manual merge, build testing starting from here

pkg/assets/extract.go

@@ -0,0 +1,51 @@
+package assets
+
+import (
+	"embed"
+	"fmt"
+	"io/fs"
+	"os"
+	"path/filepath"
+)
+
+func ExtractFiles(content embed.FS, extractDir string) error {
+	// Create the target directory if it doesn't exist
+	err := os.MkdirAll(extractDir, 0755)
+	if err != nil {
+		return fmt.Errorf("failed to create directory: %v", err)
+	}
+
+	// Walk through the embedded FS and extract files
+	err = fs.WalkDir(content, ".", func(path string, d fs.DirEntry, err error) error {
+		if err != nil {
+			return err
+		}
+
+		// Reconstruct the directory structure in the target directory
+		targetFile := filepath.Join(extractDir, path)
+		if d.IsDir() {
+			// Create the directory in the target directory
+			err := os.MkdirAll(targetFile, 0755)
+			if err != nil {
+				return fmt.Errorf("failed to create directory: %v", err)
+			}
+			return nil
+		}
+
+		// Read the file from the embedded FS
+		fileData, err := content.ReadFile(path)
+		if err != nil {
+			return fmt.Errorf("failed to read file: %v", err)
+		}
+
+		// Create the file in the target directory
+		err = os.WriteFile(targetFile, fileData, 0644)
+		if err != nil {
+			return fmt.Errorf("failed to write file: %v", err)
+		}
+
+		return nil
+	})
+
+	return err
+}

pkg/langchain/huggingface.go

@@ -0,0 +1,47 @@
+package langchain
+
+import (
+	"context"
+
+	"github.com/tmc/langchaingo/llms"
+	"github.com/tmc/langchaingo/llms/huggingface"
+)
+
+type HuggingFace struct {
+	modelPath string
+}
+
+func NewHuggingFace(repoId string) (*HuggingFace, error) {
+	return &HuggingFace{
+		modelPath: repoId,
+	}, nil
+}
+
+func (s *HuggingFace) PredictHuggingFace(text string, opts ...PredictOption) (*Predict, error) {
+	po := NewPredictOptions(opts...)
+
+	// Init client
+	llm, err := huggingface.New()
+	if err != nil {
+		return nil, err
+	}
+
+	// Convert from LocalAI to LangChainGo format of options
+	co := []llms.CallOption{
+		llms.WithModel(po.Model),
+		llms.WithMaxTokens(po.MaxTokens),
+		llms.WithTemperature(po.Temperature),
+		llms.WithStopWords(po.StopWords),
+	}
+
+	// Call Inference API
+	ctx := context.Background()
+	completion, err := llm.Call(ctx, text, co...)
+	if err != nil {
+		return nil, err
+	}
+
+	return &Predict{
+		Completion: completion,
+	}, nil
+}

pkg/langchain/langchain.go

@@ -0,0 +1,57 @@
+package langchain
+
+type PredictOptions struct {
+	Model string `json:"model"`
+	// MaxTokens is the maximum number of tokens to generate.
+	MaxTokens int `json:"max_tokens"`
+	// Temperature is the temperature for sampling, between 0 and 1.
+	Temperature float64 `json:"temperature"`
+	// StopWords is a list of words to stop on.
+	StopWords []string `json:"stop_words"`
+}
+
+type PredictOption func(p *PredictOptions)
+
+var DefaultOptions = PredictOptions{
+	Model:       "gpt2",
+	MaxTokens:   200,
+	Temperature: 0.96,
+	StopWords:   nil,
+}
+
+type Predict struct {
+	Completion string
+}
+
+func SetModel(model string) PredictOption {
+	return func(o *PredictOptions) {
+		o.Model = model
+	}
+}
+
+func SetTemperature(temperature float64) PredictOption {
+	return func(o *PredictOptions) {
+		o.Temperature = temperature
+	}
+}
+
+func SetMaxTokens(maxTokens int) PredictOption {
+	return func(o *PredictOptions) {
+		o.MaxTokens = maxTokens
+	}
+}
+
+func SetStopWords(stopWords []string) PredictOption {
+	return func(o *PredictOptions) {
+		o.StopWords = stopWords
+	}
+}
+
+// NewPredictOptions Create a new PredictOptions object with the given options.
+func NewPredictOptions(opts ...PredictOption) PredictOptions {
+	p := DefaultOptions
+	for _, opt := range opts {
+		opt(&p)
+	}
+	return p
+}

