[Refactor]: Core/API Split (#1506)

Refactors api folder to core, creates firm split between backend code and api frontend.

core/backend/embeddings.go

@@ -0,0 +1,144 @@
+package backend
+
+import (
+	"fmt"
+	"time"
+
+	"github.com/go-skynet/LocalAI/core/services"
+	"github.com/go-skynet/LocalAI/pkg/grpc"
+	"github.com/go-skynet/LocalAI/pkg/model"
+	"github.com/go-skynet/LocalAI/pkg/schema"
+	"github.com/google/uuid"
+	"github.com/rs/zerolog/log"
+)
+
+func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c schema.Config, o *schema.StartupOptions) (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),
+		model.WithExternalBackends(o.ExternalGRPCBackends, false),
+	})
+
+	if c.Backend == "" {
+		inferenceModel, err = loader.GreedyLoader(opts...)
+	} else {
+		opts = append(opts, model.WithBackendString(c.Backend))
+		inferenceModel, err = loader.BackendLoader(opts...)
+	}
+	if err != nil {
+		return nil, err
+	}
+
+	var fn func() ([]float32, error)
+	switch model := inferenceModel.(type) {
+	case *grpc.Client:
+		fn = func() ([]float32, error) {
+			predictOptions := gRPCPredictOpts(c, loader.ModelPath)
+			if len(tokens) > 0 {
+				embeds := []int32{}
+
+				for _, t := range tokens {
+					embeds = append(embeds, int32(t))
+				}
+				predictOptions.EmbeddingTokens = embeds
+
+				res, err := model.Embeddings(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
+}
+
+func EmbeddingOpenAIRequest(modelName string, input *schema.OpenAIRequest, cl *services.ConfigLoader, ml *model.ModelLoader, startupOptions *schema.StartupOptions) (*schema.OpenAIResponse, error) {
+	config, input, err := ReadConfigFromFileAndCombineWithOpenAIRequest(modelName, input, cl, startupOptions)
+	if err != nil {
+		return nil, fmt.Errorf("failed reading parameters from request:%w", err)
+	}
+
+	log.Debug().Msgf("Parameter Config: %+v", config)
+	items := []schema.Item{}
+
+	for i, s := range config.InputToken {
+		// get the model function to call for the result
+		embedFn, err := ModelEmbedding("", s, ml, *config, startupOptions)
+		if err != nil {
+			return nil, err
+		}
+
+		embeddings, err := embedFn()
+		if err != nil {
+			return nil, err
+		}
+		items = append(items, schema.Item{Embedding: embeddings, Index: i, Object: "embedding"})
+	}
+
+	for i, s := range config.InputStrings {
+		// get the model function to call for the result
+		embedFn, err := ModelEmbedding(s, []int{}, ml, *config, startupOptions)
+		if err != nil {
+			return nil, err
+		}
+
+		embeddings, err := embedFn()
+		if err != nil {
+			return nil, err
+		}
+		items = append(items, schema.Item{Embedding: embeddings, Index: i, Object: "embedding"})
+	}
+
+	id := uuid.New().String()
+	created := int(time.Now().Unix())
+	return &schema.OpenAIResponse{
+		ID:      id,
+		Created: created,
+		Model:   input.Model, // we have to return what the user sent here, due to OpenAI spec.
+		Data:    items,
+		Object:  "list",
+	}, nil
+}