MQTT Startup Refactoring Part 1: core/ packages part 1 (#1728)

This PR specifically introduces a `core` folder and moves the following packages over, without any other changes:

- `api/backend`
- `api/config`
- `api/options`
- `api/schema`

Once this is merged and we confirm there's no regressions, I can migrate over the remaining changes piece by piece to split up application startup, backend services, http, and mqtt as was the goal of the earlier PRs!

core/backend/embeddings.go

@@ -0,0 +1,92 @@
+package backend
+
+import (
+	"fmt"
+
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/pkg/grpc"
+	model "github.com/go-skynet/LocalAI/pkg/model"
+)
+
+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 := modelOpts(c, o, []model.Option{
+		model.WithLoadGRPCLoadModelOpts(grpcOpts),
+		model.WithThreads(uint32(c.Threads)),
+		model.WithAssetDir(o.AssetsDestination),
+		model.WithModel(modelFile),
+		model.WithContext(o.Context),
+	})
+
+	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.Backend:
+		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(o.Context, predictOptions)
+				if err != nil {
+					return nil, err
+				}
+
+				return res.Embeddings, nil
+			}
+			predictOptions.Embeddings = s
+
+			res, err := model.Embeddings(o.Context, predictOptions)
+			if err != nil {
+				return nil, err
+			}
+
+			return res.Embeddings, nil
+		}
+	default:
+		fn = func() ([]float32, error) {
+			return nil, fmt.Errorf("embeddings not supported by the backend")
+		}
+	}
+
+	return func() ([]float32, error) {
+		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
+}

core/backend/image.go

@@ -0,0 +1,61 @@
+package backend
+
+import (
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
+	model "github.com/go-skynet/LocalAI/pkg/model"
+)
+
+func ImageGeneration(height, width, mode, step, seed int, positive_prompt, negative_prompt, src, dst string, loader *model.ModelLoader, c config.Config, o *options.Option) (func() error, error) {
+
+	opts := modelOpts(c, o, []model.Option{
+		model.WithBackendString(c.Backend),
+		model.WithAssetDir(o.AssetsDestination),
+		model.WithThreads(uint32(c.Threads)),
+		model.WithContext(o.Context),
+		model.WithModel(c.Model),
+		model.WithLoadGRPCLoadModelOpts(&proto.ModelOptions{
+			CUDA:          c.CUDA || c.Diffusers.CUDA,
+			SchedulerType: c.Diffusers.SchedulerType,
+			PipelineType:  c.Diffusers.PipelineType,
+			CFGScale:      c.Diffusers.CFGScale,
+			LoraAdapter:   c.LoraAdapter,
+			LoraScale:     c.LoraScale,
+			LoraBase:      c.LoraBase,
+			IMG2IMG:       c.Diffusers.IMG2IMG,
+			CLIPModel:     c.Diffusers.ClipModel,
+			CLIPSubfolder: c.Diffusers.ClipSubFolder,
+			CLIPSkip:      int32(c.Diffusers.ClipSkip),
+			ControlNet:    c.Diffusers.ControlNet,
+		}),
+	})
+
+	inferenceModel, err := loader.BackendLoader(
+		opts...,
+	)
+	if err != nil {
+		return nil, err
+	}
+
+	fn := func() error {
+		_, err := inferenceModel.GenerateImage(
+			o.Context,
+			&proto.GenerateImageRequest{
+				Height:           int32(height),
+				Width:            int32(width),
+				Mode:             int32(mode),
+				Step:             int32(step),
+				Seed:             int32(seed),
+				CLIPSkip:         int32(c.Diffusers.ClipSkip),
+				PositivePrompt:   positive_prompt,
+				NegativePrompt:   negative_prompt,
+				Dst:              dst,
+				Src:              src,
+				EnableParameters: c.Diffusers.EnableParameters,
+			})
+		return err
+	}
+
+	return fn, nil
+}

core/backend/llm.go

@@ -0,0 +1,167 @@
+package backend
+
+import (
+	"context"
+	"os"
+	"regexp"
+	"strings"
+	"sync"
+	"unicode/utf8"
+
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/pkg/gallery"
+	"github.com/go-skynet/LocalAI/pkg/grpc"
+	model "github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/go-skynet/LocalAI/pkg/utils"
+)
+
+type LLMResponse struct {
+	Response string // should this be []byte?
+	Usage    TokenUsage
+}
+
+type TokenUsage struct {
+	Prompt     int
+	Completion int
+}
+
+func ModelInference(ctx context.Context, s string, images []string, loader *model.ModelLoader, c config.Config, o *options.Option, tokenCallback func(string, TokenUsage) bool) (func() (LLMResponse, error), error) {
+	modelFile := c.Model
+
+	grpcOpts := gRPCModelOpts(c)
+
+	var inferenceModel grpc.Backend
+	var err error
+
+	opts := modelOpts(c, o, []model.Option{
+		model.WithLoadGRPCLoadModelOpts(grpcOpts),
+		model.WithThreads(uint32(c.Threads)), // some models uses this to allocate threads during startup
+		model.WithAssetDir(o.AssetsDestination),
+		model.WithModel(modelFile),
+		model.WithContext(o.Context),
+	})
+
+	if c.Backend != "" {
+		opts = append(opts, model.WithBackendString(c.Backend))
+	}
+
+	// Check if the modelFile exists, if it doesn't try to load it from the gallery
+	if o.AutoloadGalleries { // experimental
+		if _, err := os.Stat(modelFile); os.IsNotExist(err) {
+			utils.ResetDownloadTimers()
+			// if we failed to load the model, we try to download it
+			err := gallery.InstallModelFromGalleryByName(o.Galleries, modelFile, loader.ModelPath, gallery.GalleryModel{}, utils.DisplayDownloadFunction)
+			if err != nil {
+				return nil, err
+			}
+		}
+	}
+
+	if c.Backend == "" {
+		inferenceModel, err = loader.GreedyLoader(opts...)
+	} else {
+		inferenceModel, err = loader.BackendLoader(opts...)
+	}
+
+	if err != nil {
+		return nil, err
+	}
+
+	// in GRPC, the backend is supposed to answer to 1 single token if stream is not supported
+	fn := func() (LLMResponse, error) {
+		opts := gRPCPredictOpts(c, loader.ModelPath)
+		opts.Prompt = s
+		opts.Images = images
+
+		tokenUsage := TokenUsage{}
+
+		// check the per-model feature flag for usage, since tokenCallback may have a cost.
+		// Defaults to off as for now it is still experimental
+		if c.FeatureFlag.Enabled("usage") {
+			userTokenCallback := tokenCallback
+			if userTokenCallback == nil {
+				userTokenCallback = func(token string, usage TokenUsage) bool {
+					return true
+				}
+			}
+
+			promptInfo, pErr := inferenceModel.TokenizeString(ctx, opts)
+			if pErr == nil && promptInfo.Length > 0 {
+				tokenUsage.Prompt = int(promptInfo.Length)
+			}
+
+			tokenCallback = func(token string, usage TokenUsage) bool {
+				tokenUsage.Completion++
+				return userTokenCallback(token, tokenUsage)
+			}
+		}
+
+		if tokenCallback != nil {
+			ss := ""
+
+			var partialRune []byte
+			err := inferenceModel.PredictStream(ctx, opts, func(chars []byte) {
+				partialRune = append(partialRune, chars...)
+
+				for len(partialRune) > 0 {
+					r, size := utf8.DecodeRune(partialRune)
+					if r == utf8.RuneError {
+						// incomplete rune, wait for more bytes
+						break
+					}
+
+					tokenCallback(string(r), tokenUsage)
+					ss += string(r)
+
+					partialRune = partialRune[size:]
+				}
+			})
+			return LLMResponse{
+				Response: ss,
+				Usage:    tokenUsage,
+			}, err
+		} else {
+			// TODO: Is the chicken bit the only way to get here? is that acceptable?
+			reply, err := inferenceModel.Predict(ctx, opts)
+			if err != nil {
+				return LLMResponse{}, err
+			}
+			return LLMResponse{
+				Response: string(reply.Message),
+				Usage:    tokenUsage,
+			}, err
+		}
+	}
+
+	return fn, 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))
+	}
+
+	for _, c := range config.TrimSuffix {
+		prediction = strings.TrimSpace(strings.TrimSuffix(prediction, c))
+	}
+	return prediction
+}

core/backend/options.go

@@ -0,0 +1,129 @@
+package backend
+
+import (
+	"os"
+	"path/filepath"
+
+	pb "github.com/go-skynet/LocalAI/pkg/grpc/proto"
+	model "github.com/go-skynet/LocalAI/pkg/model"
+
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+)
+
+func modelOpts(c config.Config, o *options.Option, opts []model.Option) []model.Option {
+	if o.SingleBackend {
+		opts = append(opts, model.WithSingleActiveBackend())
+	}
+
+	if o.ParallelBackendRequests {
+		opts = append(opts, model.EnableParallelRequests)
+	}
+
+	if c.GRPC.Attempts != 0 {
+		opts = append(opts, model.WithGRPCAttempts(c.GRPC.Attempts))
+	}
+
+	if c.GRPC.AttemptsSleepTime != 0 {
+		opts = append(opts, model.WithGRPCAttemptsDelay(c.GRPC.AttemptsSleepTime))
+	}
+
+	for k, v := range o.ExternalGRPCBackends {
+		opts = append(opts, model.WithExternalBackend(k, v))
+	}
+
+	return opts
+}
+
+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),
+		NoMulMatQ:      c.NoMulMatQ,
+		CUDA:           c.CUDA, // diffusers, transformers
+		DraftModel:     c.DraftModel,
+		AudioPath:      c.VallE.AudioPath,
+		Quantization:   c.Quantization,
+		MMProj:         c.MMProj,
+		YarnExtFactor:  c.YarnExtFactor,
+		YarnAttnFactor: c.YarnAttnFactor,
+		YarnBetaFast:   c.YarnBetaFast,
+		YarnBetaSlow:   c.YarnBetaSlow,
+		LoraAdapter:    c.LoraAdapter,
+		LoraBase:       c.LoraBase,
+		LoraScale:      c.LoraScale,
+		NGQA:           c.NGQA,
+		RMSNormEps:     c.RMSNormEps,
+		F16Memory:      c.F16,
+		MLock:          c.MMlock,
+		RopeFreqBase:   c.RopeFreqBase,
+		RopeScaling:    c.RopeScaling,
+		Type:           c.ModelType,
+		RopeFreqScale:  c.RopeFreqScale,
+		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,
+		// AutoGPTQ
+		ModelBaseName:    c.AutoGPTQ.ModelBaseName,
+		Device:           c.AutoGPTQ.Device,
+		UseTriton:        c.AutoGPTQ.Triton,
+		UseFastTokenizer: c.AutoGPTQ.UseFastTokenizer,
+		// RWKV
+		Tokenizer: c.Tokenizer,
+	}
+}
+
+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),
+		NDraft:              c.NDraft,
+		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,
+		NegativePromptScale: c.NegativePromptScale,
+		RopeFreqBase:        c.RopeFreqBase,
+		RopeFreqScale:       c.RopeFreqScale,
+		NegativePrompt:      c.NegativePrompt,
+		Mirostat:            int32(c.LLMConfig.Mirostat),
+		MirostatETA:         float32(c.LLMConfig.MirostatETA),
+		MirostatTAU:         float32(c.LLMConfig.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),
+	}
+}

