Docs Menu
Docs Home
/
MongoDB Atlas
/ /

How to Perform Semantic Search Against Data in Your Atlas Cluster

On this page

  • Prerequisites
  • Create the Atlas Vector Search Index
  • Required Access
  • Procedure
  • Run Queries Using the $vectorSearch Aggregation Pipeline Stage
  • Overview
  • Procedure

This tutorial describes how to perform an ANN search on a vector in the plot_embedding field in the sample_mflix.embedded_movies collection on your Atlas cluster. To demonstrate this, it takes you through the following steps:

  1. Create an Atlas Vector Search index on the numeric field named plot_embedding in the sample_mflix.embedded_movies collection.

  2. Run Atlas Vector Search queries against the plot_embedding field in the sample_mflix.embedded_movies collection.


Use the Select your language drop-down menu to select the client to use to create the Atlas Vector Search index and run queries.


Tip

Work with a runnable version of this tutorial as a Python notebook.

To complete this tutorial, you must have the following:

  • An Atlas cluster with MongoDB version 6.0.11, or v7.0.2 or later (including RCs).

  • The sample data loaded into your Atlas cluster.

    Note

    You can convert the embeddings in the sample data to BSON vectors for efficient storage and ingestion of vectors in Atlas. To learn more, see how to convert native embeddings to BSON vectors.

  • One of the following clients to run queries on your Atlas cluster:

    Note

    You can run Atlas Vector Search queries by using any MongoDB Driver through the $vectorSearch aggregation stage. This tutorial includes examples for only the drivers in the preceding list.

    You can also use Atlas Vector Search with local Atlas deployments that you create with the Atlas CLI. To learn more, see Create a Local Atlas Deployment.

This section demonstrates how to create an Atlas Vector Search index on the plot_embedding field in the sample_mflix.embedded_movies collection for running vector queries against the field.

To create an Atlas Vector Search index, you must have Project Data Access Admin or higher access to the project.

1
  1. If it's not already displayed, select the organization that contains your desired project from the Organizations menu in the navigation bar.

  2. If it's not already displayed, select your desired project from the Projects menu in the navigation bar.

  3. If it's not already displayed, click Clusters in the sidebar.

    The Clusters page displays.

2

You can go the Atlas Search page from the sidebar, the Data Explorer, or your cluster details page.

  1. In the sidebar, click Atlas Search under the Services heading.

  2. From the Select data source dropdown, select your cluster and click Go to Atlas Search.

    The Atlas Search page displays.

  1. Click the Browse Collections button for your cluster.

  2. Expand the database and select the collection.

  3. Click the Search Indexes tab for the collection.

    The Atlas Search page displays.

  1. Click the cluster's name.

  2. Click the Atlas Search tab.

    The Atlas Search page displays.

3
  1. Click Create Search Index.

  2. Under Atlas Vector Search, select JSON Editor and then click Next.

  3. In the Database and Collection section, find the sample_mflix database, and select the embedded_movies collection.

  4. In the Index Name field, enter vector_index.

  5. Replace the default definition with the following index definition and then click Next.

4
  1. Replace the default definition with the following index definition.

    This index definition specifies indexing the following fields in an index of the vectorSearch type:

    • plot_embedding field as the vector type. The plot_embedding field contains embeddings created using OpenAI's text-embedding-ada-002 embedding model. The index definition specifies 1536 vector dimensions and measures similarity using dotProduct.

    • genres field as the filter type for pre-filtering data by string values in the field.

    • year field as the filter type for pre-filtering data by numeric values in the field.

    1{
    2 "fields": [
    3 {
    4 "type": "vector",
    5 "path": "plot_embedding",
    6 "numDimensions": 1536,
    7 "similarity": "dotProduct"
    8 },
    9 {
    10 "type": "filter",
    11 "path": "genres"
    12 },
    13 {
    14 "type": "filter",
    15 "path": "year"
    16 }
    17 ]
    18}
5

A modal window displays to let you know that your index is building.

6

The index should take about one minute to build. While it builds, the Status column reads Initial Sync. When it finishes building, the Status column reads Active.

1

Open mongosh in a terminal window and connect to your cluster. For detailed instructions on connecting, see Connect via mongosh.

2

Example

use sample_mflix
switched to db sample_mflix
3

The following index definition indexes the plot_embedding field as the vector type and the genres and year fields as the filter type in an Atlas Vector Search index. The plot_embedding field contains embeddings created using OpenAI's text-embedding-ada-002 embeddings model. The index definition specifies 1536 vector dimensions and measures similarity using dotProduct function.

1db.embedded_movies.createSearchIndex(
2 "vector_index",
3 "vectorSearch",
4 {
5 "fields": [
6 {
7 "type": "vector",
8 "path": "plot_embedding",
9 "numDimensions": 1536,
10 "similarity": "dotProduct"
11 },
12 {
13 "type": "filter",
14 "path": "genres"
15 },
16 {
17 "type": "filter",
18 "path": "year"
19 }
20 ]
21 }
22);
1

Add the MongoDB C# Driver as a dependency in your project:

dotnet add package MongoDB.Driver
2

Create a file named IndexService.cs. Copy and paste the following code into the file, and replace the <connection-string> placeholder value.

IndexService.cs
1namespace query_quick_start;
2
3using MongoDB.Bson;
4using MongoDB.Driver;
5using System;
6using System.Threading;
7
8public 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" },
33 { "numDimensions", 1536 },
34 { "similarity", "dotProduct" }
35 },
36 new BsonDocument
37 {
38 {"type", "filter"},
39 {"path", "genres"}
40 },
41 new BsonDocument
42 {
43 {"type", "filter"},
44 {"path", "year"}
45 }
46 }
47 }
48 };
49
50 var model = new CreateSearchIndexModel(name, type, definition);
51
52 searchIndexView.CreateOne(model);
53 Console.WriteLine($"New search index named {name} is building.");
54
55 // Polling for index status
56 Console.WriteLine("Polling to check if the index is ready. This may take up to a minute.");
57 bool queryable = false;
58 while (!queryable)
59 {
60 var indexes = searchIndexView.List();
61 foreach (var index in indexes.ToEnumerable())
62 {
63 if (index["name"] == name)
64 {
65 queryable = index["queryable"].AsBoolean;
66 }
67 }
68 if (!queryable)
69 {
70 Thread.Sleep(5000);
71 }
72 }
73 Console.WriteLine($"{name} is ready for querying.");
74 }
75 catch (Exception e)
76 {
77 Console.WriteLine($"Exception: {e.Message}");
78 }
79 }
80}

This index definition indexes the plot_embedding field as the vector type and the genres and year fields as the filter type in an Atlas Vector Search index. The plot_embedding field contains embeddings created using OpenAI's text-embedding-ada-002 embeddings model. The index definition specifies 1536 vector dimensions and measures similarity using dotProduct function.

3

Update Program.cs to initialize the IndexService and call the method to create the index.

Program.cs
using query_quick_start;
var indexService = new IndexService();
indexService.CreateVectorIndex();
4

Save the file, and then compile and run your project to create the index.

dotnet run query_quick_start.csproj
New search index named vector_index is building.
Polling to check if the index is ready. This may take up to a minute.
vector_index is ready for querying.
1

Add the Go Driver as a dependency in your project:

go get go.mongodb.org/mongo-driver/mongo
2

Create a file named vector-index.go. Copy and paste the following code into the file, and replace the <connectionString> placeholder value.

vector-index.go
1package main
2
3import (
4 "context"
5 "fmt"
6 "log"
7 "time"
8
9 "go.mongodb.org/mongo-driver/bson"
10 "go.mongodb.org/mongo-driver/mongo"
11 "go.mongodb.org/mongo-driver/mongo/options"
12)
13
14func 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(ctx, 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 }
39
40 type filterField struct {
41 Type string `bson:"type"`
42 Path string `bson:"path"`
43 }
44
45 type indexDefinition struct {
46 Fields []vectorDefinitionField `bson:"fields"`
47 }
48
49 vectorDefinition := vectorDefinitionField{
50 Type: "vector",
51 Path: "plot_embedding",
52 NumDimensions: 1536,
53 Similarity: "dotProduct"}
54 genreFilterDefinition := filterField{"filter", "genres"}
55 yearFilterDefinition := filterField{"filter", "year"}
56
57 indexModel := mongo.SearchIndexModel{
58 Definition: bson.D{{"fields", [3]interface{}{
59 vectorDefinition,
60 genreFilterDefinition,
61 yearFilterDefinition}}},
62 Options: opts,
63 }
64
65 // Create the index
66 searchIndexName, err := coll.SearchIndexes().CreateOne(ctx, indexModel)
67 if err != nil {
68 log.Fatalf("failed to create the search index: %v", err)
69 }
70 log.Println("New search index named " + searchIndexName + " is building.")
71
72 // Await the creation of the index.
73 log.Println("Polling to check if the index is ready. This may take up to a minute.")
74 searchIndexes := coll.SearchIndexes()
75 var doc bson.Raw
76 for doc == nil {
77 cursor, err := searchIndexes.List(ctx, options.SearchIndexes().SetName(searchIndexName))
78 if err != nil {
79 fmt.Errorf("failed to list search indexes: %w", err)
80 }
81
82 if !cursor.Next(ctx) {
83 break
84 }
85
86 name := cursor.Current.Lookup("name").StringValue()
87 queryable := cursor.Current.Lookup("queryable").Boolean()
88 if name == searchIndexName && queryable {
89 doc = cursor.Current
90 } else {
91 time.Sleep(5 * time.Second)
92 }
93 }
94
95 log.Println(searchIndexName + " is ready for querying.")
96}

This index definition indexes the plot_embedding field as the vector type and the genres and year fields as the filter type in an Atlas Vector Search index. The plot_embedding field contains embeddings created using OpenAI's text-embedding-ada-002 embeddings model. The index definition specifies 1536 vector dimensions and measures similarity using dotProduct function.

