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classifier_run_knn.go
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classifier_run_knn.go
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// _ _
// __ _____ __ ___ ___ __ _| |_ ___
// \ \ /\ / / _ \/ _` \ \ / / |/ _` | __/ _ \
// \ V V / __/ (_| |\ V /| | (_| | || __/
// \_/\_/ \___|\__,_| \_/ |_|\__,_|\__\___|
//
// Copyright © 2016 - 2024 Weaviate B.V. All rights reserved.
//
// CONTACT: hello@weaviate.io
//
package classification
import (
"fmt"
"time"
"github.com/weaviate/weaviate/entities/models"
"github.com/weaviate/weaviate/entities/search"
)
func (c *Classifier) classifyItemUsingKNN(item search.Result, itemIndex int,
params models.Classification, filters Filters, writer Writer,
) error {
ctx, cancel := contextWithTimeout(2 * time.Second)
defer cancel()
// this type assertion is safe to make, since we have passed the parsing stage
settings := params.Settings.(*ParamsKNN)
// K is guaranteed to be set by now, no danger in dereferencing the pointer
res, err := c.vectorRepo.AggregateNeighbors(ctx, item.Vector,
item.ClassName,
params.ClassifyProperties, int(*settings.K), filters.TrainingSet())
if err != nil {
return fmt.Errorf("classify %s/%s: %v", item.ClassName, item.ID, err)
}
var classified []string
for _, agg := range res {
meta := agg.Meta()
item.Schema.(map[string]interface{})[agg.Property] = models.MultipleRef{
&models.SingleRef{
Beacon: agg.Beacon,
Classification: meta,
},
}
// append list of actually classified (can differ from scope!) properties,
// so we can build the object meta information
classified = append(classified, agg.Property)
}
c.extendItemWithObjectMeta(&item, params, classified)
err = writer.Store(item)
if err != nil {
return fmt.Errorf("store %s/%s: %v", item.ClassName, item.ID, err)
}
return nil
}