This tutorial describes how to perform an ANN search on a vector in
the plot_embedding_voyage_3_large field in the sample_mflix.embedded_movies
collection on your Atlas cluster. To demonstrate this, it takes
you through the following steps:
Create an Atlas Vector Search index on the numeric field named
plot_embedding_voyage_3_largein thesample_mflix.embedded_moviescollection.Run Atlas Vector Search queries against the
plot_embedding_voyage_3_largefield in thesample_mflix.embedded_moviescollection.
➤ Use the Select your language drop-down menu to select the client to use to create the Atlas Vector Search index and run queries.
Prerequisites
Before you begin, complete the common prerequisites. This tutorial includes examples for the following clients:
Create the Atlas Vector Search Index
This section demonstrates how to create an Atlas Vector Search index on the
plot_embedding_voyage_3_large field in the sample_mflix.embedded_movies
collection for running vector queries against the field.
Required Access
To create an Atlas Vector Search index, you must have Project Data Access Admin or higher access to the project.
Procedure
1
In Atlas, go to the Clusters page for your project.
WARNING: Navigation Improvements In Progress We're currently rolling out a new and improved navigation experience. If the following steps don't match your view in the Atlas UI, see the preview documentation.
If it's not already displayed, select the organization that contains your desired project from the Organizations menu in the navigation bar.
If it's not already displayed, select your desired project from the Projects menu in the navigation bar.
If it's not already displayed, click Clusters in the sidebar.
The Clusters page displays.
2
4
Start your index configuration.
Make the following selections on the page and then click Next.
Search Type | Select the Vector Search index type. |
Index Name and Data Source | Specify the following information:
|
Configuration Method | For a guided experience, select Visual Editor. To edit the raw index definition, select JSON Editor. |
Note
Your Atlas Search index is named default by default. If you keep this name, then your index will be the
default Search index for any Atlas Search query that does not specify a different index option in
its operators. If you are creating multiple indexes, we recommend
that you maintain a consistent, descriptive naming convention across your indexes.
5
Define the Atlas Vector Search index.
In this step, you define an index of the vectorSearch type for the following fields:
plot_embedding_voyage_3_largefield as the vector type. Theplot_embedding_voyage_3_largefield contains embeddings created using Voyage AI'svoyage-3-largeembedding model. The index definition specifies2048vector dimensions and measures similarity usingdotProduct.genresfield as the filter type for pre-filtering data by string values in the field.yearfield as the filter type for pre-filtering data by numeric values in the field.
Atlas automatically detects fields that contain vector embeddings,
as well as their corresponding dimensions. For the sample_mflix.embedded_movies
collection, the plot_embedding and plot_embedding_voyage_3_large
fields displays. For this tutorial, you need to index only
the plot_embedding_voyage_3_large field.
To configure the index, do the following:
Select Dot Product from the Similarity Method dropdown.
Click Advanced, then select Scalar quantization from the dropdown menu.
In the Filter Field section, specify the
genresandyearfields to filter the data by.
Replace the default definition with the following index definition.
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 }
7
9
Check the status.
The newly created index displays on the Atlas Search tab. While the index is building, the Status field reads Build in Progress. When the index is finished building, the Status field reads Active.
Note
Larger collections take longer to index. You will receive an email notification when your index is finished building.
1
Connect to your cluster in mongosh.
Open mongosh in a terminal window and connect to your
cluster. For detailed instructions on connecting, see
Connect via mongosh.
2
3
Run the db.collection.createSearchIndex() method.
The following index definition indexes the
plot_embedding_voyage_3_large field as the vector type
and the genres and year fields as the filter type.
The plot_embedding_voyage_3_large field contains 2048 vector
dimension embeddings created using Voyage AI's voyage-3-large
embedding model. The index measures similarity using dotProduct
function.
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 );
1
2
Define the index.
Create a file named IndexService.cs and copy and paste the
following code into the file.
This index definition indexes the
plot_embedding_voyage_3_large field as the vector type and
the genres and year fields as the filter type in an
Atlas Vector Search index. The plot_embedding_voyage_3_large field
contains embeddings created using Voyage AI's voyage-3-large
embedding model. The index definition specifies 2048 vector
dimensions and measures similarity using dotProduct function.
IndexService.cs
1 namespace query_quick_start; 2 3 using MongoDB.Bson; 4 using MongoDB.Driver; 5 using System; 6 using System.Threading; 7 8 public class IndexService 9 { 10 // Replace the placeholder with your Atlas connection string 11 private const string MongoConnectionString = "<connection-string>"; 12 public void CreateVectorIndex() 13 { 14 try 15 { 16 // Connect to your Atlas cluster 17 var client = new MongoClient(MongoConnectionString); 18 var database = client.GetDatabase("sample_mflix"); 19 var collection = database.GetCollection<BsonDocument>("embedded_movies"); 20 21 var searchIndexView = collection.SearchIndexes; 22 var name = "vector_index"; 23 var type = SearchIndexType.VectorSearch; 24 25 var definition = new BsonDocument 26 { 27 { "fields", new BsonArray 28 { 29 new BsonDocument 30 { 31 { "type", "vector" }, 32 { "path", "plot_embedding_voyage_3_large" }, 33 { "numDimensions", 2048 }, 34 { "similarity", "dotProduct" }, 35 { "quantization", "scalar"} 36 }, 37 new BsonDocument 38 { 39 {"type", "filter"}, 40 {"path", "genres"} 41 }, 42 new BsonDocument 43 { 44 {"type", "filter"}, 45 {"path", "year"} 46 } 47 } 48 } 49 }; 50 51 var model = new CreateSearchIndexModel(name, type, definition); 52 53 searchIndexView.CreateOne(model); 54 Console.WriteLine($"New search index named {name} is building."); 55 56 // Polling for index status 57 Console.WriteLine("Polling to check if the index is ready. This may take up to a minute."); 58 bool queryable = false; 59 while (!queryable) 60 { 61 var indexes = searchIndexView.List(); 62 foreach (var index in indexes.ToEnumerable()) 63 { 64 if (index["name"] == name) 65 { 66 queryable = index["queryable"].AsBoolean; 67 } 68 } 69 if (!queryable) 70 { 71 Thread.Sleep(5000); 72 } 73 } 74 Console.WriteLine($"{name} is ready for querying."); 75 } 76 catch (Exception e) 77 { 78 Console.WriteLine($"Exception: {e.Message}"); 79 } 80 } 81 }
3
Replace the <connection-string> in the code and then save the file.
