req *OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
initialMessage := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Role: "assistant"}}},
Object: "chat.completion.chunk",
}
responses <- initialMessage
ComputeChoices(s, req.N, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{{Delta: &Message{Content: &s}, Index: 0}},
Object: "chat.completion.chunk",
}
responses <- resp
return true
})
close(responses)
}
return func(c *fiber.Ctx) error {
processFunctions := false
funcs := grammar.Functions{}
model, input, err := readInput(c, o.Loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Configuration read: %+v", config)
// Allow the user to set custom actions via config file
// to be "embedded" in each model
noActionName := "answer"
noActionDescription := "use this action to answer without performing any action"
if config.FunctionsConfig.NoActionFunctionName != "" {
noActionName = config.FunctionsConfig.NoActionFunctionName
}
if config.FunctionsConfig.NoActionDescriptionName != "" {
noActionDescription = config.FunctionsConfig.NoActionDescriptionName
}
// process functions if we have any defined or if we have a function call string
if len(input.Functions) > 0 && config.ShouldUseFunctions() {
log.Debug().Msgf("Response needs to process functions")
processFunctions = true
noActionGrammar := grammar.Function{
Name: noActionName,
Description: noActionDescription,
Parameters: map[string]interface{}{
"properties": map[string]interface{}{
"message": map[string]interface{}{
"type": "string",
"description": "The message to reply the user with",
}},
},
}
// Append the no action function
funcs = append(funcs, input.Functions...)
if !config.FunctionsConfig.DisableNoAction {
funcs = append(funcs, noActionGrammar)
}
// Force picking one of the functions by the request
if config.FunctionToCall() != "" {
funcs = funcs.Select(config.FunctionToCall())
}
// Update input grammar
jsStruct := funcs.ToJSONStructure()
config.Grammar = jsStruct.Grammar("")
} else if input.JSONFunctionGrammarObject != nil {
config.Grammar = input.JSONFunctionGrammarObject.Grammar("")
}
// functions are not supported in stream mode (yet?)
toStream := input.Stream && !processFunctions
log.Debug().Msgf("Parameters: %+v", config)
var predInput string
mess := []string{}
for _, i := range input.Messages {
var content string
role := i.Role
// if function call, we might want to customize the role so we can display better that the "assistant called a json action"
// if an "assistant_function_call" role is defined, we use it, otherwise we use the role that is passed by in the request
if i.FunctionCall != nil && i.Role == "assistant" {
roleFn := "assistant_function_call"
r := config.Roles[roleFn]
if r != "" {
role = roleFn
}
}
r := config.Roles[role]
contentExists := i.Content != nil && *i.Content != ""
if r != "" {
if contentExists {
content = fmt.Sprint(r, " ", *i.Content)
}
if i.FunctionCall != nil {
j, err := json.Marshal(i.FunctionCall)
if err == nil {
if contentExists {
content += "\n" + fmt.Sprint(r, " ", string(j))
} else {
content = fmt.Sprint(r, " ", string(j))
}
}
}
} else {
if contentExists {
content = fmt.Sprint(*i.Content)
}
if i.FunctionCall != nil {
j, err := json.Marshal(i.FunctionCall)
if err == nil {
if contentExists {
content += "\n" + string(j)
} else {
content = string(j)
}
}
}
}
mess = append(mess, content)
}
predInput = strings.Join(mess, "\n")
log.Debug().Msgf("Prompt (before templating): %s", predInput)
if toStream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
// c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
templateFile := config.Model
if config.TemplateConfig.Chat != "" && !processFunctions {
templateFile = config.TemplateConfig.Chat
}
if config.TemplateConfig.Functions != "" && processFunctions {
templateFile = config.TemplateConfig.Functions
}
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
Functions []grammar.Function
}{
Input: predInput,
Functions: funcs,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
} else {
log.Debug().Msgf("Template failed loading: %s", err.Error())
}
log.Debug().Msgf("Prompt (after templating): %s", predInput)
if processFunctions {
log.Debug().Msgf("Grammar: %+v", config.Grammar)
}
if toStream {
responses := make(chan OpenAIResponse)
go process(predInput, input, config, o.Loader, responses)
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
log.Debug().Msgf("Sending chunk: %s", buf.String())
fmt.Fprintf(w, "data: %v\n", buf.String())
w.Flush()
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
FinishReason: "stop",
Index: 0,
Delta: &Message{},
}},
Object: "chat.completion.chunk",
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.WriteString("data: [DONE]\n\n")
w.Flush()
}))
return nil
}
result, err := ComputeChoices(predInput, input.N, config, o, o.Loader, func(s string, c *[]Choice) {
if processFunctions {
// As we have to change the result before processing, we can't stream the answer (yet?)
ss := map[string]interface{}{}
json.Unmarshal([]byte(s), &ss)
log.Debug().Msgf("Function return: %s %+v", s, ss)
// The grammar defines the function name as "function", while OpenAI returns "name"
func_name := ss["function"]
// Similarly, while here arguments is a map[string]interface{}, OpenAI actually want a stringified object
args := ss["arguments"] // arguments needs to be a string, but we return an object from the grammar result (TODO: fix)
d, _ := json.Marshal(args)
ss["arguments"] = string(d)
ss["name"] = func_name
// if do nothing, reply with a message
if func_name == noActionName {
log.Debug().Msgf("nothing to do, computing a reply")
// If there is a message that the LLM already sends as part of the JSON reply, use it
arguments := map[string]interface{}{}
json.Unmarshal([]byte(d), &arguments)
m, exists := arguments["message"]
if exists {
switch message := m.(type) {
case string:
if message != "" {
log.Debug().Msgf("Reply received from LLM: %s", message)
message = backend.Finetune(*config, predInput, message)
log.Debug().Msgf("Reply received from LLM(finetuned): %s", message)
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &message}})
return
}
}
}
log.Debug().Msgf("No action received from LLM, without a message, computing a reply")
// Otherwise ask the LLM to understand the JSON output and the context, and return a message
// Note: This costs (in term of CPU) another computation
config.Grammar = ""
predFunc, err := backend.ModelInference(predInput, o.Loader, *config, o, nil)
if err != nil {
log.Error().Msgf("inference error: %s", err.Error())
return
}
prediction, err := predFunc()
if err != nil {
log.Error().Msgf("inference error: %s", err.Error())
return
}
prediction = backend.Finetune(*config, predInput, prediction)
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &prediction}})
} else {
// otherwise reply with the function call
*c = append(*c, Choice{
FinishReason: "function_call",
Message: &Message{Role: "assistant", FunctionCall: ss},
})
}
return
}
*c = append(*c, Choice{Message: &Message{Role: "assistant", Content: &s}})
}, nil)
if err != nil {
return err
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "chat.completion",
}
respData, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", respData)
// Return the prediction in the response body
return c.JSON(resp)
}
}

