Este tutorial describe cómo realizar una BúsquedaANN en un vector en el plot_embedding_voyage_3_large Campo en la colección sample_mflix.embedded_movies de su clúster. Para demostrarlo, le guiaremos por los siguientes pasos:
Crea un índice de MongoDB Vector Search en el campo numérico llamado
plot_embedding_voyage_3_largeen la colecciónsample_mflix.embedded_movies.Ejecuta consultas de búsqueda de vectores de MongoDB en el campo
plot_embedding_voyage_3_largede la colecciónsample_mflix.embedded_movies.
➤ Se debe usar el menú desplegable Seleccionar lenguaje para elegir el cliente que se utilizará para crear el índice de MongoDB Vector Search y ejecutar queries.
Requisitos previos
Antes de comenzar, complete el Requisitos comunes. Este tutorial incluye ejemplos para los siguientes clientes:
Cree el índice de búsqueda vectorial de MongoDB
Esta sección demuestra cómo crear un índice de búsqueda vectorial de MongoDB en el campo plot_embedding_voyage_3_large de la colección sample_mflix.embedded_movies para ejecutar queries vectoriales en el campo.
Acceso requerido
Para crear un índice de búsqueda vectorial de MongoDB, debes tener Project Data Access Admin o un acceso superior al proyecto.
Procedimiento
En Atlas, vaya a la Search & Vector Search página para su clúster.
Puedes ir a la página de búsqueda de MongoDB desde la opción Search & Vector Search o desde el Data Explorer.
Si aún no aparece, se debe seleccionar la organización que contiene el proyecto en el menú Organizations de la barra de navegación.
Si aún no se muestra, seleccione su proyecto en el menú Projects de la barra de navegación.
En la barra lateral, haz clic en Search & Vector Search en la sección Database.
Si no tienes clústeres, haz clic en Create cluster para crear uno. Para obtener más información, consulta Crear un clúster.
Si el proyecto tiene varios clústeres, se debe seleccionar el clúster que se desea usar en el menú desplegable Select cluster y luego se debe hacer clic en Go to Search.
Aparece la página de Búsqueda y Búsqueda Vectorial.
Si aún no aparece, se debe seleccionar la organización que contiene el proyecto en el menú Organizations de la barra de navegación.
Si aún no se muestra, seleccione su proyecto en el menú Projects de la barra de navegación.
En la barra lateral, haz clic en Data Explorer en la sección Database.
Expanda la base de datos y seleccione la colección.
Haga clic en la pestaña Indexes para la colección.
Haga clic en el enlace Search and Vector Search en el banner.
Aparece la página de Búsqueda y Búsqueda Vectorial.
Se debe iniciar la configuración del índice.
Realiza las siguientes selecciones en la página y luego haz clic en Next.
Search Type | Seleccione el tipo de índice Vector Search. |
Index Name and Data Source | Especifique la siguiente información:
|
Configuration Method | For a guided experience, select Visual Editor. To edit the raw index definition, select JSON Editor. |
IMPORTANTE:
El índice de MongoDB Search se llama default por defecto. Si se mantiene este nombre, el índice será el índice de búsqueda por defecto para cualquier query de MongoDB Search que no especifique una opción de index diferente en sus operadores. Si se crean varios índices, recomendamos mantener una convención de nomenclatura coherente y descriptiva en todos los índices.
Defina el índice de búsqueda vectorial de MongoDB.
En este paso, define un índice del tipo vectorSearch para los siguientes campos:
plot_embedding_voyage_3_largecampo como el tipo de vector. El campoplot_embedding_voyage_3_largecontiene incrustaciones creadas utilizando el modelo de incrustaciónvoyage-3-largede Voyage AI. La definición del índice especifica2048dimensiones vectoriales y mide la similitud utilizandodotProduct.genresel campo como el tipo de filtro para prefiltrar datos por valores de string en el campo.yearcampo como el tipo de filtro para prefiltrar datos por valores numéricos en el campo.