Replace <connection-string> with the connection string for your
Atlas cluster or local Atlas deployment.
Your connection string should use the following format:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
To learn more, see Connect to a Cluster via Drivers.
Your connection string should use the following format:
mongodb://localhost:<port-number>/?directConnection=true
To learn more, see Connection Strings.
4
1
2
Define the index.
Create a file named vector-index.go and copy and paste the
following code into the file.
This index definition indexes the plot_embedding_voyage_3_large field
as the vector type and the genres and year fields
as the filter type in an Atlas Vector Search index. The plot_embedding_voyage_3_large
field contains embeddings created using Voyage AI's
voyage-3-large embedding model. The index definition
specifies 2048 vector dimensions and measures similarity using
dotProduct function.
vector-index.go
1 package main 2 3 import ( 4 "context" 5 "fmt" 6 "log" 7 "time" 8 9 "go.mongodb.org/mongo-driver/v2/bson" 10 "go.mongodb.org/mongo-driver/v2/mongo" 11 "go.mongodb.org/mongo-driver/v2/mongo/options" 12 ) 13 14 func main() { 15 ctx := context.Background() 16 17 // Replace the placeholder with your Atlas connection string 18 const uri = "<connectionString>" 19 20 // Connect to your Atlas cluster 21 clientOptions := options.Client().ApplyURI(uri) 22 client, err := mongo.Connect(clientOptions) 23 if err != nil { 24 log.Fatalf("failed to connect to the server: %v", err) 25 } 26 defer func() { _ = client.Disconnect(ctx) }() 27 28 // Set the namespace 29 coll := client.Database("sample_mflix").Collection("embedded_movies") 30 indexName := "vector_index" 31 opts := options.SearchIndexes().SetName(indexName).SetType("vectorSearch") 32 33 type vectorDefinitionField struct { 34 Type string `bson:"type"` 35 Path string `bson:"path"` 36 NumDimensions int `bson:"numDimensions"` 37 Similarity string `bson:"similarity"` 38 Quantization string `bson:"quantization"` 39 } 40 41 type filterField struct { 42 Type string `bson:"type"` 43 Path string `bson:"path"` 44 } 45 46 type indexDefinition struct { 47 Fields []vectorDefinitionField `bson:"fields"` 48 } 49 50 vectorDefinition := vectorDefinitionField{ 51 Type: "vector", 52 Path: "plot_embedding_voyage_3_large", 53 NumDimensions: 2048, 54 Similarity: "dotProduct", 55 Quantization: "scalar"} 56 genreFilterDefinition := filterField{"filter", "genres"} 57 yearFilterDefinition := filterField{"filter", "year"} 58 59 indexModel := mongo.SearchIndexModel{ 60 Definition: bson.D{{Key: "fields", Value: [3]interface{}{ 61 vectorDefinition, 62 genreFilterDefinition, 63 yearFilterDefinition}}}, 64 Options: opts, 65 } 66 67 // Create the index 68 searchIndexName, err := coll.SearchIndexes().CreateOne(ctx, indexModel) 69 if err != nil { 70 log.Fatalf("failed to create the search index: %v", err) 71 } 72 log.Println("New search index named " + searchIndexName + " is building.") 73 74 // Await the creation of the index. 75 log.Println("Polling to check if the index is ready. This may take up to a minute.") 76 searchIndexes := coll.SearchIndexes() 77 var doc bson.Raw 78 for doc == nil { 79 cursor, err := searchIndexes.List(ctx, options.SearchIndexes().SetName(searchIndexName)) 80 if err != nil { 81 fmt.Errorf("failed to list search indexes: %w", err) 82 } 83 84 if !cursor.Next(ctx) { 85 break 86 } 87 88 name := cursor.Current.Lookup("name").StringValue() 89 queryable := cursor.Current.Lookup("queryable").Boolean() 90 if name == searchIndexName && queryable { 91 doc = cursor.Current 92 } else { 93 time.Sleep(5 * time.Second) 94 } 95 } 96 97 log.Println(searchIndexName + " is ready for querying.") 98 }
3
Replace the <connection-string> in the code and then save the file.
Replace <connection-string> with the connection string for your
Atlas cluster or local Atlas deployment.
Your connection string should use the following format:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
To learn more, see Connect to a Cluster via Drivers.
Your connection string should use the following format:
mongodb://localhost:<port-number>/?directConnection=true
To learn more, see Connection Strings.
1
Add the MongoDB Java Sync Driver to your project.
Add the Java driver version 5.2 or higher as a dependency in your project, depending on your package manager:
If you are using Maven, add the following dependencies to the
dependenciesarray in your project'spom.xmlfile: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> Run your package manager to install the dependencies to your project.
For more detailed installation instructions and version compatibility, see the MongoDB Java Driver documentation.
2
Define the index.
Create a file named VectorIndex.java and copy and paste the
following code into the file.
This index definition indexes the
plot_embedding_voyage_3_large field as the vector type and
the genres and year fields as the filter type in an
Atlas Vector Search index. The plot_embedding_voyage_3_large field
contains embeddings created using Voyage AI's voyage-3-large
embedding model. The index definition specifies 2048 vector
dimensions and measures similarity using dotProduct function.