3
go run vector-index.go
2024/10/17 09:38:21 Creating the index.
2024/10/17 09:38:22 Polling to confirm successful index creation.
2024/10/17 09:38:22 NOTE: This may take up to a minute.
2024/10/17 09:38:48 Name of Index Created: vector_index
1
  1. 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 dependencies array in your project's pom.xml file:

    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>
  2. 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

Create a file named VectorIndex.java. Copy and paste the following code into the file, and replace the <connectionString> placeholder value.

VectorIndex.java
1import com.mongodb.client.ListSearchIndexesIterable;
2import com.mongodb.client.MongoClient;
3import com.mongodb.client.MongoClients;
4import com.mongodb.client.MongoCollection;
5import com.mongodb.client.MongoCursor;
6import com.mongodb.client.MongoDatabase;
7import com.mongodb.client.model.SearchIndexModel;
8import com.mongodb.client.model.SearchIndexType;
9import org.bson.Document;
10import org.bson.conversions.Bson;
11
12import java.util.Arrays;
13import java.util.Collections;
14import java.util.List;
15
16public class VectorIndex {
17
18 public static void main(String[] args) {
19
20 // Replace the placeholder with your Atlas connection string
21 String uri = "<connectionString>";
22
23 // Connect to your Atlas cluster
24 try (MongoClient mongoClient = MongoClients.create(uri)) {
25
26 // Set the namespace
27 MongoDatabase database = mongoClient.getDatabase("sample_mflix");
28 MongoCollection<Document> collection = database.getCollection("embedded_movies");
29
30 // Define the index details with the filter fields
31 String indexName = "vector_index";
32 Bson definition = new Document(
33 "fields",
34 Arrays.asList(
35 new Document("type", "vector")
36 .append("path", "plot_embedding")
37 .append("numDimensions", 1536)
38 .append("similarity", "dotProduct"),
39 new Document("type", "filter")
40 .append("path", "genres"),
41 new Document("type", "filter")
42 .append("path", "year")));
43
44 // Define the index model
45 SearchIndexModel indexModel = new SearchIndexModel(
46 indexName,
47 definition,
48 SearchIndexType.vectorSearch());
49
50 // Create the filtered index
51 try {
52 List<String> result = collection.createSearchIndexes(Collections.singletonList(indexModel));
53 System.out.println("New search index named " + result.get(0) + " is building.");
54 } catch (Exception e) {
55 throw new RuntimeException("Error creating index: " + e);
56 }
57
58 // Wait for Atlas to build the index
59 System.out.println("Polling to check if the index is ready. This may take up to a minute.");
60
61 ListSearchIndexesIterable<Document> searchIndexes = collection.listSearchIndexes();
62 Document doc = null;
63 while (doc == null) {
64 try (MongoCursor<Document> cursor = searchIndexes.iterator()) {
65 if (!cursor.hasNext()) {
66 break;
67 }
68 Document current = cursor.next();
69 String name = current.getString("name");
70 // When the index completes building, it becomes `queryable`
71 boolean queryable = current.getBoolean("queryable");
72 if (name.equals(indexName) && queryable) {
73 doc = current;
74 } else {
75 Thread.sleep(500);
76 }
77 } catch (Exception e) {
78 throw new RuntimeException("Failed to list search indexes: " + e);
79 mongoClient.close();
80 }
81 }
82 System.out.println(indexName + " is ready for querying.");
83
84 } catch (Exception e) {
85 throw new RuntimeException("Error connecting to MongoDB: " + e);
86 }
87 }
88}

This index definition indexes the plot_embedding field as the vector type and the genres and year fields as the filter type in an Atlas Vector Search index. The plot_embedding field contains embeddings created using OpenAI's text-embedding-ada-002 embeddings model. The index definition specifies 1536 vector dimensions and measures similarity using dotProduct function.

3

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

Add the MongoDB Node Driver as a dependency in your project:

npm install mongodb

Tip

The examples on this page assume your project manages modules as CommonJS modules. If you're using ES modules, instead, you must modify the import syntax.

2

Create a file named vector-index.js. Copy and paste the following code into the file, and replace the <connectionString> placeholder value.

vector-index.js
1const { MongoClient } = require("mongodb");
2
3// connect to your Atlas deployment
4const uri = "<connectionString>";
5
6const client = new MongoClient(uri);
7
8async 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": 1536,
22 "path": "plot_embedding",
23 "similarity": "dotProduct"
24 },
25 {
26 "type": "filter",
27 "path": "genres"
28 },
29 {
30 "type": "filter",
31 "path": "year"
32 }
33 ]
34 }
35 }
36
37 // run the helper method
38 const result = await collection.createSearchIndex(index);
39 console.log(`New search index named ${result} is building.`);
40
41 // wait for the index to be ready to query
42 console.log("Polling to check if the index is ready. This may take up to a minute.")
43 let isQueryable = false;
44 while (!isQueryable) {
45 const cursor = collection.listSearchIndexes();
46 for await (const index of cursor) {
47 if (index.name === result) {
48 if (index.queryable) {
49 console.log(`${result} is ready for querying.`);
50 isQueryable = true;
51 } else {
52 await new Promise(resolve => setTimeout(resolve, 5000));
53 }
54 }
55 }
56 }
57 } finally {
58 await client.close();
59 }
60}
61run().catch(console.dir);

This index definition indexes the plot_embedding field as the vector type and the genres and year fields as the filter type in an Atlas Vector Search index. The plot_embedding field contains embeddings created using OpenAI's text-embedding-ada-002 embeddings model. The index definition specifies 1536 vector dimensions and measures similarity using dotProduct function.

3
node vector-index.js
vector_index
1

Add the PyMongo Driver as a dependency in your project:

pip install pymongo
2

Create a file named vector-index.py. Copy and paste the following code into the file, and replace the <connectionString> placeholder value.

vector-index.py
1from pymongo.mongo_client import MongoClient
2from pymongo.operations import SearchIndexModel
3import time
4
5# Connect to your Atlas deployment
6uri = "<connectionString>"
7client = MongoClient(uri)
8
9# Access your database and collection
10database = client["sample_mflix"]
11collection = database["embedded_movies"]
12
13# Create your index model, then create the search index
14search_index_model = SearchIndexModel(
15 definition={
16 "fields": [
17 {
18 "type": "vector",
19 "path": "plot_embedding",
20 "numDimensions": 1536,
21 "similarity": "dotProduct"
22 },
23 {
24 "type": "filter",
25 "path": "genres"
26 },
27 {
28 "type": "filter",
29 "path": "year"
30 }
31 ]
32 },
33 name="vector_index",
34 type="vectorSearch",
35)
36
37result = collection.create_search_index(model=search_index_model)
38print("New search index named " + result + " is building.")
39
40# Wait for initial sync to complete
41print("Polling to check if the index is ready. This may take up to a minute.")
42predicate=None
43if predicate is None:
44 predicate = lambda index: index.get("queryable") is True
45
46while True:
47 indices = list(collection.list_search_indexes(result))
48 if len(indices) and predicate(indices[0]):
49 break
50 time.sleep(5)
51print(result + " is ready for querying.")
52
53client.close()

This index definition indexes the plot_embedding field as the vector type and the genres and year fields as the filter type in an Atlas Vector Search index. The plot_embedding field contains embeddings created using OpenAI's text-embedding-ada-002 embeddings model. The index definition specifies 1536 vector dimensions and measures similarity using dotProduct function.

3
python vector-index.py
vector_index

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.

1
  1. If it's not already displayed, select the organization that contains your desired project from the Organizations menu in the navigation bar.

  2. If it's not already displayed, select your desired project from the Projects menu in the navigation bar.

  3. If it's not already displayed, click Clusters in the sidebar.

    The Clusters page displays.

2

Click the Browse Collections button for your cluster.

The Data Explorer displays.

3
  1. Expand sample_mflix under the list of databases and select embedded_movies from the list of collections in that database.

  2. Click the Aggregation tab for the sample_mflix.embedded_movies collection.

4

The following queries use the $vectorSearch pipeline stage to search for movies that match the specified vector embeddings. Note that the queries use ada-002-text embedding, which is the same as the vector embedding in the plot_embedding field. 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 _id field and include only the title, genres, plot, and year fields in the results.

  • Add a field named score that shows the vector search score for each document in the results.

  1. Click </> Text.

  2. Replace [ ] in the left pane with the query for the pre-filter operator that you want to try.

    The following query searches the plot_embedding field using the vector embeddings for the string historical heist. The query uses ada-002-text embedding, which is the same as the vector embedding in the plot_embedding field. 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 genres field to find movies that aren't in the drama, western, or crime genre, but in the action, adventure, or family genre.

    • Filter by the year field to find movies that were released between the years 1960 and 2000, both inclusive.