Atlas detecta automáticamente los campos que incluyen incrustaciones vectoriales, así como sus dimensiones correspondientes. Para la colección sample_mflix.embedded_movies, se muestran los campos plot_embedding y plot_embedding_voyage_3_large. Para este tutorial, necesitas indexar solo el campo plot_embedding_voyage_3_large .
Para configurar el índice, haga lo siguiente:
Selecciona Dot Product del menú desplegable Similarity Method.
Haz clic en Advanced, luego selecciona la cuantificación Scalar en el menú desplegable.
En la sección Filter Field, especifica los campos
genresyyearpor los que deseas filtrar los datos.
Reemplaza la definición por defecto con la siguiente definición de índice.
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 }
Verifique el estado.
El índice recién creado aparece en la pestaña Atlas Search. Mientras se construye el índice, el campo Status muestra Build in Progress. Cuando se termina de construir el índice, el campo Status muestra Active.
Nota
Las colecciones más grandes tardan más en indexarse. Se recibirá una notificación por correo electrónico cuando el índice haya terminado de construirse.
Conéctese a su clúster mongosh en.
Se debe abrir mongosh en una ventana de terminal y realizar la conexión al clúster. Para obtener instrucciones detalladas sobre cómo realizar la conexión, se debe consultar Conectar a través de mongosh.
Ejecute el db.collection.createSearchIndex() método.
La siguiente definición de índice indexa el campo plot_embedding_voyage_3_large como el tipo vector y los campos genres y year como el tipo filter.
El campo plot_embedding_voyage_3_large contiene incrustaciones de dimensiones vectoriales 2048 creadas utilizando el modelo de incrustación voyage-3-large de Voyage IA. El índice mide la similitud utilizando la función dotProduct.
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 );
Define el índice.
Crea un archivo llamado IndexService.cs y copia y pega el siguiente código en el archivo.
Esta definición de índice indexa el campo plot_embedding_voyage_3_large como tipo vector y los campos genres y year como tipo filter en un índice de búsqueda vectorial de MongoDB. El campo plot_embedding_voyage_3_large contiene embeddings creados con el modelo de embeddings voyage-3-large de Voyage IA. La definición del índice especifica 2048 dimensiones vectoriales y mide la similitud utilizando la función dotProduct.
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 connection string 11 private const string MongoConnectionString = "<connection-string>"; 12 public void CreateVectorIndex() 13 { 14 try 15 { 16 // Connect to your 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 24 var model = new CreateVectorSearchIndexModel<Movie>( 25 m => m.PlotEmbedding, 26 name, 27 VectorSimilarity.DotProduct, 28 2048, 29 m => m.Genres, 30 m => m.Year) 31 { 32 Quantization = VectorQuantization.Scalar, 33 }; 34 35 searchIndexView.CreateOne(model); 36 Console.WriteLine($"New search index named {name} is building."); 37 38 // Polling for index status 39 Console.WriteLine("Polling to check if the index is ready. This may take up to a minute."); 40 bool queryable = false; 41 while (!queryable) 42 { 43 var indexes = searchIndexView.List(); 44 foreach (var index in indexes.ToEnumerable()) 45 { 46 if (index["name"] == name) 47 { 48 queryable = index["queryable"].AsBoolean; 49 } 50 } 51 if (!queryable) 52 { 53 Thread.Sleep(5000); 54 } 55 } 56 Console.WriteLine($"{name} is ready for querying."); 57 } 58 catch (Exception e) 59 { 60 Console.WriteLine($"Exception: {e.Message}"); 61 } 62 } 63 }
Reemplace el <connection-string> en el código y luego guarde el archivo.
Se debe sustituir <connection-string> por la cadena de conexión del clúster Atlas o de la implementación local de Atlas.
Su cadena de conexión debe usar el siguiente formato:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
Para obtener más información,consulte Conectarse a un clúster a través de bibliotecas de cliente.
Su cadena de conexión debe usar el siguiente formato:
mongodb://localhost:<port-number>/?directConnection=true
Para obtener más información, consulta Cadenas de conexión.