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package openai
import (
"bufio"
"bytes"
"encoding/json"
"errors"
"fmt"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
"github.com/valyala/fasthttp"
)
// https://platform.openai.com/docs/api-reference/completions
func CompletionEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
process := func(s string, req *OpenAIRequest, config *config.Config, loader *model.ModelLoader, responses chan OpenAIResponse) {
ComputeChoices(s, req.N, config, o, loader, func(s string, c *[]Choice) {}, func(s string) bool {
resp := OpenAIResponse{
Model: req.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
Index: 0,
Text: s,
},
},
Object: "text_completion",
}
log.Debug().Msgf("Sending goroutine: %s", s)
responses <- resp
return true
})
close(responses)
}
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.Loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("`input`: %+v", input)
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
if input.Stream {
log.Debug().Msgf("Stream request received")
c.Context().SetContentType("text/event-stream")
//c.Response().Header.SetContentType(fiber.MIMETextHTMLCharsetUTF8)
//c.Set("Content-Type", "text/event-stream")
c.Set("Cache-Control", "no-cache")
c.Set("Connection", "keep-alive")
c.Set("Transfer-Encoding", "chunked")
}
templateFile := config.Model
if config.TemplateConfig.Completion != "" {
templateFile = config.TemplateConfig.Completion
}
if input.Stream {
if len(config.PromptStrings) > 1 {
return errors.New("cannot handle more than 1 `PromptStrings` when Streaming")
}
predInput := config.PromptStrings[0]
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
}{
Input: predInput,
})
if err == nil {
predInput = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", predInput)
}
responses := make(chan OpenAIResponse)
go process(predInput, input, config, o.Loader, responses)
c.Context().SetBodyStreamWriter(fasthttp.StreamWriter(func(w *bufio.Writer) {
for ev := range responses {
var buf bytes.Buffer
enc := json.NewEncoder(&buf)
enc.Encode(ev)
log.Debug().Msgf("Sending chunk: %s", buf.String())
fmt.Fprintf(w, "data: %v\n", buf.String())
w.Flush()
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: []Choice{
{
Index: 0,
FinishReason: "stop",
},
},
Object: "text_completion",
}
respData, _ := json.Marshal(resp)
w.WriteString(fmt.Sprintf("data: %s\n\n", respData))
w.WriteString("data: [DONE]\n\n")
w.Flush()
}))
return nil
}
var result []Choice
for _, i := range config.PromptStrings {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
}{
Input: i,
})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input.N, config, o, o.Loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
result = append(result, r...)
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "text_completion",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}

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package openai
import (
"encoding/json"
"fmt"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
func EditEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.Loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
templateFile := config.Model
if config.TemplateConfig.Edit != "" {
templateFile = config.TemplateConfig.Edit
}
var result []Choice
for _, i := range config.InputStrings {
// A model can have a "file.bin.tmpl" file associated with a prompt template prefix
templatedInput, err := o.Loader.TemplatePrefix(templateFile, struct {
Input string
Instruction string
}{Input: i})
if err == nil {
i = templatedInput
log.Debug().Msgf("Template found, input modified to: %s", i)
}
r, err := ComputeChoices(i, input.N, config, o, o.Loader, func(s string, c *[]Choice) {
*c = append(*c, Choice{Text: s})
}, nil)
if err != nil {
return err
}
result = append(result, r...)
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Choices: result,
Object: "edit",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}