    1[
    2 {
    3 "$vectorSearch": {
    4 "index": "vector_index",
    5 "path": "plot_embedding",
    6 "filter": {
    7 "$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": [-0.020156775,-0.024996493,0.010778184,-0.030058576,-0.03309321,0.0031229265,-0.022772837,0.0028351594,0.00036870153,-0.02820117,0.016245758,0.0036232488,0.0020519753,-0.0076454473,0.0073380596,-0.007377301,0.039267123,-0.013433489,0.01428371,-0.017279103,-0.028358135,0.0020160044,0.00856761,0.009653277,0.0107912645,-0.026683854,0.009594415,-0.020182934,0.018077003,-0.015709465,0.003310956,0.0014878864,-0.015971072,-0.002411684,-0.029561523,-0.030450987,-0.013106481,-0.005385822,-0.018652538,0.012642129,-0.005189617,0.018835662,-0.0048102876,-0.0261214,-0.016167276,-0.007972456,0.0023381072,-0.010058766,-0.009012341,0.008358325,0.018665617,0.02163485,-0.012975678,-0.010745483,-0.002571918,-0.014479915,0.007226877,0.015003128,0.013165343,-0.028279653,0.0053727417,-0.020588424,-0.017383745,0.023518417,0.01262905,-0.011922712,0.007638907,-0.0073249796,-0.014859244,-0.00001101736,0.017043658,0.010111088,0.0074623227,0.009555174,0.008338705,-0.002240005,-0.0010603234,-0.004973792,0.003391073,0.021543289,0.013341927,0.0005980159,0.010693162,0.005336771,0.016062634,0.005768421,0.005186347,0.039790336,0.0021942237,-0.0026275094,0.010431555,0.0042151334,-0.0050359233,0.025768232,-0.021451725,0.01833861,-0.01836477,-0.013433489,0.030006256,-0.014793842,0.017475309,0.0020585153,-0.012975678,-0.017266022,-0.01593183,-0.014257549,0.0010676811,-0.007887433,-0.0045911926,0.00012303676,-0.0014976967,0.03552615,0.0065630507,-0.037435878,0.011929252,-0.00939167,0.016768971,0.01223664,0.007789331,-0.037200432,0.013145722,0.00896002,0.021857215,0.010333453,0.021582529,-0.007089534,-0.007154935,-0.02485261,0.0040254686,-0.00088864425,0.023466095,-0.020719228,-0.006690584,-0.021006994,-0.018286288,0.025545865,-0.0096598165,0.008803056,-0.023021365,-0.040078104,0.015408617,0.017043658,-0.011242535,0.0063537657,-0.026618453,0.0071614753,-0.014623798,0.00067322777,-0.00083427917,-0.028070368,0.03714811,-0.004529061,0.0054087127,0.0028727653,0.008384486,0.010026066,-0.006190262,-0.0002493436,0.0029953935,-0.026226042,-0.018417092,0.009941043,0.0036494094,-0.00982332,0.013551212,0.02574207,-0.0022645304,-0.0006004685,0.012805633,-0.024303235,0.008194821,-0.014179068,-0.02977081,0.003095131,-0.0015941641,0.029953934,0.0052680993,0.025388902,-0.031392768,-0.021386323,0.014898485,0.022419669,0.00897964,0.013243824,0.006854088,0.0066415328,-0.003839074,-0.01877026,0.021216279,-0.015055449,-0.0015508354,0.013211124,-0.008783435,0.0052157775,-0.68938524,-0.01221702,-0.04125533,-0.016232677,0.020039052,-0.0026422248,-0.0037050007,0.0064682183,-0.0047579664,0.0032749851,-0.0035382267,0.031942144,-0.00035643874,-0.011628405,-0.043086577,-0.0196074,-0.0066088317,-0.014872325,0.028331975,0.010294212,-0.013930541,0.031994462,-0.018626377,0.017462227,0.026343765,-0.010274592,0.0046827546,-0.029430721,-0.011746128,0.0024362097,0.0023054064,0.0027730279,-0.002406779,0.003917556,0.059436977,0.008665713,-0.0018901062,0.06037876,0.017880797,0.05185039,0.0067102043,-0.020300657,0.005604917,0.018704858,0.012073136,0.0144145135,0.012413224,-0.0074819434,0.015801027,-0.0061412104,0.008613391,-0.0039077457,-0.0036232488,0.008469507,0.014087505,0.0124066835,0.019267311,-0.002573553,0.005055544,-0.009417831,-0.009103903,0.011150973,-0.012046975,0.0058567133,-0.0053727417,0.018260127,-0.005588567,0.015591742,0.007495024,-0.02567667,0.024211673,0.021386323,-0.012890656,-0.016114954,0.009515933,0.009679437,0.025532786,-0.0076454473,-0.02575515,0.008319084,-0.0068410076,-0.017082898,-0.026173722,-0.0049901423,0.01918883,-0.008646091,-0.031759016,0.014820003,0.011850771,0.01836477,0.012700991,-0.0011437106,0.005058814,0.0151993325,-0.0060692686,0.027416352,0.0037344315,0.0013546307,0.018325528,-0.03152357,-0.008809595,0.014649959,-0.008345244,0.0066415328,-0.005523165,0.0043492066,-0.0015892589,0.0048855,0.034453563,-0.03837766,0.0068410076,-0.0042151334,-0.0067429054,0.0055689462,-0.011733048,-0.0212032,0.016847452,-0.0022220195,0.0059351954,-0.00449963,0.02251123,-0.01020265,0.023361452,-0.0032455544,0.016180357,0.0049443613,-0.0064747585,-0.03259616,0.012321662,0.020104453,0.009954124,-0.019411195,0.0048102876,-0.000392614,0.012184318,0.0044276887,0.005634348,-0.020562263,0.015722545,-0.005179807,-0.0067952266,0.0027861083,0.0024198592,-0.0020585153,0.0018525004,-0.045100946,-0.010176489,-0.012956058,0.0013497255,0.0105361985,0.003796563,-0.0106016,-0.013126101,0.0050359233,0.015003128,-0.0075800456,-0.015722545,-0.01755379,-0.00978408,-0.02940456,0.017606111,0.016612006,-0.016912855,0.025441224,0.0054741143,0.00448001,0.009470152,0.015382457,-0.008332164,-0.019123428,0.024564842,0.016860534,0.008286383,-0.007141855,0.006559781,0.016625088,-0.01840401,-0.011602244,-0.00489858,-0.0073184394,-0.008809595,-0.0018459603,-0.01629808,-0.005542786,0.0064257076,0.010379234,0.014663039,0.034872133,-0.013355007,0.027285548,0.011654565,-0.004032009,0.02323065,-0.02653997,-0.0009941043,0.002946342,0.010667001,0.008345244,0.018626377,0.04821406,0.031392768,0.010281132,0.026069079,0.002735422,0.01182461,-0.01593183,0.006585941,-0.010071847,0.024564842,-0.0025261368,0.004293615,-0.0068606283,-0.0066448026,-0.0074100015,-0.0014347476,0.021530207,-0.010418476,0.018495573,-0.0034924455,-0.014165987,-0.004784127,-0.012472086,0.004417878,-0.0030313642,-0.010084927,-0.010954768,0.01508161,0.0010047321,0.0042347535,-0.03345946,-0.00027346043,0.014793842,-0.019882087,0.012772933,0.021490967,0.0031932332,0.0093589695,0.00090172456,0.0048102876,0.0070045115,-0.0045584915,0.015840268,0.024342475,-0.0091300635,0.0039796876,0.003796563,0.025022654,-0.008103259,-0.025022654,0.03021554,-0.008201361,-0.0070502926,0.0011821339,0.021072397,0.004849529,-0.02495725,0.012184318,0.0019228071,-0.007226877,0.020562263,0.018861823,-0.0017593032,0.01345965,0.0022727058,0.003023189,-0.026971621,-0.0030558899,0.017723834,-0.01998673,-0.010608139,0.011491061,-0.025179617,0.0069652707,0.003924096,0.021177039,0.0045650317,-0.0009973744,0.007586586,-0.004032009,-0.008129419,-0.010091467,-0.04279881,0.019790525,0.01595799,0.0044309585,-0.0033747226,-0.018665617,-0.012818714,-0.016206518,0.014113666,-0.0020912162,0.01427063,-0.020248337,-0.0112752365,-0.020588424,-0.011039791,0.008744194,-0.015147011,0.0022269245,-0.010438096,-0.0017772885,-0.028750544,-0.008861917,-0.016991336,0.033668745,0.034636687,0.009888723,0.0023953337,0.006991431,-0.003346927,0.003103306,-0.0044571194,0.011249076,0.0033779927,0.00012446742,-0.0027027212,-0.025859794,-0.011942333,0.02694546,0.028227331,0.0064289775,-0.03385187,-0.020719228,0.00489531,0.10663077,0.041752383,-0.021700252,-0.008103259,0.0049574412,-0.01675589,-0.020182934,-0.006585941,0.007684688,-0.002859685,0.027023941,0.00856107,0.0037017306,0.016978256,0.025885954,-0.010372694,0.0025964435,0.011706887,0.021360163,-0.021674091,-0.024983412,0.0034074234,0.0032030435,0.022262705,-0.01266829,-0.002249815,0.032779284,-0.0034303141,-0.016101874,-0.005156916,-0.0212032,0.005362931,0.009077743,-0.013917461,-0.0017315074,0.010980929,-0.019450437,0.013865139,0.028227331,