LocalAI/core/backend/embeddings.go
Ettore Di Giacinto af9e5a2d05
Revert #1963 (#2056)
* Revert "fix(fncall): fix regression introduced in #1963 (#2048)"

This reverts commit 6b06d4e0af.

* Revert "fix: action-tmate back to upstream, dead code removal (#2038)"

This reverts commit fdec8a9d00.

* Revert "feat(grpc): return consumed token count and update response accordingly (#2035)"

This reverts commit e843d7df0e.

* Revert "refactor: backend/service split, channel-based llm flow (#1963)"

This reverts commit eed5706994.

* feat(grpc): return consumed token count and update response accordingly

Fixes: #1920

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2024-04-17 23:33:49 +02:00

89 lines
2.1 KiB
Go

package backend
import (
"fmt"
"github.com/go-skynet/LocalAI/core/config"
"github.com/go-skynet/LocalAI/pkg/grpc"
model "github.com/go-skynet/LocalAI/pkg/model"
)
func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, backendConfig config.BackendConfig, appConfig *config.ApplicationConfig) (func() ([]float32, error), error) {
modelFile := backendConfig.Model
grpcOpts := gRPCModelOpts(backendConfig)
var inferenceModel interface{}
var err error
opts := modelOpts(backendConfig, appConfig, []model.Option{
model.WithLoadGRPCLoadModelOpts(grpcOpts),
model.WithThreads(uint32(*backendConfig.Threads)),
model.WithAssetDir(appConfig.AssetsDestination),
model.WithModel(modelFile),
model.WithContext(appConfig.Context),
})
if backendConfig.Backend == "" {
inferenceModel, err = loader.GreedyLoader(opts...)
} else {
opts = append(opts, model.WithBackendString(backendConfig.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(backendConfig, loader.ModelPath)
if len(tokens) > 0 {
embeds := []int32{}
for _, t := range tokens {
embeds = append(embeds, int32(t))
}
predictOptions.EmbeddingTokens = embeds
res, err := model.Embeddings(appConfig.Context, predictOptions)
if err != nil {
return nil, err
}
return res.Embeddings, nil
}
predictOptions.Embeddings = s
res, err := model.Embeddings(appConfig.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
}