Guarda y ejecuta el proyecto.
Se debe guardar el archivo, y luego compilar y ejecutar el proyecto para crear el índice.
dotnet run query_quick_start.csproj
New search index named vector_index is building. Polling to check if the index is ready. This may take up to a minute. vector_index is ready for querying.
Define el índice.
Crea un archivo llamado vector-index.go y copia y pega el siguiente código en el archivo.
Esta definición de índice indexa el campo plot_embedding_voyage_3_large como tipo vector y los campos genres y year como tipo filter en un índice de búsqueda vectorial de MongoDB. El campo plot_embedding_voyage_3_large contiene incrustaciones creadas utilizando el modelo de incrustación voyage-3-large de Voyage IA. La definición del índice especifica 2048 dimensiones vectoriales y mide la similitud utilizando la función dotProduct.
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 connection string 18 const uri = "<connectionString>" 19 20 // Connect to your 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 }
Reemplace el <connection-string> en el código y luego guarde el archivo.
Se debe sustituir <connection-string> por la cadena de conexión del clúster Atlas o de la implementación local de Atlas.
Su cadena de conexión debe usar el siguiente formato:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
Para obtener más información,consulte Conectarse a un clúster a través de bibliotecas de cliente.
Su cadena de conexión debe usar el siguiente formato:
mongodb://localhost:<port-number>/?directConnection=true
Para obtener más información, consulta Cadenas de conexión.
Se debe agregar el Java Sync Driver de MongoDB al proyecto.
Se debe añadir la versión del driver de Java 5.2 o superior como dependencia en el proyecto, dependiendo del administrador de paquetes:
Si se usa Maven, se deben agregar las siguientes dependencias al arreglo de
dependenciesen el archivopom.xmldel proyecto: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> Se debe ejecutar el administrador de paquetes para instalar las dependencias en el proyecto.
Para obtener instrucciones de instalación más detalladas y compatibilidad de versiones, consulte la documentación del controlador Java de MongoDB.
Define el índice.
Crea un archivo llamado VectorIndex.java y copia y pega el siguiente código en el archivo.
Esta definición de índice indexa el campo plot_embedding_voyage_3_large como tipo vector y los campos genres y year como tipo filter en un índice de búsqueda vectorial de MongoDB. El campo plot_embedding_voyage_3_large contiene embeddings creados con el modelo de embeddings voyage-3-large de Voyage IA. La definición del índice especifica 2048 dimensiones vectoriales y mide la similitud utilizando la función dotProduct.
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 connection string 19 String uri = "<connectionString>"; 20 21 // Connect to your 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("Wait 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 }
Reemplace el <connection-string> en el código y luego guarde el archivo.
Se debe sustituir <connection-string> por la cadena de conexión del clúster Atlas o de la implementación local de Atlas.
Su cadena de conexión debe usar el siguiente formato:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
Para obtener más información,consulte Conectarse a un clúster a través de bibliotecas de cliente.
Su cadena de conexión debe usar el siguiente formato:
mongodb://localhost:<port-number>/?directConnection=true
Para obtener más información, consulta Cadenas de conexión.
Ejecuta el archivo para crear el índice.
Ejecuta el archivo en su IDE o ejecuta un comando desde la línea de comandos para ejecutar el código.
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
Añade el controlador de Nodo.js de MongoDB al proyecto.
Se debe agregar el driver de nodo de MongoDB como una dependencia para el proyecto:
npm install mongodb
Tip
Los ejemplos de esta página asumen que su proyecto gestiona módulos como módulos de CommonJS. Si usas módulos de ES, en cambio, debes modificar la sintaxis de importación.
Define el índice.
Crea un archivo llamado vector-index.js y copia y pega el siguiente código en el archivo.