-0.008757275,-0.0033649125,-0.012857955,0.011039791,0.009764459,0.00029594224,-0.026317604,0.025048813,0.037749805,-0.025807472,-0.005425063,0.021791814,-0.010012985,-0.00066995766,-0.016952096,0.0031147513,-0.016598927,0.0084368065,0.004787397,-0.0064355177,0.0015164997,-0.021216279,-0.023845425,0.013969782,-0.011255615,0.0042576445,-0.024250913,-0.009908343,-0.02289056,-0.023361452,-0.010987469,-0.013394248,0.0032553647,-0.019018786,0.021438645,0.029587684,-0.010490417,0.01263559,-0.018417092,-0.008731114,0.01875718,-0.0072399573,-0.029090632,-0.017736914,-0.04031355,-0.019712042,0.012772933,-0.030320182,-0.022341188,-0.02041838,0.011752668,0.028829027,-0.017043658,0.024996493,0.006334145,-0.0024263994,-0.0077370093,0.017802317,0.017396826,0.030398665,0.011464901,0.03016322,-0.014558396,-0.0036690298,-0.009954124,-0.006703664,-0.00035705187,-0.014519156,0.0075342646,-0.00896656,0.040078104,0.024420958,-0.016886694,-0.00092543266,-0.0017494928,0.01672973,0.016533526,0.002648765,0.0187441,-0.0055460557,0.004735076,0.03186366,0.0003435628,0.007495024,0.023453014,-0.012504786,-0.0074557825,-0.0027844731,-0.04570264,0.010477337,0.0030101088,-0.015670223,0.03351178,-0.020261416,0.00050849747,-0.009653277,-0.023466095,-0.007396921,-0.011909632,0.003436854,-0.02979697,-0.039031677,-0.014584557,0.0019555078,0.0042216736,-0.0060594585,-0.023400694,-0.00023462824,-0.017763074,-0.016180357,0.0132372845,-0.020496862,-0.007390381,-0.0058697937,-0.0096598165,0.0039796876,-0.019306554,-0.012622509,-0.0012287326,0.010863206,0.024368636,0.027730279,0.016795132,0.019908248,-0.006343955,0.0014592733,-0.005425063,0.019450437,0.004532331,-0.031889822,0.008476048,0.019712042,-0.00047906674,-0.0028286192,0.011883471,-0.012426305,0.0041497317,0.001756033,-0.0013603533,-0.008031317,-0.010281132,-0.0071222344,-0.026330685,-0.007920134,-0.026866978,-0.03026786,-0.0015328501,0.027442513,-0.005922115,0.005186347,0.003436854,0.036703378,-0.0053204205,0.013165343,0.0016939015,-0.0041431915,-0.017213702,-0.012439385,-0.015212413,0.014532236,0.0093589695,-0.0053400407,0.017422987,-0.028881347,-0.014179068,0.011307937,0.040104263,-0.007593126,-0.000631943,-0.0003404971,-0.0055198953,-0.00063030794,-0.004852799,-0.0024214943,-0.029718488,0.023322212,0.011079031,0.012988758,0.0071614753,-0.034034993,-0.01551326,0.004012388,0.006442058,0.032386873,0.0076519875,0.0465921,0.01757995,-0.0135381315,-0.016978256,0.024983412,0.0003280299,0.0026209692,0.022380428,-0.010640841,0.0027648527,-0.007959375,-0.005922115,0.0075342646,-0.03597088,-0.018874902,0.03510758,-0.015356296,0.004597733,-0.0015328501,-0.019947488,-0.013446569,0.020614585,-0.0056016473,0.035186063,0.0005248479,-0.030712591,-0.019136509,0.004202053,-0.010339993,0.014754602,0.0072922786,-0.015460939,0.027494833,-0.02974465,-0.0033616424,0.0105819795,-0.028881347,0.01720062,-0.0073707607,0.0054479535,-0.0019522378,-0.018103164,-0.009110443,-0.024630243,0.005624538,0.01879642,-0.019345794,-0.0027681228,-0.015971072,0.022354268,-0.0038194535,0.018901063,-0.017357586,-0.02493109,0.006703664,-0.0021173768,-0.005667049,-0.004535601,-0.016441964,0.0034172337,-0.02447328,-0.003310956,-0.02078463,-0.011589164,0.013263445,-0.014728441,-0.0187441,-0.019476596,0.013224204,0.015238573,-0.012380524,0.00019058435,0.010778184,0.025022654,-0.036127847,0.01470228,-0.007671608,0.032857765,0.002982313,0.009829861,0.0072203367,-0.0028237142,0.025990596,-0.029012151,0.0016955365,0.012033895,-0.0049901423,-0.013629694,0.0072464976,0.0012704261,0.0018868363,0.017043658,0.00448001,-0.009555174,-0.016520444,0.02570283,-0.00939167,0.01998673,0.002001289,-0.023662299,0.0041072206,-0.024839528,-0.007396921,-0.0034793653,-0.032020625,-0.0036003583,-0.010719323,0.022995204,-0.01757995,-0.0043851775,-0.023884665,-0.018430172,-0.009018881,0.00091562246,-0.0055689462,-0.012537487,0.016455043,0.03264848,0.018560974,0.014623798,0.0025555675,-0.0060986993,0.0058272826,-0.008462967,-0.012720612,-0.0042576445,-0.027207067,0.014152907,-0.0029610575,0.010241891,-0.011222915,-0.01140604,-0.022197304,-0.003433584,-0.0056899395,0.004372097,0.061896075,-0.005846903,-0.011863851,0.004535601,-0.0074819434,0.016847452,-0.0012647035,0.021085477,0.02409395,-0.030137058,-0.0012197399,0.009607496,-0.008220982,-0.007893973,-0.007893973,0.007972456,0.010012985,0.009143144,0.0044734697,0.015264734,-0.0032520946,0.002208939,0.011968493,-0.0012998568,-0.0114322,-0.056454662,-0.013217663,0.0017593032,-0.00244275,-0.021399405,-0.010732403,0.00694565,0.0033207664,0.0025539326,0.01102671,-0.012589809,0.010706242,-0.012413224,0.01427063,-0.000049970913,-0.0056016473,0.027965724,0.018652538,-0.009535554,0.0068867886,0.004699105,-0.001245083,-0.009071202,-0.0032946058,-0.03756668,0.034453563,-0.00408106,0.013361547,-0.0065107294,0.009300108,-0.016415803,0.0059973267,-0.017422987,0.0048822295,0.022158062,-0.025611266,0.01022227,-0.0061771814,-0.014218308,-0.00044636594,-0.019110348,-0.013747416,-0.013629694,-0.021896457,-0.0051634563,-0.020509942,-0.018731019,0.0043328563,-0.032386873,-0.023086766,0.0196074,0.20614585,-0.014649959,-0.009712138,0.01345965,-0.010928608,0.0196074,0.015814107,0.017383745,-0.0024656404,0.021399405,0.013668935,-0.0063864663,-0.0015303975,-0.0012924991,-0.0030575248,-0.015539421,-0.009692517,-0.012190859,-0.02287748,0.002936532,0.00069325697,0.013158802,-0.0070110518,-0.013629694,0.01585335,-0.019829765,0.013747416,0.016036473,0.011693806,0.0071483953,-0.010156869,-0.013799738,-0.00034703725,-0.010706242,-0.02289056,0.0039339066,-0.0015835363,-0.014532236,0.012445925,-0.00009779583,0.0053335004,0.0055329753,-0.005281179,-0.007475403,0.00040385488,-0.012942977,-0.015277814,0.012956058,0.00006162057,0.007056833,-0.02571591,-0.018731019,-0.0061771814,0.034427404,0.0010570535,0.0079528345,0.024172433,0.021386323,-0.019803606,-0.006821387,-0.011262156,0.026605371,-0.0036951904,-0.008207901,-0.019698963,0.042981934,-0.026212962,0.00856761,0.015173172,0.0024149541,-0.0008036222,-0.005752071,-0.02898599,-0.008443347,-0.0064224373,-0.014479915,0.036467932,-0.00086820626,0.026396086,0.002001289,-0.0074361623,-0.0086918725,-0.007835112,0.021464806,0.0008984545,-0.02489185,0.019515838,0.026644614,-0.0137212565,0.00448982,0.004211863,-0.022380428,-0.014100585,-0.01629808,0.0074884836,0.02652689,0.011634945,0.049626734,-0.023583818,-0.0021958589,-0.015735626,0.02733787,0.0036428692,-0.031261966,-0.012674831,0.006196802,-0.009535554,0.016886694,0.010771644,-0.021490967,0.014100585,-0.007063373,0.00043778197,-0.012151618,-0.0058894143,0.009182385,-0.005768421,-0.013995943,0.004725266,-0.01347273,-0.020797709,-0.018037762,0.020274498,0.011595704,0.0017364125,-0.02248507,0.005954816,0.0062196925,-0.014257549,-0.025127295,0.015356296,0.005179807,0.021726413,-0.0034499345,-0.017082898,0.019803606,0.005209238,0.0005939283,-0.0035807376,-0.011661106,0.006559781,0.0033207664,0.0017233322,-0.00059924216,-0.000341519,-0.0140221035,0.00084286317,-0.003306051,-0.005634348,-0.00816212,-0.009319728,-0.024447119,-0.014950806,-0.024564842,0.0137212565,-0.010084927,0.000044886958,-0.0033943432,0.0025359471,0.012478625,-0.023086766,0.014519156,0.020876192,-0.023282971,-0.0030804155,-0.014545316,-0.16805595,0.01262905,0.020719228,-