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package openai
import (
"encoding/json"
"fmt"
"github.com/go-skynet/LocalAI/api/backend"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
// https://platform.openai.com/docs/api-reference/embeddings
func EmbeddingsEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
model, input, err := readInput(c, o.Loader, true)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(model, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
items := []Item{}
for i, s := range config.InputToken {
// get the model function to call for the result
embedFn, err := backend.ModelEmbedding("", s, o.Loader, *config, o)
if err != nil {
return err
}
embeddings, err := embedFn()
if err != nil {
return err
}
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
}
for i, s := range config.InputStrings {
// get the model function to call for the result
embedFn, err := backend.ModelEmbedding(s, []int{}, o.Loader, *config, o)
if err != nil {
return err
}
embeddings, err := embedFn()
if err != nil {
return err
}
items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
}
resp := &OpenAIResponse{
Model: input.Model, // we have to return what the user sent here, due to OpenAI spec.
Data: items,
Object: "list",
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}

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package openai
import (
"encoding/base64"
"encoding/json"
"fmt"
"io/ioutil"
"os"
"path/filepath"
"strconv"
"strings"
"github.com/go-skynet/LocalAI/api/backend"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
// https://platform.openai.com/docs/api-reference/images/create
/*
*
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" \
-d '{
"prompt": "A cute baby sea otter",
"n": 1,
"size": "512x512"
}'
*
*/
func ImageEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
m, input, err := readInput(c, o.Loader, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
if m == "" {
m = model.StableDiffusionBackend
}
log.Debug().Msgf("Loading model: %+v", m)
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, 0, 0, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
log.Debug().Msgf("Parameter Config: %+v", config)
// XXX: Only stablediffusion is supported for now
if config.Backend == "" {
config.Backend = model.StableDiffusionBackend
}
sizeParts := strings.Split(input.Size, "x")
if len(sizeParts) != 2 {
return fmt.Errorf("Invalid value for 'size'")
}
width, err := strconv.Atoi(sizeParts[0])
if err != nil {
return fmt.Errorf("Invalid value for 'size'")
}
height, err := strconv.Atoi(sizeParts[1])
if err != nil {
return fmt.Errorf("Invalid value for 'size'")
}
b64JSON := false
if input.ResponseFormat == "b64_json" {
b64JSON = true
}
var result []Item
for _, i := range config.PromptStrings {
n := input.N
if input.N == 0 {
n = 1
}
for j := 0; j < n; j++ {
prompts := strings.Split(i, "|")
positive_prompt := prompts[0]
negative_prompt := ""
if len(prompts) > 1 {
negative_prompt = prompts[1]
}
mode := 0
step := 15
if input.Mode != 0 {
mode = input.Mode
}
if input.Step != 0 {
step = input.Step
}
tempDir := ""
if !b64JSON {
tempDir = o.ImageDir
}
// Create a temporary file
outputFile, err := ioutil.TempFile(tempDir, "b64")
if err != nil {
return err
}
outputFile.Close()
output := outputFile.Name() + ".png"
// Rename the temporary file
err = os.Rename(outputFile.Name(), output)
if err != nil {
return err
}
baseURL := c.BaseURL()
fn, err := backend.ImageGeneration(height, width, mode, step, input.Seed, positive_prompt, negative_prompt, output, o.Loader, *config, o)
if err != nil {
return err
}
if err := fn(); err != nil {
return err
}
item := &Item{}
if b64JSON {
defer os.RemoveAll(output)
data, err := os.ReadFile(output)
if err != nil {
return err
}
item.B64JSON = base64.StdEncoding.EncodeToString(data)
} else {
base := filepath.Base(output)
item.URL = baseURL + "/generated-images/" + base
}
result = append(result, *item)
}
}
resp := &OpenAIResponse{
Data: result,
}
jsonResult, _ := json.Marshal(resp)
log.Debug().Msgf("Response: %s", jsonResult)
// Return the prediction in the response body
return c.JSON(resp)
}
}

36
api/openai/inference.go Normal file
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@ -0,0 +1,36 @@
package openai
import (
"github.com/go-skynet/LocalAI/api/backend"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
model "github.com/go-skynet/LocalAI/pkg/model"
)
func ComputeChoices(predInput string, n int, config *config.Config, o *options.Option, loader *model.ModelLoader, cb func(string, *[]Choice), tokenCallback func(string) bool) ([]Choice, error) {
result := []Choice{}
if n == 0 {
n = 1
}
// get the model function to call for the result
predFunc, err := backend.ModelInference(predInput, loader, *config, o, tokenCallback)
if err != nil {
return result, err
}
for i := 0; i < n; i++ {
prediction, err := predFunc()
if err != nil {
return result, err
}
prediction = backend.Finetune(*config, predInput, prediction)
cb(prediction, &result)
//result = append(result, Choice{Text: prediction})
}
return result, err
}