core/backend/transcript.go

@@ -0,0 +1,39 @@
+package backend
+
+import (
+	"context"
+	"fmt"
+
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/schema"
+
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
+	model "github.com/go-skynet/LocalAI/pkg/model"
+)
+
+func ModelTranscription(audio, language string, loader *model.ModelLoader, c config.Config, o *options.Option) (*schema.Result, error) {
+
+	opts := modelOpts(c, o, []model.Option{
+		model.WithBackendString(model.WhisperBackend),
+		model.WithModel(c.Model),
+		model.WithContext(o.Context),
+		model.WithThreads(uint32(c.Threads)),
+		model.WithAssetDir(o.AssetsDestination),
+	})
+
+	whisperModel, err := o.Loader.BackendLoader(opts...)
+	if err != nil {
+		return nil, err
+	}
+
+	if whisperModel == nil {
+		return nil, fmt.Errorf("could not load whisper model")
+	}
+
+	return whisperModel.AudioTranscription(context.Background(), &proto.TranscriptRequest{
+		Dst:      audio,
+		Language: language,
+		Threads:  uint32(c.Threads),
+	})
+}

core/backend/tts.go

@@ -0,0 +1,83 @@
+package backend
+
+import (
+	"context"
+	"fmt"
+	"os"
+	"path/filepath"
+
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/pkg/grpc/proto"
+	model "github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/go-skynet/LocalAI/pkg/utils"
+)
+
+func generateUniqueFileName(dir, baseName, ext string) string {
+	counter := 1
+	fileName := baseName + ext
+
+	for {
+		filePath := filepath.Join(dir, fileName)
+		_, err := os.Stat(filePath)
+		if os.IsNotExist(err) {
+			return fileName
+		}
+
+		counter++
+		fileName = fmt.Sprintf("%s_%d%s", baseName, counter, ext)
+	}
+}
+
+func ModelTTS(backend, text, modelFile string, loader *model.ModelLoader, o *options.Option, c config.Config) (string, *proto.Result, error) {
+	bb := backend
+	if bb == "" {
+		bb = model.PiperBackend
+	}
+
+	grpcOpts := gRPCModelOpts(c)
+
+	opts := modelOpts(config.Config{}, o, []model.Option{
+		model.WithBackendString(bb),
+		model.WithModel(modelFile),
+		model.WithContext(o.Context),
+		model.WithAssetDir(o.AssetsDestination),
+		model.WithLoadGRPCLoadModelOpts(grpcOpts),
+	})
+	piperModel, err := o.Loader.BackendLoader(opts...)
+	if err != nil {
+		return "", nil, err
+	}
+
+	if piperModel == nil {
+		return "", nil, fmt.Errorf("could not load piper model")
+	}
+
+	if err := os.MkdirAll(o.AudioDir, 0755); err != nil {
+		return "", nil, fmt.Errorf("failed creating audio directory: %s", err)
+	}
+
+	fileName := generateUniqueFileName(o.AudioDir, "piper", ".wav")
+	filePath := filepath.Join(o.AudioDir, fileName)
+
+	// If the model file is not empty, we pass it joined with the model path
+	modelPath := ""
+	if modelFile != "" {
+		if bb != model.TransformersMusicGen {
+			modelPath = filepath.Join(o.Loader.ModelPath, modelFile)
+			if err := utils.VerifyPath(modelPath, o.Loader.ModelPath); err != nil {
+				return "", nil, err
+			}
+		} else {
+			modelPath = modelFile
+		}
+	}
+
+	res, err := piperModel.TTS(context.Background(), &proto.TTSRequest{
+		Text:  text,
+		Model: modelPath,
+		Dst:   filePath,
+	})
+
+	return filePath, res, err
+}

