ADAPT-Chase's picture
Add files using upload-large-folder tool
59bb539 verified
// _ _
// __ _____ __ ___ ___ __ _| |_ ___
// \ \ /\ / / _ \/ _` \ \ / / |/ _` | __/ _ \
// \ V V / __/ (_| |\ V /| | (_| | || __/
// \_/\_/ \___|\__,_| \_/ |_|\__,_|\__\___|
//
// Copyright © 2016 - 2025 Weaviate B.V. All rights reserved.
//
// CONTACT: hello@weaviate.io
//
package clients
import (
"context"
"fmt"
"strings"
"time"
"github.com/weaviate/weaviate/entities/moduletools"
"github.com/weaviate/weaviate/usecases/modulecomponents"
"github.com/weaviate/weaviate/usecases/modulecomponents/clients/nvidia"
"github.com/sirupsen/logrus"
"github.com/weaviate/weaviate/modules/multi2vec-nvidia/ent"
)
type vectorizer struct {
client *nvidia.Client
logger logrus.FieldLogger
}
func New(apiKey string, timeout time.Duration, logger logrus.FieldLogger) *vectorizer {
return &vectorizer{
client: nvidia.New(apiKey, timeout, logger),
logger: logger,
}
}
func (v *vectorizer) Vectorize(ctx context.Context,
texts, images []string, cfg moduletools.ClassConfig,
) (*modulecomponents.VectorizationCLIPResult[[]float32], error) {
return v.vectorize(ctx, texts, images, cfg)
}
func (v *vectorizer) VectorizeQuery(ctx context.Context,
input []string, cfg moduletools.ClassConfig,
) (*modulecomponents.VectorizationCLIPResult[[]float32], error) {
return v.vectorize(ctx, input, nil, cfg)
}
func (v *vectorizer) vectorize(ctx context.Context,
texts, images []string, cfg moduletools.ClassConfig,
) (*modulecomponents.VectorizationCLIPResult[[]float32], error) {
var textVectors [][]float32
var imageVectors [][]float32
settings := ent.NewClassSettings(cfg)
if len(texts) > 0 {
textEmbeddings, err := v.client.Vectorize(ctx, texts, nvidia.Settings{
BaseURL: settings.BaseURL(),
Model: settings.Model(),
})
if err != nil {
return nil, err
}
textVectors = textEmbeddings.Vector
}
if len(images) > 0 {
inputs := make([]string, len(images))
for i := range images {
if !strings.HasPrefix(images[i], "data:") {
inputs[i] = fmt.Sprintf("data:image/png;base64,%s", images[i])
} else {
inputs[i] = images[i]
}
}
imageEmbeddings, err := v.client.Vectorize(ctx, inputs, nvidia.Settings{
Model: settings.Model(),
BaseURL: settings.BaseURL(),
})
if err != nil {
return nil, err
}
imageVectors = imageEmbeddings.Vector
}
return &modulecomponents.VectorizationCLIPResult[[]float32]{
TextVectors: textVectors,
ImageVectors: imageVectors,
}, nil
}