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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!
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38 changed files with 93 additions and 90 deletions
92
core/backend/embeddings.go
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92
core/backend/embeddings.go
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package backend
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import (
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"fmt"
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config "github.com/go-skynet/LocalAI/core/config"
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"github.com/go-skynet/LocalAI/core/options"
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"github.com/go-skynet/LocalAI/pkg/grpc"
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model "github.com/go-skynet/LocalAI/pkg/model"
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)
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func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c config.Config, o *options.Option) (func() ([]float32, error), error) {
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if !c.Embeddings {
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return nil, fmt.Errorf("endpoint disabled for this model by API configuration")
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}
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modelFile := c.Model
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grpcOpts := gRPCModelOpts(c)
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var inferenceModel interface{}
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var err error
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opts := modelOpts(c, o, []model.Option{
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model.WithLoadGRPCLoadModelOpts(grpcOpts),
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model.WithThreads(uint32(c.Threads)),
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model.WithAssetDir(o.AssetsDestination),
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model.WithModel(modelFile),
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model.WithContext(o.Context),
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})
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if c.Backend == "" {
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inferenceModel, err = loader.GreedyLoader(opts...)
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} else {
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opts = append(opts, model.WithBackendString(c.Backend))
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inferenceModel, err = loader.BackendLoader(opts...)
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}
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if err != nil {
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return nil, err
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}
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var fn func() ([]float32, error)
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switch model := inferenceModel.(type) {
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case grpc.Backend:
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fn = func() ([]float32, error) {
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predictOptions := gRPCPredictOpts(c, loader.ModelPath)
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if len(tokens) > 0 {
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embeds := []int32{}
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for _, t := range tokens {
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embeds = append(embeds, int32(t))
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}
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predictOptions.EmbeddingTokens = embeds
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res, err := model.Embeddings(o.Context, predictOptions)
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if err != nil {
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return nil, err
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}
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return res.Embeddings, nil
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}
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predictOptions.Embeddings = s
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res, err := model.Embeddings(o.Context, predictOptions)
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if err != nil {
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return nil, err
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}
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return res.Embeddings, nil
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}
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default:
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fn = func() ([]float32, error) {
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return nil, fmt.Errorf("embeddings not supported by the backend")
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}
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}
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return func() ([]float32, error) {
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embeds, err := fn()
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if err != nil {
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return embeds, err
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}
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// Remove trailing 0s
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for i := len(embeds) - 1; i >= 0; i-- {
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if embeds[i] == 0.0 {
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embeds = embeds[:i]
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} else {
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break
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}
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}
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return embeds, nil
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}, nil
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}
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