0.012413224,0.026592292,-0.0024198592,0.041072205,0.002658575,-0.013708176,-0.0068867886,-0.0018639456,0.000031627806,-0.043452825,-0.028018046,-0.0105819795,0.01266829,-0.009450532,0.008292923,0.0058534434,-0.006782146,0.032229908,0.0005955633,-0.0023103117,0.003140912,0.00037687673,-0.0049247406,-0.008070557,0.017279103,-0.012759852,-0.011608784,-0.019450437,0.016167276,0.02248507,0.030529467,0.015905669,0.0061150496,-0.016834373,0.017344505,0.006667693,-0.005461034,0.0066742334,0.01998673,0.024591003,-0.007717389,0.0096598165,0.03225607,0.018626377,-0.020248337,0.0017740185,0.012589809,0.0014927916,-0.040235065,0.01713522,0.016206518,0.017776156,0.024734886,0.0040516295,-0.009627116,0.002001289,-0.010496957,-0.0121058365,-0.017266022,0.008279843,-0.02122936,-0.01349889,-0.02251123,0.004820098,-0.000071533,-0.022628954,0.015238573,-0.01833861,-0.016572766,-0.0031523572,-0.008064018,0.019973649,0.0089207785,-0.03228223,0.0040647094,-0.004784127,-0.0017920039,-0.0013775212,0.047246117,0.0030804155,-0.010660461,0.02982313,0.006088889,-0.019371955,-0.024447119,-0.011687267,-0.013708176,0.017187541,-0.018286288,0.019267311,0.0011960318,0.0046271635,0.016886694,0.0069129495,0.00029062838,0.013629694,-0.016494283,-0.017069818,0.0058240127,0.013943622,0.001675916,0.01347273,0.023335291,0.008129419,0.0047187256,0.032099105,0.0007701039,0.0068344674,0.0004672127,-0.00610851,0.026396086,-0.010738943,0.024591003,0.008220982,-0.019908248,0.024682565,-0.009404751,0.0594893,-0.009731758,-0.022628954,0.013865139,-0.016049553,0.0033371167,-0.107572556,-0.022341188,0.008050937,-0.0089731,0.004983602,0.010771644,-0.013034539,-0.013368088,-0.0071287747,0.0091758445,-0.017409906,-0.022118822,-0.011170594,-0.010908987,0.050490037,0.014584557,0.018312449,0.0014968792,-0.0057161,0.024342475,-0.02699778,0.020091372,-0.00094587065,-0.021347083,-0.003711541,0.0016677409,-0.030738752,0.040208906,0.008109799,-0.017527629,-0.0009058122,0.017776156,0.0052779093,-0.0046206233,0.0067952266,-0.01226934,-0.009162764,-0.01595799,0.021582529,-0.027390191,-0.00011210243,-0.003145817,0.01672973,-0.009999905,0.003832534,-0.01793312,-0.0004868332,0.027573315,0.001756033,-0.012112376,-0.009718678,0.0025473924,-0.027547155,-0.019084187,0.010693162,0.025558947,-0.02168717,-0.0068802484,-0.010869746,-0.028698223,-0.0051634563,-0.012131997,-0.014963887,0.022210384,0.01510777,-0.0026504,-0.013577373,0.0058599836,0.011281776,-0.0009393305,-0.00204053,0.030110897,-0.029326078,0.006491109,-0.01671665,0.0006049648,-0.024342475,-0.008325624,0.03722659,-0.007710849,-0.0055656764,-0.02043146,-0.015317055,-0.015212413,0.002815539,0.022262705,0.00818828,0.021778734,-0.0037409717,-0.02485261,0.0033779927,0.013217663,-0.0059319255,-0.018940303,0.02409395,0.015761785,-0.009672897,0.011301396,-0.011582624,0.0029725027,-0.015343216,-0.00735114,-0.075761214,0.016821291,0.0028040938,0.0017233322,0.01595799,-0.0054741143,-0.007096074,-0.011641486,-0.003554577,0.009829861,-0.037828285,0.024983412,0.003793293,-0.010895907,-0.011916172,-0.017893879,0.029640006,0.0027452323,0.004977062,0.0138913,0.0132830655,0.010725862,0.014205228,-0.003839074,0.020470701,0.0048626093,-0.010967849,0.035343025,-0.004568302,-0.007665068,0.0040091183,-0.02367538,-0.006821387,0.012112376,-0.0012475356,-0.02041838,-0.030869557,-0.004865879,0.036127847,0.019528918,0.00087147637,0.0016366751,-0.006072539,-0.012380524,-0.016886694,0.0014224849,0.0058632535,0.0053138803,0.024525601,-0.008227522,0.016167276,0.021373244,-0.019855926,-0.011602244,-0.012223559,0.009116983,0.00448001,0.0027027212,0.0112294555,-0.025048813,0.005958086,0.005578757,0.012040435,-0.019528918,-0.008096718,-0.023439934,0.00047497914,0.0073315194,0.025061894,-0.016455043,0.003992768,0.002038895,-0.0003484679,0.004444039,-0.014846164,0.0018263398,0.017305264,-0.0047154557,-0.006729825,0.011288317,-0.009764459,-0.03220375,-0.015369376,0.009594415,0.031078842,0.020967754,-0.007802411,0.022354268,-0.010778184,0.01833861,0.004581382,0.0072399573,0.010673542,-0.012112376,-0.023073684,0.0066448026,-0.027887244,0.0063504954,0.012956058,0.032151427,-0.018103164,0.0048855,-0.018286288,-0.036938824,-0.012354363,0.020039052,0.004921471,-0.03790677,0.0212686,0.02982313,0.015434778,0.0041039507,-0.016245758,0.012171238,-0.006415897,0.0072464976,-0.0024362097,-0.025218857,-0.021399405,0.036860343,0.0056572384,0.017004417,0.03432276,-0.013825899,0.028724384,0.008528369,0.018652538,-0.02443404,-0.025637427,0.006497649,-0.015447859,0.01917575,-0.016520444,-0.008678793,-0.021072397,0.015840268,-0.006324335,0.025925195,-0.03594472,0.0384823,0.01308032,0.0054217926,0.00448328,-0.027207067,-0.016847452,0.0036003583,0.01061468,-0.019816685,-0.004659864,0.023387613,-0.005461034,0.004326316,0.0037278912,-0.007540805,0.00860031,0.0015524705,0.020039052,-0.0028367946,0.0049509015,0.009162764,0.009705598,0.013982862,0.004852799,0.0061869915,-0.0083910255,0.012975678,-0.034558207,-0.029064473,-0.03058179,-0.019450437,0.01062122,-0.014179068,-0.010012985,0.007874353,-0.014126746,-0.009731758,-0.03398267,-0.000115883464,-0.0029725027,-0.024290156,0.012864495,-0.00937859,-0.035264544,0.0027959184,0.012982218,-0.012609429,0.0065270797,0.010712783],
    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]
    1year: 1993
    2plot: "A botched mid-air heist results in suitcases full of cash being search…"
    3genres: Array (3)
    4title: "Cliffhanger"
    5score: 0.7694521546363831
    6
    7genres: Array (3)
    8title: "It's a Mad, Mad, Mad, Mad World"
    9year: 1963
    10score: 0.7638954520225525
    11plot: "The dying words of a thief spark a madcap cross-country rush to find s…"
    12
    13score: 0.7538407444953918
    14year: 1991
    15plot: "A cat burglar is forced to steal Da Vinci works of art for a world dom…"
    16genres: Array (3)
    17title: "Hudson Hawk"
    18
    19plot: "In 1997, when the US President crashes into Manhattan, now a giant max…"
    20genres: Array (2)
    21title: "Escape from New York"
    22year: 1981
    23score: 0.7487208843231201
    24
    25title: "The Romanov Stones"
    26year: 1993
    27score: 0.7467736005783081
    28plot: "Patrick and Tony are hired by the wealthy gambler to steal the pricele…"
    29genres: Array (2)
    30
    31plot: "An attempted robbery turns to be an unexpected recruitment when two un…"
    32genres: Array (3)
    33title: "Crime Busters"
    34year: 1977
    35score: 0.7437351942062378
    36
    37plot: "In the aftermath of the Persian Gulf War, 4 soldiers set out to steal …"
    38genres: Array (3)
    39title: "Three Kings"
    40year: 1999
    41score: 0.7425670623779297
    42
    43plot: "A professional thief is hired by the FBI to steal a data tape from a c…"
    44genres: Array (3)
    45title: "Black Moon Rising"
    46year: 1986
    47score: 0.7397696375846863
    48
    49plot: "A group of heavily armed hijackers board a luxury ocean liner in the S…"
    50genres: Array (3)
    51title: "Deep Rising"
    52year: 1998
    53score: 0.7392246127128601
    54
    55year: 1964
    56score: 0.7357995510101318
    57plot: "A young man comes to the rescue of his girlfriend abducted by thieves …"
    58genres: Array (3)
    59title: "That Man from Rio"