Esta definición de índice indexa el campo plot_embedding_voyage_3_large como tipo vector y los campos genres y year como tipo filter en un índice de búsqueda vectorial de MongoDB. El campo plot_embedding_voyage_3_large contiene embeddings creados con el modelo de embeddings voyage-3-large de Voyage IA. La definición del índice especifica 2048 dimensiones vectoriales y mide la similitud utilizando la función dotProduct.
1 const { MongoClient } = require("mongodb"); 2 3 // connect to your 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);
Reemplace el <connection-string> en el código y luego guarde el archivo.
Se debe sustituir <connection-string> por la cadena de conexión del clúster Atlas o de la implementación local de Atlas.
Su cadena de conexión debe usar el siguiente formato:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
Para obtener más información,consulte Conectarse a un clúster a través de bibliotecas de cliente.
Su cadena de conexión debe usar el siguiente formato:
mongodb://localhost:<port-number>/?directConnection=true
Para obtener más información, consulta Cadenas de conexión.
Define el índice.
Crea un archivo llamado vector-index.py y copia y pega el siguiente código en el archivo.
Esta definición de índice indexa el campo plot_embedding_voyage_3_large como tipo vector y los campos genres y year como tipo filter en un índice de búsqueda vectorial de MongoDB. El campo plot_embedding_voyage_3_large contiene embeddings creados utilizando el modelo de embeddings voyage-3-large de Voyage IA. La definición del índice especifica 2048 dimensiones vectoriales, mide la similitud mediante la función dotProduct y permite la cuantificación automática scalar para un procesamiento eficiente de sus vectores.
1 from pymongo.mongo_client import MongoClient 2 from pymongo.operations import SearchIndexModel 3 import time 4 5 # Connect to your 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()
Reemplace el <connection-string> en el código y luego guarde el archivo.
Se debe sustituir <connection-string> por la cadena de conexión del clúster Atlas o de la implementación local de Atlas.
Su cadena de conexión debe usar el siguiente formato:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
Para obtener más información,consulte Conectarse a un clúster a través de bibliotecas de cliente.
Su cadena de conexión debe usar el siguiente formato:
mongodb://localhost:<port-number>/?directConnection=true
Para obtener más información, consulta Cadenas de conexión.
Ejecutar consultas utilizando la $vectorSearch etapa de canalización de agregación
Overview
Esta sección demuestra cómo consultar los datos vectoriales indexados en la colección sample_mflix.embedded_movies usando la etapa $vectorSearch. Estas consultas de sample también demuestran los diversos operadores de query y de pipeline de agregación que podemos utilizar en el query para prefiltrar los datos en los que realizamos la búsqueda semántica.
Procedimiento
Prepara las incrustaciones del query.
Guarde las siguientes incrustaciones en un archivo llamado query-embeddings.js:
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Conéctese a su clúster mongosh en.
Se debe abrir mongosh en una ventana de terminal y realizar la conexión al clúster. Para obtener instrucciones detalladas sobre cómo realizar la conexión, se debe consultar Conectar a través de mongosh.
Ejecuta el query de búsqueda semántica sobre los campos indexados.
Las siguientes consultas utilizan la etapa de pipeline $vectorSearch para la búsqueda de películas que coincidan con las incrustaciones vectoriales especificadas. Los queries especifican una búsqueda de hasta 100 vecinos más cercanos y limitan los resultados a solo 10 documentos. Los queries también especifican una etapa $project para realizar las siguientes acciones:
Excluye el campo
_ide incluye solo los campostitle,genres,plotyyearen los resultados.Añada un campo llamado
scoreque muestre la puntuación de búsqueda vectorial de cada documento en los resultados.
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string kids adventure. Especifica múltiples operadores del query de comparación por campo para prefiltrar los documentos con los que se relacionará la búsqueda semántica.
El filtro utiliza el operador de pipeline de agregación $and para encontrar documentos de películas que coincidan con los dos criterios siguientes:
Filtra por el campo
genrespara encontrar películas que no sean del génerodrama,westernocrime, sino del géneroaction,adventureofamily.Filtra por el campo
yearpara encontrar películas que se estrenaron entre los años1960y2000, ambos inclusive.
