9bdcbe0447
Major integrations and fixes: - Added BACKBEAT SDK integration for P2P operation timing - Implemented beat-aware status tracking for distributed operations - Added Docker secrets support for secure license management - Resolved KACHING license validation via HTTPS/TLS - Updated docker-compose configuration for clean stack deployment - Disabled rollback policies to prevent deployment failures - Added license credential storage (CHORUS-DEV-MULTI-001) Technical improvements: - BACKBEAT P2P operation tracking with phase management - Enhanced configuration system with file-based secrets - Improved error handling for license validation - Clean separation of KACHING and CHORUS deployment stacks 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
96 lines
2.6 KiB
Go
96 lines
2.6 KiB
Go
// Copyright (c) 2023 Couchbase, Inc.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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//go:build vectors
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// +build vectors
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package query
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import (
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"context"
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"encoding/json"
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"fmt"
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"github.com/blevesearch/bleve/v2/mapping"
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"github.com/blevesearch/bleve/v2/search"
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"github.com/blevesearch/bleve/v2/search/searcher"
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index "github.com/blevesearch/bleve_index_api"
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)
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type KNNQuery struct {
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VectorField string `json:"field"`
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Vector []float32 `json:"vector"`
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K int64 `json:"k"`
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BoostVal *Boost `json:"boost,omitempty"`
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// see KNNRequest.Params for description
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Params json.RawMessage `json:"params"`
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// elegibleSelector is used to filter out documents that are
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// eligible for the KNN search from a pre-filter query.
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elegibleSelector index.EligibleDocumentSelector
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}
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func NewKNNQuery(vector []float32) *KNNQuery {
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return &KNNQuery{Vector: vector}
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}
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func (q *KNNQuery) Field() string {
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return q.VectorField
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}
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func (q *KNNQuery) SetK(k int64) {
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q.K = k
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}
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func (q *KNNQuery) SetFieldVal(field string) {
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q.VectorField = field
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}
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func (q *KNNQuery) SetBoost(b float64) {
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boost := Boost(b)
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q.BoostVal = &boost
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}
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func (q *KNNQuery) Boost() float64 {
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return q.BoostVal.Value()
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}
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func (q *KNNQuery) SetParams(params json.RawMessage) {
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q.Params = params
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}
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func (q *KNNQuery) SetEligibleSelector(eligibleSelector index.EligibleDocumentSelector) {
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q.elegibleSelector = eligibleSelector
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}
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func (q *KNNQuery) Searcher(ctx context.Context, i index.IndexReader,
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m mapping.IndexMapping, options search.SearcherOptions) (search.Searcher, error) {
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fieldMapping := m.FieldMappingForPath(q.VectorField)
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similarityMetric := fieldMapping.Similarity
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if similarityMetric == "" {
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similarityMetric = index.DefaultVectorSimilarityMetric
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}
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if q.K <= 0 || len(q.Vector) == 0 {
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return nil, fmt.Errorf("k must be greater than 0 and vector must be non-empty")
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}
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if similarityMetric == index.CosineSimilarity {
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// normalize the vector
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q.Vector = mapping.NormalizeVector(q.Vector)
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}
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return searcher.NewKNNSearcher(ctx, i, m, options, q.VectorField,
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q.Vector, q.K, q.BoostVal.Value(), similarityMetric, q.Params,
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q.elegibleSelector)
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}
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