    The following query searches the plot_embedding field using the vector embeddings for the string martial arts. The query uses ada-002-text embedding, which is the same as the vector embedding in the plot_embedding field. 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 genres field to find movies that aren't in the crime genre.

    • Filter by the year field to find movies that were released in or before the year 2015 and by the genres field to find movies in the action genre.

    1[
    2 {
    3 "$vectorSearch": {
    4 "index": "vector_index",
    5 "path": "plot_embedding",
    6 "filter": {
    7 "$or": [{
    8 "genres": { "$ne": "Crime" }
    9 }, {
    10 "$and": [{
    11 "year": { "$lte": 2015 }
    12 }, {
    13 "genres": { "$eq": "Action" }
    14 }]
    15 }]
    16 },
    17 "queryVector": [-0.016465975,-0.0036450154,0.001644484,-0.028249683,-0.02077106,0.00031438665,-0.02351539,-0.017519485,-0.0025362284,-0.038888834,0.023489377,0.022695992,0.009481592,0.009995341,-0.0043506073,-0.0021297815,0.033972453,0.00070193375,0.007335553,-0.017909674,0.015191358,0.015360439,-0.00020505243,-0.023801528,-0.013539557,-0.0015290531,0.009631164,-0.026493832,-0.0245689,-0.02481602,0.02832772,-0.012473041,-0.006538917,-0.021707514,-0.01676512,-0.005865841,0.010359517,-0.013246916,0.014710125,0.0060869483,0.016192842,0.0026484078,0.002417546,-0.007764761,-0.0053781047,0.0016843157,0.009071894,0.0026158919,-0.016465975,0.019054228,0.030720878,0.028145632,-0.0124340225,-0.011491066,-0.01273967,-0.0076542073,0.00685432,0.002936172,0.03194347,-0.030798918,-0.004961903,0.012661632,-0.024646938,0.0085256295,-0.01133499,0.016648063,-0.017857648,0.01627088,-0.020823086,-0.002233832,0.008330535,0.024894057,0.008558145,0.013786677,0.027235191,-0.0075046346,-0.015308415,-0.0031442728,0.009136925,0.010548109,0.009455579,-0.0070624207,-0.001147806,0.008928824,0.011042348,-0.019314354,-0.0035702293,0.019691538,0.013929747,-0.00071615935,-0.0016477356,-0.0029556816,0.009592146,0.011699166,-0.045183886,0.018533977,-0.025063138,0.002194813,-0.013968766,0.0037848332,-0.014775156,0.0138777215,-0.023112195,-0.019288342,-0.02252691,-0.009813253,-0.0030792414,0.00088036386,0.0048285886,-0.019691538,-0.021863589,0.0068413136,0.01641395,-0.04494977,-0.0027475806,-0.014710125,0.0077192388,-0.0030954992,0.005417124,-0.008219982,0.014046803,0.01662205,0.027235191,0.0015266144,0.036261562,0.02006872,-0.032489736,-0.0019379386,0.004106739,-0.006808798,0.048825648,0.0096766865,0.0132794315,0.0066722315,-0.026116649,0.019912645,-0.017441448,-0.0014128092,-0.041880284,-0.018599007,0.018729072,0.00619425,-0.01947043,-0.009748221,-0.012121871,0.0001831043,0.037198015,0.03451872,-0.0045684627,-0.0040742233,0.022708999,-0.028847972,0.027287217,0.0008214291,0.018156795,-0.007816786,-0.017519485,0.00501718,-0.0013811064,-0.0148401875,0.012752676,-0.01686917,-0.0018013725,-0.014645093,-0.0064218603,0.016426956,0.008558145,0.013207897,-0.012518563,-0.00018208819,0.022643967,0.020745048,-0.018143788,0.0123169655,-0.018039737,0.019626506,-0.009162938,0.0030255904,-0.02942025,-0.007511138,0.0050139283,-0.006408854,0.04065769,0.011419531,0.000562116,0.032775875,-0.012043833,0.009410057,-0.012694148,-0.019041222,0.015646579,0.021109223,-0.010749706,-0.01915828,-0.6842354,-0.022748018,0.010444058,-0.013090841,0.031241132,0.0032792133,0.030772904,-0.0061389734,-0.018013725,-0.0103335045,0.0075046346,0.012395004,-0.0035442165,-0.011256952,0.017064264,-0.00813544,0.014319936,-0.044559583,0.0053065703,0.00027028716,-0.014892213,0.012499054,0.002056621,-0.006860823,-0.020875111,-0.0028890243,-0.01048958,0.0043993806,-0.004360362,0.01922331,-0.031501256,0.025882537,0.0032922195,-0.0058300737,0.053117726,0.0013900483,-0.029784426,0.055875063,0.02417871,0.038888834,-0.00365477,-0.0024793257,0.0005182197,-0.008805265,-0.007589176,0.013643608,0.03685985,-0.024152698,0.00400594,-0.0148401875,0.01971755,0.0002887805,-0.0050594504,-0.020120746,0.00209564,0.00084947393,0.004688771,-0.013526551,0.016140817,0.024191717,0.0020354858,0.008200472,-0.014463005,-0.012453532,0.0034596757,0.0014843439,-0.0266369,0.0069648735,-0.0044318964,-0.015620566,0.0060154134,0.018937172,-0.01588069,-0.0025882535,0.03251575,0.062118087,0.017805625,-0.0098522715,-0.013968766,-0.016153824,0.01641395,0.0018794102,-0.019964669,0.012290953,0.024855038,-0.015334427,-0.012017821,0.007647704,-0.01402079,-0.0008665447,0.0069778794,0.014007784,-0.009709203,-0.011022839,-0.017311385,-0.0050139283,-0.0033393675,0.0025573636,0.010463567,-0.028691897,-0.016752115,0.008974346,0.024373805,-0.003908393,-0.026142662,0.015906705,-0.012440525,0.006808798,0.033998467,-0.006808798,0.011764198,0.0033913925,0.003986431,0.0067632757,0.012154386,-0.025609404,0.008616674,0.0023037407,0.028093606,-0.02762538,0.0077127353,-0.015828667,0.014033797,0.009039378,0.0032905939,0.011829229,-0.020133752,-0.0066137034,0.008902812,-0.020667009,0.008655692,0.020693023,0.022266785,-0.01216089,0.03620954,-0.0069973893,0.0014347574,-0.0002489487,0.020536946,0.0008933702,-0.021135237,-0.0017704825,-0.007875314,-0.0022078194,0.005384608,-0.030200627,-0.010821241,-0.0011136644,-0.013383482,0.01986062,0.007647704,0.010353014,-0.0065454203,0.0041490095,0.005170004,-0.0070949364,-0.04031953,-0.0148401875,-0.0075826724,-0.020510934,0.0012607982,0.006425112,-0.017441448,0.011165908,-0.0019606997,-0.017532492,-0.017649548,0.019548468,-0.023593428,-0.027989557,0.014944238,-0.007589176,0.018039737,0.014593068,-0.000074125746,0.029342212,-0.0027589612,0.00043571103,-0.017207334,0.003755569,-0.008896309,-0.027677406,-0.0058365767,-0.010665165,0.0009974206,0.01662205,-0.0016526129,0.005726023,-0.012193406,0.013526551,-0.027183166,0.032567773,-0.01203733,-0.004792821,0.009540121,0.006899842,-0.010918789,0.022006659,0.020953149,0.0073745716,0.011022839,-0.025505353,0.018937172,0.0181698,0.013292438,-0.038706746,-0.0021818068,-0.025050133,0.041984335,-0.004565211,0.00012589691,-0.004968406,-0.004835092,-0.023788521,0.008785755,0.013578577,-0.012473041,0.008473604,-0.01922331,0.012499054,0.016218856,-0.018338881,0.024295768,-0.0015688848,0.012687645,0.037198015,-0.004158764,0.023294283,-0.010918789,-0.01405981,-0.015412465,0.0056187212,-0.010235958,0.007114446,0.01170567,0.015048289,0.027547343,-0.039461114,0.034856882,0.004243305,0.006025168,0.012941268,0.02853582,0.004786318,0.015022276,-0.0034531725,0.04073573,-0.027313229,-0.006386093,0.0016266003,-0.034102518,-0.0015705107,-0.020836093,-0.0064218603,0.007933843,-0.028769935,0.009936812,0.0038303551,0.022682985,0.020797072,0.0044253934,0.020406883,0.012082852,-0.0028955275,0.007972862,-0.0057032625,0.002684175,0.0074526095,-0.022344822,0.0052838093,-0.004965155,-0.0088312775,0.023333302,-0.009566133,0.013266426,0.0070168986,0.008850787,-0.0021525426,-0.0006653535,0.016192842,-0.0039409087,-0.049527988,0.0058008097,-0.01205684,-0.010268473,-0.016518,-0.030954992,-0.0022159482,-0.038914848,0.010730197,-0.0006629148,0.012902249,-0.0037880847,0.0011136644,-0.036079474,0.010645656,0.012785193,-0.0056122183,0.007888321,-0.0036059965,-0.013435507,-0.004327846,-0.02762538,-0.0006722631,0.02428276,0.024724975,-0.007790773,0.00027557096,0.00685432,-0.025440322,0.011634135,0.011068361,-0.003983179,0.020901123,0.019210305,0.011035845,-0.006737263,-0.01405981,0.01205684,-0.000036885052,-0.011185418,-0.02287808,-0