1 db.embedded_movies.aggregate([ 2 { 3 "$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 ]
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string star wars. Especifica el pipeline de agregación y los operadores del query de comparación para demostrar un uso combinado de los operadores para filtrar los datos.
El filtro utiliza el operador de pipeline de agregación $or para encontrar documentos de películas que coincidan con cualquiera de los siguientes criterios:
Filtra por el campo
genrespara encontrar películas que no sean de génerocrime.Filtra por el campo
yearpara encontrar las películas que se estrenaron en el año2015, o antes, y por el campogenrespara encontrar películas del géneroaction.
1 db.embedded_movies.aggregate([ 2 { 3 "$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 ]
Prepara las incrustaciones del query.
Guarde las siguientes incrustaciones en un archivo llamado query-embeddings.js:
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Conéctese a su clúster mongosh en.
Se debe abrir mongosh en una ventana de terminal y realizar la conexión al clúster. Para obtener instrucciones detalladas sobre cómo realizar la conexión, se debe consultar Conectar a través de mongosh.
Ejecuta el query de búsqueda semántica sobre los campos indexados.
Las siguientes consultas utilizan la etapa de pipeline $vectorSearch para la búsqueda de películas que coincidan con las incrustaciones vectoriales especificadas. Los queries especifican una búsqueda de hasta 100 vecinos más cercanos y limitan los resultados a solo 10 documentos. Los queries también especifican una etapa $project para realizar las siguientes acciones:
Excluye el campo
_ide incluye solo los campostitle,genres,plotyyearen los resultados.Añada un campo llamado
scoreque muestre la puntuación de búsqueda vectorial de cada documento en los resultados.
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string kids adventure. Especifica múltiples operadores del query de comparación por campo para prefiltrar los documentos con los que se relacionará la búsqueda semántica.
El filtro utiliza el operador de pipeline de agregación $and para encontrar documentos de películas que coincidan con los dos criterios siguientes:
Filtra por el campo
genrespara encontrar películas que no sean del génerodrama,westernocrime, sino del géneroaction,adventureofamily.Filtra por el campo
yearpara encontrar películas que se estrenaron entre los años1960y2000, ambos inclusive.
1 db.embedded_movies.aggregate([ 2 { 3 "$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 ]
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string star wars. Especifica el pipeline de agregación y los operadores del query de comparación para demostrar un uso combinado de los operadores para filtrar los datos.
El filtro utiliza el operador de pipeline de agregación $or para encontrar documentos de películas que coincidan con cualquiera de los siguientes criterios:
Filtra por el campo
genrespara encontrar películas que no sean de génerocrime.Filtra por el campo
yearpara encontrar las películas que se estrenaron en el año2015, o antes, y por el campogenrespara encontrar películas del géneroaction.
1 db.embedded_movies.aggregate([ 2 { 3 "$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 ]
Copie y pegue el código del operador de prefiltro que desea probar en el DataService.cs archivo.
Las siguientes consultas utilizan la etapa de pipeline $vectorSearch para la búsqueda de películas que coincidan con las incrustaciones vectoriales especificadas. Los queries especifican una búsqueda de hasta 100 vecinos más cercanos y limitan los resultados a solo 10 documentos. Los queries también especifican una etapa $project para realizar las siguientes acciones:
Excluye el campo
_ide incluye solo los campostitle,genres,plotyyearen los resultados.Añada un campo llamado
scoreque muestre la puntuación de búsqueda vectorial de cada documento en los resultados.
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string kids adventure. Especifica múltiples operadores del query de comparación por campo para prefiltrar los documentos con los que se relacionará la búsqueda semántica.
El filtro utiliza el operador de pipeline de agregación $and para encontrar documentos de películas que coincidan con los dos criterios siguientes:
Filtra por el campo
genrespara encontrar películas que no sean del génerodrama,westernocrime, sino del géneroaction,adventureofamily.Filtra por el campo
yearpara encontrar películas que se estrenaron entre los años1960y2000, ambos inclusive.