core/config/config.go

@@ -0,0 +1,429 @@
+package config
+
+import (
+	"errors"
+	"fmt"
+	"io/fs"
+	"os"
+	"path/filepath"
+	"strings"
+	"sync"
+
+	"github.com/go-skynet/LocalAI/pkg/downloader"
+	"github.com/go-skynet/LocalAI/pkg/utils"
+	"github.com/rs/zerolog/log"
+	"gopkg.in/yaml.v3"
+)
+
+type Config struct {
+	PredictionOptions `yaml:"parameters"`
+	Name              string `yaml:"name"`
+
+	F16            bool              `yaml:"f16"`
+	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"`
+
+	PromptStrings, InputStrings                []string `yaml:"-"`
+	InputToken                                 [][]int  `yaml:"-"`
+	functionCallString, functionCallNameString string   `yaml:"-"`
+
+	FunctionsConfig Functions `yaml:"function"`
+
+	FeatureFlag FeatureFlag `yaml:"feature_flags"` // Feature Flag registry. We move fast, and features may break on a per model/backend basis. Registry for (usually temporary) flags that indicate aborting something early.
+	// LLM configs (GPT4ALL, Llama.cpp, ...)
+	LLMConfig `yaml:",inline"`
+
+	// AutoGPTQ specifics
+	AutoGPTQ AutoGPTQ `yaml:"autogptq"`
+
+	// Diffusers
+	Diffusers Diffusers `yaml:"diffusers"`
+	Step      int       `yaml:"step"`
+
+	// GRPC Options
+	GRPC GRPC `yaml:"grpc"`
+
+	// Vall-e-x
+	VallE VallE `yaml:"vall-e"`
+
+	// CUDA
+	// Explicitly enable CUDA or not (some backends might need it)
+	CUDA bool `yaml:"cuda"`
+
+	DownloadFiles []File `yaml:"download_files"`
+
+	Description string `yaml:"description"`
+	Usage       string `yaml:"usage"`
+}
+
+type File struct {
+	Filename string `yaml:"filename" json:"filename"`
+	SHA256   string `yaml:"sha256" json:"sha256"`
+	URI      string `yaml:"uri" json:"uri"`
+}
+
+type VallE struct {
+	AudioPath string `yaml:"audio_path"`
+}
+
+type FeatureFlag map[string]*bool
+
+func (ff FeatureFlag) Enabled(s string) bool {
+	v, exist := ff[s]
+	return exist && v != nil && *v
+}
+
+type GRPC struct {
+	Attempts          int `yaml:"attempts"`
+	AttemptsSleepTime int `yaml:"attempts_sleep_time"`
+}
+
+type Diffusers struct {
+	CUDA             bool    `yaml:"cuda"`
+	PipelineType     string  `yaml:"pipeline_type"`
+	SchedulerType    string  `yaml:"scheduler_type"`
+	EnableParameters string  `yaml:"enable_parameters"` // A list of comma separated parameters to specify
+	CFGScale         float32 `yaml:"cfg_scale"`         // Classifier-Free Guidance Scale
+	IMG2IMG          bool    `yaml:"img2img"`           // Image to Image Diffuser
+	ClipSkip         int     `yaml:"clip_skip"`         // Skip every N frames
+	ClipModel        string  `yaml:"clip_model"`        // Clip model to use
+	ClipSubFolder    string  `yaml:"clip_subfolder"`    // Subfolder to use for clip model
+	ControlNet       string  `yaml:"control_net"`
+}
+
+type LLMConfig struct {
+	SystemPrompt    string   `yaml:"system_prompt"`
+	TensorSplit     string   `yaml:"tensor_split"`
+	MainGPU         string   `yaml:"main_gpu"`
+	RMSNormEps      float32  `yaml:"rms_norm_eps"`
+	NGQA            int32    `yaml:"ngqa"`
+	PromptCachePath string   `yaml:"prompt_cache_path"`
+	PromptCacheAll  bool     `yaml:"prompt_cache_all"`
+	PromptCacheRO   bool     `yaml:"prompt_cache_ro"`
+	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"`
+	Grammar         string   `yaml:"grammar"`
+	StopWords       []string `yaml:"stopwords"`
+	Cutstrings      []string `yaml:"cutstrings"`
+	TrimSpace       []string `yaml:"trimspace"`
+	TrimSuffix      []string `yaml:"trimsuffix"`
+
+	ContextSize  int     `yaml:"context_size"`
+	NUMA         bool    `yaml:"numa"`
+	LoraAdapter  string  `yaml:"lora_adapter"`
+	LoraBase     string  `yaml:"lora_base"`
+	LoraScale    float32 `yaml:"lora_scale"`
+	NoMulMatQ    bool    `yaml:"no_mulmatq"`
+	DraftModel   string  `yaml:"draft_model"`
+	NDraft       int32   `yaml:"n_draft"`
+	Quantization string  `yaml:"quantization"`
+	MMProj       string  `yaml:"mmproj"`
+
+	RopeScaling string `yaml:"rope_scaling"`
+	ModelType   string `yaml:"type"`
+
+	YarnExtFactor  float32 `yaml:"yarn_ext_factor"`
+	YarnAttnFactor float32 `yaml:"yarn_attn_factor"`
+	YarnBetaFast   float32 `yaml:"yarn_beta_fast"`
+	YarnBetaSlow   float32 `yaml:"yarn_beta_slow"`
+}
+
+type AutoGPTQ struct {
+	ModelBaseName    string `yaml:"model_base_name"`
+	Device           string `yaml:"device"`
+	Triton           bool   `yaml:"triton"`
+	UseFastTokenizer bool   `yaml:"use_fast_tokenizer"`
+}
+
+type Functions struct {
+	DisableNoAction         bool   `yaml:"disable_no_action"`
+	NoActionFunctionName    string `yaml:"no_action_function_name"`
+	NoActionDescriptionName string `yaml:"no_action_description_name"`
+	ParallelCalls           bool   `yaml:"parallel_calls"`
+}
+
+type TemplateConfig struct {
+	Chat        string `yaml:"chat"`
+	ChatMessage string `yaml:"chat_message"`
+	Completion  string `yaml:"completion"`
+	Edit        string `yaml:"edit"`
+	Functions   string `yaml:"function"`
+}
+
+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
+}
+
+// Load a config file for a model
+func Load(modelName, modelPath string, cm *ConfigLoader, debug bool, threads, ctx int, f16 bool) (*Config, error) {
+	// Load a config file if present after the model name
+	modelConfig := filepath.Join(modelPath, modelName+".yaml")
+
+	var cfg *Config
+
+	defaults := func() {
+		cfg = DefaultConfig(modelName)
+		cfg.ContextSize = ctx
+		cfg.Threads = threads
+		cfg.F16 = f16
+		cfg.Debug = debug
+	}
+
+	cfgExisting, exists := cm.GetConfig(modelName)
+	if !exists {
+		if _, err := os.Stat(modelConfig); err == nil {
+			if err := cm.LoadConfig(modelConfig); err != nil {
+				return nil, fmt.Errorf("failed loading model config (%s) %s", modelConfig, err.Error())
+			}
+			cfgExisting, exists = cm.GetConfig(modelName)
+			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, nil
+}
+
+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) GetAllConfigs() []Config {
+	cm.Lock()
+	defer cm.Unlock()
+	var res []Config
+	for _, v := range cm.configs {
+		res = append(res, v)
+	}
+	return res
+}
+
+func (cm *ConfigLoader) ListConfigs() []string {
+	cm.Lock()
+	defer cm.Unlock()
+	var res []string
+	for k := range cm.configs {
+		res = append(res, k)
+	}
+	return res
+}
+
+// Preload prepare models if they are not local but url or huggingface repositories
+func (cm *ConfigLoader) Preload(modelPath string) error {
+	cm.Lock()
+	defer cm.Unlock()
+
+	status := func(fileName, current, total string, percent float64) {
+		utils.DisplayDownloadFunction(fileName, current, total, percent)
+	}
+
+	log.Info().Msgf("Preloading models from %s", modelPath)
+
+	for i, config := range cm.configs {
+
+		// Download files and verify their SHA
+		for _, file := range config.DownloadFiles {
+			log.Debug().Msgf("Checking %q exists and matches SHA", file.Filename)
+
+			if err := utils.VerifyPath(file.Filename, modelPath); err != nil {
+				return err
+			}
+			// Create file path
+			filePath := filepath.Join(modelPath, file.Filename)
+
+			if err := downloader.DownloadFile(file.URI, filePath, file.SHA256, status); err != nil {
+				return err
+			}
+		}
+
+		modelURL := config.PredictionOptions.Model
+		modelURL = downloader.ConvertURL(modelURL)
+
+		if downloader.LooksLikeURL(modelURL) {
+			// md5 of model name
+			md5Name := utils.MD5(modelURL)
+
+			// check if file exists
+			if _, err := os.Stat(filepath.Join(modelPath, md5Name)); errors.Is(err, os.ErrNotExist) {
+				err := downloader.DownloadFile(modelURL, filepath.Join(modelPath, md5Name), "", status)
+				if err != nil {
+					return err
+				}
+			}
+
+			cc := cm.configs[i]
+			c := &cc
+			c.PredictionOptions.Model = md5Name
+			cm.configs[i] = *c
+		}
+		if cm.configs[i].Name != "" {
+			log.Info().Msgf("Model name: %s", cm.configs[i].Name)
+		}
+		if cm.configs[i].Description != "" {
+			log.Info().Msgf("Model description: %s", cm.configs[i].Description)
+		}
+		if cm.configs[i].Usage != "" {
+			log.Info().Msgf("Model usage: \n%s", cm.configs[i].Usage)
+		}
+	}
+	return nil
+}
+
+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") && !strings.Contains(file.Name(), ".yml") {
+			continue
+		}
+		c, err := ReadConfig(filepath.Join(path, file.Name()))
+		if err == nil {
+			cm.configs[c.Name] = *c
+		}
+	}
+
+	return nil
+}

core/config/config_test.go

@@ -0,0 +1,56 @@
+package config_test
+
+import (
+	"os"
+
+	. "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/pkg/model"
+	. "github.com/onsi/ginkgo/v2"
+	. "github.com/onsi/gomega"
+)
+
+var _ = Describe("Test cases for config related functions", func() {
+
+	var (
+		configFile string
+	)
+
+	Context("Test Read configuration functions", func() {
+		configFile = os.Getenv("CONFIG_FILE")
+		It("Test ReadConfigFile", func() {
+			config, err := ReadConfigFile(configFile)
+			Expect(err).To(BeNil())
+			Expect(config).ToNot(BeNil())
+			// two configs in config.yaml
+			Expect(config[0].Name).To(Equal("list1"))
+			Expect(config[1].Name).To(Equal("list2"))
+		})
+
+		It("Test LoadConfigs", func() {
+			cm := NewConfigLoader()
+			opts := options.NewOptions()
+			modelLoader := model.NewModelLoader(os.Getenv("MODELS_PATH"))
+			options.WithModelLoader(modelLoader)(opts)
+
+			err := cm.LoadConfigs(opts.Loader.ModelPath)
+			Expect(err).To(BeNil())
+			Expect(cm.ListConfigs()).ToNot(BeNil())
+
+			// config should includes gpt4all models's api.config
+			Expect(cm.ListConfigs()).To(ContainElements("gpt4all"))
+
+			// config should includes gpt2 models's api.config
+			Expect(cm.ListConfigs()).To(ContainElements("gpt4all-2"))
+
+			// config should includes text-embedding-ada-002 models's api.config
+			Expect(cm.ListConfigs()).To(ContainElements("text-embedding-ada-002"))
+
+			// config should includes rwkv_test models's api.config
+			Expect(cm.ListConfigs()).To(ContainElements("rwkv_test"))
+
+			// config should includes whisper-1 models's api.config
+			Expect(cm.ListConfigs()).To(ContainElements("whisper-1"))
+		})
+	})
+})

core/config/prediction.go

@@ -0,0 +1,50 @@
+package 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"`
+
+	NegativePrompt      string  `json:"negative_prompt" yaml:"negative_prompt"`
+	RopeFreqBase        float32 `json:"rope_freq_base" yaml:"rope_freq_base"`
+	RopeFreqScale       float32 `json:"rope_freq_scale" yaml:"rope_freq_scale"`
+	NegativePromptScale float32 `json:"negative_prompt_scale" yaml:"negative_prompt_scale"`
+	// AutoGPTQ
+	UseFastTokenizer bool `json:"use_fast_tokenizer" yaml:"use_fast_tokenizer"`
+
+	// Diffusers
+	ClipSkip int `json:"clip_skip" yaml:"clip_skip"`
+
+	// RWKV (?)
+	Tokenizer string `json:"tokenizer" yaml:"tokenizer"`
+}

