mirror of
https://github.com/mudler/LocalAI.git
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af9e5a2d05
* Revert "fix(fncall): fix regression introduced in #1963 (#2048)" This reverts commit6b06d4e0af
. * Revert "fix: action-tmate back to upstream, dead code removal (#2038)" This reverts commitfdec8a9d00
. * Revert "feat(grpc): return consumed token count and update response accordingly (#2035)" This reverts commite843d7df0e
. * Revert "refactor: backend/service split, channel-based llm flow (#1963)" This reverts commiteed5706994
. * 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>
89 lines
2.1 KiB
Go
89 lines
2.1 KiB
Go
package backend
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import (
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"fmt"
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"github.com/go-skynet/LocalAI/core/config"
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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, backendConfig config.BackendConfig, appConfig *config.ApplicationConfig) (func() ([]float32, error), error) {
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modelFile := backendConfig.Model
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grpcOpts := gRPCModelOpts(backendConfig)
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var inferenceModel interface{}
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var err error
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opts := modelOpts(backendConfig, appConfig, []model.Option{
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model.WithLoadGRPCLoadModelOpts(grpcOpts),
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model.WithThreads(uint32(*backendConfig.Threads)),
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model.WithAssetDir(appConfig.AssetsDestination),
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model.WithModel(modelFile),
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model.WithContext(appConfig.Context),
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})
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if backendConfig.Backend == "" {
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inferenceModel, err = loader.GreedyLoader(opts...)
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} else {
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opts = append(opts, model.WithBackendString(backendConfig.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(backendConfig, 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(appConfig.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(appConfig.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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