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| 1 | +/* Copyright 2010-present MongoDB Inc. |
| 2 | + * |
| 3 | + * Licensed under the Apache License, Version 2.0 (the "License"); |
| 4 | + * you may not use this file except in compliance with the License. |
| 5 | + * You may obtain a copy of the License at |
| 6 | + * |
| 7 | + * http://www.apache.org/licenses/LICENSE-2.0 |
| 8 | + * |
| 9 | + * Unless required by applicable law or agreed to in writing, software |
| 10 | + * distributed under the License is distributed on an "AS IS" BASIS, |
| 11 | + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 12 | + * See the License for the specific language governing permissions and |
| 13 | + * limitations under the License. |
| 14 | + */ |
| 15 | + |
| 16 | +using System; |
| 17 | +using System.Collections.Generic; |
| 18 | +using System.Linq; |
| 19 | +using System.Linq.Expressions; |
| 20 | +using MongoDB.Bson; |
| 21 | + |
| 22 | +namespace MongoDB.Driver; |
| 23 | + |
| 24 | +/// <summary> |
| 25 | +/// Defines a vector index model using strongly-typed C# APIs. |
| 26 | +/// </summary> |
| 27 | +public sealed class CreateVectorIndexModel<TDocument> : CreateSearchIndexModelBase |
| 28 | +{ |
| 29 | + /// <summary> |
| 30 | + /// Initializes a new instance of the <see cref="CreateVectorIndexModel{TDocument}"/> class, passing the |
| 31 | + /// required options for <see cref="VectorSimilarity"/> and the number of vector dimensions to the constructor. |
| 32 | + /// </summary> |
| 33 | + /// <param name="name">The index name.</param> |
| 34 | + /// <param name="field">The field containing the vectors to index.</param> |
| 35 | + /// <param name="similarity">The <see cref="VectorSimilarity"/> to use to search for top K-nearest neighbors.</param> |
| 36 | + /// <param name="dimensions">Number of vector dimensions that vector search enforces at index-time and query-time.</param> |
| 37 | + /// <param name="filterFields">Fields that may be used as filters in the vector query.</param> |
| 38 | + public CreateVectorIndexModel( |
| 39 | + FieldDefinition<TDocument> field, |
| 40 | + string name, |
| 41 | + VectorSimilarity similarity, |
| 42 | + int dimensions, |
| 43 | + params FieldDefinition<TDocument>[] filterFields) |
| 44 | + : base(name) |
| 45 | + { |
| 46 | + Field = field; |
| 47 | + Similarity = similarity; |
| 48 | + Dimensions = dimensions; |
| 49 | + FilterFields = filterFields?.ToList() ?? []; |
| 50 | + } |
| 51 | + |
| 52 | + /// <summary> |
| 53 | + /// Initializes a new instance of the <see cref="CreateVectorIndexModel{TDocument}"/> class, passing the |
| 54 | + /// required options for <see cref="VectorSimilarity"/> and the number of vector dimensions to the constructor. |
| 55 | + /// </summary> |
| 56 | + /// <param name="name">The index name.</param> |
| 57 | + /// <param name="field">An expression pointing to the field containing the vectors to index.</param> |
| 58 | + /// <param name="similarity">The <see cref="VectorSimilarity"/> to use to search for top K-nearest neighbors.</param> |
| 59 | + /// <param name="dimensions">Number of vector dimensions that vector search enforces at index-time and query-time.</param> |
| 60 | + /// <param name="filterFields">Expressions pointing to fields that may be used as filters in the vector query.</param> |
| 61 | + public CreateVectorIndexModel( |
| 62 | + Expression<Func<TDocument, object>> field, |
| 63 | + string name, |
| 64 | + VectorSimilarity similarity, |
| 65 | + int dimensions, |
| 66 | + params Expression<Func<TDocument, object>>[] filterFields) |
| 67 | + : this( |
| 68 | + new ExpressionFieldDefinition<TDocument>(field), |
| 69 | + name, |
| 70 | + similarity, |
| 71 | + dimensions, |
| 72 | + filterFields? |
| 73 | + .Select(f => (FieldDefinition<TDocument>)new ExpressionFieldDefinition<TDocument>(f)) |
| 74 | + .ToArray()) |
| 75 | + { |