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 }
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string star wars. Especifica el pipeline de agregación y los operadores del query de comparación para demostrar un uso combinado de los operadores para filtrar los datos.
El filtro utiliza el operador de pipeline de agregación $or para encontrar documentos de películas que coincidan con cualquiera de los siguientes criterios:
Filtra por el campo
genrespara encontrar películas que no sean de génerocrime.Filtra por el campo
yearpara encontrar las películas que se estrenaron en el año2015, o antes, y por el campogenrespara encontrar películas del géneroaction.
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 }
Reemplaza el <connection-string> en la query y luego guarda el archivo.
Se debe sustituir <connection-string> por la cadena de conexión del clúster Atlas o de la implementación local de Atlas.
Su cadena de conexión debe usar el siguiente formato:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
Para obtener más información,consulte Conectarse a un clúster a través de bibliotecas de cliente.
Su cadena de conexión debe usar el siguiente formato:
mongodb://localhost:<port-number>/?directConnection=true
Para obtener más información, consulta Cadenas de conexión.
Update Program.cs.
Actualiza Program.cs para inicializar DataService y llama al método para realizar el query.
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 }
Guarda y ejecuta el proyecto.
Guarda el archivo y luego compila y ejecuta el proyecto para realizar el query.
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 }
Copie y pegue el código del operador de prefiltro que desea probar en el AtlasVectorSearchTutorial.go archivo.
Las siguientes consultas utilizan la etapa de pipeline $vectorSearch para la búsqueda de películas que coincidan con las incrustaciones vectoriales especificadas. Los queries especifican una búsqueda de hasta 100 vecinos más cercanos y limitan los resultados a solo 10 documentos. Los queries también especifican una etapa $project para realizar las siguientes acciones:
Excluye el campo
_ide incluye solo los campostitle,genres,plotyyearen los resultados.Añada un campo llamado
scoreque muestre la puntuación de búsqueda vectorial de cada documento en los resultados.
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string kids adventure. Especifica múltiples operadores del query de comparación por campo para prefiltrar los documentos con los que se relacionará la búsqueda semántica.
El filtro utiliza el operador de pipeline de agregación $and para encontrar documentos de películas que coincidan con los dos criterios siguientes:
Filtra por el campo
genrespara encontrar películas que no sean del génerodrama,westernocrime, sino del géneroaction,adventureofamily.Filtra por el campo
yearpara encontrar películas que se estrenaron entre los años1960y2000, ambos inclusive.
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, 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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 }
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string star wars. Especifica el pipeline de agregación y los operadores del query de comparación para demostrar un uso combinado de los operadores para filtrar los datos.
El filtro utiliza el operador de pipeline de agregación $or para encontrar documentos de películas que coincidan con cualquiera de los siguientes criterios:
Filtra por el campo
genrespara encontrar películas que no sean de génerocrime.Filtra por el campo
yearpara encontrar las películas que se estrenaron en el año2015, o antes, y por el campogenrespara encontrar películas del géneroaction.
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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-0.008301229, -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 }
Reemplaza el <connection-string> en la query y luego guarda el archivo.
Se debe sustituir <connection-string> por la cadena de conexión del clúster Atlas o de la implementación local de Atlas.
Su cadena de conexión debe usar el siguiente formato:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
Para obtener más información,consulte Conectarse a un clúster a través de bibliotecas de cliente.
Su cadena de conexión debe usar el siguiente formato:
mongodb://localhost:<port-number>/?directConnection=true
Para obtener más información, consulta Cadenas de conexión.
Compile y ejecute el archivo AtlasVectorSearchTutorial.go.
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
Copie y pegue el código del operador de prefiltro que desea probar en el AtlasVectorSearchTutorial.java archivo.