37
api/openai/list.go Normal file
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@ -0,0 +1,37 @@
package openai
import (
config "github.com/go-skynet/LocalAI/api/config"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
)
func ListModelsEndpoint(loader *model.ModelLoader, cm *config.ConfigLoader) func(ctx *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
models, err := loader.ListModels()
if err != nil {
return err
}
var mm map[string]interface{} = map[string]interface{}{}
dataModels := []OpenAIModel{}
for _, m := range models {
mm[m] = nil
dataModels = append(dataModels, OpenAIModel{ID: m, Object: "model"})
}
for _, k := range cm.ListConfigs() {
if _, exists := mm[k]; !exists {
dataModels = append(dataModels, OpenAIModel{ID: k, Object: "model"})
}
}
return c.JSON(struct {
Object string `json:"object"`
Data []OpenAIModel `json:"data"`
}{
Object: "list",
Data: dataModels,
})
}
}

234
api/openai/request.go Normal file
View File

@ -0,0 +1,234 @@
package openai
import (
"encoding/json"
"fmt"
"os"
"path/filepath"
"strings"
config "github.com/go-skynet/LocalAI/api/config"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
func readInput(c *fiber.Ctx, loader *model.ModelLoader, randomModel bool) (string, *OpenAIRequest, error) {
input := new(OpenAIRequest)
// Get input data from the request body
if err := c.BodyParser(input); err != nil {
return "", nil, err
}
modelFile := input.Model
if c.Params("model") != "" {
modelFile = c.Params("model")
}
received, _ := json.Marshal(input)
log.Debug().Msgf("Request received: %s", string(received))
// Set model from bearer token, if available
bearer := strings.TrimLeft(c.Get("authorization"), "Bearer ")
bearerExists := bearer != "" && loader.ExistsInModelPath(bearer)
// If no model was specified, take the first available
if modelFile == "" && !bearerExists && randomModel {
models, _ := loader.ListModels()
if len(models) > 0 {
modelFile = models[0]
log.Debug().Msgf("No model specified, using: %s", modelFile)
} else {
log.Debug().Msgf("No model specified, returning error")
return "", nil, fmt.Errorf("no model specified")
}
}
// If a model is found in bearer token takes precedence
if bearerExists {
log.Debug().Msgf("Using model from bearer token: %s", bearer)
modelFile = bearer
}
return modelFile, input, nil
}
func updateConfig(config *config.Config, input *OpenAIRequest) {
if input.Echo {
config.Echo = input.Echo
}
if input.TopK != 0 {
config.TopK = input.TopK
}
if input.TopP != 0 {
config.TopP = input.TopP
}
if input.Grammar != "" {
config.Grammar = input.Grammar
}
if input.Temperature != 0 {
config.Temperature = input.Temperature
}
if input.Maxtokens != 0 {
config.Maxtokens = input.Maxtokens
}
switch stop := input.Stop.(type) {
case string:
if stop != "" {
config.StopWords = append(config.StopWords, stop)
}
case []interface{}:
for _, pp := range stop {
if s, ok := pp.(string); ok {
config.StopWords = append(config.StopWords, s)
}
}
}
if input.RepeatPenalty != 0 {
config.RepeatPenalty = input.RepeatPenalty
}
if input.Keep != 0 {
config.Keep = input.Keep
}
if input.Batch != 0 {
config.Batch = input.Batch
}
if input.F16 {
config.F16 = input.F16
}
if input.IgnoreEOS {
config.IgnoreEOS = input.IgnoreEOS
}
if input.Seed != 0 {
config.Seed = input.Seed
}
if input.Mirostat != 0 {
config.Mirostat = input.Mirostat
}
if input.MirostatETA != 0 {
config.MirostatETA = input.MirostatETA
}
if input.MirostatTAU != 0 {
config.MirostatTAU = input.MirostatTAU
}
if input.TypicalP != 0 {
config.TypicalP = input.TypicalP
}
switch inputs := input.Input.(type) {
case string:
if inputs != "" {
config.InputStrings = append(config.InputStrings, inputs)
}
case []interface{}:
for _, pp := range inputs {
switch i := pp.(type) {
case string:
config.InputStrings = append(config.InputStrings, i)
case []interface{}:
tokens := []int{}
for _, ii := range i {
tokens = append(tokens, int(ii.(float64)))
}
config.InputToken = append(config.InputToken, tokens)
}
}
}
// Can be either a string or an object
switch fnc := input.FunctionCall.(type) {
case string:
if fnc != "" {
config.SetFunctionCallString(fnc)
}
case map[string]interface{}:
var name string
n, exists := fnc["name"]
if exists {
nn, e := n.(string)
if !e {
name = nn
}
}
config.SetFunctionCallNameString(name)
}
switch p := input.Prompt.(type) {
case string:
config.PromptStrings = append(config.PromptStrings, p)
case []interface{}:
for _, pp := range p {
if s, ok := pp.(string); ok {
config.PromptStrings = append(config.PromptStrings, s)
}
}
}
}
func readConfig(modelFile string, input *OpenAIRequest, cm *config.ConfigLoader, loader *model.ModelLoader, debug bool, threads, ctx int, f16 bool) (*config.Config, *OpenAIRequest, error) {
// Load a config file if present after the model name
modelConfig := filepath.Join(loader.ModelPath, modelFile+".yaml")
var cfg *config.Config
defaults := func() {
cfg = config.DefaultConfig(modelFile)
cfg.ContextSize = ctx
cfg.Threads = threads
cfg.F16 = f16
cfg.Debug = debug
}
cfgExisting, exists := cm.GetConfig(modelFile)
if !exists {
if _, err := os.Stat(modelConfig); err == nil {
if err := cm.LoadConfig(modelConfig); err != nil {
return nil, nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
}
cfgExisting, exists = cm.GetConfig(modelFile)
if exists {
cfg = &cfgExisting
} else {
defaults()
}
} else {
defaults()
}
} else {
cfg = &cfgExisting
}
// Set the parameters for the language model prediction
updateConfig(cfg, input)
// Don't allow 0 as setting
if cfg.Threads == 0 {
if threads != 0 {
cfg.Threads = threads
} else {
cfg.Threads = 4
}
}
// Enforce debug flag if passed from CLI
if debug {
cfg.Debug = true
}
return cfg, input, nil
}