core/http/api.go

@@ -0,0 +1,308 @@
+package http
+
+import (
+	"encoding/json"
+	"errors"
+	"fmt"
+	"os"
+	"strings"
+
+	"github.com/go-skynet/LocalAI/api/localai"
+	"github.com/go-skynet/LocalAI/api/openai"
+	config "github.com/go-skynet/LocalAI/core/config"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/core/schema"
+	"github.com/go-skynet/LocalAI/internal"
+	"github.com/go-skynet/LocalAI/metrics"
+	"github.com/go-skynet/LocalAI/pkg/assets"
+	"github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/go-skynet/LocalAI/pkg/startup"
+
+	"github.com/gofiber/fiber/v2"
+	"github.com/gofiber/fiber/v2/middleware/cors"
+	"github.com/gofiber/fiber/v2/middleware/logger"
+	"github.com/gofiber/fiber/v2/middleware/recover"
+	"github.com/rs/zerolog"
+	"github.com/rs/zerolog/log"
+)
+
+func Startup(opts ...options.AppOption) (*options.Option, *config.ConfigLoader, error) {
+	options := options.NewOptions(opts...)
+
+	zerolog.SetGlobalLevel(zerolog.InfoLevel)
+	if options.Debug {
+		zerolog.SetGlobalLevel(zerolog.DebugLevel)
+	}
+
+	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())
+
+	startup.PreloadModelsConfigurations(options.ModelLibraryURL, options.Loader.ModelPath, options.ModelsURL...)
+
+	cl := config.NewConfigLoader()
+	if err := cl.LoadConfigs(options.Loader.ModelPath); err != nil {
+		log.Error().Msgf("error loading config files: %s", err.Error())
+	}
+
+	if options.ConfigFile != "" {
+		if err := cl.LoadConfigFile(options.ConfigFile); err != nil {
+			log.Error().Msgf("error loading config file: %s", err.Error())
+		}
+	}
+
+	if err := cl.Preload(options.Loader.ModelPath); err != nil {
+		log.Error().Msgf("error downloading models: %s", err.Error())
+	}
+
+	if options.PreloadJSONModels != "" {
+		if err := localai.ApplyGalleryFromString(options.Loader.ModelPath, options.PreloadJSONModels, cl, options.Galleries); err != nil {
+			return nil, nil, err
+		}
+	}
+
+	if options.PreloadModelsFromPath != "" {
+		if err := localai.ApplyGalleryFromFile(options.Loader.ModelPath, options.PreloadModelsFromPath, cl, options.Galleries); err != nil {
+			return nil, nil, err
+		}
+	}
+
+	if options.Debug {
+		for _, v := range cl.ListConfigs() {
+			cfg, _ := cl.GetConfig(v)
+			log.Debug().Msgf("Model: %s (config: %+v)", v, cfg)
+		}
+	}
+
+	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)
+		if err != nil {
+			log.Warn().Msgf("Failed extracting backend assets files: %s (might be required for some backends to work properly, like gpt4all)", err)
+		}
+	}
+
+	// turn off any process that was started by GRPC if the context is canceled
+	go func() {
+		<-options.Context.Done()
+		log.Debug().Msgf("Context canceled, shutting down")
+		options.Loader.StopAllGRPC()
+	}()
+
+	if options.WatchDog {
+		wd := model.NewWatchDog(
+			options.Loader,
+			options.WatchDogBusyTimeout,
+			options.WatchDogIdleTimeout,
+			options.WatchDogBusy,
+			options.WatchDogIdle)
+		options.Loader.SetWatchDog(wd)
+		go wd.Run()
+		go func() {
+			<-options.Context.Done()
+			log.Debug().Msgf("Context canceled, shutting down")
+			wd.Shutdown()
+		}()
+	}
+
+	return options, cl, nil
+}
+
+func App(opts ...options.AppOption) (*fiber.App, error) {
+
+	options, cl, err := Startup(opts...)
+	if err != nil {
+		return nil, fmt.Errorf("failed basic startup tasks with error %s", err.Error())
+	}
+
+	// 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,
+		// Override default error handler
+		ErrorHandler: func(ctx *fiber.Ctx, err error) error {
+			// Status code defaults to 500
+			code := fiber.StatusInternalServerError
+
+			// Retrieve the custom status code if it's a *fiber.Error
+			var e *fiber.Error
+			if errors.As(err, &e) {
+				code = e.Code
+			}
+
+			// Send custom error page
+			return ctx.Status(code).JSON(
+				schema.ErrorResponse{
+					Error: &schema.APIError{Message: err.Error(), Code: code},
+				},
+			)
+		},
+	})
+
+	if options.Debug {
+		app.Use(logger.New(logger.Config{
+			Format: "[${ip}]:${port} ${status} - ${method} ${path}\n",
+		}))
+	}
+
+	// Default middleware config
+
+	if !options.Debug {
+		app.Use(recover.New())
+	}
+
+	if options.Metrics != nil {
+		app.Use(metrics.APIMiddleware(options.Metrics))
+	}
+
+	// Auth middleware checking if API key is valid. If no API key is set, no auth is required.
+	auth := func(c *fiber.Ctx) error {
+		if len(options.ApiKeys) == 0 {
+			return c.Next()
+		}
+
+		// Check for api_keys.json file
+		fileContent, err := os.ReadFile("api_keys.json")
+		if err == nil {
+			// Parse JSON content from the file
+			var fileKeys []string
+			err := json.Unmarshal(fileContent, &fileKeys)
+			if err != nil {
+				return c.Status(fiber.StatusInternalServerError).JSON(fiber.Map{"message": "Error parsing api_keys.json"})
+			}
+
+			// Add file keys to options.ApiKeys
+			options.ApiKeys = append(options.ApiKeys, fileKeys...)
+		}
+
+		if len(options.ApiKeys) == 0 {
+			return c.Next()
+		}
+
+		authHeader := c.Get("Authorization")
+		if authHeader == "" {
+			return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Authorization header missing"})
+		}
+		authHeaderParts := strings.Split(authHeader, " ")
+		if len(authHeaderParts) != 2 || authHeaderParts[0] != "Bearer" {
+			return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Invalid Authorization header format"})
+		}
+
+		apiKey := authHeaderParts[1]
+		for _, key := range options.ApiKeys {
+			if apiKey == key {
+				return c.Next()
+			}
+		}
+
+		return c.Status(fiber.StatusUnauthorized).JSON(fiber.Map{"message": "Invalid API key"})
+
+	}
+
+	if options.CORS {
+		var c func(ctx *fiber.Ctx) error
+		if options.CORSAllowOrigins == "" {
+			c = cors.New()
+		} else {
+			c = cors.New(cors.Config{AllowOrigins: options.CORSAllowOrigins})
+		}
+
+		app.Use(c)
+	}
+
+	// LocalAI API endpoints
+	galleryService := localai.NewGalleryService(options.Loader.ModelPath)
+	galleryService.Start(options.Context, cl)
+
+	app.Get("/version", auth, func(c *fiber.Ctx) error {
+		return c.JSON(struct {
+			Version string `json:"version"`
+		}{Version: internal.PrintableVersion()})
+	})
+
+	// Make sure directories exists
+	os.MkdirAll(options.ImageDir, 0755)
+	os.MkdirAll(options.AudioDir, 0755)
+	os.MkdirAll(options.UploadDir, 0755)
+	os.MkdirAll(options.Loader.ModelPath, 0755)
+
+	// Load upload json
+	openai.LoadUploadConfig(options.UploadDir)
+
+	modelGalleryService := localai.CreateModelGalleryService(options.Galleries, options.Loader.ModelPath, galleryService)
+	app.Post("/models/apply", auth, modelGalleryService.ApplyModelGalleryEndpoint())
+	app.Get("/models/available", auth, modelGalleryService.ListModelFromGalleryEndpoint())
+	app.Get("/models/galleries", auth, modelGalleryService.ListModelGalleriesEndpoint())
+	app.Post("/models/galleries", auth, modelGalleryService.AddModelGalleryEndpoint())
+	app.Delete("/models/galleries", auth, modelGalleryService.RemoveModelGalleryEndpoint())
+	app.Get("/models/jobs/:uuid", auth, modelGalleryService.GetOpStatusEndpoint())
+	app.Get("/models/jobs", auth, modelGalleryService.GetAllStatusEndpoint())
+
+	// openAI compatible API endpoint
+
+	// chat
+	app.Post("/v1/chat/completions", auth, openai.ChatEndpoint(cl, options))
+	app.Post("/chat/completions", auth, openai.ChatEndpoint(cl, options))
+
+	// edit
+	app.Post("/v1/edits", auth, openai.EditEndpoint(cl, options))
+	app.Post("/edits", auth, openai.EditEndpoint(cl, options))
+
+	// files
+	app.Post("/v1/files", auth, openai.UploadFilesEndpoint(cl, options))
+	app.Post("/files", auth, openai.UploadFilesEndpoint(cl, options))
+	app.Get("/v1/files", auth, openai.ListFilesEndpoint(cl, options))
+	app.Get("/files", auth, openai.ListFilesEndpoint(cl, options))
+	app.Get("/v1/files/:file_id", auth, openai.GetFilesEndpoint(cl, options))
+	app.Get("/files/:file_id", auth, openai.GetFilesEndpoint(cl, options))
+	app.Delete("/v1/files/:file_id", auth, openai.DeleteFilesEndpoint(cl, options))
+	app.Delete("/files/:file_id", auth, openai.DeleteFilesEndpoint(cl, options))
+	app.Get("/v1/files/:file_id/content", auth, openai.GetFilesContentsEndpoint(cl, options))
+	app.Get("/files/:file_id/content", auth, openai.GetFilesContentsEndpoint(cl, options))
+
+	// completion
+	app.Post("/v1/completions", auth, openai.CompletionEndpoint(cl, options))
+	app.Post("/completions", auth, openai.CompletionEndpoint(cl, options))
+	app.Post("/v1/engines/:model/completions", auth, openai.CompletionEndpoint(cl, options))
+
+	// embeddings
+	app.Post("/v1/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
+	app.Post("/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
+	app.Post("/v1/engines/:model/embeddings", auth, openai.EmbeddingsEndpoint(cl, options))
+
+	// audio
+	app.Post("/v1/audio/transcriptions", auth, openai.TranscriptEndpoint(cl, options))
+	app.Post("/tts", auth, localai.TTSEndpoint(cl, options))
+
+	// images
+	app.Post("/v1/images/generations", auth, openai.ImageEndpoint(cl, options))
+
+	if options.ImageDir != "" {
+		app.Static("/generated-images", options.ImageDir)
+	}
+
+	if options.AudioDir != "" {
+		app.Static("/generated-audio", options.AudioDir)
+	}
+
+	ok := func(c *fiber.Ctx) error {
+		return c.SendStatus(200)
+	}
+
+	// Kubernetes health checks
+	app.Get("/healthz", ok)
+	app.Get("/readyz", ok)
+
+	// Experimental Backend Statistics Module
+	backendMonitor := localai.NewBackendMonitor(cl, options) // Split out for now
+	app.Get("/backend/monitor", localai.BackendMonitorEndpoint(backendMonitor))
+	app.Post("/backend/shutdown", localai.BackendShutdownEndpoint(backendMonitor))
+
+	// models
+	app.Get("/v1/models", auth, openai.ListModelsEndpoint(options.Loader, cl))
+	app.Get("/models", auth, openai.ListModelsEndpoint(options.Loader, cl))
+
+	app.Get("/metrics", metrics.MetricsHandler())
+
+	return app, nil
+}