VectorIndex.java
1 import com.mongodb.client.MongoClient; 2 import com.mongodb.client.MongoClients; 3 import com.mongodb.client.MongoCollection; 4 import com.mongodb.client.MongoDatabase; 5 import com.mongodb.client.model.SearchIndexModel; 6 import com.mongodb.client.model.SearchIndexType; 7 import org.bson.Document; 8 import org.bson.conversions.Bson; 9 10 import java.util.Arrays; 11 import java.util.Collections; 12 import java.util.List; 13 14 public class VectorIndex { 15 16 public static void main(String[] args) { 17 18 // Replace the placeholder with your Atlas connection string 19 String uri = "<connectionString>"; 20 21 // Connect to your Atlas cluster 22 try (MongoClient mongoClient = MongoClients.create(uri)) { 23 24 // Set the namespace 25 MongoDatabase database = mongoClient.getDatabase("sample_mflix"); 26 MongoCollection<Document> collection = database.getCollection("embedded_movies"); 27 28 // Define the index details with the filter fields 29 String indexName = "vector_index"; 30 Bson definition = new Document( 31 "fields", 32 Arrays.asList( 33 new Document("type", "vector") 34 .append("path", "plot_embedding_voyage_3_large") 35 .append("numDimensions", 2048) 36 .append("similarity", "dotProduct") 37 .append("quantization", "scalar"), 38 new Document("type", "filter") 39 .append("path", "genres"), 40 new Document("type", "filter") 41 .append("path", "year"))); 42 43 // Define the index model 44 SearchIndexModel indexModel = new SearchIndexModel( 45 indexName, 46 definition, 47 SearchIndexType.vectorSearch()); 48 49 // Create the index using the defined model 50 List<String> result = collection.createSearchIndexes(Collections.singletonList(indexModel)); 51 System.out.println("Successfully created vector index named: " + result.get(0)); 52 System.out.println("It may take up to a minute for the index to leave the BUILDING status and become queryable."); 53 54 // Wait for index to build and become queryable 55 System.out.println("Polling to confirm the index has left the BUILDING status."); 56 // No special handling in case of a timeout. Custom handling can be implemented. 57 waitForIndex(collection, indexName); 58 } 59 } 60 61 /** 62 * Polls the collection to check whether the specified index is ready to query. 63 */ 64 public static <T> boolean waitForIndex(final MongoCollection<T> collection, final String indexName) { 65 long startTime = System.nanoTime(); 66 long timeoutNanos = TimeUnit.SECONDS.toNanos(60); 67 while (System.nanoTime() - startTime < timeoutNanos) { 68 Document indexRecord = StreamSupport.stream(collection.listSearchIndexes().spliterator(), false) 69 .filter(index -> indexName.equals(index.getString("name"))) 70 .findAny().orElse(null); 71 if (indexRecord != null) { 72 if ("FAILED".equals(indexRecord.getString("status"))) { 73 throw new RuntimeException("Search index has FAILED status."); 74 } 75 if (indexRecord.getBoolean("queryable")) { 76 System.out.println(indexName + " index is ready to query"); 77 return true; 78 } 79 } 80 try { 81 Thread.sleep(100); // busy-wait, avoid in production 82 } catch (InterruptedException e) { 83 Thread.currentThread().interrupt(); 84 throw new RuntimeException(e); 85 } 86 } 87 return false; 88 } 89 }
3
Replace the <connection-string> in the code and then save the file.
Replace <connection-string> with the connection string for your
Atlas cluster or local Atlas deployment.
Your connection string should use the following format:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
To learn more, see Connect to a Cluster via Drivers.
Your connection string should use the following format:
mongodb://localhost:<port-number>/?directConnection=true
To learn more, see Connection Strings.
4
Run the file to create the index.
Run the file in your IDE, or execute a command from the command line to run the code.
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
1
2
Define the index.
Create a file named vector-index.js and copy and paste the
following code into the file.
This index definition indexes the
plot_embedding_voyage_3_large field as the vector type and
the genres and year fields as the filter type in an
Atlas Vector Search index. The plot_embedding_voyage_3_large field
contains embeddings created using Voyage AI's voyage-3-large
embedding model. The index definition specifies 2048 vector
dimensions and measures similarity using dotProduct function.
vector-index.js
1 const { MongoClient } = require("mongodb"); 2 3 // connect to your Atlas deployment 4 const uri = "<connectionString>"; 5 6 const client = new MongoClient(uri); 7 8 async function run() { 9 try { 10 const database = client.db("sample_mflix"); 11 const collection = database.collection("embedded_movies"); 12 13 // define your Atlas 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);
3
Replace the <connection-string> in the code and then save the file.
Replace <connection-string> with the connection string for your
Atlas cluster or local Atlas deployment.
Your connection string should use the following format:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
To learn more, see Connect to a Cluster via Drivers.
Your connection string should use the following format:
mongodb://localhost:<port-number>/?directConnection=true
To learn more, see Connection Strings.
1
2
Define the index.
Create a file named vector-index.py and copy and paste the
following code into the file.