.010340008,-0.017805625,0.10004445,-0.0103920335,-0.0067112506,0.0101579195,-0.019587487,-0.023658458,-0.014996263,-0.0056252247,0.003189795,0.011022839,-0.009462083,-0.017155308,-0.010053869,0.0041977833,0.0023427596,0.01216089,-0.004285576,-0.003175163,0.0022809797,-0.006376338,0.028431771,-0.023112195,0.03280189,0.025843518,0.028509809,0.0067437664,0.000053498567,0.009527114,0.008259,-0.03293195,-0.0032401944,0.0038108458,0.0053553437,0.013734652,-0.0080443965,-0.0177536,0.014931232,0.006051181,0.034128528,-0.030408729,0.015659584,0.04341503,0.00082183554,-0.01831287,0.012421016,-0.024048647,-0.01655702,0.01627088,-0.0214734,-0.025856523,0.019821601,0.01191377,-0.026337756,-0.030044552,0.0096051525,0.026090637,-0.00149166,0.019275336,-0.0049586515,-0.011120386,-0.0010518845,-0.020549953,0.020927135,0.0032922195,0.004054714,-0.020836093,0.00082102267,-0.015763635,-0.0068478165,-0.0015916459,-0.014124841,-0.008870296,0.010951304,-0.019678531,0.0029410494,-0.008070408,0.03092898,-0.008141943,0.0028093606,0.017129296,-0.02671494,-0.017766604,-0.028587846,-0.028249683,0.010053869,0.0061129606,0.0047700605,-0.012128375,-0.011627631,0.010424549,0.020640997,0.017831637,0.024477856,0.000978724,0.00071412715,-0.014306929,0.00279798,0.012733167,0.014645093,0.013149369,-0.006447873,-0.033582266,0.011465053,0.00060560583,-0.0015802654,-0.01620585,0.010795228,0.021798559,-0.0015022276,0.0061292187,0.03553321,-0.01666107,0.029056072,-0.003648267,0.020393878,0.021083212,-0.00060519937,0.020016694,-0.00827851,-0.023034155,0.023203239,-0.016296893,-0.017207334,0.051504947,-0.010144914,-0.019392392,0.020445902,-0.022982132,0.0019330613,0.01441098,-0.031189106,0.02393159,-0.0031020024,-0.006073942,-0.025492348,-0.01866404,-0.01121143,0.01567259,0.01143904,-0.0037360594,-0.008941831,-0.00005959527,0.018820114,-0.00044790443,0.012791695,-0.021512419,0.0009762854,0.0043180916,-0.02091413,0.007790773,-0.030876955,0.006200753,0.00017294314,-0.0009608404,-0.021356344,-0.031371195,-0.02256593,-0.025752474,0.0216815,0.016609045,0.04312889,0.0022078194,0.031657334,0.0011949538,-0.01013841,-0.0037490658,-0.019652518,-0.0024354295,-0.039513137,0.01662205,0.03784833,0.006431615,0.003113383,-0.010613141,-0.0014875955,0.012551079,0.0010844002,0.0006515343,-0.004106739,-0.023775516,-0.0042042863,0.0001352452,0.008213478,-0.01108787,-0.017207334,-0.008480107,0.02733924,0.016426956,0.013383482,-0.009045881,0.017181322,-0.003466179,-0.005248042,-0.0060609356,0.010593631,0.011484562,-0.00082508713,-0.0064673824,0.008473604,0.0074005844,0.015932716,-0.0062755393,-0.0064056027,-0.012648626,-0.011452046,0.010626147,-0.008460598,-0.040163454,-0.00718598,-0.022708999,-0.010105895,-0.020940142,-0.008272006,-0.0464585,0.005696759,0.0025866278,-0.020640997,0.024555894,0.0016339164,-0.010704185,0.021317326,-0.0064608795,0.038758773,0.005072457,0.022513904,0.0088312775,0.009377542,-0.0055634445,0.016960215,0.014254904,-0.016426956,0.004965155,0.012876237,-0.000355641,-0.0117186755,0.016817145,-0.00048367176,-0.034180555,-0.024490861,0.021746533,0.007836295,0.016361924,-0.014749143,-0.012447028,-0.034128528,0.02492007,-0.0076672137,0.019249324,-0.024503868,-0.009546624,-0.028275695,0.030200627,-0.01887214,0.008746737,0.015594553,-0.018911159,-0.0045847204,-0.008603667,-0.0030646094,0.0016030264,0.0022078194,0.04083978,0.016036768,0.005995904,0.011016335,0.014788163,-0.0020094733,-0.0012624239,-0.012258437,0.026740951,-0.01736341,-0.008746737,-0.0126811415,-0.0026906782,0.0028126123,0.011868248,-0.002944301,-0.006912848,-0.019743562,0.0008844284,-0.00002194813,0.023567414,-0.025674434,-0.002485829,-0.028015569,-0.022266785,0.0009779112,-0.025570385,0.009572636,-0.017324392,-0.030512778,-0.008245993,-0.024972094,0.0067567728,-0.012590098,-0.022513904,0.00848661,0.04435148,-0.0326198,-0.0048318403,-0.031501256,0.0071534645,-0.010359517,0.01947043,-0.013032312,-0.032879926,0.03423258,-0.019314354,-0.007972862,-0.022409854,0.0067567728,-0.0072315023,-0.0031979238,0.0042725694,0.02133033,-0.013487533,-0.0018859134,-0.023593428,-0.0148401875,0.00803139,0.0037815815,-0.00084540946,0.0021249042,-0.040111426,0.0071924836,0.010235958,0.022630962,-0.009000359,-0.017272366,0.010008347,-0.035377134,0.010541606,-0.026506837,-0.01273967,-0.0088312775,0.019873625,-0.012212915,0.040111426,-0.008896309,0.013981772,0.022487892,0.014319936,-0.0062170113,0.01228445,-0.02140837,-0.0048448467,0.0011030968,-0.006470634,-0.003449921,0.004136003,-0.016400944,0.013851709,0.024061654,-0.020693023,-0.0083500445,0.009364536,-0.040345542,0.0068868357,-0.0042693177,0.012830715,0.0004094952,0.009058887,-0.008811768,0.008577654,0.00048367176,-0.0020582469,-0.0035507197,0.00032942518,0.010424549,-0.0032954712,0.0057065138,-0.0014046803,-0.018403914,-0.023905579,0.021291312,-0.01275918,0.021213274,0.00069502415,-0.006951867,-0.011777204,-0.009819756,0.00071981736,-0.0017298379,0.011959292,0.011881255,-0.039357062,-0.0025102159,-0.0062917974,-0.0142418975,-0.017194327,-0.008057402,0.010444058,-0.0011526833,0.013578577,-0.0041262484,-0.003625506,0.0016648063,-0.028249683,0.021421375,0.0153214205,-0.0074526095,0.019652518,0.016465975,-0.004158764,-0.020354858,-0.022227766,-0.016244868,-0.019353373,-0.00365477,-0.015399459,0.013201394,-0.029992526,0.010372524,-0.013292438,0.010457065,-0.0030824929,0.017428441,-0.0009746596,0.0005300067,0.009299504,-0.028379746,-0.003012584,-0.002593131,-0.0071209488,-0.016114805,-0.009403555,-0.010502587,-0.001316075,0.0075826724,0.027781455,-0.005582954,0.00104782,-0.021447388,0.0058690924,-0.001032375,0.01911926,0.18895552,-0.006295049,-0.010587128,0.047264893,-0.00097547245,0.032437712,0.035819348,-0.010769216,-0.013734652,0.01588069,0.0024500617,0.00061251543,-0.009130422,-0.0040937327,-0.0014339446,-0.0073550623,-0.017805625,0.0035734808,-0.0117186755,-0.019873625,-0.013272929,0.00425306,-0.011640638,-0.0027296972,0.008024887,0.0060154134,0.0070949364,0.010040863,0.006376338,-0.0058073127,-0.010522096,0.012486047,0.015932716,-0.019054228,-0.02502412,0.0069973893,-0.01335747,-0.012492551,0.010652159,0.0032548264,-0.015503509,0.008649189,0.009598649,0.0056122183,-0.009162938,0.023788521,-0.011595116,0.009988838,0.008005377,0.004841595,-0.02632475,-0.009735215,0.029966515,0.028093606,-0.0068933386,-0.0024972095,0.0046465006,0.0058333254,0.017142303,0.011243946,-0.0013030686,0.020680016,-0.012102362,0.028847972,-0.008226484,0.0035051976,-0.01461908,0.0073550623,0.002163923,-0.016895182,-0.001193328,-0.017025245,0.0024988353,-0.012843721,-0.022839062,-0.031475246,0.025674434,0.022370836,0.011972299,0.02382754,-0.011900764,-0.03204752,0.00695837,-0.008915818,-0.01781863,0.0044156387,-0.0011502446,0.017688567,-0.013194891,0.0021314074,0.0012225922,-0.027001077,-0.00074583,0.012271443,0.010294486,0.014710125,0.01641395,0.009540121,-0.008330535,0.0005958511,-0.026662914,-0.0019444418,0.024737982,0.012147884,-0.0067892885,0.016335912,-0.017558504,-0.0058170673,-0.0009689693,0.0025866278,0.0105676185,-0.02442583,-0.01170567,-0.005397614,-0.018078756,-0.019704543,0.005498413,0.016648063,0.024490861,-0.013942753,0.015867686,-0.002645156,0.008805265,-0.007296534,0.0083500445,-0.0025362284,-0.031553283,0.0077517545,0.0035832354,-0.041594144,0.006704747,-0.011185418,0.0037913362,-0.012011318,-0.025830511,0.041802246,-0.01003436,0.0097937435,0.003641764,0.022787036,-0.0017867404,-0.0026110145