core/http/api_test.go

@@ -0,0 +1,870 @@
+package http_test
+
+import (
+	"bytes"
+	"context"
+	"embed"
+	"encoding/json"
+	"errors"
+	"fmt"
+	"io"
+	"net/http"
+	"os"
+	"path/filepath"
+	"runtime"
+
+	. "github.com/go-skynet/LocalAI/core/http"
+	"github.com/go-skynet/LocalAI/core/options"
+	"github.com/go-skynet/LocalAI/metrics"
+	"github.com/go-skynet/LocalAI/pkg/downloader"
+	"github.com/go-skynet/LocalAI/pkg/gallery"
+	"github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/gofiber/fiber/v2"
+	. "github.com/onsi/ginkgo/v2"
+	. "github.com/onsi/gomega"
+	"gopkg.in/yaml.v3"
+
+	openaigo "github.com/otiai10/openaigo"
+	"github.com/sashabaranov/go-openai"
+	"github.com/sashabaranov/go-openai/jsonschema"
+)
+
+const testPrompt = `### System:
+You are an AI assistant that follows instruction extremely well. Help as much as you can.
+
+### User:
+
+Can you help rephrasing sentences?
+
+### Response:`
+
+type modelApplyRequest struct {
+	ID        string                 `json:"id"`
+	URL       string                 `json:"url"`
+	Name      string                 `json:"name"`
+	Overrides map[string]interface{} `json:"overrides"`
+}
+
+func getModelStatus(url string) (response map[string]interface{}) {
+	// Create the HTTP request
+	resp, err := http.Get(url)
+	if err != nil {
+		fmt.Println("Error creating request:", err)
+		return
+	}
+	defer resp.Body.Close()
+
+	body, err := io.ReadAll(resp.Body)
+	if err != nil {
+		fmt.Println("Error reading response body:", err)
+		return
+	}
+
+	// Unmarshal the response into a map[string]interface{}
+	err = json.Unmarshal(body, &response)
+	if err != nil {
+		fmt.Println("Error unmarshaling JSON response:", err)
+		return
+	}
+	return
+}
+
+func getModels(url string) (response []gallery.GalleryModel) {
+	downloader.GetURI(url, func(url string, i []byte) error {
+		// Unmarshal YAML data into a struct
+		return json.Unmarshal(i, &response)
+	})
+	return
+}
+
+func postModelApplyRequest(url string, request modelApplyRequest) (response map[string]interface{}) {
+
+	//url := "http://localhost:AI/models/apply"
+
+	// Create the request payload
+
+	payload, err := json.Marshal(request)
+	if err != nil {
+		fmt.Println("Error marshaling JSON:", err)
+		return
+	}
+
+	// Create the HTTP request
+	req, err := http.NewRequest("POST", url, bytes.NewBuffer(payload))
+	if err != nil {
+		fmt.Println("Error creating request:", err)
+		return
+	}
+	req.Header.Set("Content-Type", "application/json")
+
+	// Make the request
+	client := &http.Client{}
+	resp, err := client.Do(req)
+	if err != nil {
+		fmt.Println("Error making request:", err)
+		return
+	}
+	defer resp.Body.Close()
+
+	body, err := io.ReadAll(resp.Body)
+	if err != nil {
+		fmt.Println("Error reading response body:", err)
+		return
+	}
+
+	// Unmarshal the response into a map[string]interface{}
+	err = json.Unmarshal(body, &response)
+	if err != nil {
+		fmt.Println("Error unmarshaling JSON response:", err)
+		return
+	}
+	return
+}
+
+//go:embed backend-assets/*
+var backendAssets embed.FS
+
+var _ = Describe("API test", func() {
+
+	var app *fiber.App
+	var modelLoader *model.ModelLoader
+	var client *openai.Client
+	var client2 *openaigo.Client
+	var c context.Context
+	var cancel context.CancelFunc
+	var tmpdir string
+
+	commonOpts := []options.AppOption{
+		options.WithDebug(true),
+		options.WithDisableMessage(true),
+	}
+
+	Context("API with ephemeral models", func() {
+		BeforeEach(func() {
+			var err error
+			tmpdir, err = os.MkdirTemp("", "")
+			Expect(err).ToNot(HaveOccurred())
+
+			modelLoader = model.NewModelLoader(tmpdir)
+			c, cancel = context.WithCancel(context.Background())
+
+			g := []gallery.GalleryModel{
+				{
+					Name: "bert",
+					URL:  "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
+				},
+				{
+					Name:            "bert2",
+					URL:             "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
+					Overrides:       map[string]interface{}{"foo": "bar"},
+					AdditionalFiles: []gallery.File{{Filename: "foo.yaml", URI: "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml"}},
+				},
+			}
+			out, err := yaml.Marshal(g)
+			Expect(err).ToNot(HaveOccurred())
+			err = os.WriteFile(filepath.Join(tmpdir, "gallery_simple.yaml"), out, 0644)
+			Expect(err).ToNot(HaveOccurred())
+
+			galleries := []gallery.Gallery{
+				{
+					Name: "test",
+					URL:  "file://" + filepath.Join(tmpdir, "gallery_simple.yaml"),
+				},
+			}
+
+			metricsService, err := metrics.SetupMetrics()
+			Expect(err).ToNot(HaveOccurred())
+
+			app, err = App(
+				append(commonOpts,
+					options.WithMetrics(metricsService),
+					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")
+
+			defaultConfig := openai.DefaultConfig("")
+			defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
+
+			client2 = openaigo.NewClient("")
+			client2.BaseURL = defaultConfig.BaseURL
+
+			// Wait for API to be ready
+			client = openai.NewClientWithConfig(defaultConfig)
+			Eventually(func() error {
+				_, err := client.ListModels(context.TODO())
+				return err
+			}, "2m").ShouldNot(HaveOccurred())
+		})
+
+		AfterEach(func() {
+			cancel()
+			app.Shutdown()
+			os.RemoveAll(tmpdir)
+		})
+
+		Context("Applying models", func() {
+			It("applies models from a gallery", func() {
+
+				models := getModels("http://127.0.0.1:9090/models/available")
+				Expect(len(models)).To(Equal(2), fmt.Sprint(models))
+				Expect(models[0].Installed).To(BeFalse(), fmt.Sprint(models))
+				Expect(models[1].Installed).To(BeFalse(), fmt.Sprint(models))
+
+				response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
+					ID: "test@bert2",
+				})
+
+				Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
+
+				uuid := response["uuid"].(string)
+				resp := map[string]interface{}{}
+				Eventually(func() bool {
+					response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
+					fmt.Println(response)
+					resp = response
+					return response["processed"].(bool)
+				}, "360s", "10s").Should(Equal(true))
+				Expect(resp["message"]).ToNot(ContainSubstring("error"))
+
+				dat, err := os.ReadFile(filepath.Join(tmpdir, "bert2.yaml"))
+				Expect(err).ToNot(HaveOccurred())
+
+				_, err = os.ReadFile(filepath.Join(tmpdir, "foo.yaml"))
+				Expect(err).ToNot(HaveOccurred())
+
+				content := map[string]interface{}{}
+				err = yaml.Unmarshal(dat, &content)
+				Expect(err).ToNot(HaveOccurred())
+				Expect(content["backend"]).To(Equal("bert-embeddings"))
+				Expect(content["foo"]).To(Equal("bar"))
+
+				models = getModels("http://127.0.0.1:9090/models/available")
+				Expect(len(models)).To(Equal(2), fmt.Sprint(models))
+				Expect(models[0].Name).To(Or(Equal("bert"), Equal("bert2")))
+				Expect(models[1].Name).To(Or(Equal("bert"), Equal("bert2")))
+				for _, m := range models {
+					if m.Name == "bert2" {
+						Expect(m.Installed).To(BeTrue())
+					} else {
+						Expect(m.Installed).To(BeFalse())
+					}
+				}
+			})
+			It("overrides models", func() {
+				response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
+					URL:  "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
+					Name: "bert",
+					Overrides: map[string]interface{}{
+						"backend": "llama",
+					},
+				})
+
+				Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
+
+				uuid := response["uuid"].(string)
+
+				Eventually(func() bool {
+					response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
+					return response["processed"].(bool)
+				}, "360s", "10s").Should(Equal(true))
+
+				dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
+				Expect(err).ToNot(HaveOccurred())
+
+				content := map[string]interface{}{}
+				err = yaml.Unmarshal(dat, &content)
+				Expect(err).ToNot(HaveOccurred())
+				Expect(content["backend"]).To(Equal("llama"))
+			})
+			It("apply models without overrides", func() {
+				response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
+					URL:       "https://raw.githubusercontent.com/go-skynet/model-gallery/main/bert-embeddings.yaml",
+					Name:      "bert",
+					Overrides: map[string]interface{}{},
+				})
+
+				Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
+
+				uuid := response["uuid"].(string)
+
+				Eventually(func() bool {
+					response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
+					return response["processed"].(bool)
+				}, "360s", "10s").Should(Equal(true))
+
+				dat, err := os.ReadFile(filepath.Join(tmpdir, "bert.yaml"))
+				Expect(err).ToNot(HaveOccurred())
+
+				content := map[string]interface{}{}
+				err = yaml.Unmarshal(dat, &content)
+				Expect(err).ToNot(HaveOccurred())
+				Expect(content["backend"]).To(Equal("bert-embeddings"))
+			})
+
+			It("runs openllama(llama-ggml backend)", Label("llama"), func() {
+				if runtime.GOOS != "linux" {
+					Skip("test supported only on linux")
+				}
+				response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
+					URL:       "github:go-skynet/model-gallery/openllama_3b.yaml",
+					Name:      "openllama_3b",
+					Overrides: map[string]interface{}{"backend": "llama-ggml", "mmap": true, "f16": true, "context_size": 128},
+				})
+
+				Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
+
+				uuid := response["uuid"].(string)
+
+				Eventually(func() bool {
+					response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
+					return response["processed"].(bool)
+				}, "360s", "10s").Should(Equal(true))
+
+				By("testing completion")
+				resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "openllama_3b", Prompt: "Count up to five: one, two, three, four, "})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp.Choices)).To(Equal(1))
