このチュートリアルでは、クラスター上の sample_mflix.embedded_movies
コレクション内の plot_embedding_voyage_3_large
フィールド内のベクトルに対して ANN 検索を実行する方法について説明します。これを示すには、次の手順に従います。
sample_mflix.embedded_movies
コレクション内のplot_embedding_voyage_3_large
という名前の数値フィールドにMongoDB ベクトル検索インデックスを作成します。sample_mflix.embedded_movies
コレクションのplot_embedding_voyage_3_large
フィールドに対してMongoDB ベクトル検索クエリを実行します。
➤ [ 言語を選択 ] ドロップダウン メニューを使用して、 MongoDB ベクトル検索インデックスを作成し、クエリを実行するために使用するクライアントを選択します。
前提条件
始める前に、共通の前提条件を履行してください。このチュートリアルには、以下のクライアントの例が含まれています。
MongoDB ベクトル検索インデックスの作成
このセクションでは、フィールドに対してベクトルクエリを実行中ために、sample_mflix.embedded_movies
コレクションの plot_embedding_voyage_3_large
フィールドにMongoDB ベクトル検索インデックスを作成する方法を説明します。
必要なアクセス権
MongoDB ベクトル検索インデックスを作成するには、プロジェクトに対する Project Data Access Admin
以上のアクセス権が必要です。
手順
Atlas で、クラスターのSearch & Vector Search ページに移動します。
MongoDB Search ページには、Search & Vector Search オプションまたは Data Explorer から移動できます。
まだ表示されていない場合は、プロジェクトを含む組織をナビゲーション バーの Organizations メニューで選択します。
まだ表示されていない場合は、ナビゲーション バーの Projects メニューからプロジェクトを選択します。
サイドバーで、 Database見出しの下のSearch & Vector Searchをクリックします。
クラスターがない場合は、Create clusterをクリックしてクラスターを作成してください。詳細については、「 クラスターの作成 」を参照してください。
プロジェクトに複数のクラスターがある場合は、Select cluster ドロップダウンから使用するクラスターを選択し、[Go to Atlas Search] をクリックします。
[ 検索とベクトル検索 ]ページが表示されます。
まだ表示されていない場合は、プロジェクトを含む組織をナビゲーション バーの Organizations メニューで選択します。
まだ表示されていない場合は、ナビゲーション バーの Projects メニューからプロジェクトを選択します。
サイドバーで、 Database見出しの下のData Explorerをクリックします。
データベースを展開し、コレクションを選択します。
コレクションのIndexesタブをクリックします。
Atlas Searchページが表示されます。
インデックスの設定を開始します。
ページで次の選択を行い、Next をクリックしてください。
Search Type | Vector Search のインデックスタイプを選択します。 |
Index Name and Data Source | 以下の情報を指定してください。
|
Configuration Method | For a guided experience, select Visual Editor. To edit the raw index definition, select JSON Editor. |
重要:
MongoDB Searchインデックスの名前はデフォルトで default
です。この名前を維持する場合、インデックスは、演算子に別の index
オプションを指定していないMongoDB Search クエリのデフォルトの検索インデックスになります。複数のインデックスを作成する場合は、インデックス間で一貫した記述的な命名規則を維持することをお勧めします。
MongoDB ベクトル検索インデックスを定義します。
このステップでは、次のフィールドに対して vectorSearch タイプのインデックスを定義します。
plot_embedding_voyage_3_large
ベクトル タイプとしてのフィールド。plot_embedding_voyage_3_large
フィールドには、Voyage AI のvoyage-3-large
埋め込みモデルを使用して作成された埋め込みが含まれます。インデックス定義では、2048
ベクトル次元を指定し、dotProduct
を使用して類似性を測定します。genres
フィールドの string 値でデータを事前にフィルタリングするフィルタータイプとして、 フィールドを使用します。year
フィールド には、フィールド内の数値でデータを事前にフィルタリングするためのフィルタータイプが含まれています。
Atlas は、ベクトル埋め込みを含むフィールドとその対応する次元を自動的に検出します。sample_mflix.embedded_movies
コレクションでは、plot_embedding
フィールドと plot_embedding_voyage_3_large
フィールドが表示されます。このチュートリアルでは、plot_embedding_voyage_3_large
フィールドのみのインデックスを作成する必要があります。
インデックスを設定するには、次の操作を行う必要があります。
Similarity MethodドロップダウンからDot Productを選択します。
[Advanced] をクリックして、ドロップダウンメニューから Scalar 量子化を選択します。
Filter Field セクションで、
genres
フィールドとyear
フィールドを指定してデータをフィルタリングします。
デフォルトの定義を、以下のインデックス定義で置き換えます。
1 { 2 "fields": [ 3 { 4 "type": "vector", 5 "path": "plot_embedding_voyage_3_large", 6 "numDimensions": 2048, 7 "similarity": "dotProduct", 8 "quantization": "scalar" 9 }, 10 { 11 "type": "filter", 12 "path": "genres" 13 }, 14 { 15 "type": "filter", 16 "path": "year" 17 } 18 ] 19 }
mongosh
内のクラスターに接続します。
ターミナル ウィンドウでmongosh
を開き、クラスターに接続します。 接続の詳細な手順については、「 mongosh 経由での接続 」を参照してください。
db.collection.createSearchIndex()
メソッドを実行します。
次のインデックス定義を使用すると、plot_embedding_voyage_3_large
フィールドが vector
タイプとして、genres
と year
フィールドが filter
タイプとしてインデックス化されます。
plot_embedding_voyage_3_large
フィールドには、Voyage AI の voyage-3-large
埋め込みモデルを使用して作成された 2048
次元のベクトル埋め込みが含まれています。インデックスは dotProduct
関数を使用して類似性を測定します。
1 db.embedded_movies.createSearchIndex( 2 "vector_index", 3 "vectorSearch", 4 { 5 "fields": [ 6 { 7 "type": "vector", 8 "path": "plot_embedding_voyage_3_large", 9 "numDimensions": 2048, 10 "similarity": "dotProduct" 11 }, 12 { 13 "type": "filter", 14 "path": "genres" 15 }, 16 { 17 "type": "filter", 18 "path": "year" 19 } 20 ] 21 } 22 );
インデックスを定義します。
IndexService.cs
という名前のファイルを作成し、次のコードをコピーしてファイルに貼り付けます。
このインデックス定義は、 MongoDB ベクトル検索インデックスの で、plot_embedding_voyage_3_large
フィールドをvector
タイプとしてインデックス化し、genres
フィールドと year
フィールドを filter
タイプとしてインデックス化します。plot_embedding_voyage_3_large
フィールドには、Voyage AI の voyage-3-large
埋め込みモデルを使用して作成された埋め込みが含まれます。インデックス定義では、2048
ベクトル次元を指定し、dotProduct
関数を使用して類似性を測定します。
1 namespace query_quick_start; 2 3 using MongoDB.Bson; 4 using MongoDB.Driver; 5 using System; 6 using System.Threading; 7 8 public class IndexService 9 { 10 // Replace the placeholder with your Atlas connection string 11 private const string MongoConnectionString = "<connection-string>"; 12 public void CreateVectorIndex() 13 { 14 try 15 { 16 // Connect to your Atlas cluster 17 var client = new MongoClient(MongoConnectionString); 18 var database = client.GetDatabase("sample_mflix"); 19 var collection = database.GetCollection<BsonDocument>("embedded_movies"); 20 21 var searchIndexView = collection.SearchIndexes; 22 var name = "vector_index"; 23 var type = SearchIndexType.VectorSearch; 24 25 var definition = new BsonDocument 26 { 27 { "fields", new BsonArray 28 { 29 new BsonDocument 30 { 31 { "type", "vector" }, 32 { "path", "plot_embedding_voyage_3_large" }, 33 { "numDimensions", 2048 }, 34 { "similarity", "dotProduct" }, 35 { "quantization", "scalar"} 36 }, 37 new BsonDocument 38 { 39 {"type", "filter"}, 40 {"path", "genres"} 41 }, 42 new BsonDocument 43 { 44 {"type", "filter"}, 45 {"path", "year"} 46 } 47 } 48 } 49 }; 50 51 var model = new CreateSearchIndexModel(name, type, definition); 52 53 searchIndexView.CreateOne(model); 54 Console.WriteLine($"New search index named {name} is building."); 55 56 // Polling for index status 57 Console.WriteLine("Polling to check if the index is ready. This may take up to a minute."); 58 bool queryable = false; 59 while (!queryable) 60 { 61 var indexes = searchIndexView.List(); 62 foreach (var index in indexes.ToEnumerable()) 63 { 64 if (index["name"] == name) 65 { 66 queryable = index["queryable"].AsBoolean; 67 } 68 } 69 if (!queryable) 70 { 71 Thread.Sleep(5000); 72 } 73 } 74 Console.WriteLine($"{name} is ready for querying."); 75 } 76 catch (Exception e) 77 { 78 Console.WriteLine($"Exception: {e.Message}"); 79 } 80 } 81 }
コード内の <connection-string>
を置き換え、ファイルを保存します。
<connection-string>
を Atlas クラスターまたはローカル Atlas 配置の接続文字列に置き換えます。
接続stringには、次の形式を使用する必要があります。
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
詳しくは、ドライバーを使用してクラスターに接続する を参照してください。
接続stringには、次の形式を使用する必要があります。
mongodb://localhost:<port-number>/?directConnection=true
詳細については、「接続文字列 」を参照してください。
インデックスを定義します。
vector-index.go
という名前のファイルを作成し、次のコードをコピーしてファイルに貼り付けます。
このインデックス定義は、 MongoDB ベクトル検索インデックスの で、plot_embedding_voyage_3_large
フィールドをvector
タイプとしてインデックス化し、genres
フィールドと year
フィールドを filter
タイプとしてインデックス化します。plot_embedding_voyage_3_large
フィールドには、Voyage AI の voyage-3-large
埋め込みモデルを使用して作成された埋め込みが含まれます。インデックス定義では、2048
ベクトル次元を指定し、dotProduct
関数を使用して類似性を測定します。
1 package main 2 3 import ( 4 "context" 5 "fmt" 6 "log" 7 "time" 8 9 "go.mongodb.org/mongo-driver/v2/bson" 10 "go.mongodb.org/mongo-driver/v2/mongo" 11 "go.mongodb.org/mongo-driver/v2/mongo/options" 12 ) 13 14 func main() { 15 ctx := context.Background() 16 17 // Replace the placeholder with your Atlas connection string 18 const uri = "<connectionString>" 19 20 // Connect to your Atlas cluster 21 clientOptions := options.Client().ApplyURI(uri) 22 client, err := mongo.Connect(clientOptions) 23 if err != nil { 24 log.Fatalf("failed to connect to the server: %v", err) 25 } 26 defer func() { _ = client.Disconnect(ctx) }() 27 28 // Set the namespace 29 coll := client.Database("sample_mflix").Collection("embedded_movies") 30 indexName := "vector_index" 31 opts := options.SearchIndexes().SetName(indexName).SetType("vectorSearch") 32 33 type vectorDefinitionField struct { 34 Type string `bson:"type"` 35 Path string `bson:"path"` 36 NumDimensions int `bson:"numDimensions"` 37 Similarity string `bson:"similarity"` 38 Quantization string `bson:"quantization"` 39 } 40 41 type filterField struct { 42 Type string `bson:"type"` 43 Path string `bson:"path"` 44 } 45 46 type indexDefinition struct { 47 Fields []vectorDefinitionField `bson:"fields"` 48 } 49 50 vectorDefinition := vectorDefinitionField{ 51 Type: "vector", 52 Path: "plot_embedding_voyage_3_large", 53 NumDimensions: 2048, 54 Similarity: "dotProduct", 55 Quantization: "scalar"} 56 genreFilterDefinition := filterField{"filter", "genres"} 57 yearFilterDefinition := filterField{"filter", "year"} 58 59 indexModel := mongo.SearchIndexModel{ 60 Definition: bson.D{{Key: "fields", Value: [3]interface{}{ 61 vectorDefinition, 62 genreFilterDefinition, 63 yearFilterDefinition}}}, 64 Options: opts, 65 } 66 67 // Create the index 68 searchIndexName, err := coll.SearchIndexes().CreateOne(ctx, indexModel) 69 if err != nil { 70 log.Fatalf("failed to create the search index: %v", err) 71 } 72 log.Println("New search index named " + searchIndexName + " is building.") 73 74 // Await the creation of the index. 75 log.Println("Polling to check if the index is ready. This may take up to a minute.") 76 searchIndexes := coll.SearchIndexes() 77 var doc bson.Raw 78 for doc == nil { 79 cursor, err := searchIndexes.List(ctx, options.SearchIndexes().SetName(searchIndexName)) 80 if err != nil { 81 fmt.Errorf("failed to list search indexes: %w", err) 82 } 83 84 if !cursor.Next(ctx) { 85 break 86 } 87 88 name := cursor.Current.Lookup("name").StringValue() 89 queryable := cursor.Current.Lookup("queryable").Boolean() 90 if name == searchIndexName && queryable { 91 doc = cursor.Current 92 } else { 93 time.Sleep(5 * time.Second) 94 } 95 } 96 97 log.Println(searchIndexName + " is ready for querying.") 98 }
コード内の <connection-string>
を置き換え、ファイルを保存します。
<connection-string>
を Atlas クラスターまたはローカル Atlas 配置の接続文字列に置き換えます。
接続stringには、次の形式を使用する必要があります。
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
詳しくは、ドライバーを使用してクラスターに接続する を参照してください。
接続stringには、次の形式を使用する必要があります。
mongodb://localhost:<port-number>/?directConnection=true
詳細については、「接続文字列 」を参照してください。
MongoDB Java Sync Driver をプロジェクトに追加します。
Java ドライバーバージョン 5.2 以降をプロジェクトの依存関係として追加してください。パッケージマネージャーに応じて、次のいずれかのタブを選択してください。
Maven を使用している場合は、プロジェクトの
pom.xml
ファイルのdependencies
配列に次の依存関係を追加します。pom.xml<dependencies> <!-- MongoDB Java Sync Driver v5.2.0 or later --> <dependency> <groupId>org.mongodb</groupId> <artifactId>mongodb-driver-sync</artifactId> <version>[5.2.0,)</version> </dependency> </dependencies> パッケージマネージャーを実行して、プロジェクトに依存関係をインストールします。
詳しいインストール手順やバージョンの互換性については MongoDB Java Driver のドキュメントを参照ください。
インデックスを定義します。
VectorIndex.java
という名前のファイルを作成し、次のコードをコピーしてファイルに貼り付けます。
このインデックス定義は、 MongoDB ベクトル検索インデックスの で、plot_embedding_voyage_3_large
フィールドをvector
タイプとしてインデックス化し、genres
フィールドと year
フィールドを filter
タイプとしてインデックス化します。plot_embedding_voyage_3_large
フィールドには、Voyage AI の voyage-3-large
埋め込みモデルを使用して作成された埋め込みが含まれます。インデックス定義では、2048
ベクトル次元を指定し、dotProduct
関数を使用して類似性を測定します。
1 import com.mongodb.client.MongoClient; 2 import com.mongodb.client.MongoClients; 3 import com.mongodb.client.MongoCollection; 4 import com.mongodb.client.MongoDatabase; 5 import com.mongodb.client.model.SearchIndexModel; 6 import com.mongodb.client.model.SearchIndexType; 7 import org.bson.Document; 8 import org.bson.conversions.Bson; 9 10 import java.util.Arrays; 11 import java.util.Collections; 12 import java.util.List; 13 14 public class VectorIndex { 15 16 public static void main(String[] args) { 17 18 // Replace the placeholder with your Atlas connection string 19 String uri = "<connectionString>"; 20 21 // Connect to your Atlas cluster 22 try (MongoClient mongoClient = MongoClients.create(uri)) { 23 24 // Set the namespace 25 MongoDatabase database = mongoClient.getDatabase("sample_mflix"); 26 MongoCollection<Document> collection = database.getCollection("embedded_movies"); 27 28 // Define the index details with the filter fields 29 String indexName = "vector_index"; 30 Bson definition = new Document( 31 "fields", 32 Arrays.asList( 33 new Document("type", "vector") 34 .append("path", "plot_embedding_voyage_3_large") 35 .append("numDimensions", 2048) 36 .append("similarity", "dotProduct") 37 .append("quantization", "scalar"), 38 new Document("type", "filter") 39 .append("path", "genres"), 40 new Document("type", "filter") 41 .append("path", "year"))); 42 43 // Define the index model 44 SearchIndexModel indexModel = new SearchIndexModel( 45 indexName, 46 definition, 47 SearchIndexType.vectorSearch()); 48 49 // Create the index using the defined model 50 List<String> result = collection.createSearchIndexes(Collections.singletonList(indexModel)); 51 System.out.println("Successfully created vector index named: " + result.get(0)); 52 System.out.println("It may take up to a minute for the index to leave the BUILDING status and become queryable."); 53 54 // Wait for index to build and become queryable 55 System.out.println("Polling to confirm the index has left the BUILDING status."); 56 // No special handling in case of a timeout. Custom handling can be implemented. 57 waitForIndex(collection, indexName); 58 } 59 } 60 61 /** 62 * Polls the collection to check whether the specified index is ready to query. 63 */ 64 public static <T> boolean waitForIndex(final MongoCollection<T> collection, final String indexName) { 65 long startTime = System.nanoTime(); 66 long timeoutNanos = TimeUnit.SECONDS.toNanos(60); 67 while (System.nanoTime() - startTime < timeoutNanos) { 68 Document indexRecord = StreamSupport.stream(collection.listSearchIndexes().spliterator(), false) 69 .filter(index -> indexName.equals(index.getString("name"))) 70 .findAny().orElse(null); 71 if (indexRecord != null) { 72 if ("FAILED".equals(indexRecord.getString("status"))) { 73 throw new RuntimeException("Search index has FAILED status."); 74 } 75 if (indexRecord.getBoolean("queryable")) { 76 System.out.println(indexName + " index is ready to query"); 77 return true; 78 } 79 } 80 try { 81 Thread.sleep(100); // busy-wait, avoid in production 82 } catch (InterruptedException e) { 83 Thread.currentThread().interrupt(); 84 throw new RuntimeException(e); 85 } 86 } 87 return false; 88 } 89 }