pkg/model/initializers.go

@@ -7,10 +7,11 @@ import (
 
 	rwkv "github.com/donomii/go-rwkv.cpp"
 	whisper "github.com/ggerganov/whisper.cpp/bindings/go/pkg/whisper"
+	"github.com/go-skynet/LocalAI/pkg/langchain"
 	"github.com/go-skynet/LocalAI/pkg/stablediffusion"
 	bloomz "github.com/go-skynet/bloomz.cpp"
 	bert "github.com/go-skynet/go-bert.cpp"
-	gpt2 "github.com/go-skynet/go-gpt2.cpp"
+	transformers "github.com/go-skynet/go-ggml-transformers.cpp"
 	llama "github.com/go-skynet/go-llama.cpp"
 	"github.com/hashicorp/go-multierror"
 	gpt4all "github.com/nomic-ai/gpt4all/gpt4all-bindings/golang"
@@ -23,61 +24,61 @@ const (
 	LlamaBackend           = "llama"
 	BloomzBackend          = "bloomz"
 	StarcoderBackend       = "starcoder"
-	StableLMBackend        = "stablelm"
+	GPTJBackend            = "gptj"
 	DollyBackend           = "dolly"
-	RedPajamaBackend       = "redpajama"
+	MPTBackend             = "mpt"
 	GPTNeoXBackend         = "gptneox"
 	ReplitBackend          = "replit"
 	Gpt2Backend            = "gpt2"
 	Gpt4AllLlamaBackend    = "gpt4all-llama"
 	Gpt4AllMptBackend      = "gpt4all-mpt"
 	Gpt4AllJBackend        = "gpt4all-j"
+	Gpt4All                = "gpt4all"
 	BertEmbeddingsBackend  = "bert-embeddings"
 	RwkvBackend            = "rwkv"
 	WhisperBackend         = "whisper"
 	StableDiffusionBackend = "stablediffusion"
+	LCHuggingFaceBackend   = "langchain-huggingface"
 )
 
 var backends []string = []string{
 	LlamaBackend,
-	Gpt4AllLlamaBackend,
-	Gpt4AllMptBackend,
-	Gpt4AllJBackend,
-	Gpt2Backend,
-	WhisperBackend,
+	Gpt4All,
 	RwkvBackend,
-	BloomzBackend,
-	StableLMBackend,
-	DollyBackend,
-	RedPajamaBackend,
-	ReplitBackend,
 	GPTNeoXBackend,
+	WhisperBackend,
 	BertEmbeddingsBackend,
+	GPTJBackend,
+	Gpt2Backend,
+	DollyBackend,
+	MPTBackend,
+	ReplitBackend,
 	StarcoderBackend,
+	BloomzBackend,
 }
 
 var starCoder = func(modelFile string) (interface{}, error) {
-	return gpt2.NewStarcoder(modelFile)
+	return transformers.NewStarcoder(modelFile)
 }
 
-var redPajama = func(modelFile string) (interface{}, error) {
-	return gpt2.NewRedPajama(modelFile)
+var mpt = func(modelFile string) (interface{}, error) {
+	return transformers.NewMPT(modelFile)
 }
 
 var dolly = func(modelFile string) (interface{}, error) {
-	return gpt2.NewDolly(modelFile)
+	return transformers.NewDolly(modelFile)
 }
 
 var gptNeoX = func(modelFile string) (interface{}, error) {
-	return gpt2.NewGPTNeoX(modelFile)
+	return transformers.NewGPTNeoX(modelFile)
 }
 
 var replit = func(modelFile string) (interface{}, error) {
-	return gpt2.NewReplit(modelFile)
+	return transformers.NewReplit(modelFile)
 }
 