+				Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
+
+				By("testing functions")
+				resp2, err := client.CreateChatCompletion(
+					context.TODO(),
+					openai.ChatCompletionRequest{
+						Model: "openllama_3b",
+						Messages: []openai.ChatCompletionMessage{
+							{
+								Role:    "user",
+								Content: "What is the weather like in San Francisco (celsius)?",
+							},
+						},
+						Functions: []openai.FunctionDefinition{
+							openai.FunctionDefinition{
+								Name:        "get_current_weather",
+								Description: "Get the current weather",
+								Parameters: jsonschema.Definition{
+									Type: jsonschema.Object,
+									Properties: map[string]jsonschema.Definition{
+										"location": {
+											Type:        jsonschema.String,
+											Description: "The city and state, e.g. San Francisco, CA",
+										},
+										"unit": {
+											Type: jsonschema.String,
+											Enum: []string{"celcius", "fahrenheit"},
+										},
+									},
+									Required: []string{"location"},
+								},
+							},
+						},
+					})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp2.Choices)).To(Equal(1))
+				Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil())
+				Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name)
+
+				var res map[string]string
+				err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res)
+				Expect(err).ToNot(HaveOccurred())
+				Expect(res["location"]).To(Equal("San Francisco, California, United States"), fmt.Sprint(res))
+				Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res))
+				Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
+
+			})
+
+			It("runs openllama gguf(llama-cpp)", Label("llama-gguf"), func() {
+				if runtime.GOOS != "linux" {
+					Skip("test supported only on linux")
+				}
+				modelName := "codellama"
+				response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
+					URL:       "github:go-skynet/model-gallery/codellama-7b-instruct.yaml",
+					Name:      modelName,
+					Overrides: map[string]interface{}{"backend": "llama", "mmap": true, "f16": true, "context_size": 128},
+				})
+
+				Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
+
+				uuid := response["uuid"].(string)
+
+				Eventually(func() bool {
+					response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
+					return response["processed"].(bool)
+				}, "360s", "10s").Should(Equal(true))
+
+				By("testing chat")
+				resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: modelName, Messages: []openai.ChatCompletionMessage{
+					{
+						Role:    "user",
+						Content: "How much is 2+2?",
+					},
+				}})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp.Choices)).To(Equal(1))
+				Expect(resp.Choices[0].Message.Content).To(Or(ContainSubstring("4"), ContainSubstring("four")))
+
+				By("testing functions")
+				resp2, err := client.CreateChatCompletion(
+					context.TODO(),
+					openai.ChatCompletionRequest{
+						Model: modelName,
+						Messages: []openai.ChatCompletionMessage{
+							{
+								Role:    "user",
+								Content: "What is the weather like in San Francisco (celsius)?",
+							},
+						},
+						Functions: []openai.FunctionDefinition{
+							openai.FunctionDefinition{
+								Name:        "get_current_weather",
+								Description: "Get the current weather",
+								Parameters: jsonschema.Definition{
+									Type: jsonschema.Object,
+									Properties: map[string]jsonschema.Definition{
+										"location": {
+											Type:        jsonschema.String,
+											Description: "The city and state, e.g. San Francisco, CA",
+										},
+										"unit": {
+											Type: jsonschema.String,
+											Enum: []string{"celcius", "fahrenheit"},
+										},
+									},
+									Required: []string{"location"},
+								},
+							},
+						},
+					})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp2.Choices)).To(Equal(1))
+				Expect(resp2.Choices[0].Message.FunctionCall).ToNot(BeNil())
+				Expect(resp2.Choices[0].Message.FunctionCall.Name).To(Equal("get_current_weather"), resp2.Choices[0].Message.FunctionCall.Name)
+
+				var res map[string]string
+				err = json.Unmarshal([]byte(resp2.Choices[0].Message.FunctionCall.Arguments), &res)
+				Expect(err).ToNot(HaveOccurred())
+				Expect(res["location"]).To(Equal("San Francisco"), fmt.Sprint(res))
+				Expect(res["unit"]).To(Equal("celcius"), fmt.Sprint(res))
+				Expect(string(resp2.Choices[0].FinishReason)).To(Equal("function_call"), fmt.Sprint(resp2.Choices[0].FinishReason))
+			})
+
+			It("runs gpt4all", Label("gpt4all"), func() {
+				if runtime.GOOS != "linux" {
+					Skip("test supported only on linux")
+				}
+
+				response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
+					URL:  "github:go-skynet/model-gallery/gpt4all-j.yaml",
+					Name: "gpt4all-j",
+				})
+
+				Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
+
+				uuid := response["uuid"].(string)
+
+				Eventually(func() bool {
+					response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
+					return response["processed"].(bool)
+				}, "960s", "10s").Should(Equal(true))
+
+				resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "gpt4all-j", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: "How are you?"}}})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp.Choices)).To(Equal(1))
+				Expect(resp.Choices[0].Message.Content).To(ContainSubstring("well"))
+			})
+
+		})
+	})
+
+	Context("Model gallery", func() {
+		BeforeEach(func() {
+			var err error
+			tmpdir, err = os.MkdirTemp("", "")
+			Expect(err).ToNot(HaveOccurred())
+
+			modelLoader = model.NewModelLoader(tmpdir)
+			c, cancel = context.WithCancel(context.Background())
+
+			galleries := []gallery.Gallery{
+				{
+					Name: "model-gallery",
+					URL:  "https://raw.githubusercontent.com/go-skynet/model-gallery/main/index.yaml",
+				},
+			}
+
+			metricsService, err := metrics.SetupMetrics()
+			Expect(err).ToNot(HaveOccurred())
+
+			app, err = App(
+				append(commonOpts,
+					options.WithContext(c),
+					options.WithMetrics(metricsService),
+					options.WithAudioDir(tmpdir),
+					options.WithImageDir(tmpdir),
+					options.WithGalleries(galleries),
+					options.WithModelLoader(modelLoader),
+					options.WithBackendAssets(backendAssets),
+					options.WithBackendAssetsOutput(tmpdir))...,
+			)
+			Expect(err).ToNot(HaveOccurred())
+			go app.Listen("127.0.0.1:9090")
+
+			defaultConfig := openai.DefaultConfig("")
+			defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
+
+			client2 = openaigo.NewClient("")
+			client2.BaseURL = defaultConfig.BaseURL
+
+			// Wait for API to be ready
+			client = openai.NewClientWithConfig(defaultConfig)
+			Eventually(func() error {
+				_, err := client.ListModels(context.TODO())
+				return err
+			}, "2m").ShouldNot(HaveOccurred())
+		})
+
+		AfterEach(func() {
+			cancel()
+			app.Shutdown()
+			os.RemoveAll(tmpdir)
+		})
+		It("installs and is capable to run tts", Label("tts"), func() {
+			if runtime.GOOS != "linux" {
+				Skip("test supported only on linux")
+			}
+
+			response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
+				ID: "model-gallery@voice-en-us-kathleen-low",
+			})
+
+			Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
+
+			uuid := response["uuid"].(string)
+
+			Eventually(func() bool {
+				response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
+				fmt.Println(response)
+				return response["processed"].(bool)
+			}, "360s", "10s").Should(Equal(true))
+
+			// An HTTP Post to the /tts endpoint should return a wav audio file
+			resp, err := http.Post("http://127.0.0.1:9090/tts", "application/json", bytes.NewBuffer([]byte(`{"input": "Hello world", "model": "en-us-kathleen-low.onnx"}`)))
+			Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
+			dat, err := io.ReadAll(resp.Body)
+			Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
+
+			Expect(resp.StatusCode).To(Equal(200), fmt.Sprint(string(dat)))
+			Expect(resp.Header.Get("Content-Type")).To(Equal("audio/x-wav"))
+		})
+		It("installs and is capable to generate images", Label("stablediffusion"), func() {
+			if runtime.GOOS != "linux" {
+				Skip("test supported only on linux")
+			}
+
+			response := postModelApplyRequest("http://127.0.0.1:9090/models/apply", modelApplyRequest{
+				ID: "model-gallery@stablediffusion",
+				Overrides: map[string]interface{}{
+					"parameters": map[string]interface{}{"model": "stablediffusion_assets"},
+				},
+			})
+
+			Expect(response["uuid"]).ToNot(BeEmpty(), fmt.Sprint(response))
+
+			uuid := response["uuid"].(string)
+
+			Eventually(func() bool {
+				response := getModelStatus("http://127.0.0.1:9090/models/jobs/" + uuid)
+				fmt.Println(response)
+				return response["processed"].(bool)
+			}, "360s", "10s").Should(Equal(true))
+
+			resp, err := http.Post(
+				"http://127.0.0.1:9090/v1/images/generations",
+				"application/json",
+				bytes.NewBuffer([]byte(`{
+					 			"prompt": "floating hair, portrait, ((loli)), ((one girl)), cute face, hidden hands, asymmetrical bangs, beautiful detailed eyes, eye shadow, hair ornament, ribbons, bowties, buttons, pleated skirt, (((masterpiece))), ((best quality)), colorful|((part of the head)), ((((mutated hands and fingers)))), deformed, blurry, bad anatomy, disfigured, poorly drawn face, mutation, mutated, extra limb, ugly, poorly drawn hands, missing limb, blurry, floating limbs, disconnected limbs, malformed hands, blur, out of focus, long neck, long body, Octane renderer, lowres, bad anatomy, bad hands, text",
+								"mode": 2,  "seed":9000,
+					 			"size": "256x256", "n":2}`)))