This index definition indexes the
plot_embedding_voyage_3_large field as the vector type and
the genres and year fields as the filter type in an
Atlas Vector Search index. The plot_embedding_voyage_3_large field
contains embeddings created using Voyage AI's voyage-3-large
embedding model. The index definition specifies 2048 vector
dimensions, measures similarity using dotProduct function, and
enables automatic scalar quantization for efficient processing
of your vectors.
vector-index.py
1 from pymongo.mongo_client import MongoClient 2 from pymongo.operations import SearchIndexModel 3 import time 4 5 # Connect to your Atlas deployment 6 uri = "<connectionString>" 7 client = MongoClient(uri) 8 9 # Access your database and collection 10 database = client["sample_mflix"] 11 collection = database["embedded_movies"] 12 13 # Create your index model, then create the search index 14 search_index_model = SearchIndexModel( 15 definition={ 16 "fields": [ 17 { 18 "type": "vector", 19 "path": "plot_embedding_voyage_3_large", 20 "numDimensions": 2048, 21 "similarity": "dotProduct", 22 "quantization": "scalar" 23 }, 24 { 25 "type": "filter", 26 "path": "genres" 27 }, 28 { 29 "type": "filter", 30 "path": "year" 31 } 32 ] 33 }, 34 name="vector_index", 35 type="vectorSearch" 36 ) 37 38 result = collection.create_search_index(model=search_index_model) 39 print("New search index named " + result + " is building.") 40 41 # Wait for initial sync to complete 42 print("Polling to check if the index is ready. This may take up to a minute.") 43 predicate=None 44 if predicate is None: 45 predicate = lambda index: index.get("queryable") is True 46 47 while True: 48 indices = list(collection.list_search_indexes(result)) 49 if len(indices) and predicate(indices[0]): 50 break 51 time.sleep(5) 52 print(result + " is ready for querying.") 53 54 client.close()
3
Replace the <connection-string> in the code and then save the file.
Replace <connection-string> with the connection string for your
Atlas cluster or local Atlas deployment.
Your connection string should use the following format:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
To learn more, see Connect to a Cluster via Drivers.
Your connection string should use the following format:
mongodb://localhost:<port-number>/?directConnection=true
To learn more, see Connection Strings.
Run Queries Using the $vectorSearch Aggregation Pipeline Stage
Overview
This section demonstrates how to query the indexed vector data in
the sample_mflix.embedded_movies collection using the
the $vectorSearch stage. These sample queries also demonstrate
the various query and aggregation
pipeline operators that we can use
in the query to pre-filter the data that we perform the semantic
search on.
Procedure
1
Prepare your query embeddings.
Save the following embeddings in a file named query-embeddings.js:
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2
Connect to your cluster in mongosh.
Open mongosh in a terminal window and connect to your
cluster. For detailed instructions on connecting, see
Connect via mongosh.
3
5
Run the semantic search query against the indexed fields.
The following queries use the $vectorSearch pipeline stage
to search for movies that match the specified vector embeddings. The queries
specify a search for up to 100 nearest neighbors and limit the
results to 10 documents only. The queries also specify a
$project stage to perform the following actions:
Exclude the
_idfield and include only thetitle,genres,plot, andyearfields in the results.Add a field named
scorethat shows the vector search score for each document in the results.
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string kids adventure. It specifies multiple
comparison query operators per field to pre-filter the documents
against which to perform the semantic search.
The filter uses the $and aggregation pipeline operator to find
movie documents that match both the following criteria:
Filter by the
genresfield to find movies that aren't in thedrama,western, orcrimegenre, but in theaction,adventure, orfamilygenre.Filter by the
yearfield to find movies that were released between the years1960and2000, both inclusive.
1 db.embedded_movies.aggregate([ 2 { 3 "$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 ]
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string star wars. It specifies aggregation pipeline and
comparison query operators to demonstrate a combined use of the
operators to filter the data.
The filter uses the $or aggregation pipeline operator to find
movie documents that match either one of the following criteria:
Filter by the
genresfield to find movies that aren't in thecrimegenre.Filter by the
yearfield to find movies that were released in or before the year2015and by thegenresfield to find movies in theactiongenre.
1 db.embedded_movies.aggregate([ 2 { 3 "$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 ]
1
Prepare your query embeddings.
Save the following embeddings in a file named query-embeddings.js:
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2
Connect to your cluster in mongosh.
Open mongosh in a terminal window and connect to your
cluster. For detailed instructions on connecting, see
Connect via mongosh.
3
5
Run the semantic search query against the indexed fields.
The following queries use the $vectorSearch pipeline stage
to search for movies that match the specified vector embeddings. The queries
specify a search for up to 100 nearest neighbors and limit the
results to 10 documents only. The queries also specify a
$project stage to perform the following actions:
Exclude the
_idfield and include only thetitle,genres,plot, andyearfields in the results.Add a field named
scorethat shows the vector search score for each document in the results.
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string kids adventure. It specifies multiple
comparison query operators per field to pre-filter the documents
against which to perform the semantic search.
The filter uses the $and aggregation pipeline operator to find
movie documents that match both the following criteria:
Filter by the
genresfield to find movies that aren't in thedrama,western, orcrimegenre, but in theaction,adventure, orfamilygenre.Filter by the
yearfield to find movies that were released between the years1960and2000, both inclusive.
1 db.embedded_movies.aggregate([ 2 { 3 "$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 ]
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string star wars. It specifies aggregation pipeline and
comparison query operators to demonstrate a combined use of the
operators to filter the data.
The filter uses the $or aggregation pipeline operator to find
movie documents that match either one of the following criteria:
Filter by the
genresfield to find movies that aren't in thecrimegenre.Filter by the
yearfield to find movies that were released in or before the year2015and by thegenresfield to find movies in theactiongenre.
1 db.embedded_movies.aggregate([ 2 { 3 "$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 ]
2
Copy and paste the code for the pre-filter operator you want to try into the DataService.cs file.
The following queries use the $vectorSearch pipeline stage
to search for movies that match the specified vector embeddings. The queries
specify a search for up to 100 nearest neighbors and limit the
results to 10 documents only. The queries also specify a
$project stage to perform the following actions:
Exclude the
_idfield and include only thetitle,genres,plot, andyearfields in the results.Add a field named
scorethat shows the vector search score for each document in the results.