コード内の <connection-string>
を置き換え、ファイルを保存します。
<connection-string>
を Atlas クラスターまたはローカル Atlas 配置の接続文字列に置き換えます。
接続stringには、次の形式を使用する必要があります。
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
詳しくは、ドライバーを使用してクラスターに接続する を参照してください。
接続stringには、次の形式を使用する必要があります。
mongodb://localhost:<port-number>/?directConnection=true
詳細については、「接続文字列 」を参照してください。
ファイルを実行してインデックスを作成します。
IDE でファイルを実行するか、コマンドラインからコマンドを実行してコードを実行します。
javac VectorIndex.java java VectorIndex
Successfully created a vector index named: [vector_index] It may take up to a minute for the index to build before you can query using it. Polling to confirm the index has completed building. vector_index index is ready to query
インデックスを定義します。
vector-index.js
という名前のファイルを作成し、次のコードをコピーしてファイルに貼り付けます。
このインデックス定義は、 MongoDB ベクトル検索インデックスの で、plot_embedding_voyage_3_large
フィールドをvector
タイプとしてインデックス化し、genres
フィールドと year
フィールドを filter
タイプとしてインデックス化します。plot_embedding_voyage_3_large
フィールドには、Voyage AI の voyage-3-large
埋め込みモデルを使用して作成された埋め込みが含まれます。インデックス定義では、2048
ベクトル次元を指定し、dotProduct
関数を使用して類似性を測定します。
1 const { MongoClient } = require("mongodb"); 2 3 // connect to your Atlas deployment 4 const uri = "<connectionString>"; 5 6 const client = new MongoClient(uri); 7 8 async function run() { 9 try { 10 const database = client.db("sample_mflix"); 11 const collection = database.collection("embedded_movies"); 12 13 // define your MongoDB Vector Search index 14 const index = { 15 name: "vector_index", 16 type: "vectorSearch", 17 definition: { 18 "fields": [ 19 { 20 "type": "vector", 21 "numDimensions": 2048, 22 "path": "plot_embedding_voyage_3_large", 23 "similarity": "dotProduct", 24 "quantization": "scalar" 25 }, 26 { 27 "type": "filter", 28 "path": "genres" 29 }, 30 { 31 "type": "filter", 32 "path": "year" 33 } 34 ] 35 } 36 } 37 38 // run the helper method 39 const result = await collection.createSearchIndex(index); 40 console.log(`New search index named ${result} is building.`); 41 42 // wait for the index to be ready to query 43 console.log("Polling to check if the index is ready. This may take up to a minute.") 44 let isQueryable = false; 45 while (!isQueryable) { 46 const cursor = collection.listSearchIndexes(); 47 for await (const index of cursor) { 48 if (index.name === result) { 49 if (index.queryable) { 50 console.log(`${result} is ready for querying.`); 51 isQueryable = true; 52 } else { 53 await new Promise(resolve => setTimeout(resolve, 5000)); 54 } 55 } 56 } 57 } 58 } finally { 59 await client.close(); 60 } 61 } 62 run().catch(console.dir);
コード内の <connection-string>
を置き換え、ファイルを保存します。
<connection-string>
を Atlas クラスターまたはローカル Atlas 配置の接続文字列に置き換えます。
接続stringには、次の形式を使用する必要があります。
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
詳しくは、ドライバーを使用してクラスターに接続する を参照してください。
接続stringには、次の形式を使用する必要があります。
mongodb://localhost:<port-number>/?directConnection=true
詳細については、「接続文字列 」を参照してください。
インデックスを定義します。
vector-index.py
という名前のファイルを作成し、次のコードをコピーしてファイルに貼り付けます。
このインデックス定義は、 MongoDB ベクトル検索インデックスの で、plot_embedding_voyage_3_large
フィールドをvector
タイプとしてインデックス化し、genres
フィールドと year
フィールドを filter
タイプとしてインデックス化します。plot_embedding_voyage_3_large
フィールドには、Voyage AI の voyage-3-large
埋め込みモデルを使用して作成された埋め込みが含まれます。インデックス定義では、2048
ベクトル次元を指定し、dotProduct
関数を使用して類似性を測定し、ベクトルを効率的に処理するための自動 scalar
量子化を有効にします。
1 from pymongo.mongo_client import MongoClient 2 from pymongo.operations import SearchIndexModel 3 import time 4 5 # Connect to your Atlas deployment 6 uri = "<connectionString>" 7 client = MongoClient(uri) 8 9 # Access your database and collection 10 database = client["sample_mflix"] 11 collection = database["embedded_movies"] 12 13 # Create your index model, then create the search index 14 search_index_model = SearchIndexModel( 15 definition={ 16 "fields": [ 17 { 18 "type": "vector", 19 "path": "plot_embedding_voyage_3_large", 20 "numDimensions": 2048, 21 "similarity": "dotProduct", 22 "quantization": "scalar" 23 }, 24 { 25 "type": "filter", 26 "path": "genres" 27 }, 28 { 29 "type": "filter", 30 "path": "year" 31 } 32 ] 33 }, 34 name="vector_index", 35 type="vectorSearch" 36 ) 37 38 result = collection.create_search_index(model=search_index_model) 39 print("New search index named " + result + " is building.") 40 41 # Wait for initial sync to complete 42 print("Polling to check if the index is ready. This may take up to a minute.") 43 predicate=None 44 if predicate is None: 45 predicate = lambda index: index.get("queryable") is True 46 47 while True: 48 indices = list(collection.list_search_indexes(result)) 49 if len(indices) and predicate(indices[0]): 50 break 51 time.sleep(5) 52 print(result + " is ready for querying.") 53 54 client.close()
コード内の <connection-string>
を置き換え、ファイルを保存します。
<connection-string>
を Atlas クラスターまたはローカル Atlas 配置の接続文字列に置き換えます。
接続stringには、次の形式を使用する必要があります。
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
詳しくは、ドライバーを使用してクラスターに接続する を参照してください。
接続stringには、次の形式を使用する必要があります。
mongodb://localhost:<port-number>/?directConnection=true
詳細については、「接続文字列 」を参照してください。
$vectorSearch
集計パイプライン ステージを使用してクエリを実行します。
Overview
このセクションでは、 $vectorSearch
ステージを使用して、 sample_mflix.embedded_movies
コレクション内のインデックス付きベクトル データをクエリする方法を説明します。 これらのサンプル クエリでは、セマンティック検索を実行するデータを事前にフィルタリングするためにクエリで使用できるさまざまなクエリおよび集計パイプライン演算子も示されています。
手順
クエリの埋め込みを準備します。
次の埋め込みを query-embeddings.js
という名前のファイルに保存してください。
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mongosh
内のクラスターに接続します。
ターミナル ウィンドウでmongosh
を開き、クラスターに接続します。 接続の詳細な手順については、「 mongosh 経由での接続 」を参照してください。
インデックス フィールドに対してセマンティック検索クエリを実行します。
次のクエリは、$vectorSearch
パイプライン ステージを使用して、指定されたベクター埋め込みに一致する映画を検索します。クエリは、最大 100
件の最近傍を検索し、結果を 10
件のドキュメントのみに制限します。クエリは、次のアクションを実行するための $project
ステージも指定します。
_id
フィールドを除外し、結果にはtitle
、genres
、plot
、およびyear
フィールドのみが含まれます。結果内の各ドキュメントのベクトル検索スコアを表示する
score
という名前のフィールドを追加します。
次のクエリは、文字列 kids adventure のベクトル埋め込みを使用して、plot_embedding_voyage_3_large
フィールドを検索します。フィールドごとに複数の比較クエリ演算子を指定して、セマンティック検索を実行するドキュメントを事前にフィルタリングします。
フィルターでは、 $and
集計パイプライン演算子を使用して、次の両方の条件に一致するドキュメントを検索します。
genres
フィールドでフィルタリングして、drama
、western
、またはcrime
ジャンルではなく、action
、adventure
、またはfamily
ジャンルに含まれる映画を検索します。year
フィールドでフィルタリングして、1960
から2000
年(両端を含む)の間にリリースされた映画を検索します。
1 db.embedded_movies.aggregate([ 2 { 3 "$vectorSearch": { 4 "index": "vector_index", 5 "path": "plot_embedding_voyage_3_large", 6 "filter": { 7 "$and": [{ 8 "genres": { 9 "$nin": ["Drama", "Western", "Crime"], 10 "$in": ["Action", "Adventure", "Family"] 11 }, 12 }, { 13 "year": { 14 "$gte": 1960, 15 "$lte": 2000 16 } 17 }] 18 }, 19 "queryVector": KIDS_ADVENTURE_EMBEDDING, 20 "numCandidates": 200, 21 "limit": 10 22 } 23 }, 24 { 25 "$project": { 26 "_id": 0, 27 "title": 1, 28 "genres": 1, 29 "plot": 1, 30 "year": 1, 31 "score": { $meta: "vectorSearchScore" } 32 } 33 } 34 ])
1 [ 2 { 3 plot: 'Three young boys, Rocky, Colt and Tum Tum together with their neighbor girl, computer whiz Amanda are visiting Mega Mountain amusement park when it is invaded by an army of ninjas led by ...', 4 genres: [ 'Action', 'Adventure', 'Comedy' ], 5 title: '3 Ninjas: High Noon at Mega Mountain', 6 year: 1998, 7 score: 0.7746343612670898 8 }, 9 { 10 plot: "A two-week trek through the Cascade Mountains tries the survival instincts of five adventurous teenagers. At first, it's all a good time. Shooting the rapids, exploring caves and making new...", 11 genres: [ 'Action', 'Adventure', 'Family' ], 12 title: 'White Wolves: A Cry in the Wild II', 13 year: 1993, 14 score: 0.770106315612793 15 }, 16 { 17 plot: 'A futuristic, sensitive tale of adventure and confrontation when a 10 year old boy is accidentally kidnapped by a spaceship filled with a motley crew of space pirates.', 18 genres: [ 'Action', 'Adventure', 'Sci-Fi' ], 19 title: 'Space Raiders', 20 year: 1983, 21 score: 0.7569591999053955 22 }, 23 { 24 plot: 'Wicket the Ewok and his friends agree to help two shipwrecked human children on a quest to find their parents.', 25 genres: [ 'Adventure', 'Family', 'Fantasy' ], 26 title: 'The Ewok Adventure', 27 year: 1984, 28 score: 0.7515435218811035 29 }, 30 { 31 plot: 'A young boy accidentally joins a band of dwarves as they jump from era to era looking for treasure to steal.', 32 genres: [ 'Adventure', 'Comedy', 'Fantasy' ], 33 title: 'Time Bandits', 34 year: 1981, 35 score: 0.7513599395751953 36 }, 37 { 38 plot: 'A down-on-his-luck inventor turns a broken-down Grand Prix car into a fancy vehicle for his children, and then they go off on a magical fantasy adventure to save their grandfather in a far-off land.', 39 genres: [ 'Adventure', 'Family', 'Fantasy' ], 40 title: 'Chitty Chitty Bang Bang', 41 year: 1968, 42 score: 0.7492260932922363 43 }, 44 { 45 plot: 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.', 46 genres: [ 'Action', 'Adventure', 'Comedy' ], 47 title: 'Forest Warrior', 48 year: 1996, 49 score: 0.7473714351654053 50 }, 51 { 52 plot: 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.', 53 genres: [ 'Action', 'Adventure', 'Comedy' ], 54 title: 'Forest Warrior', 55 year: 1996, 56 score: 0.7473714351654053 57 }, 58 { 59 plot: 'A young boy is whisked away to the mythical land of Tao where he becomes the center of a conflict between an evil lord and a group of animal warriors.', 60 genres: [ 'Action', 'Fantasy', 'Adventure' ], 61 title: 'Warriors of Virtue', 62 year: 1997, 63 score: 0.7464213371276855 64 }, 65 { 66 plot: 'A young prince is taken for tuition at a seaside hotel but there quickly bores and wanders off to visit a nearby lighthouse. Befriended by the keeper, he learns of a secret world he can see...', 67 genres: [ 'Animation', 'Adventure', 'Fantasy' ], 68 title: 'Taxandria', 69 year: 1994, 70 score: 0.7453246116638184 71 } 72 ]
次のクエリは、ベクター埋め込みを使用して plot_embedding_voyage_3_large
フィールドで star wars という文字列を検索します。集計パイプラインと比較クエリ演算子を指定し、演算子を組み合わせてデータをフィルタリングする方法を示します。
フィルターでは、 $or
集計パイプライン演算子を使用して、次のいずれかの条件に一致する映画のドキュメントを検索します。
genres
フィールドでフィルタリングして、crime
ジャンルに該当しない映画を検索します。year
フィールドでフィルタリングして、2015
年以前にリリースされた映画を検索し、genres
フィールドでフィルタリングしてaction
ジャンルの映画を検索します。
1 db.embedded_movies.aggregate([ 2 { 3 "$vectorSearch": { 4 "index": "vector_index", 5 "path": "plot_embedding_voyage_3_large", 6 "filter": { 7 "$or": [{ 8 "genres": { "$ne": "Crime" } 9 }, { 10 "$and": [{ 11 "year": { "$lte": 2015 } 12 }, { 13 "genres": { "$eq": "Action" } 14 }] 15 }] 16 }, 17 "queryVector": STAR_WARS_EMBEDDING, 18 "numCandidates": 200, 19 "limit": 10 20 } 21 }, 22 { 23 "$project": { 24 "_id": 0, 25 "title": 1, 26 "genres": 1, 27 "plot": 1, 28 "released": 1, 29 "score": { $meta: "vectorSearchScore" } 30 } 31 } 32 ])
1 [ 2 { 3 plot: "Luke Skywalker joins forces with a Jedi Knight, a cocky pilot, a wookiee and two droids to save the universe from the Empire's world-destroying battle-station, while also attempting to rescue Princess Leia from the evil Darth Vader.", 4 genres: [ 'Action', 'Adventure', 'Fantasy' ], 5 title: 'Star Wars: Episode IV - A New Hope', 6 released: ISODate('1977-05-25T00:00:00.000Z'), 7 score: 0.79868483543396 8 }, 9 { 10 plot: "A Duke's son leads desert warriors against the galactic emperor and his father's evil nemesis when they assassinate his father and free their desert world from the emperor's rule.", 11 genres: [ 'Action', 'Adventure', 'Sci-Fi' ], 12 title: 'Dune', 13 released: ISODate('1984-12-14T00:00:00.000Z'), 14 score: 0.7949700355529785 15 }, 16 { 17 plot: 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...', 18 genres: [ 'Action', 'Adventure', 'Sci-Fi' ], 19 title: 'Message from Space', 20 released: ISODate('1978-10-30T00:00:00.000Z'), 21 score: 0.7913978099822998 22 }, 23 { 24 plot: 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...', 25 genres: [ 'Action', 'Adventure', 'Sci-Fi' ], 26 title: 'Message from Space', 27 released: ISODate('1978-10-30T00:00:00.000Z'), 28 score: 0.7913978099822998 29 }, 30 { 31 plot: 'After the rebels have been brutally overpowered by the Empire on their newly established base, Luke Skywalker takes advanced Jedi training with Master Yoda, while his friends are pursued by Darth Vader as part of his plan to capture Luke.', 32 genres: [ 'Action', 'Adventure', 'Fantasy' ], 33 title: 'Star Wars: Episode V - The Empire Strikes Back', 34 released: ISODate('1980-06-20T00:00:00.000Z'), 35 score: 0.7809884548187256 36 }, 37 { 38 plot: 'After rescuing Han Solo from the palace of Jabba the Hutt, the rebels attempt to destroy the second Death Star, while Luke struggles to make Vader return from the dark side of the Force.', 39 genres: [ 'Action', 'Adventure', 'Fantasy' ], 40 title: 'Star Wars: Episode VI - Return of the Jedi', 41 released: ISODate('1983-05-25T00:00:00.000Z'), 42 score: 0.7784996032714844 43 }, 44 { 45 plot: 'Two Jedi Knights escape a hostile blockade to find allies and come across a young boy who may bring balance to the Force, but the long dormant Sith resurface to reclaim their old glory.', 46 genres: [ 'Action', 'Adventure', 'Fantasy' ], 47 title: 'Star Wars: Episode I - The Phantom Menace', 48 released: ISODate('1999-05-19T00:00:00.000Z'), 49 score: 0.7766742706298828 50 }, 51 { 52 plot: 'The army of the Marauders, led by by King Terak and the witch Charal attack the Ewoks village. The parents and the brother of Cindel all die in this attack. Cindel and the Ewok Wicket ...', 53 genres: [ 'Adventure', 'Family', 'Fantasy' ], 54 title: 'Ewoks: The Battle for Endor', 55 released: ISODate('1985-11-24T00:00:00.000Z'), 56 score: 0.7676119804382324 57 }, 58 { 59 plot: 'A prince and a fellowship of companions set out to rescue his bride from a fortress of alien invaders who have arrived on their home planet.', 60 genres: [ 'Action', 'Adventure', 'Fantasy' ], 61 title: 'Krull', 62 released: ISODate('1983-07-29T00:00:00.000Z'), 63 score: 0.7624373435974121 64 }, 65 { 66 plot: 'An outlaw smuggler and her alien companion are recruited by the Emperor of the Galaxy to rescue his son and destroy a secret weapon by the evil Count Zarth Arn.', 67 genres: [ 'Action', 'Adventure', 'Fantasy' ], 68 title: 'Starcrash', 69 released: ISODate('1979-03-09T00:00:00.000Z'), 70 score: 0.7582714557647705 71 } 72 ]