+			// The response should contain an URL
+			Expect(err).ToNot(HaveOccurred(), fmt.Sprint(resp))
+			dat, err := io.ReadAll(resp.Body)
+			Expect(err).ToNot(HaveOccurred(), string(dat))
+			Expect(string(dat)).To(ContainSubstring("http://127.0.0.1:9090/"), string(dat))
+			Expect(string(dat)).To(ContainSubstring(".png"), string(dat))
+
+		})
+	})
+
+	Context("API query", func() {
+		BeforeEach(func() {
+			modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
+			c, cancel = context.WithCancel(context.Background())
+
+			metricsService, err := metrics.SetupMetrics()
+			Expect(err).ToNot(HaveOccurred())
+
+			app, err = App(
+				append(commonOpts,
+					options.WithExternalBackend("huggingface", os.Getenv("HUGGINGFACE_GRPC")),
+					options.WithContext(c),
+					options.WithModelLoader(modelLoader),
+					options.WithMetrics(metricsService),
+				)...)
+			Expect(err).ToNot(HaveOccurred())
+			go app.Listen("127.0.0.1:9090")
+
+			defaultConfig := openai.DefaultConfig("")
+			defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
+
+			client2 = openaigo.NewClient("")
+			client2.BaseURL = defaultConfig.BaseURL
+
+			// Wait for API to be ready
+			client = openai.NewClientWithConfig(defaultConfig)
+			Eventually(func() error {
+				_, err := client.ListModels(context.TODO())
+				return err
+			}, "2m").ShouldNot(HaveOccurred())
+		})
+		AfterEach(func() {
+			cancel()
+			app.Shutdown()
+		})
+		It("returns the models list", func() {
+			models, err := client.ListModels(context.TODO())
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(models.Models)).To(Equal(6)) // If "config.yaml" should be included, this should be 8?
+		})
+		It("can generate completions", func() {
+			resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "testmodel", Prompt: testPrompt})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Text).ToNot(BeEmpty())
+		})
+
+		It("can generate chat completions ", func() {
+			resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "testmodel", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: testPrompt}}})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
+		})
+
+		It("can generate completions from model configs", func() {
+			resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "gpt4all", Prompt: testPrompt})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Text).ToNot(BeEmpty())
+		})
+
+		It("can generate chat completions from model configs", func() {
+			resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "gpt4all-2", Messages: []openai.ChatCompletionMessage{openai.ChatCompletionMessage{Role: "user", Content: testPrompt}}})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
+		})
+
+		It("returns errors", func() {
+			backends := len(model.AutoLoadBackends) + 1 // +1 for huggingface
+			_, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "foomodel", Prompt: testPrompt})
+			Expect(err).To(HaveOccurred())
+			Expect(err.Error()).To(ContainSubstring(fmt.Sprintf("error, status code: 500, message: could not load model - all backends returned error: %d errors occurred:", backends)))
+		})
+		It("transcribes audio", func() {
+			if runtime.GOOS != "linux" {
+				Skip("test supported only on linux")
+			}
+			resp, err := client.CreateTranscription(
+				context.Background(),
+				openai.AudioRequest{
+					Model:    openai.Whisper1,
+					FilePath: filepath.Join(os.Getenv("TEST_DIR"), "audio.wav"),
+				},
+			)
+			Expect(err).ToNot(HaveOccurred())
+			Expect(resp.Text).To(ContainSubstring("This is the Micro Machine Man presenting"))
+		})
+
+		It("calculate embeddings", func() {
+			if runtime.GOOS != "linux" {
+				Skip("test supported only on linux")
+			}
+			resp, err := client.CreateEmbeddings(
+				context.Background(),
+				openai.EmbeddingRequest{
+					Model: openai.AdaEmbeddingV2,
+					Input: []string{"sun", "cat"},
+				},
+			)
+			Expect(err).ToNot(HaveOccurred(), err)
+			Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
+			Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
+
+			sunEmbedding := resp.Data[0].Embedding
+			resp2, err := client.CreateEmbeddings(
+				context.Background(),
+				openai.EmbeddingRequest{
+					Model: openai.AdaEmbeddingV2,
+					Input: []string{"sun"},
+				},
+			)
+			Expect(err).ToNot(HaveOccurred())
+			Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
+		})
+
+		Context("External gRPC calls", func() {
+			It("calculate embeddings with sentencetransformers", func() {
+				if runtime.GOOS != "linux" {
+					Skip("test supported only on linux")
+				}
+				resp, err := client.CreateEmbeddings(
+					context.Background(),
+					openai.EmbeddingRequest{
+						Model: openai.AdaCodeSearchCode,
+						Input: []string{"sun", "cat"},
+					},
+				)
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp.Data[0].Embedding)).To(BeNumerically("==", 384))
+				Expect(len(resp.Data[1].Embedding)).To(BeNumerically("==", 384))
+
+				sunEmbedding := resp.Data[0].Embedding
+				resp2, err := client.CreateEmbeddings(
+					context.Background(),
+					openai.EmbeddingRequest{
+						Model: openai.AdaCodeSearchCode,
+						Input: []string{"sun"},
+					},
+				)
+				Expect(err).ToNot(HaveOccurred())
+				Expect(resp2.Data[0].Embedding).To(Equal(sunEmbedding))
+				Expect(resp2.Data[0].Embedding).ToNot(Equal(resp.Data[1].Embedding))
+			})
+		})
+
+		Context("backends", func() {
+			It("runs rwkv completion", func() {
+				if runtime.GOOS != "linux" {
+					Skip("test supported only on linux")
+				}
+				resp, err := client.CreateCompletion(context.TODO(), openai.CompletionRequest{Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,"})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp.Choices) > 0).To(BeTrue())
+				Expect(resp.Choices[0].Text).To(ContainSubstring("five"))
+
+				stream, err := client.CreateCompletionStream(context.TODO(), openai.CompletionRequest{
+					Model: "rwkv_test", Prompt: "Count up to five: one, two, three, four,", Stream: true,
+				})
+				Expect(err).ToNot(HaveOccurred())
+				defer stream.Close()
+
+				tokens := 0
+				text := ""
+				for {
+					response, err := stream.Recv()
+					if errors.Is(err, io.EOF) {
+						break
+					}
+
+					Expect(err).ToNot(HaveOccurred())
+					text += response.Choices[0].Text
+					tokens++
+				}
+				Expect(text).ToNot(BeEmpty())
+				Expect(text).To(ContainSubstring("five"))
+				Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
+			})
+			It("runs rwkv chat completion", func() {
+				if runtime.GOOS != "linux" {
+					Skip("test supported only on linux")
+				}
+				resp, err := client.CreateChatCompletion(context.TODO(),
+					openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
+				Expect(err).ToNot(HaveOccurred())
+				Expect(len(resp.Choices) > 0).To(BeTrue())
+				Expect(resp.Choices[0].Message.Content).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
+
+				stream, err := client.CreateChatCompletionStream(context.TODO(), openai.ChatCompletionRequest{Model: "rwkv_test", Messages: []openai.ChatCompletionMessage{{Content: "Can you count up to five?", Role: "user"}}})
+				Expect(err).ToNot(HaveOccurred())
+				defer stream.Close()
+
+				tokens := 0
+				text := ""
+				for {
+					response, err := stream.Recv()
+					if errors.Is(err, io.EOF) {
+						break
+					}
+
+					Expect(err).ToNot(HaveOccurred())
+					text += response.Choices[0].Delta.Content
+					tokens++
+				}
+				Expect(text).ToNot(BeEmpty())
+				Expect(text).To(Or(ContainSubstring("Sure"), ContainSubstring("five")))
+
+				Expect(tokens).ToNot(Or(Equal(1), Equal(0)))
+			})
+		})
+	})
+
+	Context("Config file", func() {
+		BeforeEach(func() {
+			modelLoader = model.NewModelLoader(os.Getenv("MODELS_PATH"))
+			c, cancel = context.WithCancel(context.Background())
+
+			metricsService, err := metrics.SetupMetrics()
+			Expect(err).ToNot(HaveOccurred())
+
+			app, err = App(
+				append(commonOpts,
+					options.WithContext(c),
+					options.WithMetrics(metricsService),
+					options.WithModelLoader(modelLoader),
+					options.WithConfigFile(os.Getenv("CONFIG_FILE")))...,
+			)
+			Expect(err).ToNot(HaveOccurred())
+			go app.Listen("127.0.0.1:9090")
+
+			defaultConfig := openai.DefaultConfig("")
+			defaultConfig.BaseURL = "http://127.0.0.1:9090/v1"
+			client2 = openaigo.NewClient("")
+			client2.BaseURL = defaultConfig.BaseURL
+			// Wait for API to be ready
+			client = openai.NewClientWithConfig(defaultConfig)
+			Eventually(func() error {
+				_, err := client.ListModels(context.TODO())
+				return err
+			}, "2m").ShouldNot(HaveOccurred())
+		})
+		AfterEach(func() {
+			cancel()
+			app.Shutdown()
+		})
+		It("can generate chat completions from config file (list1)", func() {
+			resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list1", Messages: []openai.ChatCompletionMessage{{Role: "user", Content: testPrompt}}})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
+		})
+		It("can generate chat completions from config file (list2)", func() {
+			resp, err := client.CreateChatCompletion(context.TODO(), openai.ChatCompletionRequest{Model: "list2", Messages: []openai.ChatCompletionMessage{{Role: "user", Content: testPrompt}}})
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Message.Content).ToNot(BeEmpty())
+		})
+		It("can generate edit completions from config file", func() {
+			request := openaigo.EditCreateRequestBody{
+				Model:       "list2",
+				Instruction: "foo",
+				Input:       "bar",
+			}
+			resp, err := client2.CreateEdit(context.Background(), request)
+			Expect(err).ToNot(HaveOccurred())
+			Expect(len(resp.Choices)).To(Equal(1))
+			Expect(resp.Choices[0].Text).ToNot(BeEmpty())
+		})
+
+	})
+})