91
api/openai/transcription.go Normal file
View File

@ -0,0 +1,91 @@
package openai
import (
"fmt"
"io"
"net/http"
"os"
"path"
"path/filepath"
"github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
config "github.com/go-skynet/LocalAI/api/config"
"github.com/go-skynet/LocalAI/api/options"
model "github.com/go-skynet/LocalAI/pkg/model"
whisperutil "github.com/go-skynet/LocalAI/pkg/whisper"
"github.com/gofiber/fiber/v2"
"github.com/rs/zerolog/log"
)
// https://platform.openai.com/docs/api-reference/audio/create
func TranscriptEndpoint(cm *config.ConfigLoader, o *options.Option) func(c *fiber.Ctx) error {
return func(c *fiber.Ctx) error {
m, input, err := readInput(c, o.Loader, false)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
config, input, err := readConfig(m, input, cm, o.Loader, o.Debug, o.Threads, o.ContextSize, o.F16)
if err != nil {
return fmt.Errorf("failed reading parameters from request:%w", err)
}
// retrieve the file data from the request
file, err := c.FormFile("file")
if err != nil {
return err
}
f, err := file.Open()
if err != nil {
return err
}
defer f.Close()
dir, err := os.MkdirTemp("", "whisper")
if err != nil {
return err
}
defer os.RemoveAll(dir)
dst := filepath.Join(dir, path.Base(file.Filename))
dstFile, err := os.Create(dst)
if err != nil {
return err
}
if _, err := io.Copy(dstFile, f); err != nil {
log.Debug().Msgf("Audio file copying error %+v - %+v - err %+v", file.Filename, dst, err)
return err
}
log.Debug().Msgf("Audio file copied to: %+v", dst)
whisperModel, err := o.Loader.BackendLoader(
model.WithBackendString(model.WhisperBackend),
model.WithModelFile(config.Model),
model.WithThreads(uint32(config.Threads)),
model.WithAssetDir(o.AssetsDestination))
if err != nil {
return err
}
if whisperModel == nil {
return fmt.Errorf("could not load whisper model")
}
w, ok := whisperModel.(whisper.Model)
if !ok {
return fmt.Errorf("loader returned non-whisper object")
}
tr, err := whisperutil.Transcript(w, dst, input.Language, uint(config.Threads))
if err != nil {
return err
}
log.Debug().Msgf("Trascribed: %+v", tr)
// TODO: handle different outputs here
return c.Status(http.StatusOK).JSON(fiber.Map{"text": tr})
}
}