クエリの埋め込みを準備します。
次の埋め込みを query-embeddings.js
という名前のファイルに保存してください。
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mongosh
内のクラスターに接続します。
ターミナル ウィンドウでmongosh
を開き、クラスターに接続します。 接続の詳細な手順については、「 mongosh 経由での接続 」を参照してください。
インデックス フィールドに対してセマンティック検索クエリを実行します。
次のクエリは、$vectorSearch
パイプライン ステージを使用して、指定されたベクター埋め込みに一致する映画を検索します。クエリは、最大 100
件の最近傍を検索し、結果を 10
件のドキュメントのみに制限します。クエリは、次のアクションを実行するための $project
ステージも指定します。
_id
フィールドを除外し、結果にはtitle
、genres
、plot
、およびyear
フィールドのみが含まれます。結果内の各ドキュメントのベクトル検索スコアを表示する
score
という名前のフィールドを追加します。
次のクエリは、文字列 kids adventure のベクトル埋め込みを使用して、plot_embedding_voyage_3_large
フィールドを検索します。フィールドごとに複数の比較クエリ演算子を指定して、セマンティック検索を実行するドキュメントを事前にフィルタリングします。
フィルターでは、 $and
集計パイプライン演算子を使用して、次の両方の条件に一致するドキュメントを検索します。
genres
フィールドでフィルタリングして、drama
、western
、またはcrime
ジャンルではなく、action
、adventure
、またはfamily
ジャンルに含まれる映画を検索します。year
フィールドでフィルタリングして、1960
から2000
年(両端を含む)の間にリリースされた映画を検索します。
1 db.embedded_movies.aggregate([ 2 { 3 "$vectorSearch": { 4 "index": "vector_index", 5 "path": "plot_embedding_voyage_3_large", 6 "filter": { 7 "$and": [{ 8 "genres": { 9 "$nin": ["Drama", "Western", "Crime"], 10 "$in": ["Action", "Adventure", "Family"] 11 }, 12 }, { 13 "year": { 14 "$gte": 1960, 15 "$lte": 2000 16 } 17 }] 18 }, 19 "queryVector": KIDS_ADVENTURE_EMBEDDING, 20 "numCandidates": 200, 21 "limit": 10 22 } 23 }, 24 { 25 "$project": { 26 "_id": 0, 27 "title": 1, 28 "genres": 1, 29 "plot": 1, 30 "year": 1, 31 "score": { $meta: "vectorSearchScore" } 32 } 33 } 34 ])
1 [ 2 { 3 plot: 'Three young boys, Rocky, Colt and Tum Tum together with their neighbor girl, computer whiz Amanda are visiting Mega Mountain amusement park when it is invaded by an army of ninjas led by ...', 4 genres: [ 'Action', 'Adventure', 'Comedy' ], 5 title: '3 Ninjas: High Noon at Mega Mountain', 6 year: 1998, 7 score: 0.7746343612670898 8 }, 9 { 10 plot: "A two-week trek through the Cascade Mountains tries the survival instincts of five adventurous teenagers. At first, it's all a good time. Shooting the rapids, exploring caves and making new...", 11 genres: [ 'Action', 'Adventure', 'Family' ], 12 title: 'White Wolves: A Cry in the Wild II', 13 year: 1993, 14 score: 0.770106315612793 15 }, 16 { 17 plot: 'A futuristic, sensitive tale of adventure and confrontation when a 10 year old boy is accidentally kidnapped by a spaceship filled with a motley crew of space pirates.', 18 genres: [ 'Action', 'Adventure', 'Sci-Fi' ], 19 title: 'Space Raiders', 20 year: 1983, 21 score: 0.7569591999053955 22 }, 23 { 24 plot: 'Wicket the Ewok and his friends agree to help two shipwrecked human children on a quest to find their parents.', 25 genres: [ 'Adventure', 'Family', 'Fantasy' ], 26 title: 'The Ewok Adventure', 27 year: 1984, 28 score: 0.7515435218811035 29 }, 30 { 31 plot: 'A young boy accidentally joins a band of dwarves as they jump from era to era looking for treasure to steal.', 32 genres: [ 'Adventure', 'Comedy', 'Fantasy' ], 33 title: 'Time Bandits', 34 year: 1981, 35 score: 0.7513599395751953 36 }, 37 { 38 plot: 'A down-on-his-luck inventor turns a broken-down Grand Prix car into a fancy vehicle for his children, and then they go off on a magical fantasy adventure to save their grandfather in a far-off land.', 39 genres: [ 'Adventure', 'Family', 'Fantasy' ], 40 title: 'Chitty Chitty Bang Bang', 41 year: 1968, 42 score: 0.7492260932922363 43 }, 44 { 45 plot: 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.', 46 genres: [ 'Action', 'Adventure', 'Comedy' ], 47 title: 'Forest Warrior', 48 year: 1996, 49 score: 0.7473714351654053 50 }, 51 { 52 plot: 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.', 53 genres: [ 'Action', 'Adventure', 'Comedy' ], 54 title: 'Forest Warrior', 55 year: 1996, 56 score: 0.7473714351654053 57 }, 58 { 59 plot: 'A young boy is whisked away to the mythical land of Tao where he becomes the center of a conflict between an evil lord and a group of animal warriors.', 60 genres: [ 'Action', 'Fantasy', 'Adventure' ], 61 title: 'Warriors of Virtue', 62 year: 1997, 63 score: 0.7464213371276855 64 }, 65 { 66 plot: 'A young prince is taken for tuition at a seaside hotel but there quickly bores and wanders off to visit a nearby lighthouse. Befriended by the keeper, he learns of a secret world he can see...', 67 genres: [ 'Animation', 'Adventure', 'Fantasy' ], 68 title: 'Taxandria', 69 year: 1994, 70 score: 0.7453246116638184 71 } 72 ]
次のクエリは、ベクター埋め込みを使用して plot_embedding_voyage_3_large
フィールドで star wars という文字列を検索します。集計パイプラインと比較クエリ演算子を指定し、演算子を組み合わせてデータをフィルタリングする方法を示します。
フィルターでは、 $or
集計パイプライン演算子を使用して、次のいずれかの条件に一致する映画のドキュメントを検索します。
genres
フィールドでフィルタリングして、crime
ジャンルに該当しない映画を検索します。year
フィールドでフィルタリングして、2015
年以前にリリースされた映画を検索し、genres
フィールドでフィルタリングしてaction
ジャンルの映画を検索します。
1 db.embedded_movies.aggregate([ 2 { 3 "$vectorSearch": { 4 "index": "vector_index", 5 "path": "plot_embedding_voyage_3_large", 6 "filter": { 7 "$or": [{ 8 "genres": { "$ne": "Crime" } 9 }, { 10 "$and": [{ 11 "year": { "$lte": 2015 } 12 }, { 13 "genres": { "$eq": "Action" } 14 }] 15 }] 16 }, 17 "queryVector": STAR_WARS_EMBEDDING, 18 "numCandidates": 200, 19 "limit": 10 20 } 21 }, 22 { 23 "$project": { 24 "_id": 0, 25 "title": 1, 26 "genres": 1, 27 "plot": 1, 28 "released": 1, 29 "score": { $meta: "vectorSearchScore" } 30 } 31 } 32 ])
1 [ 2 { 3 plot: "Luke Skywalker joins forces with a Jedi Knight, a cocky pilot, a wookiee and two droids to save the universe from the Empire's world-destroying battle-station, while also attempting to rescue Princess Leia from the evil Darth Vader.", 4 genres: [ 'Action', 'Adventure', 'Fantasy' ], 5 title: 'Star Wars: Episode IV - A New Hope', 6 released: ISODate('1977-05-25T00:00:00.000Z'), 7 score: 0.79868483543396 8 }, 9 { 10 plot: "A Duke's son leads desert warriors against the galactic emperor and his father's evil nemesis when they assassinate his father and free their desert world from the emperor's rule.", 11 genres: [ 'Action', 'Adventure', 'Sci-Fi' ], 12 title: 'Dune', 13 released: ISODate('1984-12-14T00:00:00.000Z'), 14 score: 0.7949700355529785 15 }, 16 { 17 plot: 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...', 18 genres: [ 'Action', 'Adventure', 'Sci-Fi' ], 19 title: 'Message from Space', 20 released: ISODate('1978-10-30T00:00:00.000Z'), 21 score: 0.7913978099822998 22 }, 23 { 24 plot: 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...', 25 genres: [ 'Action', 'Adventure', 'Sci-Fi' ], 26 title: 'Message from Space', 27 released: ISODate('1978-10-30T00:00:00.000Z'), 28 score: 0.7913978099822998 29 }, 30 { 31 plot: 'After the rebels have been brutally overpowered by the Empire on their newly established base, Luke Skywalker takes advanced Jedi training with Master Yoda, while his friends are pursued by Darth Vader as part of his plan to capture Luke.', 32 genres: [ 'Action', 'Adventure', 'Fantasy' ], 33 title: 'Star Wars: Episode V - The Empire Strikes Back', 34 released: ISODate('1980-06-20T00:00:00.000Z'), 35 score: 0.7809884548187256 36 }, 37 { 38 plot: 'After rescuing Han Solo from the palace of Jabba the Hutt, the rebels attempt to destroy the second Death Star, while Luke struggles to make Vader return from the dark side of the Force.', 39 genres: [ 'Action', 'Adventure', 'Fantasy' ], 40 title: 'Star Wars: Episode VI - Return of the Jedi', 41 released: ISODate('1983-05-25T00:00:00.000Z'), 42 score: 0.7784996032714844 43 }, 44 { 45 plot: 'Two Jedi Knights escape a hostile blockade to find allies and come across a young boy who may bring balance to the Force, but the long dormant Sith resurface to reclaim their old glory.', 46 genres: [ 'Action', 'Adventure', 'Fantasy' ], 47 title: 'Star Wars: Episode I - The Phantom Menace', 48 released: ISODate('1999-05-19T00:00:00.000Z'), 49 score: 0.7766742706298828 50 }, 51 { 52 plot: 'The army of the Marauders, led by by King Terak and the witch Charal attack the Ewoks village. The parents and the brother of Cindel all die in this attack. Cindel and the Ewok Wicket ...', 53 genres: [ 'Adventure', 'Family', 'Fantasy' ], 54 title: 'Ewoks: The Battle for Endor', 55 released: ISODate('1985-11-24T00:00:00.000Z'), 56 score: 0.7676119804382324 57 }, 58 { 59 plot: 'A prince and a fellowship of companions set out to rescue his bride from a fortress of alien invaders who have arrived on their home planet.', 60 genres: [ 'Action', 'Adventure', 'Fantasy' ], 61 title: 'Krull', 62 released: ISODate('1983-07-29T00:00:00.000Z'), 63 score: 0.7624373435974121 64 }, 65 { 66 plot: 'An outlaw smuggler and her alien companion are recruited by the Emperor of the Galaxy to rescue his son and destroy a secret weapon by the evil Count Zarth Arn.', 67 genres: [ 'Action', 'Adventure', 'Fantasy' ], 68 title: 'Starcrash', 69 released: ISODate('1979-03-09T00:00:00.000Z'), 70 score: 0.7582714557647705 71 } 72 ]
試したいプレフィルター演算子のコードをコピーして、DataService.cs
ファイルに貼り付けます。
次のクエリは、$vectorSearch
パイプライン ステージを使用して、指定されたベクター埋め込みに一致する映画を検索します。クエリは、最大 100
件の最近傍を検索し、結果を 10
件のドキュメントのみに制限します。クエリは、次のアクションを実行するための $project
ステージも指定します。
_id
フィールドを除外し、結果にはtitle
、genres
、plot
、およびyear
フィールドのみが含まれます。結果内の各ドキュメントのベクトル検索スコアを表示する
score
という名前のフィールドを追加します。
次のクエリは、文字列 kids adventure のベクトル埋め込みを使用して、plot_embedding_voyage_3_large
フィールドを検索します。フィールドごとに複数の比較クエリ演算子を指定して、セマンティック検索を実行するドキュメントを事前にフィルタリングします。
フィルターでは、 $and
集計パイプライン演算子を使用して、次の両方の条件に一致するドキュメントを検索します。
genres
フィールドでフィルタリングして、drama
、western
、またはcrime
ジャンルではなく、action
、adventure
、またはfamily
ジャンルに含まれる映画を検索します。year
フィールドでフィルタリングして、1960
から2000
年(両端を含む)の間にリリースされた映画を検索します。
1 namespace query_quick_start; 2 3 using MongoDB.Driver; 4 using MongoDB.Bson; 5 6 public class DataService 7 { 8 private const string ConnectionString = "<connection-string>"; 9 private static readonly MongoClient Client = new MongoClient(ConnectionString); 10 private static readonly IMongoDatabase Database = Client.GetDatabase("sample_mflix"); 11 private static readonly IMongoCollection<BsonDocument> Collection = Database.GetCollection<BsonDocument>("embedded_movies"); 12 13 public List<BsonDocument>? PerformVectorQuery() 14 { 15 double[] queryVector = { 16 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17 }; 18 var filter = Builders<BsonDocument>.Filter.And( 19 Builders<BsonDocument>.Filter.And( 20 Builders<BsonDocument>.Filter.Nin("genres", ["Drama", "Western", "Crime"]), 21 Builders<BsonDocument>.Filter.In("genres", ["Action", "Adventure", "Family"]) 22 ), 23 Builders<BsonDocument>.Filter.And( 24 Builders<BsonDocument>.Filter.Gte("year", 1960), 25 Builders<BsonDocument>.Filter.Lte("year", 2000) 26 ) 27 ); 28 29 var options = new VectorSearchOptions<BsonDocument>() 30 { 31 IndexName = "vector_index", 32 Filter = filter, 33 NumberOfCandidates = 200, 34 }; 35 36 var pipeline = new EmptyPipelineDefinition<BsonDocument>() 37 .VectorSearch("plot_embedding_voyage_3_large", queryVector, 10, options) 38 .Project(Builders<BsonDocument>.Projection 39 .Exclude("_id") 40 .Include("title") 41 .Include("genres") 42 .Include("plot") 43 .Include("year") 44 .Meta("score", "vectorSearchScore") 45 ); 46 return Collection.Aggregate<BsonDocument>(pipeline).ToList(); 47 } 48 }
次のクエリは、ベクター埋め込みを使用して plot_embedding_voyage_3_large
フィールドで star wars という文字列を検索します。集計パイプラインと比較クエリ演算子を指定し、演算子を組み合わせてデータをフィルタリングする方法を示します。
フィルターでは、 $or
集計パイプライン演算子を使用して、次のいずれかの条件に一致する映画のドキュメントを検索します。
genres
フィールドでフィルタリングして、crime
ジャンルに該当しない映画を検索します。year
フィールドでフィルタリングして、2015
年以前にリリースされた映画を検索し、genres
フィールドでフィルタリングしてaction
ジャンルの映画を検索します。
1 namespace query_quick_start; 2 3 using MongoDB.Driver; 4 using MongoDB.Bson; 5 6 public class DataService 7 { 8 private const string ConnectionString = "<connection-string>"; 9 private static readonly MongoClient Client = new MongoClient(ConnectionString); 10 private static readonly IMongoDatabase Database = Client.GetDatabase("sample_mflix"); 11 private static readonly IMongoCollection<BsonDocument> Collection = Database.GetCollection<BsonDocument>("embedded_movies"); 12 13 public List<BsonDocument>? PerformVectorQuery() 14 { 15 double[] queryVector = { 16 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17 }; 18 var filter = Builders<BsonDocument>.Filter.Or( 19 Builders<BsonDocument>.Filter.Ne("genres", "Crime"), 20 Builders<BsonDocument>.Filter.And( 21 Builders<BsonDocument>.Filter.Lte("year", 2015), 22 Builders<BsonDocument>.Filter.Eq("genres", "Action") 23 ) 24 ); 25 26 var options = new VectorSearchOptions<BsonDocument>() 27 { 28 IndexName = "vector_index", 29 Filter = filter, 30 NumberOfCandidates = 200, 31 }; 32 33 var pipeline = new EmptyPipelineDefinition<BsonDocument>() 34 .VectorSearch("plot_embedding_voyage_3_large", queryVector, 10, options) 35 .Project(Builders<BsonDocument>.Projection 36 .Exclude("_id") 37 .Include("title") 38 .Include("genres") 39 .Include("plot") 40 .Include("year") 41 .Meta("score", "vectorSearchScore") 42 ); 43 return Collection.Aggregate<BsonDocument>(pipeline).ToList(); 44 } 45 }
クエリ内の <connection-string>
を置き換え、ファイルを保存します。
<connection-string>
を Atlas クラスターまたはローカル Atlas 配置の接続文字列に置き換えます。
接続stringには、次の形式を使用する必要があります。
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
詳しくは、ドライバーを使用してクラスターに接続する を参照してください。
接続stringには、次の形式を使用する必要があります。
mongodb://localhost:<port-number>/?directConnection=true
詳細については、「接続文字列 」を参照してください。
Update Program.cs
.