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string kids adventure. It specifies multiple
comparison query operators per field to pre-filter the documents
against which to perform the semantic search.
The filter uses the $and aggregation pipeline operator to find
movie documents that match both the following criteria:
Filter by the
genresfield to find movies that aren't in thedrama,western, orcrimegenre, but in theaction,adventure, orfamilygenre.Filter by the
yearfield to find movies that were released between the years1960and2000, both inclusive.
DataService.cs
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 }
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string star wars. It specifies aggregation pipeline and
comparison query operators to demonstrate a combined use of the
operators to filter the data.
The filter uses the $or aggregation pipeline operator to find
movie documents that match either one of the following criteria:
Filter by the
genresfield to find movies that aren't in thecrimegenre.Filter by the
yearfield to find movies that were released in or before the year2015and by thegenresfield to find movies in theactiongenre.
DataService.cs
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 }
3
Replace the <connection-string> in the query and then save the file.
Replace <connection-string> with the connection string for your
Atlas cluster or local Atlas deployment.
Your connection string should use the following format:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
To learn more, see Connect to a Cluster via Drivers.
Your connection string should use the following format:
mongodb://localhost:<port-number>/?directConnection=true
To learn more, see Connection Strings.
4
Update Program.cs.
Update Program.cs to initialize the DataService and call the
method to perform the query.
Program.cs
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 }
5
Save and run the project.
Save the file, and then compile and run your project to perform the 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 }
2
Copy and paste the code for the pre-filter operator you want to try into the AtlasVectorSearchTutorial.go file.
The following queries use the $vectorSearch pipeline stage
to search for movies that match the specified vector embeddings. The queries
specify a search for up to 100 nearest neighbors and limit the
results to 10 documents only. The queries also specify a
$project stage to perform the following actions:
Exclude the
_idfield and include only thetitle,genres,plot, andyearfields in the results.Add a field named
scorethat shows the vector search score for each document in the results.
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string kids adventure. It specifies multiple
comparison query operators per field to pre-filter the documents
against which to perform the semantic search.
The filter uses the $and aggregation pipeline operator to find
movie documents that match both the following criteria:
Filter by the
genresfield to find movies that aren't in thedrama,western, orcrimegenre, but in theaction,adventure, orfamilygenre.Filter by the
yearfield to find movies that were released between the years1960and2000, both inclusive.
1 package main 2 3 import ( 4 "context" 5 "fmt" 6 "log" 7 8 "go.mongodb.org/mongo-driver/bson" 9 "go.mongodb.org/mongo-driver/mongo" 10 "go.mongodb.org/mongo-driver/mongo/options" 11 ) 12 13 func main() { 14 ctx := context.Background() 15 16 // Replace the placeholder with your Atlas connection string 17 const uri = "<connection-string>" 18 19 // Connect to your Atlas cluster 20 clientOptions := options.Client().ApplyURI(uri) 21 client, err := mongo.Connect(ctx, clientOptions) 22 if err != nil { 23 log.Fatalf("failed to connect to the server: %v", err) 24 } 25 defer func() { _ = client.Disconnect(ctx) }() 26 27 // Set the namespace 28 coll := client.Database("sample_mflix").Collection("embedded_movies") 29 30 queryVector := [2048]float64{ 31 -0.021090532, -0.026399033, -0.024103465, -0.025538195, -0.000549233, 0.011836523, -0.013199517, -0.003766167, -0.005165028, -0.02238179, 0.037876874, 0.010617003, 0.010903949, -0.001354026, 0.006850836, -0.018005863, -0.02195137, 0.019512329, 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0.024533885, 0.032568373, 0.028694602, -0.021090532, -0.019942747, 0.054806691, -0.004483532, -0.020086221, -0.01599724, 0.018651491, 0.020373167, 0.000504397, -0.007424728, -0.063702017, -0.014203828, 0.030846696, -0.006599758, -0.027259871, -0.024103465, -0.020660114, -0.004985687, 0.005559579, -0.034146577, -0.011549577, -0.00173961, 0.008321434, 0.007030177, -0.015638558, 32 } 33 34 genresFilterCondition := bson.D{ 35 {"$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 }
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string star wars. It specifies aggregation pipeline and
comparison query operators to demonstrate a combined use of the
operators to filter the data.
The filter uses the $or aggregation pipeline operator to find
movie documents that match either one of the following criteria:
Filter by the
genresfield to find movies that aren't in thecrimegenre.Filter by the
yearfield to find movies that were released in or before the year2015and by thegenresfield to find movies in theactiongenre.