84
api/options.go → api/options/options.go
View File

@ -1,4 +1,4 @@
package api
package options
import (
"context"
@ -11,35 +11,35 @@ import (
)
type Option struct {
context context.Context
configFile string
loader *model.ModelLoader
uploadLimitMB, threads, ctxSize int
f16 bool
debug, disableMessage bool
imageDir string
audioDir string
cors bool
preloadJSONModels string
preloadModelsFromPath string
corsAllowOrigins string
Context context.Context
ConfigFile string
Loader *model.ModelLoader
UploadLimitMB, Threads, ContextSize int
F16 bool
Debug, DisableMessage bool
ImageDir string
AudioDir string
CORS bool
PreloadJSONModels string
PreloadModelsFromPath string
CORSAllowOrigins string
galleries []gallery.Gallery
Galleries []gallery.Gallery
backendAssets embed.FS
assetsDestination string
BackendAssets embed.FS
AssetsDestination string
}
type AppOption func(*Option)
func newOptions(o ...AppOption) *Option {
func NewOptions(o ...AppOption) *Option {
opt := &Option{
context: context.Background(),
uploadLimitMB: 15,
threads: 1,
ctxSize: 512,
debug: true,
disableMessage: true,
Context: context.Background(),
UploadLimitMB: 15,
Threads: 1,
ContextSize: 512,
Debug: true,
DisableMessage: true,
}
for _, oo := range o {
oo(opt)
@ -49,25 +49,25 @@ func newOptions(o ...AppOption) *Option {
func WithCors(b bool) AppOption {
return func(o *Option) {
o.cors = b
o.CORS = b
}
}
func WithCorsAllowOrigins(b string) AppOption {
return func(o *Option) {
o.corsAllowOrigins = b
o.CORSAllowOrigins = b
}
}
func WithBackendAssetsOutput(out string) AppOption {
return func(o *Option) {
o.assetsDestination = out
o.AssetsDestination = out
}
}
func WithBackendAssets(f embed.FS) AppOption {
return func(o *Option) {
o.backendAssets = f
o.BackendAssets = f
}
}
@ -81,89 +81,89 @@ func WithStringGalleries(galls string) AppOption {
if err := json.Unmarshal([]byte(galls), &galleries); err != nil {
log.Error().Msgf("failed loading galleries: %s", err.Error())
}
o.galleries = append(o.galleries, galleries...)
o.Galleries = append(o.Galleries, galleries...)
}
}
func WithGalleries(galleries []gallery.Gallery) AppOption {
return func(o *Option) {
o.galleries = append(o.galleries, galleries...)
o.Galleries = append(o.Galleries, galleries...)
}
}
func WithContext(ctx context.Context) AppOption {
return func(o *Option) {
o.context = ctx
o.Context = ctx
}
}
func WithYAMLConfigPreload(configFile string) AppOption {
return func(o *Option) {
o.preloadModelsFromPath = configFile
o.PreloadModelsFromPath = configFile
}
}
func WithJSONStringPreload(configFile string) AppOption {
return func(o *Option) {
o.preloadJSONModels = configFile
o.PreloadJSONModels = configFile
}
}
func WithConfigFile(configFile string) AppOption {
return func(o *Option) {
o.configFile = configFile
o.ConfigFile = configFile
}
}
func WithModelLoader(loader *model.ModelLoader) AppOption {
return func(o *Option) {
o.loader = loader
o.Loader = loader
}
}
func WithUploadLimitMB(limit int) AppOption {
return func(o *Option) {
o.uploadLimitMB = limit
o.UploadLimitMB = limit
}
}
func WithThreads(threads int) AppOption {
return func(o *Option) {
o.threads = threads
o.Threads = threads
}
}
func WithContextSize(ctxSize int) AppOption {
return func(o *Option) {
o.ctxSize = ctxSize
o.ContextSize = ctxSize
}
}
func WithF16(f16 bool) AppOption {
return func(o *Option) {
o.f16 = f16
o.F16 = f16
}
}
func WithDebug(debug bool) AppOption {
return func(o *Option) {
o.debug = debug
o.Debug = debug
}
}
func WithDisableMessage(disableMessage bool) AppOption {
return func(o *Option) {
o.disableMessage = disableMessage
o.DisableMessage = disableMessage
}
}
func WithAudioDir(audioDir string) AppOption {
return func(o *Option) {
o.audioDir = audioDir
o.AudioDir = audioDir
}
}
func WithImageDir(imageDir string) AppOption {
return func(o *Option) {
o.imageDir = imageDir
o.ImageDir = imageDir
}
}

