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// _ _
// __ _____ __ ___ ___ __ _| |_ ___
// \ \ /\ / / _ \/ _` \ \ / / |/ _` | __/ _ \
// \ V V / __/ (_| |\ V /| | (_| | || __/
// \_/\_/ \___|\__,_| \_/ |_|\__,_|\__\___|
//
// Copyright © 2016 - 2024 Weaviate B.V. All rights reserved.
//
// CONTACT: [email protected]
//
package modtransformers
import (
"context"
"fmt"
"github.com/pkg/errors"
"github.com/sirupsen/logrus"
"github.com/weaviate/weaviate/entities/models"
"github.com/weaviate/weaviate/entities/modulecapabilities"
"github.com/weaviate/weaviate/entities/moduletools"
"github.com/weaviate/weaviate/entities/schema"
"github.com/weaviate/weaviate/modules/text2vec-transformers/vectorizer"
)
func (m *TransformersModule) ClassConfigDefaults() map[string]interface{} {
return map[string]interface{}{
"vectorizeClassName": vectorizer.DefaultVectorizeClassName,
"poolingStrategy": vectorizer.DefaultPoolingStrategy,
}
}
func (m *TransformersModule) PropertyConfigDefaults(
dt *schema.DataType,
) map[string]interface{} {
return map[string]interface{}{
"skip": !vectorizer.DefaultPropertyIndexed,
"vectorizePropertyName": vectorizer.DefaultVectorizePropertyName,
}
}
func (m *TransformersModule) ValidateClass(ctx context.Context,
class *models.Class, cfg moduletools.ClassConfig,
) error {
settings := vectorizer.NewClassSettings(cfg)
return NewConfigValidator(m.logger).Do(ctx, class, cfg, settings)
}
var _ = modulecapabilities.ClassConfigurator(New())
type ConfigValidator struct {
logger logrus.FieldLogger
}
type ClassSettings interface {
VectorizeClassName() bool
VectorizePropertyName(propName string) bool
PropertyIndexed(propName string) bool
}
func NewConfigValidator(logger logrus.FieldLogger) *ConfigValidator {
return &ConfigValidator{logger: logger}
}
func (cv *ConfigValidator) Do(ctx context.Context, class *models.Class,
cfg moduletools.ClassConfig, settings ClassSettings,
) error {
// In text2vec-transformers (as opposed to e.g. text2vec-contextionary) the
// assumption is that the models will be able to deal with any words, even
// previously unseen ones. Therefore we do not need to validate individual
// properties, but only the overall "index state"
if err := cv.validateIndexState(ctx, class, settings); err != nil {
return errors.Errorf("invalid combination of properties")
}
cv.checkForPossibilityOfDuplicateVectors(ctx, class, settings)
return nil
}
func (cv *ConfigValidator) validateIndexState(ctx context.Context,
class *models.Class, settings ClassSettings,
) error {
if settings.VectorizeClassName() {
// if the user chooses to vectorize the classname, vector-building will
// always be possible, no need to investigate further
return nil
}
// search if there is at least one indexed, string/text prop. If found pass
// validation
for _, prop := range class.Properties {
if len(prop.DataType) < 1 {
return errors.Errorf("property %s must have at least one datatype: "+
"got %v", prop.Name, prop.DataType)
}
if prop.DataType[0] != string(schema.DataTypeText) {
// we can only vectorize text-like props
continue
}
if settings.PropertyIndexed(prop.Name) {
// found at least one, this is a valid schema
return nil
}
}
return fmt.Errorf("invalid properties: didn't find a single property which is " +
"of type string or text and is not excluded from indexing. In addition the " +
"class name is excluded from vectorization as well, meaning that it cannot be " +
"used to determine the vector position. To fix this, set 'vectorizeClassName' " +
"to true if the class name is contextionary-valid. Alternatively add at least " +
"contextionary-valid text/string property which is not excluded from " +
"indexing.")
}
func (cv *ConfigValidator) checkForPossibilityOfDuplicateVectors(
ctx context.Context, class *models.Class, settings ClassSettings,
) {
if !settings.VectorizeClassName() {
// if the user choses not to vectorize the class name, this means they must
// have chosen something else to vectorize, otherwise the validation would
// have error'd before we ever got here. We can skip further checking.
return
}
// search if there is at least one indexed, string/text prop. If found exit
for _, prop := range class.Properties {
// length check skipped, because validation has already passed
if prop.DataType[0] != string(schema.DataTypeText) {
// we can only vectorize text-like props
continue
}
if settings.PropertyIndexed(prop.Name) {
// found at least one
return
}
}
cv.logger.WithField("module", "text2vec-transformers").
WithField("class", class.Class).
Warnf("text2vec-contextionary: Class %q does not have any properties "+
"indexed (or only non text-properties indexed) and the vector position is "+
"only determined by the class name. Each object will end up with the same "+
"vector which leads to a severe performance penalty on imports. Consider "+
"setting vectorIndexConfig.skip=true for this property", class.Class)
}
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