1 package main 2 3 import ( 4 "context" 5 "fmt" 6 "log" 7 8 "go.mongodb.org/mongo-driver/bson" 9 "go.mongodb.org/mongo-driver/mongo" 10 "go.mongodb.org/mongo-driver/mongo/options" 11 ) 12 13 func main() { 14 ctx := context.Background() 15 16 // Replace the placeholder with your Atlas connection string 17 const uri = "<connection-string>" 18 19 // Connect to your Atlas cluster 20 clientOptions := options.Client().ApplyURI(uri) 21 client, err := mongo.Connect(ctx, clientOptions) 22 if err != nil { 23 log.Fatalf("failed to connect to the server: %v", err) 24 } 25 defer func() { _ = client.Disconnect(ctx) }() 26 27 // Set the namespace 28 coll := client.Database("sample_mflix").Collection("embedded_movies") 29 30 queryVector := [2048]float64{ 31 -0.025189938, 0.014741838, -0.013024342, -0.0197512, 0.011235285, 0.004651551, 0.043509893, 0.003112961, 0.013310592, -0.033348043, 0.037212405, -0.021039322, -0.026048684, 0.012809656, 0.029483676, 0.003578116, -0.044654887, 0.032632418, 0.014312465, -0.058967352, 0.025333062, -0.055246111, 0.02189807, -0.017604331, -0.002880384, 0.045227386, 0.004794675, 0.017604331, 0.023186192, -0.054673612, -0.011306847, -0.012523406, -0.012380281, 0.002540462, 0.015958399, -0.042364895, -0.001467028, -0.020180576, -0.058108605, -0.035065539, 0.010090288, -0.033348043, 0.058394853, -0.013883091, 0.002048471, -0.020753073, -0.029769925, 0.031916797, -0.014741838, -0.040933646, -0.004096943, 0.020753073, -0.002540462, 0.028052431, -0.02404494, 0.006547953, -0.003578116, 0.003757022, 0.019178702, -0.037784904, -0.02833868, 0.01753277, 0.029769925, 0.017747456, -0.031344298, 0.022899942, 0.006333265, 0.010376536, -0.024474313, -0.012094032, -0.004651551, 0.007764512, 0.017962143, 0.013811528, 0.037212405, -0.03148742, 0.000666424, 0.024474313, -0.021325571, 0.041219898, 0.011235285, 0.046658635, 0.019035578, 0.020753073, 0.010662786, -0.001726441, -0.012738093, -0.027193682, -0.014598713, -0.013167467, 0.013596841, 0.001932183, 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-0.031916797, -0.0301993, 0.032203045, -0.003757022, 0.017174957, 0.033491168, 0.003900147, 0.002325775, 0.006726858, 0.020180576, 0.017389644, 0.009088415, 0.018319955, -0.003631788, 0.00586811, -0.006691077, -0.014240902, -0.009052633, 0.031630546, 0.04436864, -0.022899942, -0.003327648, -0.006691077, 0.013310592, -0.035924286, -0.008158104, -0.005116706, -0.040647399, 0.002397338, 0.014455589, -0.030342424, 0.028624929, -0.031773672, 0.043509893, -0.001833785, -0.025619311, 0.032775544, -0.046944883, 0.013739966, -0.030485548, 0.018319955, 0.016745584, -0.020323699, -0.015815273, -0.020896198, -0.015171212, 0.026334934, 0.035638034, 0.008873728, 0.003291867, -0.02647806, 0.003649678, 0.003613897, 0.009804038, -0.013525278, 0.005367174, 0.007657168, -0.017103394, -0.015815273, -0.000398065, 0.013310592, 0.014240902, 0.003935928, 0.001735386, -0.018606203, 0.008265448, -0.068127327, 0.012165595, -0.007836075, 0.02189807, -0.000983982, 0.019178702, -0.009589351, -0.013739966, 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0.00370335, 0.011449971, 0.023472441, 0.000197915, -0.011950907, 0.023329318, -0.009804038, -0.025619311, 0.0074067, -0.003953818, 0.014312465, 0.048662379, -0.027193682, 0.019894326, -0.042364895, 0.003327648, 0.042937394, -0.040933646, -0.020466823, 0.056104861, 0.020896198, -0.014527151, -0.036210533, -0.022470569, 0.035924286, -0.013167467, -0.055532362, -0.006190141, -0.027909305, 0.012881218, 0.003005618, 0.005689205, 0.01109216, -0.016387772, -0.021468697, 0.018176829, -0.021611821, 0.032918669, 0.002951946, -0.008837947, -0.031773672, -0.029913051, 0.017318081, 0.017461207, -0.02833868, -0.027479932, -0.023615567, 0.037212405, -0.023615567, -0.02404494, 0.029626802, 0.002951946, 0.004043271, -0.001377575, 0.007800293, 0.024188064, -0.027336806, -0.002361557, -0.00307718, -0.025189938, 0.007192013, -0.000207978, 0.040933646, 0.010877473, -0.000720096, -0.006941545, 0.003059289, 0.032775544, -0.007657168, 0.019321827, -0.012094032, 0.042078644, -0.010591224, 0.011807784, -0.016173085, -0.015529023, -0.023615567, 0.016173085, -0.018606203, 0.007192013, -0.008587479, 0.000257177, 0.002245268, -0.011879345, 0.044082388, -0.005939673, -0.003059289, -0.013954652, -0.026621183, 0.039502401, -0.006440609, 0.014384027, 0.012094032, -0.034779288, -0.002379447, 0.023329318, 0.029483676, -0.002325775, -0.001565426, 0.025619311, 0.018606203, -0.016101522, -0.0301993, 0.002576244, 0.035208661, 0.002325775, -0.011664659, -0.022470569, -0.047231134, -0.016888708, -0.017747456, 0.05152487, 0.009374664, -0.010591224, 0.009303101, -0.005009362, -0.029197427, 0.001726441, -0.023758691, -0.002934055, -0.017461207, 0.018606203, -0.002665696, -0.003578116, -0.018606203, -0.004651551, -0.021325571, 0.005367174, -0.009124196, 0.016888708, -0.01295278, 0.002048471, -0.011593096, 0.017604331, -0.008515916, 0.006082797, -0.036067411, -0.027336806, -0.010018725, -0.001306012, 0.026334934, -0.019321827, -0.030914923, -0.026764309, -0.0024689, -0.005581861, -0.002755149, 0.019464951, -0.01295278, 0.011163722, 0.000639588, 0.025476186, 0.029483676, 0.042651143, -0.011306847, 0.002737259, 0.010090288, -0.015600586, 0.038357403, 0.029197427, -0.008193886, 0.044082388, 0.032489292, -0.00123445, -0.008372792, 0.009124196, -0.00309507, -0.041792396, 0.007764512, -0.009947163, 0.044941138, 0.030056175, -0.013024342, -0.019321827, 0.019321827, 0.008551697, -0.053814866, 0.038071156, -0.037784904, 