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Copy pathvector_search_result_field_masked.go
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vector_search_result_field_masked.go
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// Copyright 2024 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
package firestore
// [START firestore_vector_search_distance_result_field_masked]
import (
"context"
"fmt"
"io"
"cloud.google.com/go/firestore"
)
func vectorSearchDistanceResultFieldMasked(w io.Writer, projectID string) error {
ctx := context.Background()
client, err := firestore.NewClient(ctx, projectID)
if err != nil {
return fmt.Errorf("firestore.NewClient: %w", err)
}
defer client.Close()
collection := client.Collection("coffee-beans")
// Requires a vector index
// https://firebase.google.com/docs/firestore/vector-search#create_and_manage_vector_indexes
vectorQuery := collection.Select("color", "vector_distance").
FindNearest("embedding_field",
[]float32{3.0, 1.0, 2.0},
10,
firestore.DistanceMeasureEuclidean,
&firestore.FindNearestOptions{
DistanceResultField: "vector_distance",
})
docs, err := vectorQuery.Documents(ctx).GetAll()
if err != nil {
fmt.Fprintf(w, "failed to get vector query results: %v", err)
return err
}
for _, doc := range docs {
fmt.Fprintf(w, "%v, Distance: %v\n", doc.Data()["color"], doc.Data()["vector_distance"])
}
return nil
}
// [END firestore_vector_search_distance_result_field_masked]