Program.cs
を更新して DataService
を初期化し、メソッドを呼び出してクエリを実行します。
1 using query_quick_start; 2 3 var dataService = new DataService(); 4 var results = dataService.PerformVectorQuery(); 5 if (results != null) 6 { 7 foreach (var document in results) 8 { 9 Console.WriteLine(document); 10 } 11 } 12 else 13 { 14 Console.WriteLine("The query returned no results."); 15 }
プロジェクトを保存して実行します。
ファイルを保存し、プロジェクトをコンパイルして実行して、クエリを実行します。
dotnet run query_quick_start.csproj
1 { "plot" : "Three young boys, Rocky, Colt and Tum Tum together with their neighbor girl, computer whiz Amanda are visiting Mega Mountain amusement park when it is invaded by an army of ninjas led by ...", "genres" : ["Action", "Adventure", "Comedy"], "title" : "3 Ninjas: High Noon at Mega Mountain", "year" : 1998, "score" : 0.77463436126708984 } 2 { "plot" : "A two-week trek through the Cascade Mountains tries the survival instincts of five adventurous teenagers. At first, it's all a good time. Shooting the rapids, exploring caves and making new...", "genres" : ["Action", "Adventure", "Family"], "title" : "White Wolves: A Cry in the Wild II", "year" : 1993, "score" : 0.77010631561279297 } 3 { "plot" : "A futuristic, sensitive tale of adventure and confrontation when a 10 year old boy is accidentally kidnapped by a spaceship filled with a motley crew of space pirates.", "genres" : ["Action", "Adventure", "Sci-Fi"], "title" : "Space Raiders", "year" : 1983, "score" : 0.75695919990539551 } 4 { "plot" : "Wicket the Ewok and his friends agree to help two shipwrecked human children on a quest to find their parents.", "genres" : ["Adventure", "Family", "Fantasy"], "title" : "The Ewok Adventure", "year" : 1984, "score" : 0.75154352188110352 } 5 { "plot" : "A young boy accidentally joins a band of dwarves as they jump from era to era looking for treasure to steal.", "genres" : ["Adventure", "Comedy", "Fantasy"], "title" : "Time Bandits", "year" : 1981, "score" : 0.75135993957519531 } 6 { "plot" : "A down-on-his-luck inventor turns a broken-down Grand Prix car into a fancy vehicle for his children, and then they go off on a magical fantasy adventure to save their grandfather in a far-off land.", "genres" : ["Adventure", "Family", "Fantasy"], "title" : "Chitty Chitty Bang Bang", "year" : 1968, "score" : 0.74922609329223633 } 7 { "plot" : "A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.", "genres" : ["Action", "Adventure", "Comedy"], "title" : "Forest Warrior", "year" : 1996, "score" : 0.74737143516540527 } 8 { "plot" : "A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.", "genres" : ["Action", "Adventure", "Comedy"], "title" : "Forest Warrior", "year" : 1996, "score" : 0.74737143516540527 } 9 { "plot" : "A young boy is whisked away to the mythical land of Tao where he becomes the center of a conflict between an evil lord and a group of animal warriors.", "genres" : ["Action", "Fantasy", "Adventure"], "title" : "Warriors of Virtue", "year" : 1997, "score" : 0.74642133712768555 } 10 { "plot" : "A young prince is taken for tuition at a seaside hotel but there quickly bores and wanders off to visit a nearby lighthouse. Befriended by the keeper, he learns of a secret world he can see...", "genres" : ["Animation", "Adventure", "Fantasy"], "title" : "Taxandria", "year" : 1994, "score" : 0.74532461166381836 }
dotnet run query_quick_start.csproj
1 { "year" : 1977, "plot" : "Luke Skywalker joins forces with a Jedi Knight, a cocky pilot, a wookiee and two droids to save the universe from the Empire's world-destroying battle-station, while also attempting to rescue Princess Leia from the evil Darth Vader.", "genres" : ["Action", "Adventure", "Fantasy"], "title" : "Star Wars: Episode IV - A New Hope", "score" : 0.79868483543395996 } 2 { "plot" : "A Duke's son leads desert warriors against the galactic emperor and his father's evil nemesis when they assassinate his father and free their desert world from the emperor's rule.", "genres" : ["Action", "Adventure", "Sci-Fi"], "title" : "Dune", "year" : 1984, "score" : 0.79497003555297852 } 3 { "plot" : "In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...", "genres" : ["Action", "Adventure", "Sci-Fi"], "title" : "Message from Space", "year" : 1978, "score" : 0.7913978099822998 } 4 { "plot" : "In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...", "genres" : ["Action", "Adventure", "Sci-Fi"], "title" : "Message from Space", "year" : 1978, "score" : 0.7913978099822998 } 5 { "year" : 1980, "plot" : "After the rebels have been brutally overpowered by the Empire on their newly established base, Luke Skywalker takes advanced Jedi training with Master Yoda, while his friends are pursued by Darth Vader as part of his plan to capture Luke.", "genres" : ["Action", "Adventure", "Fantasy"], "title" : "Star Wars: Episode V - The Empire Strikes Back", "score" : 0.78098845481872559 } 6 { "plot" : "After rescuing Han Solo from the palace of Jabba the Hutt, the rebels attempt to destroy the second Death Star, while Luke struggles to make Vader return from the dark side of the Force.", "genres" : ["Action", "Adventure", "Fantasy"], "title" : "Star Wars: Episode VI - Return of the Jedi", "year" : 1983, "score" : 0.77849960327148438 } 7 { "plot" : "Two Jedi Knights escape a hostile blockade to find allies and come across a young boy who may bring balance to the Force, but the long dormant Sith resurface to reclaim their old glory.", "genres" : ["Action", "Adventure", "Fantasy"], "title" : "Star Wars: Episode I - The Phantom Menace", "year" : 1999, "score" : 0.77667427062988281 } 8 { "plot" : "The army of the Marauders, led by by King Terak and the witch Charal attack the Ewoks village. The parents and the brother of Cindel all die in this attack. Cindel and the Ewok Wicket ...", "genres" : ["Adventure", "Family", "Fantasy"], "title" : "Ewoks: The Battle for Endor", "year" : 1985, "score" : 0.76761198043823242 } 9 { "plot" : "A prince and a fellowship of companions set out to rescue his bride from a fortress of alien invaders who have arrived on their home planet.", "genres" : ["Action", "Adventure", "Fantasy"], "title" : "Krull", "year" : 1983, "score" : 0.76243734359741211 } 10 { "plot" : "An outlaw smuggler and her alien companion are recruited by the Emperor of the Galaxy to rescue his son and destroy a secret weapon by the evil Count Zarth Arn.", "genres" : ["Action", "Adventure", "Fantasy"], "title" : "Starcrash", "year" : 1978, "score" : 0.75827145576477051 }
試したいプレフィルター演算子のコードをコピーして、AtlasVectorSearchTutorial.go
ファイルに貼り付けます。
次のクエリは、$vectorSearch
パイプライン ステージを使用して、指定されたベクター埋め込みに一致する映画を検索します。クエリは、最大 100
件の最近傍を検索し、結果を 10
件のドキュメントのみに制限します。クエリは、次のアクションを実行するための $project
ステージも指定します。
_id
フィールドを除外し、結果にはtitle
、genres
、plot
、およびyear
フィールドのみが含まれます。結果内の各ドキュメントのベクトル検索スコアを表示する
score
という名前のフィールドを追加します。
次のクエリは、文字列 kids adventure のベクトル埋め込みを使用して、plot_embedding_voyage_3_large
フィールドを検索します。フィールドごとに複数の比較クエリ演算子を指定して、セマンティック検索を実行するドキュメントを事前にフィルタリングします。
フィルターでは、 $and
集計パイプライン演算子を使用して、次の両方の条件に一致するドキュメントを検索します。
genres
フィールドでフィルタリングして、drama
、western
、またはcrime
ジャンルではなく、action
、adventure
、またはfamily
ジャンルに含まれる映画を検索します。year
フィールドでフィルタリングして、1960
から2000
年(両端を含む)の間にリリースされた映画を検索します。
1 package main 2 3 import ( 4 "context" 5 "fmt" 6 "log" 7 8 "go.mongodb.org/mongo-driver/bson" 9 "go.mongodb.org/mongo-driver/mongo" 10 "go.mongodb.org/mongo-driver/mongo/options" 11 ) 12 13 func main() { 14 ctx := context.Background() 15 16 // Replace the placeholder with your Atlas connection string 17 const uri = "<connection-string>" 18 19 // Connect to your Atlas cluster 20 clientOptions := options.Client().ApplyURI(uri) 21 client, err := mongo.Connect(ctx, clientOptions) 22 if err != nil { 23 log.Fatalf("failed to connect to the server: %v", err) 24 } 25 defer func() { _ = client.Disconnect(ctx) }() 26 27 // Set the namespace 28 coll := client.Database("sample_mflix").Collection("embedded_movies") 29 30 queryVector := [2048]float64{ 31 -0.021090532, -0.026399033, -0.024103465, -0.025538195, -0.000549233, 0.011836523, -0.013199517, -0.003766167, -0.005165028, -0.02238179, 0.037876874, 0.010617003, 0.010903949, -0.001354026, 0.006850836, -0.018005863, -0.02195137, 0.019512329, -0.041894119, -0.008357302, 0.027546817, -0.025251249, 0.004340059, -0.02195137, -0.003748232, -0.006205208, 0.021377478, 0.008931194, -0.00173961, -0.009827901, -0.016642869, -0.033572685, -0.026399033, 0.015208139, 0.010114847, -0.0233861, -0.011406104, -0.033142265, -0.008895326, -0.014347301, -0.019081909, -0.049067769, 0.034433521, -0.023673046, 0.004160717, -0.01334299, -0.06714537, 0.032568373, -0.022525262, -0.024677357, 0.011334368, 0.027403345, 0.026399033, -0.016786342, -0.015925504, 0.013916882, -0.005487842, -0.0233861, 0.026542507, -0.052798066, -0.025681669, -0.025394723, 0.014203828, 0.014921193, -0.031564061, 0.010760476, 0.010688739, 0.013916882, -0.037876874, 0.039598551, -0.000816003, 0.003766167, -0.001694775, 0.026972925, -0.009469219, 0.015351612, -0.007245387, 0.028981548, -0.035724778, 0.010688739, 0.001228488, 0.004106915, -0.024677357, 0.028551128, -0.033716157, -0.013486463, 0.018292809, -0.018221073, 0.009612692, -0.003622693, -0.001138817, -0.021234006, -0.045624416, 0.020803586, 0.007675806, -0.009612692, -0.021664424, -0.026685979, -0.025968615, 0.001775478, -0.007496465, 0.02051664, -0.054519743, 0.018221073, 0.014132091, -0.009684428, -0.025825141, -0.014921193, -0.057389203, -0.020660114, -0.028264182, -0.008931194, -0.019942747, -0.003228143, -0.014419037, 0.021234006, -0.004573202, 0.007317123, 0.018651491, -0.016571132, -0.036155198, -0.032855317, 0.000726332, -0.031851009, 0.018938437, 0.021234006, -0.048206929, 0.017934127, -0.013414727, -0.009469219, 0.064849801, 0.006348681, -0.039024659, 0.021377478, -0.022668736, -0.026829453, -0.019081909, 0.027977237, -0.004627005, -0.038450766, 0.004465597, -0.041894119, 0.008213829, 0.03055975, 0.052224174, -0.00277979, -0.032137953, -0.013629936, 0.022094844, -0.005918262, 0.020660114, 0.010617003, -0.020373167, -0.001614071, 0.021090532, -0.005523711, 0.004878082, -0.021090532, 0.029698912, 0.000726332, 0.003371616, -0.022238316, 0.008715985, 0.038737711, 0.013486463, -0.008536644, 0.040172443, 0.017503707, -0.028838074, 0.061693393, -0.003066736, 0.008285566, -0.034576993, 0.01578203, -0.02238179, 0.015925504, 0.066571474, -0.038737711, -0.050215553, 0.009325746, -0.010903949, -0.041607171, -0.006384549, 0.026972925, -0.000119374, -0.003066736, -0.024103465, 0.005093292, 0.028981548, 0.026829453, -0.001703742, 0.043041904, 0.010186584, 0.010688739, 0.004357993, -0.016571132, -0.010545266, -0.033142265, -0.005559579, -0.000365408, -0.00717365, 0.019655801, 0.047633037, 0.044476632, 0.01456251, -0.002977065, 0.025681669, -0.015423348, -0.02051664, -0.019512329, 0.014705983, 0.002977065, 0.03055975, -0.014347301, 0.024390411, 0.005882393, -0.012195205, 0.004071047, -0.028694602, 0.031277116, -0.010114847, 0.005272633, 0.017934127, 0.037589926, -0.046198308, -0.02195137, -0.037876874, 0.021234006, -0.034720469, -0.018005863, 0.03055975, -0.015495085, -0.035150886, 0.004178651, 0.005882393, 0.075753748, 0.00595413, -0.083214343, -0.016284186, 0.022238316, -0.032998793, -0.00491395, -0.009254009, -0.007819279, 0.046198308, -0.008464907, 0.014634247, 0.031707536, -0.00317434, -0.026255561, -0.010617003, -0.033285737, 0.020086221, -0.016858079, -0.012195205, -0.041894119, 0.000721849, 0.038163818, 0.02238179, 0.011406104, 0.010330057, 0.032137953, -0.01047353, 0.039311603, -0.01291257, -0.03099017, -0.018938437, -0.013271254, -0.001820314, -0.005380238, 0.003299879, -0.024533885, -0.001093982, 0.012123469, -0.005236765, 0.014132091, -0.018221073, 0.013629936, 0.022238316, -0.00317434, 0.034003101, 0.019081909, 0.008034488, -0.02912502, 0.026542507, -0.011334368, -0.077475421, 0.038163818, -0.003568891, 0.019081909, 0.019512329, 0.002385239, -0.032568373, -0.020373167, 0.038737711, -0.013773409, 0.01621245, -0.028407656, -0.021090532, -0.004411795, -0.013916882, -0.001533368, 0.004322124, -0.024820831, 0.004627005, -0.004591136, 0.014849456, -0.014275564, -0.020229694, 0.0233861, 0.015566821, 0.022525262, -0.024390411, -0.028694602, 0.001766511, -0.036011726, 0.006456285, -0.011262631, 0.005523711, 0.012266942, -0.019225383, -0.015423348, 0.011836523, -0.011334368, -0.009827901, -0.011119158, 0.007030177, 0.00277979, 0.004537334, -0.016571132, 0.013127781, -0.013701673, -0.016571132, 0.002941197, 0.000959476, -0.004483532, 0.010760476, 0.043041904, -0.032568373, -0.015423348, 0.006169339, -0.02094706, -0.050215553, 0.012769097, 0.015495085, 0.001318158, 0.00164994, -0.045337472, 0.001533368, 0.005595447, 0.039311603, -0.030703224, 0.023242628, -0.008787721, -0.021234006, -0.021234006, -0.001524401, 0.007281255, 0.01334299, 0.00164994, -0.005451974, -0.011047422, -0.021234006, -0.033572685, -0.015423348, -0.005236765, 0.025681669, -0.02051664, -0.024103465, -0.021377478, -0.00738886, -0.031707536, 0.017790653, -0.026829453, 0.007783411, -0.003335747, 0.024677357, 0.006384549, 0.035724778, -0.004017244, -0.018651491, -0.014060355, -0.029842386, -0.012553888, 0.006994309, -0.00317434, 0.018292809, 0.019942747, -0.01169305, 0.002456975, 0.010330057, -0.031707536, 0.00799862, -0.019655801, -0.006205208, -0.012769097, -0.035294361, 0.026112087, -0.004483532, 0.02094706, 0.019081909, 0.001676841, -0.040746335, -0.004035179, -0.014992929, 0.004375927, -0.049928606, -0.02051664, 0.004268322, 0.015351612, -0.037016038, -0.001452664, -0.021234006, -0.005738921, -0.051650282, -0.008285566, 0.012840834, -0.015925504, 0.018794963, -0.001228488, -0.035868254, -0.00347922, -0.003264011, 0.002528712, 0.01477772, -0.010545266, 0.018221073, 0.018149335, -0.028838074, -0.012984307, -0.037302982, -0.041607171, -0.043328848, -0.019799275, -0.019225383, -0.011047422, 0.011908259, 0.021664424, -0.012553888, 0.004662873, 0.005451974, -0.024533885, 0.0067791, 0.022812208, -0.037589926, -0.031564061, 0.007101914, -0.00760407, -0.025107777, 0.015566821, 0.020803586, -0.033572685, 0.062841177, 0.034146577, -0.007532333, -0.001865149, -0.023673046, 0.032424901, 