415
api/prediction.go
View File

@ -1,415 +0,0 @@
package api
import (
"context"
"fmt"
"os"
"path/filepath"
"regexp"
"strings"
"sync"
"github.com/donomii/go-rwkv.cpp"
"github.com/go-skynet/LocalAI/pkg/grpc"
pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
"github.com/go-skynet/LocalAI/pkg/langchain"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/go-skynet/LocalAI/pkg/stablediffusion"
"github.com/go-skynet/bloomz.cpp"
bert "github.com/go-skynet/go-bert.cpp"
)
// mutex still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
var mutexMap sync.Mutex
var mutexes map[string]*sync.Mutex = make(map[string]*sync.Mutex)
func gRPCModelOpts(c Config) *pb.ModelOptions {
b := 512
if c.Batch != 0 {
b = c.Batch
}
return &pb.ModelOptions{
ContextSize: int32(c.ContextSize),
Seed: int32(c.Seed),
NBatch: int32(b),
F16Memory: c.F16,
MLock: c.MMlock,
NUMA: c.NUMA,
Embeddings: c.Embeddings,
LowVRAM: c.LowVRAM,
NGPULayers: int32(c.NGPULayers),
MMap: c.MMap,
MainGPU: c.MainGPU,
Threads: int32(c.Threads),
TensorSplit: c.TensorSplit,
}
}
func gRPCPredictOpts(c Config, modelPath string) *pb.PredictOptions {
promptCachePath := ""
if c.PromptCachePath != "" {
p := filepath.Join(modelPath, c.PromptCachePath)
os.MkdirAll(filepath.Dir(p), 0755)
promptCachePath = p
}
return &pb.PredictOptions{
Temperature: float32(c.Temperature),
TopP: float32(c.TopP),
TopK: int32(c.TopK),
Tokens: int32(c.Maxtokens),
Threads: int32(c.Threads),
PromptCacheAll: c.PromptCacheAll,
PromptCacheRO: c.PromptCacheRO,
PromptCachePath: promptCachePath,
F16KV: c.F16,
DebugMode: c.Debug,
Grammar: c.Grammar,
Mirostat: int32(c.Mirostat),
MirostatETA: float32(c.MirostatETA),
MirostatTAU: float32(c.MirostatTAU),
Debug: c.Debug,
StopPrompts: c.StopWords,
Repeat: int32(c.RepeatPenalty),
NKeep: int32(c.Keep),
Batch: int32(c.Batch),
IgnoreEOS: c.IgnoreEOS,
Seed: int32(c.Seed),
FrequencyPenalty: float32(c.FrequencyPenalty),
MLock: c.MMlock,
MMap: c.MMap,
MainGPU: c.MainGPU,
TensorSplit: c.TensorSplit,
TailFreeSamplingZ: float32(c.TFZ),
TypicalP: float32(c.TypicalP),
}
}
func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst string, loader *model.ModelLoader, c Config, o *Option) (func() error, error) {
if c.Backend != model.StableDiffusionBackend {
return nil, fmt.Errorf("endpoint only working with stablediffusion models")
}
inferenceModel, err := loader.BackendLoader(
model.WithBackendString(c.Backend),
model.WithAssetDir(o.assetsDestination),
model.WithThreads(uint32(c.Threads)),
model.WithModelFile(c.ImageGenerationAssets),
)
if err != nil {
return nil, err
}
var fn func() error
switch model := inferenceModel.(type) {
case *stablediffusion.StableDiffusion:
fn = func() error {
return model.GenerateImage(height, width, mode, step, seed, positive_prompt, negative_prompt, dst)
}
default:
fn = func() error {
return fmt.Errorf("creation of images not supported by the backend")
}
}
return func() error {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[c.Backend]
if !ok {
m := &sync.Mutex{}
mutexes[c.Backend] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
return fn()
}, nil
}
func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c Config, o *Option) (func() ([]float32, error), error) {
if !c.Embeddings {
return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
}
modelFile := c.Model
grpcOpts := gRPCModelOpts(c)
var inferenceModel interface{}
var err error
opts := []model.Option{
model.WithLoadGRPCOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)),
model.WithAssetDir(o.assetsDestination),
model.WithModelFile(modelFile),
}
if c.Backend == "" {
inferenceModel, err = loader.GreedyLoader(opts...)
} else {
opts = append(opts, model.WithBackendString(c.Backend))
inferenceModel, err = loader.BackendLoader(opts...)
}
if err != nil {
return nil, err
}
var fn func() ([]float32, error)
switch model := inferenceModel.(type) {
case *grpc.Client:
fn = func() ([]float32, error) {
predictOptions := gRPCPredictOpts(c, loader.ModelPath)
if len(tokens) > 0 {
embeds := []int32{}
for _, t := range tokens {
embeds = append(embeds, int32(t))
}
predictOptions.EmbeddingTokens = embeds
res, err := model.Embeddings(context.TODO(), predictOptions)
if err != nil {
return nil, err
}
return res.Embeddings, nil
}
predictOptions.Embeddings = s
res, err := model.Embeddings(context.TODO(), predictOptions)
if err != nil {
return nil, err
}
return res.Embeddings, nil
}
// bert embeddings
case *bert.Bert:
fn = func() ([]float32, error) {
if len(tokens) > 0 {
return model.TokenEmbeddings(tokens, bert.SetThreads(c.Threads))
}
return model.Embeddings(s, bert.SetThreads(c.Threads))
}
default:
fn = func() ([]float32, error) {
return nil, fmt.Errorf("embeddings not supported by the backend")
}
}
return func() ([]float32, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[modelFile]
if !ok {
m := &sync.Mutex{}
mutexes[modelFile] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
embeds, err := fn()
if err != nil {
return embeds, err
}
// Remove trailing 0s
for i := len(embeds) - 1; i >= 0; i-- {
if embeds[i] == 0.0 {
embeds = embeds[:i]
} else {
break
}
}
return embeds, nil
}, nil
}
func ModelInference(s string, loader *model.ModelLoader, c Config, o *Option, tokenCallback func(string) bool) (func() (string, error), error) {
supportStreams := false
modelFile := c.Model
grpcOpts := gRPCModelOpts(c)
var inferenceModel interface{}
var err error
opts := []model.Option{
model.WithLoadGRPCOpts(grpcOpts),
model.WithThreads(uint32(c.Threads)), // GPT4all uses this
model.WithAssetDir(o.assetsDestination),
model.WithModelFile(modelFile),
}
if c.Backend == "" {
inferenceModel, err = loader.GreedyLoader(opts...)
} else {
opts = append(opts, model.WithBackendString(c.Backend))
inferenceModel, err = loader.BackendLoader(opts...)
}
if err != nil {
return nil, err
}
var fn func() (string, error)
switch model := inferenceModel.(type) {
case *rwkv.RwkvState:
supportStreams = true
fn = func() (string, error) {
stopWord := "\n"
if len(c.StopWords) > 0 {
stopWord = c.StopWords[0]
}
if err := model.ProcessInput(s); err != nil {
return "", err
}
response := model.GenerateResponse(c.Maxtokens, stopWord, float32(c.Temperature), float32(c.TopP), tokenCallback)
return response, nil
}
case *bloomz.Bloomz:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []bloomz.PredictOption{
bloomz.SetTemperature(c.Temperature),
bloomz.SetTopP(c.TopP),
bloomz.SetTopK(c.TopK),
bloomz.SetTokens(c.Maxtokens),
bloomz.SetThreads(c.Threads),
}
if c.Seed != 0 {
predictOptions = append(predictOptions, bloomz.SetSeed(c.Seed))
}
return model.Predict(
s,
predictOptions...,
)
}
case *grpc.Client:
// in GRPC, the backend is supposed to answer to 1 single token if stream is not supported
supportStreams = true
fn = func() (string, error) {
opts := gRPCPredictOpts(c, loader.ModelPath)
opts.Prompt = s
if tokenCallback != nil {
ss := ""
err := model.PredictStream(context.TODO(), opts, func(s string) {
tokenCallback(s)
ss += s
})
return ss, err
} else {
reply, err := model.Predict(context.TODO(), opts)
return reply.Message, err
}
}
case *langchain.HuggingFace:
fn = func() (string, error) {
// Generate the prediction using the language model
predictOptions := []langchain.PredictOption{
langchain.SetModel(c.Model),
langchain.SetMaxTokens(c.Maxtokens),
langchain.SetTemperature(c.Temperature),
langchain.SetStopWords(c.StopWords),
}
pred, er := model.PredictHuggingFace(s, predictOptions...)
if er != nil {
return "", er
}
return pred.Completion, nil
}
}
return func() (string, error) {
// This is still needed, see: https://github.com/ggerganov/llama.cpp/discussions/784
mutexMap.Lock()
l, ok := mutexes[modelFile]
if !ok {
m := &sync.Mutex{}
mutexes[modelFile] = m
l = m
}
mutexMap.Unlock()
l.Lock()
defer l.Unlock()
res, err := fn()
if tokenCallback != nil && !supportStreams {
tokenCallback(res)
}
return res, err
}, nil
}
func ComputeChoices(predInput string, input *OpenAIRequest, config *Config, o *Option, loader *model.ModelLoader, cb func(string, *[]Choice), tokenCallback func(string) bool) ([]Choice, error) {
result := []Choice{}
n := input.N
if input.N == 0 {
n = 1
}
// get the model function to call for the result
predFunc, err := ModelInference(predInput, loader, *config, o, tokenCallback)
if err != nil {
return result, err
}
for i := 0; i < n; i++ {
prediction, err := predFunc()
if err != nil {
return result, err
}
prediction = Finetune(*config, predInput, prediction)
cb(prediction, &result)
//result = append(result, Choice{Text: prediction})
}
return result, err
}
var cutstrings map[string]*regexp.Regexp = make(map[string]*regexp.Regexp)
var mu sync.Mutex = sync.Mutex{}
func Finetune(config Config, input, prediction string) string {
if config.Echo {
prediction = input + prediction
}
for _, c := range config.Cutstrings {
mu.Lock()
reg, ok := cutstrings[c]
if !ok {
cutstrings[c] = regexp.MustCompile(c)
reg = cutstrings[c]
}
mu.Unlock()
prediction = reg.ReplaceAllString(prediction, "")
}
for _, c := range config.TrimSpace {
prediction = strings.TrimSpace(strings.TrimPrefix(prediction, c))
}
return prediction
}

