LocalAI/core/backend/embeddings.go

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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
}