-var stableLM = func(modelFile string) (interface{}, error) {
-	return gpt2.NewStableLM(modelFile)
+var gptJ = func(modelFile string) (interface{}, error) {
+	return transformers.NewGPTJ(modelFile)
 }
 
 var bertEmbeddings = func(modelFile string) (interface{}, error) {
@@ -87,8 +88,9 @@ var bertEmbeddings = func(modelFile string) (interface{}, error) {
 var bloomzLM = func(modelFile string) (interface{}, error) {
 	return bloomz.New(modelFile)
 }
-var gpt2LM = func(modelFile string) (interface{}, error) {
-	return gpt2.New(modelFile)
+
+var transformersLM = func(modelFile string) (interface{}, error) {
+	return transformers.New(modelFile)
 }
 
 var stableDiffusion = func(assetDir string) (interface{}, error) {
@@ -99,6 +101,10 @@ var whisperModel = func(modelFile string) (interface{}, error) {
 	return whisper.New(modelFile)
 }
 
+var lcHuggingFace = func(repoId string) (interface{}, error) {
+	return langchain.NewHuggingFace(repoId)
+}
+
 func llamaLM(opts ...llama.ModelOption) func(string) (interface{}, error) {
 	return func(s string) (interface{}, error) {
 		return llama.New(s, opts...)
@@ -130,14 +136,14 @@ func (ml *ModelLoader) BackendLoader(backendString string, modelFile string, lla
 		return ml.LoadModel(modelFile, llamaLM(llamaOpts...))
 	case BloomzBackend:
 		return ml.LoadModel(modelFile, bloomzLM)
-	case StableLMBackend:
-		return ml.LoadModel(modelFile, stableLM)
+	case GPTJBackend:
+		return ml.LoadModel(modelFile, gptJ)
 	case DollyBackend:
 		return ml.LoadModel(modelFile, dolly)
-	case RedPajamaBackend:
-		return ml.LoadModel(modelFile, redPajama)
+	case MPTBackend:
+		return ml.LoadModel(modelFile, mpt)
 	case Gpt2Backend:
-		return ml.LoadModel(modelFile, gpt2LM)
+		return ml.LoadModel(modelFile, transformersLM)
 	case GPTNeoXBackend:
 		return ml.LoadModel(modelFile, gptNeoX)
 	case ReplitBackend:
@@ -146,18 +152,16 @@ func (ml *ModelLoader) BackendLoader(backendString string, modelFile string, lla
 		return ml.LoadModel(modelFile, stableDiffusion)
 	case StarcoderBackend:
 		return ml.LoadModel(modelFile, starCoder)
-	case Gpt4AllLlamaBackend:
-		return ml.LoadModel(modelFile, gpt4allLM(gpt4all.SetThreads(int(threads)), gpt4all.SetModelType(gpt4all.LLaMAType)))
-	case Gpt4AllMptBackend:
-		return ml.LoadModel(modelFile, gpt4allLM(gpt4all.SetThreads(int(threads)), gpt4all.SetModelType(gpt4all.MPTType)))
-	case Gpt4AllJBackend:
-		return ml.LoadModel(modelFile, gpt4allLM(gpt4all.SetThreads(int(threads)), gpt4all.SetModelType(gpt4all.GPTJType)))
+	case Gpt4AllLlamaBackend, Gpt4AllMptBackend, Gpt4AllJBackend, Gpt4All:
+		return ml.LoadModel(modelFile, gpt4allLM(gpt4all.SetThreads(int(threads))))
 	case BertEmbeddingsBackend:
 		return ml.LoadModel(modelFile, bertEmbeddings)
 	case RwkvBackend:
 		return ml.LoadModel(modelFile, rwkvLM(filepath.Join(ml.ModelPath, modelFile+tokenizerSuffix), threads))
 	case WhisperBackend:
 		return ml.LoadModel(modelFile, whisperModel)
+	case LCHuggingFaceBackend:
+		return ml.LoadModel(modelFile, lcHuggingFace)
 	default:
 		return nil, fmt.Errorf("backend unsupported: %s", backendString)
 	}

pkg/stablediffusion/generate.go

@@ -8,6 +8,18 @@ import (
 )
 
 func GenerateImage(height, width, mode, step, seed int, positive_prompt, negative_prompt, dst, asset_dir string) error {
+	if height > 512 || width > 512 {
+		return stableDiffusion.GenerateImageUpscaled(
+			height,
+			width,
+			step,
+			seed,
+			positive_prompt,
+			negative_prompt,
+			dst,
+			asset_dir,
+		)
+	}
 	return stableDiffusion.GenerateImage(
 		height,
 		width,