35
main.go
View File

@ -5,6 +5,7 @@ import (
"path/filepath"
api "github.com/go-skynet/LocalAI/api"
"github.com/go-skynet/LocalAI/api/options"
"github.com/go-skynet/LocalAI/internal"
model "github.com/go-skynet/LocalAI/pkg/model"
"github.com/rs/zerolog"
@ -129,23 +130,23 @@ For a list of compatible model, check out: https://localai.io/model-compatibilit
Copyright: "Ettore Di Giacinto",
Action: func(ctx *cli.Context) error {
app, err := api.App(
api.WithConfigFile(ctx.String("config-file")),
api.WithJSONStringPreload(ctx.String("preload-models")),
api.WithYAMLConfigPreload(ctx.String("preload-models-config")),
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")),
api.WithF16(ctx.Bool("f16")),
api.WithStringGalleries(ctx.String("galleries")),
api.WithDisableMessage(false),
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")))
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")))
if err != nil {
return err
}

3
pkg/grpc/llm/falcon/falcon.go
View File

@ -126,6 +126,9 @@ func (llm *LLM) PredictStream(opts *pb.PredictOptions, results chan string) {
predictOptions := buildPredictOptions(opts)
predictOptions = append(predictOptions, ggllm.SetTokenCallback(func(token string) bool {
if token == "<|endoftext|>" {
return true
}
results <- token
return true
}))