0.018508019, -0.005703052, -0.015853768, 0.019655801, 0.042181063, 0.006671495, -0.004573202, 0.024390411, 0.009756165, -0.00029143, 0.000107605, 0.032711845, -0.005523711, -0.015566821, 0.009110536, 0.017216761, 0.006241076, -0.003945508, 0.007783411, 0.024246939, 0.048206929, 0.00277979, -0.002367305, -0.05107639, -0.016284186, -0.016929815, 0.016858079, 0.000703914, -0.021234006, 0.021234006, -0.014634247, 0.001389895, 0.008321434, -0.016499396, 0.014921193, 0.025394723, 0.035437834, 0.013486463, -0.022668736, -0.012338678, -0.034003101, -0.005559579, -0.008106225, 0.023959992, -0.019368855, 0.024533885, -0.000600793, 0.009756165, -0.001936886, -0.014490774, 0.018077599, 0.004447663, 0.011262631, -0.003658562, 0.043328848, -0.018938437, 0.00799862, -0.018221073, 0.041320227, 0.000363166, -0.003730298, 0.002851526, -0.024103465, 0.003515089, -0.0135582, -0.003497155, -0.006814968, 0.014060355, 0.027116399, -0.003192274, 0.011406104, 0.042468011, -0.036442146, -0.007245387, 0.032424901, -0.038737711, 0.008680117, -0.035581306, 0.027546817, 0.021664424, -0.000757717, -0.022238316, 0.018221073, -0.006205208, 0.005093292, 0.001264356, -0.002116227, 0.001098465, 0.017431971, -0.042181063, 0.010760476, 0.033285737, 0.002708053, -0.007352991, -0.009827901, -0.031994481, -0.020803586, 0.009971374, -0.014849456, -0.003658562, 0.024964303, -0.001793413, 0.021090532, 0.01578203, 0.012984307, 0.006922573, -0.032711845, -0.013701673, 0.00390964, 0.017503707, -0.015351612, 0.006922573, 0.028694602, 0.012266942, -0.027259871, 0.007675806, -0.002295568, -0.020086221, 0.00595413, -0.027833764, 0.001551302, 0.008644248, -0.002187963, 0.00040576, 0.024964303, 0.013916882, -0.015925504, 0.014347301, -0.011549577, 0.018938437, -0.032424901, 0.003730298, 0.003281945, 0.032998793, 0.005595447, 0.025681669, 0.011047422, 0.026399033, 0.02912502, -0.006241076, 0.004627005, 0.024390411, 0.001542335, -0.034576993, 0.011477841, -0.00491395, -0.014347301, 0.023529572, -0.004770477, -0.014921193, -0.028264182, 0.02812071, 0.00164994, 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-0.018651491, -0.049067769, 0.033429209, -0.002089326, -0.033716157, -0.000932575, -0.001080531, 0.036155198, -0.004106915, 0.005272633, -0.02195137, -0.010043111, -0.027403345, -0.035868254, 0.006814968, 0.039598551, 0.037302982, -0.041320227, -0.025394723, -0.025394723, -0.000699431, 0.003604759, 0.016355922, -0.00799862, -0.006994309, 0.035150886, 0.020229694, -0.007747543, 0.017647181, 0.026399033, -0.030416278, -0.011908259, 0.026542507, -0.012195205, 0.034146577, -0.006169339, -0.008859458, 0.0045194, 0.019799275, -0.031277116, -0.022812208, 0.007066045, 0.039885495, 0.001264356, -0.026542507, -0.016355922, 0.002214865, -0.018938437, -0.02955544, -0.008070357, -0.006420417, -0.001389895, 0.002241766, -0.018292809, 0.016355922, -0.002134161, 0.037302982, 0.00180238, -0.013199517, -0.020086221, -0.011621314, 0.021377478, -0.005272633, -0.02195137, -0.017216761, 0.037876874, 0.033142265, 0.041607171, -0.011477841, 0.031133642, -0.045050524, -0.003981376, -0.025394723, -0.031707536, 0.024533885, 0.032568373, 0.028694602, -0.021090532, -0.019942747, 0.054806691, -0.004483532, -0.020086221, -0.01599724, 0.018651491, 0.020373167, 0.000504397, -0.007424728, -0.063702017, -0.014203828, 0.030846696, -0.006599758, -0.027259871, -0.024103465, -0.020660114, -0.004985687, 0.005559579, -0.034146577, -0.011549577, -0.00173961, 0.008321434, 0.007030177, -0.015638558, 32 } 33 34 genresFilterCondition := bson.D{ 35 {"$and", bson.A{ 36 bson.D{{"genres", bson.D{{"$nin", bson.A{"Drama", "Western", "Crime"}}}}}, 37 bson.D{{"genres", bson.D{{"$in", bson.A{"Action", "Adventure", "Family"}}}}}, 38 }}} 39 40 yearFilterCondition := bson.D{ 41 {"$and", bson.A{ 42 bson.D{{"year", bson.D{{"$gte", 1960}}}}, 43 bson.D{{"year", bson.D{{"$lte", 2000}}}}, 44 }}, 45 } 46 47 filter := bson.D{{"$and", bson.A{ 48 genresFilterCondition, yearFilterCondition, 49 }}, 50 } 51 52 vectorSearchStage := bson.D{ 53 {"$vectorSearch", bson.D{ 54 {"index", "vector_index"}, 55 {"path", "plot_embedding_voyage_3_large"}, 56 {"filter", filter}, 57 {"queryVector", queryVector}, 58 {"numCandidates", 200}, 59 {"limit", 10}, 60 }}, 61 } 62 63 projectStage := bson.D{ 64 {"$project", bson.D{ 65 {"_id", 0}, 66 {"plot", 1}, 67 {"title", 1}, 68 {"genres", 1}, 69 {"year", 1}, 70 {"score", bson.D{{"$meta", "vectorSearchScore"}}}, 71 }}} 72 73 cursor, err := coll.Aggregate(ctx, mongo.Pipeline{vectorSearchStage, projectStage}) 74 if err != nil { 75 log.Fatalf("failed to retrieve data from the server: %v", err) 76 } 77 // display the results 78 type ProjectedMovieResult struct { 79 Title string `bson:"title"` 80 Plot string `bson:"plot"` 81 Genres []string `bson:"genres"` 82 Year int32 `bson:"year"` 83 Score float64 `bson:"score"` 84 } 85 86 var results []ProjectedMovieResult 87 if err = cursor.All(ctx, &results); err != nil { 88 log.Fatalf("failed to unmarshal results to ProjectedMovieResult objects: %v", err) 89 } 90 for _, result := range results { 91 fmt.Printf("Title: %v \nPlot: %v \nGenres: %v \nYear: %v \nScore: %v \n\n", result.Title, result.Plot, result.Genres, result.Year, result.Score) 92 } 93 }
次のクエリは、ベクター埋め込みを使用して plot_embedding_voyage_3_large
フィールドで star wars という文字列を検索します。集計パイプラインと比較クエリ演算子を指定し、演算子を組み合わせてデータをフィルタリングする方法を示します。
フィルターでは、 $or
集計パイプライン演算子を使用して、次のいずれかの条件に一致する映画のドキュメントを検索します。
genres
フィールドでフィルタリングして、crime
ジャンルに該当しない映画を検索します。year
フィールドでフィルタリングして、2015
年以前にリリースされた映画を検索し、genres
フィールドでフィルタリングしてaction
ジャンルの映画を検索します。
1 package main 2 3 import ( 4 "context" 5 "fmt" 6 "log" 7 8 "go.mongodb.org/mongo-driver/bson" 9 "go.mongodb.org/mongo-driver/mongo" 10 "go.mongodb.org/mongo-driver/mongo/options" 11 ) 12 13 func main() { 14 ctx := context.Background() 15 16 // Replace the placeholder with your Atlas connection string 17 const uri = "<connection-string>" 18 19 // Connect to your Atlas cluster 20 clientOptions := options.Client().ApplyURI(uri) 21 client, err := mongo.Connect(ctx, clientOptions) 22 if err != nil { 23 log.Fatalf("failed to connect to the server: %v", err) 24 } 25 defer func() { _ = client.Disconnect(ctx) }() 26 27 // Set the namespace 28 coll := client.Database("sample_mflix").Collection("embedded_movies") 29 30 queryVector := [2048]float64{ 31 -0.025189938, 0.014741838, -0.013024342, -0.0197512, 0.011235285, 0.004651551, 0.043509893, 0.003112961, 0.013310592, -0.033348043, 0.037212405, -0.021039322, -0.026048684, 0.012809656, 0.029483676, 0.003578116, -0.044654887, 0.032632418, 0.014312465, -0.058967352, 0.025333062, -0.055246111, 0.02189807, -0.017604331, -0.002880384, 0.045227386, 0.004794675, 0.017604331, 0.023186192, -0.054673612, -0.011306847, -0.012523406, -0.012380281, 0.002540462, 0.015958399, -0.042364895, -0.001467028, -0.020180576, -0.058108605, -0.035065539, 0.010090288, -0.033348043, 0.058394853, -0.013883091, 0.002048471, -0.020753073, -0.029769925, 0.031916797, -0.014741838, -0.040933646, -0.004096943, 0.020753073, -0.002540462, 0.028052431, -0.02404494, 0.006547953, -0.003578116, 0.003757022, 0.019178702, -0.037784904, -0.02833868, 0.01753277, 0.029769925, 0.017747456, -0.031344298, 0.022899942, 0.006333265, 0.010376536, -0.024474313, -0.012094032, -0.004651551, 0.007764512, 0.017962143, 0.013811528, 0.037212405, -0.03148742, 0.000666424, 0.024474313, -0.021325571, 0.041219898, 0.011235285, 0.046658635, 0.019035578, 0.020753073, 0.010662786, -0.001726441, -0.012738093, -0.027193682, -0.014598713, -0.013167467, 0.013596841, 0.001932183, 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-0.031916797, -0.0301993, 0.032203045, -0.003757022, 0.017174957, 0.033491168, 0.003900147, 0.002325775, 0.006726858, 0.020180576, 0.017389644, 0.009088415, 0.018319955, -0.003631788, 0.00586811, -0.006691077, -0.014240902, -0.009052633, 0.031630546, 0.04436864, -0.022899942, -0.003327648, -0.006691077, 0.013310592, -0.035924286, -0.008158104, -0.005116706, -0.040647399, 0.002397338, 0.014455589, -0.030342424, 0.028624929, -0.031773672, 0.043509893, -0.001833785, -0.025619311, 0.032775544, -0.046944883, 0.013739966, -0.030485548, 0.018319955, 0.016745584, -0.020323699, -0.015815273, -0.020896198, -0.015171212, 0.026334934, 0.035638034, 0.008873728, 0.003291867, -0.02647806, 0.003649678, 0.003613897, 0.009804038, -0.013525278, 0.005367174, 0.007657168, -0.017103394, -0.015815273, -0.000398065, 0.013310592, 0.014240902, 0.003935928, 0.001735386, -0.018606203, 0.008265448, -0.068127327, 0.012165595, -0.007836075, 0.02189807, -0.000983982, 0.019178702, -0.009589351, -0.013739966, -0.007800293, 0.040361151, 0.027623056, -0.002540462, -0.03663991, 0.011163722, -0.016316209, -0.006333265, -0.010877473, -0.023329318, -0.021468697, 0.013596841, 0.032059919, 0.007442481, 0.02433119, -0.003613897, -0.013596841, 0.010448099, 0.010877473, -0.0098756, 0.033920541, -0.006691077, -0.039502401, -0.010877473, -0.016960271, 0.014097777, -0.008122323, 0.007478263, 0.010018725, -0.030485548, -0.011020597, 0.000317558, 0.00461577, 0.020466823, 0.070703574, -0.024617439, 0.002111088, -0.024617439, -0.004204286, -0.048662379, -0.006834202, 0.027766181, -0.002504681, 0.025189938, 0.033920541, -0.02833868, -0.000773768, -0.03578116, 0.015958399, 0.006369046, 0.033204917, -0.006762639, 0.02003745, -0.020180576, 0.015886836, -0.015385899, -0.029340552, -0.009446226, 0.015529023, -0.010376536, -0.012881218, -0.000715623, 0.014312465, -0.029197427, -0.000684315, 0.000360048, 0.015815273, -0.027050557, 0.006655296, 0.018892452, -0.021182448, 0.031201173, 0.014240902, -0.022756819, 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-0.021039322, 0.008086543, -0.009088415, -0.031630546, 0.020896198, -0.018749328, 0.022613693, -0.014097777, 0.004347411, 0.014813401, -0.013525278, -0.001726441, 0.010448099, 0.036067411, -0.026048684, -0.020753073, -0.005045144, 0.033348043, -0.002576244, 0.02404494, 0.022041194, 0.017031832, -0.000297431, -0.003184523, -0.012738093, 0.022756819, -0.016888708, 0.021039322, -0.000313085, 0.032203045, -0.011235285, 0.001583316, -0.00461577, -0.026334934, -0.002934055, -0.005939673, 0.001458082, 0.007156232, -0.005689205, -0.042937394, 0.011378409, 0.007156232, 0.00554608, 0.026621183, -0.014455589, -0.017604331, -0.02647806, -0.03578116, -0.009804038, 0.006905764, -0.0197512, -0.035494912, -0.027623056, -0.00461577, 0.011521534, 0.006905764, 0.009517789, 0.003112961, 0.033920541, -0.004687332, -0.005045144, -0.009231539, 0.000126911, 0.008694822, -0.029340552, 0.011163722, 0.047517382, -0.039788652, -0.033348043, -0.003041399, -0.007657168, -0.035065539, -0.012165595, -0.024617439, 0.0049378, 0.017461207, 0.029626802, -0.004723113, -0.000366757, -0.041792396, 0.041219898, -0.009446226, 0.016960271, -0.017747456, -0.036067411, 0.025046812, 0.027336806, 0.025905561, 0.049234878, 0.016602458, -0.005796548, 0.021325571, -0.003524444, -0.000872166, 0.014670276, 0.020323699, 0.002737259, 0.009660914, -0.006440609, -0.062402345, -0.062688597, -0.008158104, -0.018749328, 0.005438737, -0.002066362, 0.000205742, -0.018749328, 0.017103394, -0.03578116, 0.000265004, -0.03663991, -0.024760563, 0.054101113, -0.00647639, -0.026334934, 0.034779288, 0.022756819, -0.033348043, -0.02433119, -0.041792396, -0.014455589, -0.023329318, -0.004687332, -0.013453716, -0.018319955, -0.014455589, 0.043509893, 0.013453716, -0.014813401, 0.009052633, -0.034349915, 0.052097369, -0.003774913, 0.016316209, -0.027050557, 0.028195554, -0.007549825, -0.020466823, 0.014598713, -0.005939673, 0.003273976, -0.052097369, 0.002701478, -0.02404494, -0.005903892, 0.009947163, -0.00043161, 0.02189807, 0.042078644, -0.020609949, 0.007836075, 0.018892452, 0.001207614, 0.009159978, -0.029197427, -0.023329318, 0.004347411, -0.019464951, 0.020180576, 0.019894326, 0.00615436, 0.021468697, -0.017461207, -0.011879345, -0.002307885, 0.016101522, -0.029626802, -0.014455589, 0.020323699, 0.020753073, 0.018176829, -0.006082797, 0.027766181, 0.016530896, -0.008444354, 0.001806949, 0.029626802, -0.012451844, 0.023186192, 0.006869983, -0.034063663, -0.012094032, -0.021611821, -0.008050761, 0.05581861, -0.004257958, -0.025333062, -0.004526317, 0.018033706, 0.027479932, 0.025476186, 0.008802165, -0.009589351, 0.012809656, 0.012523406, 0.0400749, 0.018033706, 0.011020597, 0.014956526, 0.013883091, -0.006655296, 0.019608077, -0.03234617, 0.007585606, -0.036067411, -0.024617439, -0.001628043, 0.022041194, 0.026764309, -0.038643654, -0.009124196, -0.020323699, -0.013883091, 0.02404494, 0.002361557, -0.03234617, -0.0049378, 0.018606203, 0.022327444, 0.043509893, -0.030485548, -0.003560225, 0.007442481, 0.00370335, 0.011449971, 0.023472441, 0.000197915, -0.011950907, 0.023329318, -0.009804038, -0.025619311, 0.0074067, -0.003953818, 0.014312465, 0.048662379, -0.027193682, 0.019894326, -0.042364895, 0.003327648, 0.042937394, -0.040933646, -0.020466823, 0.056104861, 0.020896198, -0.014527151, -0.036210533, -0.022470569, 0.035924286, -0.013167467, -0.055532362, -0.006190141, -0.027909305, 0.012881218, 0.003005618, 0.005689205, 0.01109216, -0.016387772, -0.021468697, 0.018176829, -0.021611821, 0.032918669, 0.002951946, -0.008837947, -0.031773672, -0.029913051, 0.017318081, 0.017461207, -0.02833868, -0.027479932, -0.023615567, 0.037212405, -0.023615567, -0.02404494, 0.029626802, 0.002951946, 0.004043271, -0.001377575, 0.007800293, 0.024188064, -0.027336806, -0.002361557, -0.00307718, -0.025189938, 0.007192013, -0.000207978, 0.040933646, 0.010877473, -0.000720096, -0.006941545, 0.003059289, 0.032775544, -0.007657168, 0.019321827, -0.012094032, 0.042078644, -0.010591224, 0.011807784, -0.016173085, -0.015529023, -0.023615567, 0.016173085, -0.018606203, 0.007192013, -0.008587479, 0.000257177, 0.002245268, -0.011879345, 0.044082388, -0.005939673, -0.003059289, -0.013954652, -0.026621183, 0.039502401, -0.006440609, 0.014384027, 0.012094032, -0.034779288, -0.002379447, 0.023329318, 0.029483676, -0.002325775, -0.001565426, 0.025619311, 0.018606203, -0.016101522, -0.0301993, 0.002576244, 0.035208661, 0.002325775, -0.011664659, -0.022470569, -0.047231134, -0.016888708, -0.017747456, 0.05152487, 