core/http/apt_suite_test.go

@@ -0,0 +1,13 @@
+package http_test
+
+import (
+	"testing"
+
+	. "github.com/onsi/ginkgo/v2"
+	. "github.com/onsi/gomega"
+)
+
+func TestLocalAI(t *testing.T) {
+	RegisterFailHandler(Fail)
+	RunSpecs(t, "LocalAI test suite")
+}

core/options/options.go

@@ -0,0 +1,269 @@
+package options
+
+import (
+	"context"
+	"embed"
+	"encoding/json"
+	"time"
+
+	"github.com/go-skynet/LocalAI/metrics"
+	"github.com/go-skynet/LocalAI/pkg/gallery"
+	model "github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/rs/zerolog/log"
+)
+
+type Option struct {
+	Context                             context.Context
+	ConfigFile                          string
+	Loader                              *model.ModelLoader
+	UploadLimitMB, Threads, ContextSize int
+	F16                                 bool
+	Debug, DisableMessage               bool
+	ImageDir                            string
+	AudioDir                            string
+	UploadDir                           string
+	CORS                                bool
+	PreloadJSONModels                   string
+	PreloadModelsFromPath               string
+	CORSAllowOrigins                    string
+	ApiKeys                             []string
+	Metrics                             *metrics.Metrics
+
+	ModelLibraryURL string
+
+	Galleries []gallery.Gallery
+
+	BackendAssets     embed.FS
+	AssetsDestination string
+
+	ExternalGRPCBackends map[string]string
+
+	AutoloadGalleries bool
+
+	SingleBackend           bool
+	ParallelBackendRequests bool
+
+	WatchDogIdle bool
+	WatchDogBusy bool
+	WatchDog     bool
+
+	ModelsURL []string
+
+	WatchDogBusyTimeout, WatchDogIdleTimeout time.Duration
+}
+
+type AppOption func(*Option)
+
+func NewOptions(o ...AppOption) *Option {
+	opt := &Option{
+		Context:        context.Background(),
+		UploadLimitMB:  15,
+		Threads:        1,
+		ContextSize:    512,
+		Debug:          true,
+		DisableMessage: true,
+	}
+	for _, oo := range o {
+		oo(opt)
+	}
+	return opt
+}
+
+func WithModelsURL(urls ...string) AppOption {
+	return func(o *Option) {
+		o.ModelsURL = urls
+	}
+}
+
+func WithCors(b bool) AppOption {
+	return func(o *Option) {
+		o.CORS = b
+	}
+}
+
+func WithModelLibraryURL(url string) AppOption {
+	return func(o *Option) {
+		o.ModelLibraryURL = url
+	}
+}
+
+var EnableWatchDog = func(o *Option) {
+	o.WatchDog = true
+}
+
+var EnableWatchDogIdleCheck = func(o *Option) {
+	o.WatchDog = true
+	o.WatchDogIdle = true
+}
+
+var EnableWatchDogBusyCheck = func(o *Option) {
+	o.WatchDog = true
+	o.WatchDogBusy = true
+}
+
+func SetWatchDogBusyTimeout(t time.Duration) AppOption {
+	return func(o *Option) {
+		o.WatchDogBusyTimeout = t
+	}
+}
+
+func SetWatchDogIdleTimeout(t time.Duration) AppOption {
+	return func(o *Option) {
+		o.WatchDogIdleTimeout = t
+	}
+}
+
+var EnableSingleBackend = func(o *Option) {
+	o.SingleBackend = true
+}
+
+var EnableParallelBackendRequests = func(o *Option) {
+	o.ParallelBackendRequests = true
+}
+
+var EnableGalleriesAutoload = func(o *Option) {
+	o.AutoloadGalleries = true
+}
+
+func WithExternalBackend(name string, uri string) AppOption {
+	return func(o *Option) {
+		if o.ExternalGRPCBackends == nil {
+			o.ExternalGRPCBackends = make(map[string]string)
+		}
+		o.ExternalGRPCBackends[name] = uri
+	}
+}
+
+func WithCorsAllowOrigins(b string) AppOption {
+	return func(o *Option) {
+		o.CORSAllowOrigins = b
+	}
+}
+
+func WithBackendAssetsOutput(out string) AppOption {
+	return func(o *Option) {
+		o.AssetsDestination = out
+	}
+}
+
+func WithBackendAssets(f embed.FS) AppOption {
+	return func(o *Option) {
+		o.BackendAssets = f
+	}
+}
+
+func WithStringGalleries(galls string) AppOption {
+	return func(o *Option) {
+		if galls == "" {
+			log.Debug().Msgf("no galleries to load")
+			o.Galleries = []gallery.Gallery{}
+			return
+		}
+		var galleries []gallery.Gallery
+		if err := json.Unmarshal([]byte(galls), &galleries); err != nil {
+			log.Error().Msgf("failed loading galleries: %s", err.Error())
+		}
+		o.Galleries = append(o.Galleries, galleries...)
+	}
+}
+
+func WithGalleries(galleries []gallery.Gallery) AppOption {
+	return func(o *Option) {
+		o.Galleries = append(o.Galleries, galleries...)
+	}
+}
+
+func WithContext(ctx context.Context) AppOption {
+	return func(o *Option) {
+		o.Context = ctx
+	}
+}
+
+func WithYAMLConfigPreload(configFile string) AppOption {
+	return func(o *Option) {
+		o.PreloadModelsFromPath = configFile
+	}
+}
+
+func WithJSONStringPreload(configFile string) AppOption {
+	return func(o *Option) {
+		o.PreloadJSONModels = configFile
+	}
+}
+func WithConfigFile(configFile string) AppOption {
+	return func(o *Option) {
+		o.ConfigFile = configFile
+	}
+}
+
+func WithModelLoader(loader *model.ModelLoader) AppOption {
+	return func(o *Option) {
+		o.Loader = loader
+	}
+}
+
+func WithUploadLimitMB(limit int) AppOption {
+	return func(o *Option) {
+		o.UploadLimitMB = limit
+	}
+}
+
+func WithThreads(threads int) AppOption {
+	return func(o *Option) {
+		o.Threads = threads
+	}
+}
+
+func WithContextSize(ctxSize int) AppOption {
+	return func(o *Option) {
+		o.ContextSize = ctxSize
+	}
+}
+
+func WithF16(f16 bool) AppOption {
+	return func(o *Option) {
+		o.F16 = f16
+	}
+}
+
+func WithDebug(debug bool) AppOption {
+	return func(o *Option) {
+		o.Debug = debug
+	}
+}
+
+func WithDisableMessage(disableMessage bool) AppOption {
+	return func(o *Option) {
+		o.DisableMessage = disableMessage
+	}
+}
+
+func WithAudioDir(audioDir string) AppOption {
+	return func(o *Option) {
+		o.AudioDir = audioDir
+	}
+}
+
+func WithImageDir(imageDir string) AppOption {
+	return func(o *Option) {
+		o.ImageDir = imageDir
+	}
+}
+
+func WithUploadDir(uploadDir string) AppOption {
+	return func(o *Option) {
+		o.UploadDir = uploadDir
+	}
+}
+
+func WithApiKeys(apiKeys []string) AppOption {
+	return func(o *Option) {
+		o.ApiKeys = apiKeys
+	}
+}
+
+func WithMetrics(meter *metrics.Metrics) AppOption {
+	return func(o *Option) {
+		o.Metrics = meter
+	}
+}

core/schema/openai.go

@@ -0,0 +1,156 @@
+package schema
+
+import (
+	"context"
+
+	config "github.com/go-skynet/LocalAI/core/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"`
+	FinishReason string   `json:"finish_reason,omitempty"`
+	Message      *Message `json:"message,omitempty"`
+	Delta        *Message `json:"delta,omitempty"`
+	Text         string   `json:"text,omitempty"`
+}
+
+type Content struct {
+	Type     string     `json:"type" yaml:"type"`
+	Text     string     `json:"text" yaml:"text"`
+	ImageURL ContentURL `json:"image_url" yaml:"image_url"`
+}
+
+type ContentURL struct {
+	URL string `json:"url" yaml:"url"`
+}
+
+type Message struct {
+	// The message role
+	Role string `json:"role,omitempty" yaml:"role"`
+
+	// The message name (used for tools calls)
+	Name string `json:"name,omitempty" yaml:"name"`
+
+	// The message content
+	Content interface{} `json:"content" yaml:"content"`
+
+	StringContent string   `json:"string_content,omitempty" yaml:"string_content,omitempty"`
+	StringImages  []string `json:"string_images,omitempty" yaml:"string_images,omitempty"`
+
+	// A result of a function call
+	FunctionCall interface{} `json:"function_call,omitempty" yaml:"function_call,omitempty"`
+
+	ToolCalls []ToolCall `json:"tool_calls,omitempty" yaml:"tool_call,omitempty"`
+}
+
+type ToolCall struct {
+	Index        int          `json:"index"`
+	ID           string       `json:"id"`
+	Type         string       `json:"type"`
+	FunctionCall FunctionCall `json:"function"`
+}
+
+type FunctionCall struct {
+	Name      string `json:"name,omitempty"`
+	Arguments string `json:"arguments"`
+}
+
+type OpenAIModel struct {
+	ID     string `json:"id"`
+	Object string `json:"object"`
+}
+
+type ChatCompletionResponseFormatType string
+
+type ChatCompletionResponseFormat struct {
+	Type ChatCompletionResponseFormatType `json:"type,omitempty"`
+}
+
+type OpenAIRequest struct {
+	config.PredictionOptions
+
+	Context context.Context
+	Cancel  context.CancelFunc
+
+	// whisper
+	File string `json:"file" validate:"required"`
+	//whisper/image
+	ResponseFormat ChatCompletionResponseFormat `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
+
+	Tools       []grammar.Tool `json:"tools,omitempty" yaml:"tools"`
+	ToolsChoice interface{}    `json:"tool_choice,omitempty" yaml:"tool_choice"`
+
+	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"`
+
+	Backend string `json:"backend" yaml:"backend"`
+
+	// AutoGPTQ
+	ModelBaseName string `json:"model_base_name" yaml:"model_base_name"`
+}

core/schema/whisper.go

@@ -0,0 +1,16 @@
+package schema
+
+import "time"
+
+type Segment struct {
+	Id     int           `json:"id"`
+	Start  time.Duration `json:"start"`
+	End    time.Duration `json:"end"`
+	Text   string        `json:"text"`
+	Tokens []int         `json:"tokens"`
+}
+
+type Result struct {
+	Segments []Segment `json:"segments"`
+	Text     string    `json:"text"`
+}