0.012165595, -0.008444354, -0.029626802, -0.006905764, -0.028195554, -0.01080591, -0.0098756, -0.032203045, 0.040361151, -0.033920541, 0.004454754, -0.036067411, 0.011879345, -0.011235285, 0.020609949, -0.004579989, 0.0074067, -0.017103394, 0.01789058, 0.011449971, -0.007836075, 0.000427138, -0.007120451, 0.008337011, 0.00123445, -0.003273976, -0.007263576, -0.011449971, 0.022756819, 0.002576244, -0.013310592, -0.013382155, -0.011664659, -0.013453716, -0.005152487, -0.050379876, -0.034636162, -0.011306847, 0.015028087, 0.008480135, -0.047517382, -0.00586811, -0.008301229, -0.01416934, 0.000876638, 0.000326503, 0.01080591, 0.004150615, 0.005259831, -0.008837947, 0.017031832, -0.016316209, -0.036210533, -0.013883091, -0.000295195, 0.014240902, 0.020753073, -0.022899942, -0.038929902, 0.00586811, -0.008050761, 0.00016437, -0.001932183, 0.001789058, 0.017031832, 0.045227386, -0.016745584, -0.005689205, 0.008372792, 0.008301229, -0.016674021, -0.004222177, 0.005832329, 0.016173085, -0.009374664, -0.006869983, -0.052669868, 0.035065539, 0.000123557, 0.007478263, 0.033491168, 0.054387365, 0.002254213, -0.007836075, -0.020323699, -0.019178702, -0.010376536, -0.039788652, -0.032632418, -0.012380281, -0.002540462, -0.016602458, -0.022756819, 0.019608077, 0.001887456, 0.032918669, 0.008050761, -0.013739966, 0.006547953, -0.016674021, 0.001574371, 0.019321827, -0.016960271, -0.031201173, 0.027766181, 0.006655296, 0.020753073, 0.009804038, 0.024903689, -0.043509893, 0.015815273, -0.017962143, -0.043223642, 0.033920541, -0.007764512, -0.006762639, 0.017819017, -0.026621183, 0.046658635, -0.004490536, 0.024188064, -0.010304974, 0.004651551, 0.047231134, -0.038071156, 0.009589351, -0.033920541, -0.027050557, 0.050093625, 0.008515916, -0.025189938, -0.008050761, 0.011950907, 0.004973582, 0.014527151, -0.009374664, -0.003721241, 0.019608077, 0.049807377, 0.016602458, 0.02404494, 32 } 33 34 genresFilterCondition := bson.D{{"genres", bson.D{{"$ne", "Crime"}}}} 35 36 yearAndGenresFilterCondition := bson.D{ 37 {"$and", bson.A{ 38 bson.D{{"year", bson.D{{"$lte", 2015}}}}, 39 bson.D{{"genres", bson.D{{"$eq", "Action"}}}}, 40 }}, 41 } 42 43 filter := bson.D{{"$or", bson.A{ 44 genresFilterCondition, yearAndGenresFilterCondition, 45 }}, 46 } 47 48 vectorSearchStage := bson.D{ 49 {"$vectorSearch", bson.D{ 50 {"index", "vector_index"}, 51 {"path", "plot_embedding_voyage_3_large"}, 52 {"filter", filter}, 53 {"queryVector", queryVector}, 54 {"numCandidates", 200}, 55 {"limit", 10}, 56 }}, 57 } 58 59 projectStage := bson.D{ 60 {"$project", bson.D{ 61 {"_id", 0}, 62 {"plot", 1}, 63 {"title", 1}, 64 {"genres", 1}, 65 {"year", 1}, 66 {"score", bson.D{{"$meta", "vectorSearchScore"}}}, 67 }}} 68 69 cursor, err := coll.Aggregate(ctx, mongo.Pipeline{vectorSearchStage, projectStage}) 70 if err != nil { 71 log.Fatalf("failed to retrieve data from the server: %v", err) 72 } 73 // display the results 74 type ProjectedMovieResult struct { 75 Title string `bson:"title"` 76 Plot string `bson:"plot"` 77 Genres []string `bson:"genres"` 78 Year int32 `bson:"year"` 79 Score float64 `bson:"score"` 80 } 81 82 var results []ProjectedMovieResult 83 if err = cursor.All(ctx, &results); err != nil { 84 log.Fatalf("failed to unmarshal results to ProjectedMovieResult objects: %v", err) 85 } 86 for _, result := range results { 87 fmt.Printf("Title: %v \nPlot: %v \nGenres: %v \nYear: %v \nScore: %v \n\n", result.Title, result.Plot, result.Genres, result.Year, result.Score) 88 } 89 }
3
Replace the <connection-string> in the query and then save the file.
Replace <connection-string> with the connection string for your
Atlas cluster or local Atlas deployment.
Your connection string should use the following format:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
To learn more, see Connect to a Cluster via Drivers.
Your connection string should use the following format:
mongodb://localhost:<port-number>/?directConnection=true
To learn more, see Connection Strings.
4
Compile and run AtlasVectorSearchTutorial.go file.
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
2
Copy and paste the code for the pre-filter operator you want to try into the AtlasVectorSearchTutorial.java file.
The following queries use the $vectorSearch pipeline stage
to search for movies that match the specified vector embeddings. The queries
specify a search for up to 100 nearest neighbors and limit the
results to 10 documents only. The queries also specify a
$project stage to perform the following actions:
Exclude the
_idfield and include only thetitle,genres,plot, andyearfields in the results.Add a field named
scorethat shows the vector search score for each document in the results.
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string kids adventure. It specifies multiple
comparison query operators per field to pre-filter the documents
against which to perform the semantic search.
The filter uses the $and aggregation pipeline operator to find
movie documents that match both the following criteria:
Filter by the
genresfield to find movies that aren't in thedrama,western, orcrimegenre, but in theaction,adventure, orfamilygenre.Filter by the
yearfield to find movies that were released between the years1960and2000, both 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 }
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string star wars. It specifies aggregation pipeline and
comparison query operators to demonstrate a combined use of the
operators to filter the data.