0.009374664, -0.010591224, 0.009303101, -0.005009362, -0.029197427, 0.001726441, -0.023758691, -0.002934055, -0.017461207, 0.018606203, -0.002665696, -0.003578116, -0.018606203, -0.004651551, -0.021325571, 0.005367174, -0.009124196, 0.016888708, -0.01295278, 0.002048471, -0.011593096, 0.017604331, -0.008515916, 0.006082797, -0.036067411, -0.027336806, -0.010018725, -0.001306012, 0.026334934, -0.019321827, -0.030914923, -0.026764309, -0.0024689, -0.005581861, -0.002755149, 0.019464951, -0.01295278, 0.011163722, 0.000639588, 0.025476186, 0.029483676, 0.042651143, -0.011306847, 0.002737259, 0.010090288, -0.015600586, 0.038357403, 0.029197427, -0.008193886, 0.044082388, 0.032489292, -0.00123445, -0.008372792, 0.009124196, -0.00309507, -0.041792396, 0.007764512, -0.009947163, 0.044941138, 0.030056175, -0.013024342, -0.019321827, 0.019321827, 0.008551697, -0.053814866, 0.038071156, -0.037784904, 0.012165595, -0.008444354, -0.029626802, -0.006905764, -0.028195554, -0.01080591, -0.0098756, -0.032203045, 0.040361151, -0.033920541, 0.004454754, -0.036067411, 0.011879345, -0.011235285, 0.020609949, -0.004579989, 0.0074067, -0.017103394, 0.01789058, 0.011449971, -0.007836075, 0.000427138, -0.007120451, 0.008337011, 0.00123445, -0.003273976, -0.007263576, -0.011449971, 0.022756819, 0.002576244, -0.013310592, -0.013382155, -0.011664659, -0.013453716, -0.005152487, -0.050379876, -0.034636162, -0.011306847, 0.015028087, 0.008480135, -0.047517382, -0.00586811, -0.008301229, -0.01416934, 0.000876638, 0.000326503, 0.01080591, 0.004150615, 0.005259831, -0.008837947, 0.017031832, -0.016316209, -0.036210533, -0.013883091, -0.000295195, 0.014240902, 0.020753073, -0.022899942, -0.038929902, 0.00586811, -0.008050761, 0.00016437, -0.001932183, 0.001789058, 0.017031832, 0.045227386, -0.016745584, -0.005689205, 0.008372792, 0.008301229, -0.016674021, -0.004222177, 0.005832329, 0.016173085, -0.009374664, -0.006869983, -0.052669868, 0.035065539, 0.000123557, 0.007478263, 0.033491168, 0.054387365, 0.002254213, -0.007836075, -0.020323699, -0.019178702, -0.010376536, -0.039788652, -0.032632418, -0.012380281, -0.002540462, -0.016602458, -0.022756819, 0.019608077, 0.001887456, 0.032918669, 0.008050761, -0.013739966, 0.006547953, -0.016674021, 0.001574371, 0.019321827, -0.016960271, -0.031201173, 0.027766181, 0.006655296, 0.020753073, 0.009804038, 0.024903689, -0.043509893, 0.015815273, -0.017962143, -0.043223642, 0.033920541, -0.007764512, -0.006762639, 0.017819017, -0.026621183, 0.046658635, -0.004490536, 0.024188064, -0.010304974, 0.004651551, 0.047231134, -0.038071156, 0.009589351, -0.033920541, -0.027050557, 0.050093625, 0.008515916, -0.025189938, -0.008050761, 0.011950907, 0.004973582, 0.014527151, -0.009374664, -0.003721241, 0.019608077, 0.049807377, 0.016602458, 0.02404494, 32 } 33 34 genresFilterCondition := bson.D{{"genres", bson.D{{"$ne", "Crime"}}}} 35 36 yearAndGenresFilterCondition := bson.D{ 37 {"$and", bson.A{ 38 bson.D{{"year", bson.D{{"$lte", 2015}}}}, 39 bson.D{{"genres", bson.D{{"$eq", "Action"}}}}, 40 }}, 41 } 42 43 filter := bson.D{{"$or", bson.A{ 44 genresFilterCondition, yearAndGenresFilterCondition, 45 }}, 46 } 47 48 vectorSearchStage := bson.D{ 49 {"$vectorSearch", bson.D{ 50 {"index", "vector_index"}, 51 {"path", "plot_embedding_voyage_3_large"}, 52 {"filter", filter}, 53 {"queryVector", queryVector}, 54 {"numCandidates", 200}, 55 {"limit", 10}, 56 }}, 57 } 58 59 projectStage := bson.D{ 60 {"$project", bson.D{ 61 {"_id", 0}, 62 {"plot", 1}, 63 {"title", 1}, 64 {"genres", 1}, 65 {"year", 1}, 66 {"score", bson.D{{"$meta", "vectorSearchScore"}}}, 67 }}} 68 69 cursor, err := coll.Aggregate(ctx, mongo.Pipeline{vectorSearchStage, projectStage}) 70 if err != nil { 71 log.Fatalf("failed to retrieve data from the server: %v", err) 72 } 73 // display the results 74 type ProjectedMovieResult struct { 75 Title string `bson:"title"` 76 Plot string `bson:"plot"` 77 Genres []string `bson:"genres"` 78 Year int32 `bson:"year"` 79 Score float64 `bson:"score"` 80 } 81 82 var results []ProjectedMovieResult 83 if err = cursor.All(ctx, &results); err != nil { 84 log.Fatalf("failed to unmarshal results to ProjectedMovieResult objects: %v", err) 85 } 86 for _, result := range results { 87 fmt.Printf("Title: %v \nPlot: %v \nGenres: %v \nYear: %v \nScore: %v \n\n", result.Title, result.Plot, result.Genres, result.Year, result.Score) 88 } 89 }
クエリ内の <connection-string>
を置き換え、ファイルを保存します。
<connection-string>
を Atlas クラスターまたはローカル Atlas 配置の接続文字列に置き換えます。
接続stringには、次の形式を使用する必要があります。
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
詳しくは、ドライバーを使用してクラスターに接続する を参照してください。
接続stringには、次の形式を使用する必要があります。
mongodb://localhost:<port-number>/?directConnection=true
詳細については、「接続文字列 」を参照してください。
AtlasVectorSearchTutorial.go
ファイルをコンパイルして実行します。
go run AtlasVectorSearchTutorial.go
1 Title: 3 Ninjas: High Noon at Mega Mountain 2 Plot: Three young boys, Rocky, Colt and Tum Tum together with their neighbor girl, computer whiz Amanda are visiting Mega Mountain amusement park when it is invaded by an army of ninjas led by ... 3 Genres: [Action Adventure Comedy] 4 Year: 1998 5 Score: 0.7746343612670898 6 7 Title: White Wolves: A Cry in the Wild II 8 Plot: A two-week trek through the Cascade Mountains tries the survival instincts of five adventurous teenagers. At first, it's all a good time. Shooting the rapids, exploring caves and making new... 9 Genres: [Action Adventure Family] 10 Year: 1993 11 Score: 0.770106315612793 12 13 Title: Space Raiders 14 Plot: A futuristic, sensitive tale of adventure and confrontation when a 10 year old boy is accidentally kidnapped by a spaceship filled with a motley crew of space pirates. 15 Genres: [Action Adventure Sci-Fi] 16 Year: 1983 17 Score: 0.7569591999053955 18 19 Title: The Ewok Adventure 20 Plot: Wicket the Ewok and his friends agree to help two shipwrecked human children on a quest to find their parents. 21 Genres: [Adventure Family Fantasy] 22 Year: 1984 23 Score: 0.7515435218811035 24 25 Title: Time Bandits 26 Plot: A young boy accidentally joins a band of dwarves as they jump from era to era looking for treasure to steal. 27 Genres: [Adventure Comedy Fantasy] 28 Year: 1981 29 Score: 0.7513599395751953 30 31 Title: Chitty Chitty Bang Bang 32 Plot: A down-on-his-luck inventor turns a broken-down Grand Prix car into a fancy vehicle for his children, and then they go off on a magical fantasy adventure to save their grandfather in a far-off land. 33 Genres: [Adventure Family Fantasy] 34 Year: 1968 35 Score: 0.7492260932922363 36 37 Title: Forest Warrior 38 Plot: A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks. 39 Genres: [Action Adventure Comedy] 40 Year: 1996 41 Score: 0.7473714351654053 42 43 Title: Forest Warrior 44 Plot: A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks. 45 Genres: [Action Adventure Comedy] 46 Year: 1996 47 Score: 0.7473714351654053 48 49 Title: Warriors of Virtue 50 Plot: A young boy is whisked away to the mythical land of Tao where he becomes the center of a conflict between an evil lord and a group of animal warriors. 51 Genres: [Action Fantasy Adventure] 52 Year: 1997 53 Score: 0.7464213371276855 54 55 Title: Taxandria 56 Plot: A young prince is taken for tuition at a seaside hotel but there quickly bores and wanders off to visit a nearby lighthouse. Befriended by the keeper, he learns of a secret world he can see... 57 Genres: [Animation Adventure Fantasy] 58 Year: 1994 59 Score: 0.7453246116638184
go run AtlasVectorSearchTutorial.go
1 Title: Star Wars: Episode IV - A New Hope 2 Plot: Luke Skywalker joins forces with a Jedi Knight, a cocky pilot, a wookiee and two droids to save the universe from the Empire's world-destroying battle-station, while also attempting to rescue Princess Leia from the evil Darth Vader. 3 Genres: [Action Adventure Fantasy] 4 Year: 1977 5 Score: 0.79868483543396 6 7 Title: Dune 8 Plot: A Duke's son leads desert warriors against the galactic emperor and his father's evil nemesis when they assassinate his father and free their desert world from the emperor's rule. 9 Genres: [Action Adventure Sci-Fi] 10 Year: 1984 11 Score: 0.7949700355529785 12 13 Title: Message from Space 14 Plot: In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ... 15 Genres: [Action Adventure Sci-Fi] 16 Year: 1978 17 Score: 0.7913978099822998 18 19 Title: Message from Space 20 Plot: In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ... 21 Genres: [Action Adventure Sci-Fi] 22 Year: 1978 23 Score: 0.7913978099822998 24 25 Title: Star Wars: Episode V - The Empire Strikes Back 26 Plot: After the rebels have been brutally overpowered by the Empire on their newly established base, Luke Skywalker takes advanced Jedi training with Master Yoda, while his friends are pursued by Darth Vader as part of his plan to capture Luke. 27 Genres: [Action Adventure Fantasy] 28 Year: 1980 29 Score: 0.7809884548187256 30 31 Title: Star Wars: Episode VI - Return of the Jedi 32 Plot: After rescuing Han Solo from the palace of Jabba the Hutt, the rebels attempt to destroy the second Death Star, while Luke struggles to make Vader return from the dark side of the Force. 33 Genres: [Action Adventure Fantasy] 34 Year: 1983 35 Score: 0.7784996032714844 36 37 Title: Star Wars: Episode I - The Phantom Menace 38 Plot: Two Jedi Knights escape a hostile blockade to find allies and come across a young boy who may bring balance to the Force, but the long dormant Sith resurface to reclaim their old glory. 39 Genres: [Action Adventure Fantasy] 40 Year: 1999 41 Score: 0.7766742706298828 42 43 Title: Ewoks: The Battle for Endor 44 Plot: The army of the Marauders, led by by King Terak and the witch Charal attack the Ewoks village. The parents and the brother of Cindel all die in this attack. Cindel and the Ewok Wicket ... 45 Genres: [Adventure Family Fantasy] 46 Year: 1985 47 Score: 0.7676119804382324 48 49 Title: Krull 50 Plot: A prince and a fellowship of companions set out to rescue his bride from a fortress of alien invaders who have arrived on their home planet. 51 Genres: [Action Adventure Fantasy] 52 Year: 1983 53 Score: 0.7624373435974121 54 55 Title: Starcrash 56 Plot: An outlaw smuggler and her alien companion are recruited by the Emperor of the Galaxy to rescue his son and destroy a secret weapon by the evil Count Zarth Arn. 57 Genres: [Action Adventure Fantasy] 58 Year: 1978 59 Score: 0.7582714557647705
試したいプレフィルター演算子のコードをコピーして、AtlasVectorSearchTutorial.java
ファイルに貼り付けます。
次のクエリは、$vectorSearch
パイプライン ステージを使用して、指定されたベクター埋め込みに一致する映画を検索します。クエリは、最大 100
件の最近傍を検索し、結果を 10
件のドキュメントのみに制限します。クエリは、次のアクションを実行するための $project
ステージも指定します。
_id
フィールドを除外し、結果にはtitle
、genres
、plot
、およびyear
フィールドのみが含まれます。結果内の各ドキュメントのベクトル検索スコアを表示する
score
という名前のフィールドを追加します。
次のクエリは、文字列 kids adventure のベクトル埋め込みを使用して、plot_embedding_voyage_3_large
フィールドを検索します。フィールドごとに複数の比較クエリ演算子を指定して、セマンティック検索を実行するドキュメントを事前にフィルタリングします。
フィルターでは、 $and
集計パイプライン演算子を使用して、次の両方の条件に一致するドキュメントを検索します。
genres
フィールドでフィルタリングして、drama
、western
、またはcrime
ジャンルではなく、action
、adventure
、またはfamily
ジャンルに含まれる映画を検索します。year
フィールドでフィルタリングして、1960
から2000
年(両端を含む)の間にリリースされた映画を検索します。
1 import static com.mongodb.client.model.Aggregates.*; 2 import static com.mongodb.client.model.Projections.*; 3 import static com.mongodb.client.model.search.SearchPath.fieldPath; 4 import static java.util.Arrays.asList; 5 6 import com.mongodb.client.MongoClient; 7 import com.mongodb.client.MongoClients; 8 import com.mongodb.client.MongoCollection; 9 import com.mongodb.client.MongoDatabase; 10 import com.mongodb.client.model.*; 11 import com.mongodb.client.model.search.VectorSearchOptions; 12 import java.util.Arrays; 13 import java.util.List; 14 import com.mongodb.client.model.search.FieldSearchPath; 15 import org.bson.Document; 16 import org.bson.conversions.Bson; 17 18 public class AtlasVectorSearchTutorial { 19 public static void main( String[] args ) { 20 // specify connection 21 String uri = "<connection-string>"; 22 23 // establish connection and set namespace 24 try (MongoClient mongoClient = MongoClients.create(uri)) { 25 MongoDatabase database = mongoClient.getDatabase("sample_mflix"); 26 MongoCollection<Document> collection = database.getCollection("embedded_movies"); 27 28 // define $vectorSearch query options 29 List<Double> queryVector = 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30 String indexName = "vector_index"; 31 FieldSearchPath fieldSearchPath = fieldPath("plot_embedding_voyage_3_large"); 32 int numCandidates = 200; 33 int limit = 10; 34 List<String> genresNotInCriteria = Arrays.asList("Drama", "Western", "Crime"); 35 List<String> genresInCriteria = Arrays.asList("Action", "Adventure", "Family"); 36 Bson criteria = Filters.and( 37 Filters.nin("genres", genresNotInCriteria), 38 Filters.in("genres", genresInCriteria), 39 Filters.gte("year", 1960), 40 Filters.lte("year", 2000)); 41 VectorSearchOptions options = VectorSearchOptions 42 .approximateVectorSearchOptions(numCandidates) 43 .filter(criteria); 44 45 // define pipeline 46 List<Bson> pipeline = asList( 47 vectorSearch( 48 fieldSearchPath, 49 queryVector, 50 indexName, 51 limit, 52 options), 53 project( 54 fields(exclude("_id"), include("title"), include("plot"), include("year"), 55 include("genres"), metaVectorSearchScore("score")))); 56 57 // run query and print results 58 collection.aggregate(pipeline) 59 .forEach(doc -> System.out.println(doc.toJson())); 60 } 61 } 62 }
次のクエリは、ベクター埋め込みを使用して plot_embedding_voyage_3_large
フィールドで star wars という文字列を検索します。集計パイプラインと比較クエリ演算子を指定し、演算子を組み合わせてデータをフィルタリングする方法を示します。
フィルターでは、 $or
集計パイプライン演算子を使用して、次のいずれかの条件に一致する映画のドキュメントを検索します。
genres
フィールドでフィルタリングして、crime
ジャンルに該当しない映画を検索します。year
フィールドでフィルタリングして、2015
年以前にリリースされた映画を検索し、genres
フィールドでフィルタリングしてaction
ジャンルの映画を検索します。
