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>
71 lines
2.0 KiB
Go
71 lines
2.0 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 index
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type VectorField interface {
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Vector() []float32
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// Dimensionality of the vector
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Dims() int
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// Similarity metric to be used for scoring the vectors
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Similarity() string
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// nlist/nprobe config (recall/latency) the index is optimized for
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IndexOptimizedFor() string
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}
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// -----------------------------------------------------------------------------
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const (
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EuclideanDistance = "l2_norm"
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InnerProduct = "dot_product"
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CosineSimilarity = "cosine"
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)
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const DefaultVectorSimilarityMetric = EuclideanDistance
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// Supported similarity metrics for vector fields
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var SupportedVectorSimilarityMetrics = map[string]struct{}{
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EuclideanDistance: {},
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InnerProduct: {},
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CosineSimilarity: {},
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}
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// -----------------------------------------------------------------------------
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const (
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IndexOptimizedForRecall = "recall"
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IndexOptimizedForLatency = "latency"
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IndexOptimizedForMemoryEfficient = "memory-efficient"
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)
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const DefaultIndexOptimization = IndexOptimizedForRecall
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var SupportedVectorIndexOptimizations = map[string]int{
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IndexOptimizedForRecall: 0,
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IndexOptimizedForLatency: 1,
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IndexOptimizedForMemoryEfficient: 2,
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}
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// Reverse maps vector index optimizations': int -> string
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var VectorIndexOptimizationsReverseLookup = map[int]string{
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0: IndexOptimizedForRecall,
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1: IndexOptimizedForLatency,
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2: IndexOptimizedForMemoryEfficient,
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}
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