The filter uses the $or aggregation pipeline operator to find
movie documents that match either one of the following criteria:
Filter by the
genresfield to find movies that aren't in thecrimegenre.Filter by the
yearfield to find movies that were released in or before the year2015and by thegenresfield to find movies in theactiongenre.
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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3,-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)); 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 }
3
Replace the <connection-string> in the query and then save the file.
Replace <connection-string> with the connection string for your
Atlas cluster or local Atlas deployment.
Your connection string should use the following format:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
To learn more, see Connect to a Cluster via Drivers.
Your connection string should use the following format:
mongodb://localhost:<port-number>/?directConnection=true
To learn more, see Connection Strings.
4
Compile and run AtlasVectorSearchTutorial.java file.
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 }
2
Copy and paste the sample query for the pre-filter operator you want to try into the atlas-vector-search-tutorial.js file.
The following queries use the $vectorSearch pipeline stage
to search for movies that match the specified vector embeddings. The queries
specify a search for up to 100 nearest neighbors and limit the
results to 10 documents only. The queries also specify a
$project stage to perform the following actions:
Exclude the
_idfield and include only thetitle,genres,plot, andyearfields in the results.Add a field named
scorethat shows the vector search score for each document in the results.
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string kids adventure. It specifies multiple
comparison query operators per field to pre-filter the documents
against which to perform the semantic search.
The filter uses the $and aggregation pipeline operator to find
movie documents that match both the following criteria:
Filter by the
genresfield to find movies that aren't in thedrama,western, orcrimegenre, but in theaction,adventure, orfamilygenre.Filter by the
yearfield to find movies that were released between the years1960and2000, both inclusive.
1 const { MongoClient } = require("mongodb"); 2 3 // connect to your Atlas cluster 4 const uri = "<connection-string>"; 5 6 const client = new MongoClient(uri); 7 8 async function run() { 9 try { 10 await client.connect(); 11 12 // set namespace 13 const database = client.db("sample_mflix"); 14 const coll = database.collection("embedded_movies"); 15 16 // define pipeline 17 const agg = [ 18 { 19 '$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);
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string star wars. It specifies aggregation pipeline and
comparison query operators to demonstrate a combined use of the
operators to filter the data.
The filter uses the $or aggregation pipeline operator to find
movie documents that match either one of the following criteria:
Filter by the
genresfield to find movies that aren't in thecrimegenre.Filter by the
yearfield to find movies that were released in or before the year2015and by thegenresfield to find movies in theactiongenre.
1 const { MongoClient } = require("mongodb"); 2 3 // connect to your Atlas cluster 4 const uri = "<connection-string>"; 5 6 const client = new MongoClient(uri); 7 8 async function run() { 9 try { 10 await client.connect(); 11 12 // set namespace 13 const database = client.db("sample_mflix"); 14 const coll = database.collection("embedded_movies"); 15 16 // define pipeline 17 const agg = [ 18 { 19 '$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);
3
Replace the <connection-string> in the query and then save the file.
Replace <connection-string> with the connection string for your
Atlas cluster or local Atlas deployment.
Your connection string should use the following format:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
To learn more, see Connect to a Cluster via Drivers.
Your connection string should use the following format:
mongodb://localhost:<port-number>/?directConnection=true
To learn more, see Connection Strings.
4
Query your collection.
Run the following command to query your collection:
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}'
2
Copy and paste the query for the pre-filter operator that you want to try into the atlas-vector-search-tutorial.py file.
The following queries use the $vectorSearch pipeline stage
to search for movies that match the specified vector embeddings. The queries
specify a search for up to 100 nearest neighbors and limit the
results to 10 documents only. The queries also specify a
$project stage to perform the following actions:
Exclude the
_idfield and include only thetitle,genres,plot, andyearfields in the results.Add a field named
scorethat shows the vector search score for each document in the results.
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string kids adventure. It specifies multiple
comparison query operators per field to pre-filter the documents
against which to perform the semantic search.
The filter uses the $and aggregation pipeline operator to find
movie documents that match both the following criteria:
Filter by the
genresfield to find movies that aren't in thedrama,western, orcrimegenre, but in theaction,adventure, orfamilygenre.Filter by the
yearfield to find movies that were released between the years1960and2000, both inclusive.
1 import pymongo 2 3 # connect to your Atlas cluster 4 client = pymongo.MongoClient("<connection-string>") 5 6 # define pipeline 7 pipeline = [ 8 { 9 '$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)
The following query searches the plot_embedding_voyage_3_large field using the
vector embeddings for the string star wars. It specifies aggregation pipeline and
comparison query operators to demonstrate a combined use of the
operators to filter the data.
The filter uses the $or aggregation pipeline operator to find
movie documents that match either one of the following criteria:
Filter by the
genresfield to find movies that aren't in thecrimegenre.Filter by the
yearfield to find movies that were released in or before the year2015and by thegenresfield to find movies in theactiongenre.
1 import pymongo 2 3 # connect to your Atlas cluster 4 client = pymongo.MongoClient("<connection-string>") 5 6 # define pipeline 7 pipeline = [ 8 { 9 '$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)
3
Replace the <connection-string> in the query and then save the file.
Replace <connection-string> with the connection string for your
Atlas cluster or local Atlas deployment.
Your connection string should use the following format:
mongodb+srv://<db_username>:<db_password>@<clusterName>.<hostname>.mongodb.net
To learn more, see Connect to a Cluster via Drivers.
Your connection string should use the following format:
mongodb://localhost:<port-number>/?directConnection=true
To learn more, see Connection Strings.
4
Run the command to query your collection.
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}