1 import static com.mongodb.client.model.Aggregates.*; 2 import static com.mongodb.client.model.Projections.*; 3 import static com.mongodb.client.model.search.SearchPath.fieldPath; 4 import static java.util.Arrays.asList; 5 6 import com.mongodb.client.MongoClient; 7 import com.mongodb.client.MongoClients; 8 import com.mongodb.client.MongoCollection; 9 import com.mongodb.client.MongoDatabase; 10 import com.mongodb.client.model.*; 11 import com.mongodb.client.model.search.VectorSearchOptions; 12 import java.util.List; 13 import com.mongodb.client.model.search.FieldSearchPath; 14 import org.bson.Document; 15 import org.bson.conversions.Bson; 16 17 public class AtlasVectorSearchTutorial { 18 public static void main( String[] args ) { 19 // specify connection 20 String uri = "<connection-string>"; 21 22 // establish connection and set namespace 23 try (MongoClient mongoClient = MongoClients.create(uri)) { 24 MongoDatabase database = mongoClient.getDatabase("sample_mflix"); 25 MongoCollection<Document> collection = database.getCollection("embedded_movies"); 26 27 // define $vectorSearch query options 28 List<Double> queryVector = 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29 String indexName = "vector_index"; 30 FieldSearchPath fieldSearchPath = fieldPath("plot_embedding_voyage_3_large"); 31 int numCandidates = 200; 32 int limit = 10; 33 Bson criteria = Filters.or( 34 Filters.lte("year", 2015), 35 Filters.and( 36 Filters.lte("year", 2015), 37 Filters.eq("genres", "Action"))); 38 VectorSearchOptions options = VectorSearchOptions 39 .approximateVectorSearchOptions(numCandidates) 40 .filter(criteria); 41 42 // define pipeline 43 List<Bson> pipeline = asList( 44 vectorSearch( 45 fieldSearchPath, 46 queryVector, 47 indexName, 48 limit, 49 options), 50 project( 51 fields(exclude("_id"), include("title"), include("plot"), include("year"), 52 include("genres"), metaVectorSearchScore("score")))); 53 54 // run query and print results 55 collection.aggregate(pipeline) 56 .forEach(doc -> System.out.println(doc.toJson())); 57 } 58 } 59 }
クエリ内の <connection-string>
を置き換え、ファイルを保存します。
<connection-string>
を Atlas クラスターまたはローカル Atlas 配置の接続文字列に置き換えます。
接続stringには、次の形式を使用する必要があります。
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
詳しくは、ドライバーを使用してクラスターに接続する を参照してください。
接続stringには、次の形式を使用する必要があります。
mongodb://localhost:<port-number>/?directConnection=true
詳細については、「接続文字列 」を参照してください。
AtlasVectorSearchTutorial.java
ファイルをコンパイルして実行します。
javac AtlasVectorSearchTutorial.java java AtlasVectorSearchTutorial
1 { 2 "plot": 'Three young boys, Rocky, Colt and Tum Tum together with their neighbor girl, computer whiz Amanda are visiting Mega Mountain amusement park when it is invaded by an army of ninjas led by ...', 3 "genres": [ 'Action', 'Adventure', 'Comedy' ], 4 "title": '3 Ninjas: High Noon at Mega Mountain', 5 "year": 1998, 6 "score": 0.7746343612670898 7 }, 8 { 9 "plot": "A two-week trek through the Cascade Mountains tries the survival instincts of five adventurous teenagers. At first, it's all a good time. Shooting the rapids, exploring caves and making new...", 10 "genres": [ 'Action', 'Adventure', 'Family' ], 11 "title": 'White Wolves: A Cry in the Wild II', 12 "year": 1993, 13 "score": 0.770106315612793 14 }, 15 { 16 "plot": 'A futuristic, sensitive tale of adventure and confrontation when a 10 year old boy is accidentally kidnapped by a spaceship filled with a motley crew of space pirates.', 17 "genres": [ 'Action', 'Adventure', 'Sci-Fi' ], 18 "title": 'Space Raiders', 19 "year": 1983, 20 "score": 0.7569591999053955 21 }, 22 { 23 "plot": 'Wicket the Ewok and his friends agree to help two shipwrecked human children on a quest to find their parents.', 24 "genres": [ 'Adventure', 'Family', 'Fantasy' ], 25 "title": 'The Ewok Adventure', 26 "year": 1984, 27 "score": 0.7515435218811035 28 }, 29 { 30 "plot": 'A young boy accidentally joins a band of dwarves as they jump from era to era looking for treasure to steal.', 31 "genres": [ 'Adventure', 'Comedy', 'Fantasy' ], 32 "title": 'Time Bandits', 33 "year": 1981, 34 "score": 0.7513599395751953 35 }, 36 { 37 "plot": 'A down-on-his-luck inventor turns a broken-down Grand Prix car into a fancy vehicle for his children, and then they go off on a magical fantasy adventure to save their grandfather in a far-off land.', 38 "genres": [ 'Adventure', 'Family', 'Fantasy' ], 39 "title": 'Chitty Chitty Bang Bang', 40 "year": 1968, 41 "score": 0.7492260932922363 42 }, 43 { 44 "plot": 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.', 45 "genres": [ 'Action', 'Adventure', 'Comedy' ], 46 "title": 'Forest Warrior', 47 "year": 1996, 48 "score": 0.7473714351654053 49 }, 50 { 51 "plot": 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.', 52 "genres": [ 'Action', 'Adventure', 'Comedy' ], 53 "title": 'Forest Warrior', 54 "year": 1996, 55 "score": 0.7473714351654053 56 }, 57 { 58 "plot": 'A young boy is whisked away to the mythical land of Tao where he becomes the center of a conflict between an evil lord and a group of animal warriors.', 59 "genres": [ 'Action', 'Fantasy', 'Adventure' ], 60 "title": 'Warriors of Virtue', 61 "year": 1997, 62 "score": 0.7464213371276855 63 }, 64 { 65 "plot": 'A young prince is taken for tuition at a seaside hotel but there quickly bores and wanders off to visit a nearby lighthouse. Befriended by the keeper, he learns of a secret world he can see...', 66 "genres": [ 'Animation', 'Adventure', 'Fantasy' ], 67 "title": 'Taxandria', 68 "year": 1994, 69 "score": 0.7453246116638184 70 }
javac AtlasVectorSearchTutorial.java java AtlasVectorSearchTutorial
1 { 2 "plot": "Luke Skywalker joins forces with a Jedi Knight, a cocky pilot, a wookiee and two droids to save the universe from the Empire's world-destroying battle-station, while also attempting to rescue Princess Leia from the evil Darth Vader.", 3 "genres": [ 'Action', 'Adventure', 'Fantasy' ], 4 "title": 'Star Wars: Episode IV - A New Hope', 5 "released": ISODate('1977-05-25T00:00:00.000Z'), 6 "score": 0.79868483543396 7 }, 8 { 9 "plot": "A Duke's son leads desert warriors against the galactic emperor and his father's evil nemesis when they assassinate his father and free their desert world from the emperor's rule.", 10 "genres": [ 'Action', 'Adventure', 'Sci-Fi' ], 11 "title": 'Dune', 12 "released": ISODate('1984-12-14T00:00:00.000Z'), 13 "score": 0.7949700355529785 14 }, 15 { 16 "plot": 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...', 17 "genres": [ 'Action', 'Adventure', 'Sci-Fi' ], 18 "title": 'Message from Space', 19 "released": ISODate('1978-10-30T00:00:00.000Z'), 20 "score": 0.7913978099822998 21 }, 22 { 23 "plot": 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...', 24 "genres": [ 'Action', 'Adventure', 'Sci-Fi' ], 25 "title": 'Message from Space', 26 "released": ISODate('1978-10-30T00:00:00.000Z'), 27 "score": 0.7913978099822998 28 }, 29 { 30 "plot": 'After the rebels have been brutally overpowered by the Empire on their newly established base, Luke Skywalker takes advanced Jedi training with Master Yoda, while his friends are pursued by Darth Vader as part of his plan to capture Luke.', 31 "genres": [ 'Action', 'Adventure', 'Fantasy' ], 32 "title": 'Star Wars: Episode V - The Empire Strikes Back', 33 "released": ISODate('1980-06-20T00:00:00.000Z'), 34 "score": 0.7809884548187256 35 }, 36 { 37 "plot": 'After rescuing Han Solo from the palace of Jabba the Hutt, the rebels attempt to destroy the second Death Star, while Luke struggles to make Vader return from the dark side of the Force.', 38 "genres": [ 'Action', 'Adventure', 'Fantasy' ], 39 "title": 'Star Wars: Episode VI - Return of the Jedi', 40 "released": ISODate('1983-05-25T00:00:00.000Z'), 41 "score": 0.7784996032714844 42 }, 43 { 44 "plot": 'Two Jedi Knights escape a hostile blockade to find allies and come across a young boy who may bring balance to the Force, but the long dormant Sith resurface to reclaim their old glory.', 45 "genres": [ 'Action', 'Adventure', 'Fantasy' ], 46 "title": 'Star Wars: Episode I - The Phantom Menace', 47 "released": ISODate('1999-05-19T00:00:00.000Z'), 48 "score": 0.7766742706298828 49 }, 50 { 51 "plot": 'The army of the Marauders, led by by King Terak and the witch Charal attack the Ewoks village. The parents and the brother of Cindel all die in this attack. Cindel and the Ewok Wicket ...', 52 "genres": [ 'Adventure', 'Family', 'Fantasy' ], 53 "title": 'Ewoks: The Battle for Endor', 54 "released": ISODate('1985-11-24T00:00:00.000Z'), 55 "score": 0.7676119804382324 56 }, 57 { 58 "plot": 'A prince and a fellowship of companions set out to rescue his bride from a fortress of alien invaders who have arrived on their home planet.', 59 "genres": [ 'Action', 'Adventure', 'Fantasy' ], 60 "title": 'Krull', 61 "released": ISODate('1983-07-29T00:00:00.000Z'), 62 "score": 0.7624373435974121 63 }, 64 { 65 "plot": 'An outlaw smuggler and her alien companion are recruited by the Emperor of the Galaxy to rescue his son and destroy a secret weapon by the evil Count Zarth Arn.', 66 "genres": [ 'Action', 'Adventure', 'Fantasy' ], 67 "title": 'Starcrash', 68 "released": ISODate('1979-03-09T00:00:00.000Z'), 69 "score": 0.7582714557647705 70 }
試したいプレフィルター演算子のサンプルクエリをコピーして、atlas-vector-search-tutorial.js
ファイルに貼り付けます。
次のクエリは、$vectorSearch
パイプライン ステージを使用して、指定されたベクター埋め込みに一致する映画を検索します。クエリは、最大 100
件の最近傍を検索し、結果を 10
件のドキュメントのみに制限します。クエリは、次のアクションを実行するための $project
ステージも指定します。
_id
フィールドを除外し、結果にはtitle
、genres
、plot
、およびyear
フィールドのみが含まれます。結果内の各ドキュメントのベクトル検索スコアを表示する
score
という名前のフィールドを追加します。
次のクエリは、文字列 kids adventure のベクトル埋め込みを使用して、plot_embedding_voyage_3_large
フィールドを検索します。フィールドごとに複数の比較クエリ演算子を指定して、セマンティック検索を実行するドキュメントを事前にフィルタリングします。
フィルターでは、 $and
集計パイプライン演算子を使用して、次の両方の条件に一致するドキュメントを検索します。
genres
フィールドでフィルタリングして、drama
、western
、またはcrime
ジャンルではなく、action
、adventure
、またはfamily
ジャンルに含まれる映画を検索します。year
フィールドでフィルタリングして、1960
から2000
年(両端を含む)の間にリリースされた映画を検索します。
1 const { MongoClient } = require("mongodb"); 2 3 // connect to your Atlas cluster 4 const uri = "<connection-string>"; 5 6 const client = new MongoClient(uri); 7 8 async function run() { 9 try { 10 await client.connect(); 11 12 // set namespace 13 const database = client.db("sample_mflix"); 14 const coll = database.collection("embedded_movies"); 15 16 // define pipeline 17 const agg = [ 18 { 19 '$vectorSearch': { 20 'index': 'vector_index', 21 'path': 'plot_embedding_voyage_3_large', 22 'filter': { 23 '$and': [ 24 { 25 'genres': { 26 '$nin': [ 27 'Drama', 'Western', 'Crime' 28 ], 29 '$in': [ 30 'Action', 'Adventure', 'Family' 31 ] 32 } 33 }, { 34 'year': { 35 '$gte': 1960, 36 '$lte': 2000 37 } 38 } 39 ] 40 }, 41 'queryVector': 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42 'numCandidates': 200, 43 'limit': 10 44 } 45 }, { 46 '$project': { 47 '_id': 0, 48 'title': 1, 49 'genres': 1, 50 'plot': 1, 51 'year': 1, 52 'score': { 53 '$meta': 'vectorSearchScore' 54 } 55 } 56 } 57 ]; 58 59 // run pipeline 60 const result = coll.aggregate(agg); 61 62 // print results 63 await result.forEach((doc) => console.dir(JSON.stringify(doc))); 64 } finally { 65 await client.close(); 66 } 67 } 68 run().catch(console.dir);
次のクエリは、ベクター埋め込みを使用して plot_embedding_voyage_3_large
フィールドで star wars という文字列を検索します。集計パイプラインと比較クエリ演算子を指定し、演算子を組み合わせてデータをフィルタリングする方法を示します。
フィルターでは、 $or
集計パイプライン演算子を使用して、次のいずれかの条件に一致する映画のドキュメントを検索します。
genres
フィールドでフィルタリングして、crime
ジャンルに該当しない映画を検索します。year
フィールドでフィルタリングして、2015
年以前にリリースされた映画を検索し、genres
フィールドでフィルタリングしてaction
ジャンルの映画を検索します。
1 const { MongoClient } = require("mongodb"); 2 3 // connect to your Atlas cluster 4 const uri = "<connection-string>"; 5 6 const client = new MongoClient(uri); 7 8 async function run() { 9 try { 10 await client.connect(); 11 12 // set namespace 13 const database = client.db("sample_mflix"); 14 const coll = database.collection("embedded_movies"); 15 16 // define pipeline 17 const agg = [ 18 { 19 '$vectorSearch': { 20 'index': 'vector_index', 21 'path': 'plot_embedding_voyage_3_large', 22 'filter': { 23 '$or': [ 24 { 25 'genres': { 26 '$ne': 'Crime' 27 } 28 }, { 29 '$and': [ 30 { 31 'year': { 32 '$lte': 2015 33 } 34 }, { 35 'genres': { 36 '$eq': 'Action' 37 } 38 } 39 ] 40 } 41 ] 42 }, 43 'queryVector': 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7962143,-0.043223642,0.033920541,-0.007764512,-0.006762639,0.017819017,-0.026621183,0.046658635,-0.004490536,0.024188064,-0.010304974,0.004651551,0.047231134,-0.038071156,0.009589351,-0.033920541,-0.027050557,0.050093625,0.008515916,-0.025189938,-0.008050761,0.011950907,0.004973582,0.014527151,-0.009374664,-0.003721241,0.019608077,0.049807377,0.016602458,0.02404494], 44 'numCandidates': 200, 45 'limit': 10 46 } 47 }, { 48 '$project': { 49 '_id': 0, 50 'title': 1, 51 'genres': 1, 52 'plot': 1, 53 'released': 1, 54 'score': { 55 '$meta': 'vectorSearchScore' 56 } 57 } 58 } 59 ]; 60 61 // run pipeline 62 const result = coll.aggregate(agg); 63 64 // print results 65 await result.forEach((doc) => console.dir(JSON.stringify(doc))); 66 } finally { 67 await client.close(); 68 } 69 } 70 run().catch(console.dir);
クエリ内の <connection-string>
を置き換え、ファイルを保存します。
<connection-string>
を Atlas クラスターまたはローカル Atlas 配置の接続文字列に置き換えます。
接続stringには、次の形式を使用する必要があります。
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
詳しくは、ドライバーを使用してクラスターに接続する を参照してください。
接続stringには、次の形式を使用する必要があります。
mongodb://localhost:<port-number>/?directConnection=true
詳細については、「接続文字列 」を参照してください。
コレクションをクエリします。
次のコマンドを実行して、コレクションをクエリします。
node atlas-vector-search-tutorial.js