Las siguientes consultas utilizan la etapa de pipeline $vectorSearch para la búsqueda de películas que coincidan con las incrustaciones vectoriales especificadas. Los queries especifican una búsqueda de hasta 100 vecinos más cercanos y limitan los resultados a solo 10 documentos. Los queries también especifican una etapa $project para realizar las siguientes acciones:
Excluye el campo
_ide incluye solo los campostitle,genres,plotyyearen los resultados.Añada un campo llamado
scoreque muestre la puntuación de búsqueda vectorial de cada documento en los resultados.
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string kids adventure. Especifica múltiples operadores del query de comparación por campo para prefiltrar los documentos con los que se relacionará la búsqueda semántica.
El filtro utiliza el operador de pipeline de agregación $and para encontrar documentos de películas que coincidan con los dos criterios siguientes:
Filtra por el campo
genrespara encontrar películas que no sean del génerodrama,westernocrime, sino del géneroaction,adventureofamily.Filtra por el campo
yearpara encontrar películas que se estrenaron entre los años1960y2000, ambos inclusive.
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 }
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string star wars. Especifica el pipeline de agregación y los operadores del query de comparación para demostrar un uso combinado de los operadores para filtrar los datos.
El filtro utiliza el operador de pipeline de agregación $or para encontrar documentos de películas que coincidan con cualquiera de los siguientes criterios:
Filtra por el campo
genrespara encontrar películas que no sean de génerocrime.Filtra por el campo
yearpara encontrar las películas que se estrenaron en el año2015, o antes, y por el campogenrespara encontrar películas del géneroaction.
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 }
Reemplaza el <connection-string> en la query y luego guarda el archivo.
Se debe sustituir <connection-string> por la cadena de conexión del clúster Atlas o de la implementación local de Atlas.
Su cadena de conexión debe usar el siguiente formato:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
Para obtener más información,consulte Conectarse a un clúster a través de bibliotecas de cliente.
Su cadena de conexión debe usar el siguiente formato:
mongodb://localhost:<port-number>/?directConnection=true
Para obtener más información, consulta Cadenas de conexión.
Compile y ejecute el archivo AtlasVectorSearchTutorial.java.
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 }
Copie y pegue la consulta de muestra para el operador de prefiltro que desea probar en el atlas-vector-search-tutorial.js archivo.
Las siguientes consultas utilizan la etapa de pipeline $vectorSearch para la búsqueda de películas que coincidan con las incrustaciones vectoriales especificadas. Los queries especifican una búsqueda de hasta 100 vecinos más cercanos y limitan los resultados a solo 10 documentos. Los queries también especifican una etapa $project para realizar las siguientes acciones:
Excluye el campo
_ide incluye solo los campostitle,genres,plotyyearen los resultados.Añada un campo llamado
scoreque muestre la puntuación de búsqueda vectorial de cada documento en los resultados.
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string kids adventure. Especifica múltiples operadores del query de comparación por campo para prefiltrar los documentos con los que se relacionará la búsqueda semántica.
El filtro utiliza el operador de pipeline de agregación $and para encontrar documentos de películas que coincidan con los dos criterios siguientes:
Filtra por el campo
genrespara encontrar películas que no sean del génerodrama,westernocrime, sino del géneroaction,adventureofamily.Filtra por el campo
yearpara encontrar películas que se estrenaron entre los años1960y2000, ambos inclusive.
1 const { MongoClient } = require("mongodb"); 2 3 // connect to your Atlas cluster 4 const uri = "<connection-string>"; 5 6 const client = new MongoClient(uri); 7 8 async function run() { 9 try { 10 await client.connect(); 11 12 // set namespace 13 const database = client.db("sample_mflix"); 14 const coll = database.collection("embedded_movies"); 15 16 // define pipeline 17 const agg = [ 18 { 19 '$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);
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string star wars. Especifica el pipeline de agregación y los operadores del query de comparación para demostrar un uso combinado de los operadores para filtrar los datos.
El filtro utiliza el operador de pipeline de agregación $or para encontrar documentos de películas que coincidan con cualquiera de los siguientes criterios:
Filtra por el campo
genrespara encontrar películas que no sean de génerocrime.Filtra por el campo
yearpara encontrar las películas que se estrenaron en el año2015, o antes, y por el campogenrespara encontrar películas del géneroaction.