| 76 | + } |
| 77 | + |
| 78 | + /// <summary> |
| 79 | + /// The field containing the vectors to index. |
| 80 | + /// </summary> |
| 81 | + public FieldDefinition<TDocument> Field { get; } |
| 82 | + |
| 83 | + /// <summary> |
| 84 | + /// The <see cref="VectorSimilarity"/> to use to search for top K-nearest neighbors. |
| 85 | + /// </summary> |
| 86 | + public VectorSimilarity Similarity { get; } |
| 87 | + |
| 88 | + /// <summary> |
| 89 | + /// Number of vector dimensions that vector search enforces at index-time and query-time. |
| 90 | + /// </summary> |
| 91 | + public int Dimensions { get; } |
| 92 | + |
| 93 | + /// <summary> |
| 94 | + /// Fields that may be used as filters in the vector query. |
| 95 | + /// </summary> |
| 96 | + public IReadOnlyList<FieldDefinition<TDocument>> FilterFields { get; } |
| 97 | + |
| 98 | + /// <summary> |
| 99 | + /// Type of automatic vector quantization for your vectors. |
| 100 | + /// </summary> |
| 101 | + public VectorQuantization? Quantization { get; init; } |
| 102 | + |
| 103 | + /// <summary> |
| 104 | + /// Maximum number of edges (or connections) that a node can have in the Hierarchical Navigable Small Worlds graph. |
| 105 | + /// </summary> |
| 106 | + public int? HnswMaxEdges { get; init; } |
| 107 | + |
| 108 | + /// <summary> |
| 109 | + /// Analogous to numCandidates at query-time, this parameter controls the maximum number of nodes to evaluate to find the closest neighbors to connect to a new node. |
| 110 | + /// </summary> |
| 111 | + public int? HnswNumEdgeCandidates { get; init; } |
| 112 | + |
| 113 | + /// <inheritdoc/> |
| 114 | + public override SearchIndexType? Type => SearchIndexType.VectorSearch; |
| 115 | + |
| 116 | + /// <summary> |
| 117 | + /// Renders the index model to a <see cref="BsonDocument"/>. |
| 118 | + /// </summary> |
| 119 | + /// <param name="renderArgs">The render arguments.</param> |
| 120 | + /// <returns>A <see cref="BsonDocument" />.</returns> |
| 121 | + public BsonDocument Render(RenderArgs<TDocument> renderArgs) |
| 122 | + { |
| 123 | + var similarityValue = Similarity == VectorSimilarity.DotProduct |
| 124 | + ? "dotProduct" // Because neither "DotProduct" or "dotproduct" are allowed. |
| 125 | + : Similarity.ToString().ToLowerInvariant(); |
| 126 | + |
| 127 | + var vectorField = new BsonDocument |
| 128 | + { |
| 129 | + { "type", BsonString.Create("vector") }, |
| 130 | + { "path", Field.Render(renderArgs).FieldName }, |
| 131 | + { "numDimensions", BsonInt32.Create(Dimensions) }, |
| 132 | + { "similarity", BsonString.Create(similarityValue) }, |
| 133 | + }; |
| 134 | + |
| 135 | + if (Quantization.HasValue) |
| 136 | + { |
| 137 | + vectorField.Add("quantization", BsonString.Create(Quantization.ToString()?.ToLower())); |
| 138 | + } |
| 139 | + |
| 140 | + if (HnswMaxEdges != null || HnswNumEdgeCandidates != null) |
| 141 | + { |
| 142 | + var hnswDocument = new BsonDocument |
| 143 | + { |
| 144 | + { "maxEdges", BsonInt32.Create(HnswMaxEdges ?? 16) }, |
| 145 | + { "numEdgeCandidates", BsonInt32.Create(HnswNumEdgeCandidates ?? 100) } |
| 146 | + }; |
| 147 | + vectorField.Add("hnswOptions", hnswDocument); |
| 148 | + } |
| 149 | + |
| 150 | + var fieldDocuments = new List<BsonDocument> { vectorField }; |
| 151 | + |
| 152 | + if (FilterFields != null) |
| 153 | + { |
| 154 | + foreach (var filterPath in FilterFields) |
| 155 | + { |
| 156 | + var fieldDocument = new BsonDocument |
| 157 | + { |
| 158 | + { "type", BsonString.Create("filter") }, |
| 159 | + { "path", BsonString.Create(filterPath.Render(renderArgs).FieldName) } |
| 160 | + }; |
| 161 | + |
| 162 | + fieldDocuments.Add(fieldDocument); |
| 163 | + } |
| 164 | + } |
| 165 | + |
| 166 | + return new BsonDocument { { "fields", BsonArray.Create(fieldDocuments) } }; |
| 167 | + } |
| 168 | +} |
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