'{"plot":"Three young boys, Rocky, Colt and Tum Tum together with their neighbor girl, computer whiz Amanda are visiting Mega Mountain amusement park when it is invaded by an army of ninjas led by ...","genres":["Action","Adventure","Comedy"],"title":"3 Ninjas: High Noon at Mega Mountain","year":1998,"score":0.7746343612670898}' `{"plot":"A two-week trek through the Cascade Mountains tries the survival instincts of five adventurous teenagers. At first, it's all a good time. Shooting the rapids, exploring caves and making new...","genres":["Action","Adventure","Family"],"title":"White Wolves: A Cry in the Wild II","year":1993,"score":0.770106315612793}` '{"plot":"A futuristic, sensitive tale of adventure and confrontation when a 10 year old boy is accidentally kidnapped by a spaceship filled with a motley crew of space pirates.","genres":["Action","Adventure","Sci-Fi"],"title":"Space Raiders","year":1983,"score":0.7569591999053955}' '{"plot":"Wicket the Ewok and his friends agree to help two shipwrecked human children on a quest to find their parents.","genres":["Adventure","Family","Fantasy"],"title":"The Ewok Adventure","year":1984,"score":0.7515435218811035}' '{"plot":"A young boy accidentally joins a band of dwarves as they jump from era to era looking for treasure to steal.","genres":["Adventure","Comedy","Fantasy"],"title":"Time Bandits","year":1981,"score":0.7513599395751953}' '{"plot":"A down-on-his-luck inventor turns a broken-down Grand Prix car into a fancy vehicle for his children, and then they go off on a magical fantasy adventure to save their grandfather in a far-off land.","genres":["Adventure","Family","Fantasy"],"title":"Chitty Chitty Bang Bang","year":1968,"score":0.7492260932922363}' '{"plot":"A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.","genres":["Action","Adventure","Comedy"],"title":"Forest Warrior","year":1996,"score":0.7473714351654053}' '{"plot":"A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.","genres":["Action","Adventure","Comedy"],"title":"Forest Warrior","year":1996,"score":0.7473714351654053}' '{"plot":"A young boy is whisked away to the mythical land of Tao where he becomes the center of a conflict between an evil lord and a group of animal warriors.","genres":["Action","Fantasy","Adventure"],"title":"Warriors of Virtue","year":1997,"score":0.7464213371276855}' '{"plot":"A young prince is taken for tuition at a seaside hotel but there quickly bores and wanders off to visit a nearby lighthouse. Befriended by the keeper, he learns of a secret world he can see...","genres":["Animation","Adventure","Fantasy"],"title":"Taxandria","year":1994,"score":0.7453246116638184}'
node atlas-search-tutorial.js
`{"plot":"Luke Skywalker joins forces with a Jedi Knight, a cocky pilot, a wookiee and two droids to save the universe from the Empire's world-destroying battle-station, while also attempting to rescue Princess Leia from the evil Darth Vader.","genres":["Action","Adventure","Fantasy"],"title":"Star Wars: Episode IV - A New Hope","released":"1977-05-25T00:00:00.000Z","score":0.79868483543396}` `{"plot":"A Duke's son leads desert warriors against the galactic emperor and his father's evil nemesis when they assassinate his father and free their desert world from the emperor's rule.","genres":["Action","Adventure","Sci-Fi"],"title":"Dune","released":"1984-12-14T00:00:00.000Z","score":0.7949700355529785}` '{"plot":"In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...","genres":["Action","Adventure","Sci-Fi"],"title":"Message from Space","released":"1978-10-30T00:00:00.000Z","score":0.7913978099822998}' '{"plot":"In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...","genres":["Action","Adventure","Sci-Fi"],"title":"Message from Space","released":"1978-10-30T00:00:00.000Z","score":0.7913978099822998}' '{"plot":"After the rebels have been brutally overpowered by the Empire on their newly established base, Luke Skywalker takes advanced Jedi training with Master Yoda, while his friends are pursued by Darth Vader as part of his plan to capture Luke.","genres":["Action","Adventure","Fantasy"],"title":"Star Wars: Episode V - The Empire Strikes Back","released":"1980-06-20T00:00:00.000Z","score":0.7809884548187256}' '{"plot":"After rescuing Han Solo from the palace of Jabba the Hutt, the rebels attempt to destroy the second Death Star, while Luke struggles to make Vader return from the dark side of the Force.","genres":["Action","Adventure","Fantasy"],"title":"Star Wars: Episode VI - Return of the Jedi","released":"1983-05-25T00:00:00.000Z","score":0.7784996032714844}' '{"plot":"Two Jedi Knights escape a hostile blockade to find allies and come across a young boy who may bring balance to the Force, but the long dormant Sith resurface to reclaim their old glory.","genres":["Action","Adventure","Fantasy"],"title":"Star Wars: Episode I - The Phantom Menace","released":"1999-05-19T00:00:00.000Z","score":0.7766742706298828}' '{"plot":"The army of the Marauders, led by by King Terak and the witch Charal attack the Ewoks village. The parents and the brother of Cindel all die in this attack. Cindel and the Ewok Wicket ...","genres":["Adventure","Family","Fantasy"],"title":"Ewoks: The Battle for Endor","released":"1985-11-24T00:00:00.000Z","score":0.7676119804382324}' '{"plot":"A prince and a fellowship of companions set out to rescue his bride from a fortress of alien invaders who have arrived on their home planet.","genres":["Action","Adventure","Fantasy"],"title":"Krull","released":"1983-07-29T00:00:00.000Z","score":0.7624373435974121}' '{"plot":"An outlaw smuggler and her alien companion are recruited by the Emperor of the Galaxy to rescue his son and destroy a secret weapon by the evil Count Zarth Arn.","genres":["Action","Adventure","Fantasy"],"title":"Starcrash","released":"1979-03-09T00:00:00.000Z","score":0.7582714557647705}'
試したいプレフィルター演算子のクエリをコピーして、atlas-vector-search-tutorial.py
ファイルに貼り付けます。
次のクエリは、$vectorSearch
パイプライン ステージを使用して、指定されたベクター埋め込みに一致する映画を検索します。クエリは、最大 100
件の最近傍を検索し、結果を 10
件のドキュメントのみに制限します。クエリは、次のアクションを実行するための $project
ステージも指定します。
_id
フィールドを除外し、結果にはtitle
、genres
、plot
、およびyear
フィールドのみが含まれます。結果内の各ドキュメントのベクトル検索スコアを表示する
score
という名前のフィールドを追加します。
次のクエリは、文字列 kids adventure のベクトル埋め込みを使用して、plot_embedding_voyage_3_large
フィールドを検索します。フィールドごとに複数の比較クエリ演算子を指定して、セマンティック検索を実行するドキュメントを事前にフィルタリングします。
フィルターでは、 $and
集計パイプライン演算子を使用して、次の両方の条件に一致するドキュメントを検索します。
genres
フィールドでフィルタリングして、drama
、western
、またはcrime
ジャンルではなく、action
、adventure
、またはfamily
ジャンルに含まれる映画を検索します。year
フィールドでフィルタリングして、1960
から2000
年(両端を含む)の間にリリースされた映画を検索します。
1 import pymongo 2 3 # connect to your Atlas cluster 4 client = pymongo.MongoClient("<connection-string>") 5 6 # define pipeline 7 pipeline = [ 8 { 9 '$vectorSearch': { 10 'index': 'vector_index', 11 'path': 'plot_embedding_voyage_3_large', 12 'filter': { 13 '$and': [ 14 { 15 'genres': { 16 '$nin': [ 17 'Drama', 'Western', 'Crime' 18 ], 19 '$in': [ 20 'Action', 'Adventure', 'Family' 21 ] 22 } 23 }, { 24 'year': { 25 '$gte': 1960, 26 '$lte': 2000 27 } 28 } 29 ] 30 }, 31 'queryVector': 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32 'numCandidates': 200, 33 'limit': 10 34 } 35 }, { 36 '$project': { 37 '_id': 0, 38 'title': 1, 39 'genres': 1, 40 'plot': 1, 41 'year': 1, 42 'score': { 43 '$meta': 'vectorSearchScore' 44 } 45 } 46 } 47 ] 48 49 # run pipeline 50 result = client["sample_mflix"]["embedded_movies"].aggregate(pipeline) 51 52 # print results 53 for i in result: 54 print(i)
次のクエリは、ベクター埋め込みを使用して plot_embedding_voyage_3_large
フィールドで star wars という文字列を検索します。集計パイプラインと比較クエリ演算子を指定し、演算子を組み合わせてデータをフィルタリングする方法を示します。
フィルターでは、 $or
集計パイプライン演算子を使用して、次のいずれかの条件に一致する映画のドキュメントを検索します。
genres
フィールドでフィルタリングして、crime
ジャンルに該当しない映画を検索します。year
フィールドでフィルタリングして、2015
年以前にリリースされた映画を検索し、genres
フィールドでフィルタリングしてaction
ジャンルの映画を検索します。
1 import pymongo 2 3 # connect to your Atlas cluster 4 client = pymongo.MongoClient("<connection-string>") 5 6 # define pipeline 7 pipeline = [ 8 { 9 '$vectorSearch': { 10 'index': 'vector_index', 11 'path': 'plot_embedding_voyage_3_large', 12 'filter': { 13 '$or': [ 14 { 15 'genres': { 16 '$ne': 'Crime' 17 } 18 }, { 19 '$and': [ 20 { 21 'year': { 22 '$lte': 2015 23 } 24 }, { 25 'genres': { 26 '$eq': 'Action' 27 } 28 } 29 ] 30 } 31 ] 32 }, 33 'queryVector': 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34 'numCandidates': 200, 35 'limit': 10 36 } 37 }, { 38 '$project': { 39 '_id': 0, 40 'title': 1, 41 'genres': 1, 42 'plot': 1, 43 'year': 1, 44 'score': { 45 '$meta': 'vectorSearchScore' 46 } 47 } 48 } 49 ] 50 51 # run pipeline 52 result = client["sample_mflix"]["embedded_movies"].aggregate(pipeline) 53 54 # print results 55 for i in result: 56 print(i)
クエリ内の <connection-string>
を置き換え、ファイルを保存します。
<connection-string>
を Atlas クラスターまたはローカル Atlas 配置の接続文字列に置き換えます。
接続stringには、次の形式を使用する必要があります。
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
詳しくは、ドライバーを使用してクラスターに接続する を参照してください。
接続stringには、次の形式を使用する必要があります。
mongodb://localhost:<port-number>/?directConnection=true
詳細については、「接続文字列 」を参照してください。
コマンドを実行して、コレクションをクエリします。
python atlas-vector-search-tutorial.py
{'plot': 'Three young boys, Rocky, Colt and Tum Tum together with their neighbor girl, computer whiz Amanda are visiting Mega Mountain amusement park when it is invaded by an army of ninjas led by ...', 'genres': ['Action', 'Adventure', 'Comedy'], 'title': '3 Ninjas: High Noon at Mega Mountain', 'year': 1998, 'score': 0.7746343612670898} {'plot': "A two-week trek through the Cascade Mountains tries the survival instincts of five adventurous teenagers. At first, it's all a good time. Shooting the rapids, exploring caves and making new...", 'genres': ['Action', 'Adventure', 'Family'], 'title': 'White Wolves: A Cry in the Wild II', 'year': 1993, 'score': 0.770106315612793} {'plot': 'A futuristic, sensitive tale of adventure and confrontation when a 10 year old boy is accidentally kidnapped by a spaceship filled with a motley crew of space pirates.', 'genres': ['Action', 'Adventure', 'Sci-Fi'], 'title': 'Space Raiders', 'year': 1983, 'score': 0.7569591999053955} {'plot': 'Wicket the Ewok and his friends agree to help two shipwrecked human children on a quest to find their parents.', 'genres': ['Adventure', 'Family', 'Fantasy'], 'title': 'The Ewok Adventure', 'year': 1984, 'score': 0.7515435218811035} {'plot': 'A young boy accidentally joins a band of dwarves as they jump from era to era looking for treasure to steal.', 'genres': ['Adventure', 'Comedy', 'Fantasy'], 'title': 'Time Bandits', 'year': 1981, 'score': 0.7513599395751953} {'plot': 'A down-on-his-luck inventor turns a broken-down Grand Prix car into a fancy vehicle for his children, and then they go off on a magical fantasy adventure to save their grandfather in a far-off land.', 'genres': ['Adventure', 'Family', 'Fantasy'], 'title': 'Chitty Chitty Bang Bang', 'year': 1968, 'score': 0.7492260932922363} {'plot': 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.', 'genres': ['Action', 'Adventure', 'Comedy'], 'title': 'Forest Warrior', 'year': 1996, 'score': 0.7473714351654053} {'plot': 'A shape-shifting mountain man and a group of children team up to protect an enchanted forest from evil lumberjacks.', 'genres': ['Action', 'Adventure', 'Comedy'], 'title': 'Forest Warrior', 'year': 1996, 'score': 0.7473714351654053} {'plot': 'A young boy is whisked away to the mythical land of Tao where he becomes the center of a conflict between an evil lord and a group of animal warriors.', 'genres': ['Action', 'Fantasy', 'Adventure'], 'title': 'Warriors of Virtue', 'year': 1997, 'score': 0.7464213371276855} {'plot': 'A young prince is taken for tuition at a seaside hotel but there quickly bores and wanders off to visit a nearby lighthouse. Befriended by the keeper, he learns of a secret world he can see...', 'genres': ['Animation', 'Adventure', 'Fantasy'], 'title': 'Taxandria', 'year': 1994, 'score': 0.7453246116638184}
python atlas-vector-search-tutorial.py
{'year': 1977, 'plot': "Luke Skywalker joins forces with a Jedi Knight, a cocky pilot, a wookiee and two droids to save the universe from the Empire's world-destroying battle-station, while also attempting to rescue Princess Leia from the evil Darth Vader.", 'genres': ['Action', 'Adventure', 'Fantasy'], 'title': 'Star Wars: Episode IV - A New Hope', 'score': 0.79868483543396} {'plot': "A Duke's son leads desert warriors against the galactic emperor and his father's evil nemesis when they assassinate his father and free their desert world from the emperor's rule.", 'genres': ['Action', 'Adventure', 'Sci-Fi'], 'title': 'Dune', 'year': 1984, 'score': 0.7949700355529785} {'plot': 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...', 'genres': ['Action', 'Adventure', 'Sci-Fi'], 'title': 'Message from Space', 'year': 1978, 'score': 0.7913978099822998} {'plot': 'In this Star Wars take-off, the peaceful planet of Jillucia has been nearly wiped out by the Gavanas, whose leader takes orders from his mother (played a comic actor in drag) rather than ...', 'genres': ['Action', 'Adventure', 'Sci-Fi'], 'title': 'Message from Space', 'year': 1978, 'score': 0.7913978099822998} {'year': 1980, 'plot': 'After the rebels have been brutally overpowered by the Empire on their newly established base, Luke Skywalker takes advanced Jedi training with Master Yoda, while his friends are pursued by Darth Vader as part of his plan to capture Luke.', 'genres': ['Action', 'Adventure', 'Fantasy'], 'title': 'Star Wars: Episode V - The Empire Strikes Back', 'score': 0.7809884548187256} {'plot': 'After rescuing Han Solo from the palace of Jabba the Hutt, the rebels attempt to destroy the second Death Star, while Luke struggles to make Vader return from the dark side of the Force.', 'genres': ['Action', 'Adventure', 'Fantasy'], 'title': 'Star Wars: Episode VI - Return of the Jedi', 'year': 1983, 'score': 0.7784996032714844} {'plot': 'Two Jedi Knights escape a hostile blockade to find allies and come across a young boy who may bring balance to the Force, but the long dormant Sith resurface to reclaim their old glory.', 'genres': ['Action', 'Adventure', 'Fantasy'], 'title': 'Star Wars: Episode I - The Phantom Menace', 'year': 1999, 'score': 0.7766742706298828} {'plot': 'The army of the Marauders, led by by King Terak and the witch Charal attack the Ewoks village. The parents and the brother of Cindel all die in this attack. Cindel and the Ewok Wicket ...', 'genres': ['Adventure', 'Family', 'Fantasy'], 'title': 'Ewoks: The Battle for Endor', 'year': 1985, 'score': 0.7676119804382324} {'plot': 'A prince and a fellowship of companions set out to rescue his bride from a fortress of alien invaders who have arrived on their home planet.', 'genres': ['Action', 'Adventure', 'Fantasy'], 'title': 'Krull', 'year': 1983, 'score': 0.7624373435974121} {'plot': 'An outlaw smuggler and her alien companion are recruited by the Emperor of the Galaxy to rescue his son and destroy a secret weapon by the evil Count Zarth Arn.', 'genres': ['Action', 'Adventure', 'Fantasy'], 'title': 'Starcrash', 'year': 1978, 'score': 0.7582714557647705}