1 const { MongoClient } = require("mongodb"); 2 3 // connect to your Atlas cluster 4 const uri = "<connection-string>"; 5 6 const client = new MongoClient(uri); 7 8 async function run() { 9 try { 10 await client.connect(); 11 12 // set namespace 13 const database = client.db("sample_mflix"); 14 const coll = database.collection("embedded_movies"); 15 16 // define pipeline 17 const agg = [ 18 { 19 '$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);
Reemplaza el <connection-string> en la query y luego guarda el archivo.
Se debe sustituir <connection-string> por la cadena de conexión del clúster Atlas o de la implementación local de Atlas.
Su cadena de conexión debe usar el siguiente formato:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
Para obtener más información,consulte Conectarse a un clúster a través de bibliotecas de cliente.
Su cadena de conexión debe usar el siguiente formato:
mongodb://localhost:<port-number>/?directConnection=true
Para obtener más información, consulta Cadenas de conexión.
Consultar la colección.
Ejecute el siguiente comando para consultar su colección:
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}'
Copie y pegue la consulta del operador de prefiltro que desea probar en el atlas-vector-search-tutorial.py archivo.
Las siguientes consultas utilizan la etapa de pipeline $vectorSearch para la búsqueda de películas que coincidan con las incrustaciones vectoriales especificadas. Los queries especifican una búsqueda de hasta 100 vecinos más cercanos y limitan los resultados a solo 10 documentos. Los queries también especifican una etapa $project para realizar las siguientes acciones:
Excluye el campo
_ide incluye solo los campostitle,genres,plotyyearen los resultados.Añada un campo llamado
scoreque muestre la puntuación de búsqueda vectorial de cada documento en los resultados.
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string kids adventure. Especifica múltiples operadores del query de comparación por campo para prefiltrar los documentos con los que se relacionará la búsqueda semántica.
El filtro utiliza el operador de pipeline de agregación $and para encontrar documentos de películas que coincidan con los dos criterios siguientes:
Filtra por el campo
genrespara encontrar películas que no sean del génerodrama,westernocrime, sino del géneroaction,adventureofamily.Filtra por el campo
yearpara encontrar películas que se estrenaron entre los años1960y2000, ambos inclusive.
1 import pymongo 2 3 # connect to your Atlas cluster 4 client = pymongo.MongoClient("<connection-string>") 5 6 # define pipeline 7 pipeline = [ 8 { 9 '$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)
El siguiente query busca en el campo plot_embedding_voyage_3_large utilizando las incrustaciones vectoriales para el string star wars. Especifica el pipeline de agregación y los operadores del query de comparación para demostrar un uso combinado de los operadores para filtrar los datos.
El filtro utiliza el operador de pipeline de agregación $or para encontrar documentos de películas que coincidan con cualquiera de los siguientes criterios:
Filtra por el campo
genrespara encontrar películas que no sean de génerocrime.Filtra por el campo
yearpara encontrar las películas que se estrenaron en el año2015, o antes, y por el campogenrespara encontrar películas del géneroaction.
1 import pymongo 2 3 # connect to your Atlas cluster 4 client = pymongo.MongoClient("<connection-string>") 5 6 # define pipeline 7 pipeline = [ 8 { 9 '$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)
Reemplaza el <connection-string> en la query y luego guarda el archivo.
Se debe sustituir <connection-string> por la cadena de conexión del clúster Atlas o de la implementación local de Atlas.
Su cadena de conexión debe usar el siguiente formato:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
Para obtener más información,consulte Conectarse a un clúster a través de bibliotecas de cliente.
Su cadena de conexión debe usar el siguiente formato:
mongodb://localhost:<port-number>/?directConnection=true
Para obtener más información, consulta Cadenas de conexión.
Se debe ejecutar el comando para ejecutar una query sobre la colección.
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}