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feat: add experimental support for embeddings as arrays (#207)
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parent
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commit
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2
Makefile
2
Makefile
@ -3,7 +3,7 @@ GOTEST=$(GOCMD) test
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GOVET=$(GOCMD) vet
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BINARY_NAME=local-ai
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GOLLAMA_VERSION?=cf9b522db63898dcc5eb86e37c979ab85cbd583e
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GOLLAMA_VERSION?=b4e97a42d0c10ada6b529b0ec17b05c72435aeab
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GOGPT4ALLJ_VERSION?=1f7bff57f66cb7062e40d0ac3abd2217815e5109
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GOGPT2_VERSION?=245a5bfe6708ab80dc5c733dcdbfbe3cfd2acdaa
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RWKV_REPO?=https://github.com/donomii/go-rwkv.cpp
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@ -33,6 +33,7 @@ type Config struct {
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Mirostat int `yaml:"mirostat"`
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PromptStrings, InputStrings []string
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InputToken [][]int
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}
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type TemplateConfig struct {
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@ -186,8 +187,15 @@ func updateConfig(config *Config, input *OpenAIRequest) {
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}
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case []interface{}:
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for _, pp := range inputs {
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if s, ok := pp.(string); ok {
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config.InputStrings = append(config.InputStrings, s)
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switch i := pp.(type) {
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case string:
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config.InputStrings = append(config.InputStrings, i)
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case []interface{}:
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tokens := []int{}
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for _, ii := range i {
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tokens = append(tokens, int(ii.(float64)))
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}
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config.InputToken = append(config.InputToken, tokens)
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}
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}
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}
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@ -177,10 +177,23 @@ func embeddingsEndpoint(cm ConfigMerger, debug bool, loader *model.ModelLoader,
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log.Debug().Msgf("Parameter Config: %+v", config)
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items := []Item{}
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for i, s := range config.InputStrings {
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for i, s := range config.InputToken {
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// get the model function to call for the result
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embedFn, err := ModelEmbedding(s, loader, *config)
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embedFn, err := ModelEmbedding("", s, loader, *config)
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if err != nil {
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return err
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}
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embeddings, err := embedFn()
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if err != nil {
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return err
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}
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items = append(items, Item{Embedding: embeddings, Index: i, Object: "embedding"})
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}
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for i, s := range config.InputStrings {
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// get the model function to call for the result
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embedFn, err := ModelEmbedding(s, []int{}, loader, *config)
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if err != nil {
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return err
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}
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@ -32,7 +32,7 @@ func defaultLLamaOpts(c Config) []llama.ModelOption {
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return llamaOpts
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}
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func ModelEmbedding(s string, loader *model.ModelLoader, c Config) (func() ([]float32, error), error) {
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func ModelEmbedding(s string, tokens []int, loader *model.ModelLoader, c Config) (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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@ -57,6 +57,9 @@ func ModelEmbedding(s string, loader *model.ModelLoader, c Config) (func() ([]fl
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case *llama.LLama:
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fn = func() ([]float32, error) {
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predictOptions := buildLLamaPredictOptions(c)
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if len(tokens) > 0 {
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return model.TokenEmbeddings(tokens, predictOptions...)
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}
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return model.Embeddings(s, predictOptions...)
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}
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default:
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