,0.028145632,0.011152902,0.004311588,-0.021915615,-0.009182448,0.02077106,-0.006171489,-0.0055309287,-0.019379387,0.0022647218,-0.021213274,-0.014983257,0.01158211,-0.0149572445,-0.021278305,-0.011725179,-0.021798559,0.019691538,-0.04835742,0.011536588,0.029082086,-0.0006828307,-0.020003688,-0.0067957914,-0.16679278,0.015646579,0.037119977,-0.026480826,0.0109317945,0.0053488407,0.013825696,-0.00035117008,-0.0013892354,-0.0014022416,0.021915615,0.008974346,-0.03274986,-0.0078688115,0.023034155,0.003518204,-0.017857648,0.025037127,0.0137606645,0.02411368,0.025765479,0.0024338039,-0.00607069,-0.005114727,-0.009071894,-0.0094295675,0.021096218,0.016400944,-0.013175381,-0.0047440478,-0.015789647,-0.006548672,0.017766604,0.0077452515,0.0044221417,0.00838256,0.0007568041,-0.015386452,-0.017649548,0.014306929,-0.003066235,0.02783348,-0.006984383,-0.02586953,0.005108224,0.02432178,0.00885729,0.0023297535,0.007166471,-0.0021281557,-0.0052740546,-0.0035149525,0.014085822,0.00063893443,0.031215118,-0.00425306,0.014202879,-0.018351888,-0.0032158075,-0.0055081677,0.003999437,-0.0017753599,0.022748018,-0.023684472,-0.007946849,-0.019145273,-0.022487892,0.018247837,-0.004535947,0.008993856,-0.0043018335,0.005498413,-0.0022647218,-0.023112195,0.0055114194,0.008818271,-0.00536835,0.022604948,-0.020406883,-0.024386812,-0.014931232,0.01761053,0.0037588205,-0.0034986946,0.01831287,0.036001436,-0.000008446474,-0.024907064,-0.0036612733,-0.011725179,0.023047162,-0.029758412,-0.014554049,-0.012934765,0.015412465,0.021850582,-0.011523581,-0.0022858572,-0.0040742233,-0.0056187212,0.010307493,-0.019184291,0.005192765,0.008018384,0.022722006,-0.0058138156,0.03771827,0.01028148,0.029212149,-0.0054366332,0.0014079319,-0.0009974206,0.011627631,0.026480826,0.0025346025,0.018937172,0.0085971635,-0.012395004,0.011608122,0.00065397297,0.040085416,0.008883302,-0.0013339586,-0.0064413697,-0.007296534,0.0028467537,-0.092917,-0.00801188,0.016192842,0.027469303,-0.033166062,0.017662555,-0.002692304,0.036079474,-0.0144760115,0.020445902,-0.00036641184,-0.018442933,-0.008493113,-0.01476215,0.018703058,0.001552627,0.0065876907,-0.017974706,-0.0076542073,0.022149729,-0.010066876,0.004932639,-0.0061292187,0.0016436711,-0.007959855,0.0031393955,-0.0324117,0.037093967,0.007114446,0.019821601,-0.016518,-0.0034596757,0.021668496,-0.03332214,0.012785193,-0.007810283,-0.018833121,-0.0029963262,0.0210572,-0.019392392,0.0021135237,0.015685597,0.013116853,-0.027495317,0.011250449,-0.0071924836,-0.019106254,0.0107562095,0.014007784,-0.034492705,-0.03394644,-0.024750987,-0.041047882,-0.006685238,0.0068868357,0.008694711,0.019093247,0.01261611,-0.009748221,-0.0027394518,0.014918226,-0.0032710843,-0.0044936766,0.01546449,0.018208819,0.004288827,-0.021538433,-0.026897028,0.023879565,-0.018299863,-0.012245431,0.015516515,-0.040891804,-0.011816223,-0.02221476,0.012082852,-0.02417871,-0.009338523,0.010047366,-0.027079115,-0.016010754,-0.021863589,-0.004305085,-0.027261203,0.024100672,0.000711282,0.001071394,-0.0037263047,-0.007829792,-0.0049456456,-0.021603463,0.03274986,0.01866404,-0.032567773,-0.0044318964,0.017935688,0.018638028,-0.015282402,-0.009377542,0.03012259,0.015178352,-0.004792821,-0.048305396,0.007075427,0.020784067,0.010678172,0.0019509449,0.0045684627,0.02242286,-0.011374009,0.024477856,-0.0021736778,-0.021291312,-0.009188951,0.02692304,-0.0038628709,-0.02442583,-0.029394237,0.019054228,0.01606278,-0.0035051976,-0.00012284856,0.01911926,0.0088768,0.007036408,0.0015461239,-0.0030711126,0.0034629272,-0.015152339,0.02097916,-0.031163093,0.0061909985,0.012694148,-0.021902608,-0.030044552,0.031553283,0.0002003783,-0.037119977,0.0003367412,0.015347433,0.003105254,0.034102518,0.001911926,-0.008102925,0.0003306445,0.011647142,-0.004288827,0.019665524,-0.011907267,0.01391674,0.0014428863,-0.01655702,-0.0020387375,0.009975832,-0.0009982334,-0.018586002,-0.0137606645,-0.031787395,0.02481602,0.0059308726,-0.0011941409,-0.009598649,0.0126811415,0.015828667,-0.0058918535,-0.0040807263,-0.00406772,-0.0015233628,-0.01402079,-0.0052577965,0.0018290109,-0.018182807,-0.014736137,0.014423986,-0.001820882,-0.013799684,0.0029085337,0.009949819,0.02407466,0.01992565,-0.01986062,0.02892601,0.0029768168,0.00044018193,-0.012882739,0.022487892,0.0061682374,0.014528036,0.0021785551,0.006304804,0.0010722068,-0.0075696665,-0.0040417076,0.0097937435,-0.01216089,-0.0044026324,-0.018494958,0.053898104,-0.0037100469,-0.013929747,0.0210572,0.014293923,0.028613858,-0.005791055,-0.008863793,-0.021668496,0.0011803217,0.0053781047,-0.020588972,-0.030304678,-0.015893698,-0.0041295,0.04705679,0.020198783,-0.007010395,0.0039344057,0.00019905735,0.010587128,0.0026549108,-0.015165345,-0.023996623,0.01476215,-0.0021200269,0.0458342,0.02221476,-0.021174256,0.009000359,0.027573355,-0.007634698,-0.0053520924,-0.0032190592,0.010196939,0.014033797,0.01203733,-0.032307647,-0.00873373,-0.016609045,-0.014593068,-0.014658099,0.015828667,-0.024087666,0.03043474,-0.0020598727,0.006327565,0.0019850864,-0.004236802,0.015932716,0.00049139425,-0.0023232503,-0.018351888,-0.025466334,-0.010457065,-0.00039587924,0.0017330894,-0.024334786,-0.018599007,-0.0031442728,-0.030564804,0.036807828,0.0051895133,-0.015620566,0.020680016,0.021239286,0.019171285,-0.00803139,-0.027963543,-0.0049261358,0.018429926,0.011217933,-0.015984742,-0.020575965,-0.007472119,-0.0071924836,-0.035975423,-0.028405758,0.027573355,0.0015770138,-0.009279994,-0.007634698,0.007810283,0.039929338,-0.029186135,0.025245227,-0.02446485,-0.011770701,0.009611655,-0.0033718832,-0.015451483,0.007829792,-0.018403914],
    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]
    1title: "Ong-bak 2"
    2score: 0.7976737022399902
    3year: 2008
    4plot: "A young Thai boxer learns the skills and inner meaning of martial arts…"
    5genres: Array (1)
    6
    7score: 0.7929348349571228
    8plot: "A handyman/martial arts master agrees to teach a bullied boy karate an…"
    9genres: Array (3)
    10title: "The Karate Kid"
    11year: 1984
    12
    13plot: "A young martial artist embarks on an adventure, encountering other mar…"
    14genres: Array (3)
    15title: "Circle of Iron"
    16year: 1978
    17score: 0.7852014899253845
    18
    19plot: "A lionized account of the life of the martial arts superstar."
    20genres: Array (3)
    21title: "Dragon: The Bruce Lee Story"
    22year: 1993
    23score: 0.7763040661811829
    24
    25score: 0.7731232643127441
    26plot: "A martial arts instructor from the police force gets imprisoned after …"
    27genres: Array (2)
    28title: "Kung Fu Killer"
    29year: 2014
    30
    31plot: "A young woman is trained by a martial arts specialist to become a prof…"
    32genres: Array (3)
    33title: "Naked Killer"
    34year: 1992
    35score: 0.7693743109703064
    36
    37plot: "The life of the greatest karate master of a generation."
    38genres: Array (3)
    39title: "The Real Miyagi"
    40year: 2015
    41score: 0.768799901008606
    42
    43plot: "At his new high school, a rebellious teen is lured into an underground…"
    44genres: Array (3)
    45title: "Never Back Down"
    46year: 2008
    47score: 0.768179714679718
    48
    49score: 0.7679706811904907
    50plot: "Three young martial arts masters emerge from the back streets of Hong …"
    51genres: Array (2)
    52title: "Dragon Tiger Gate"
    53year: 2006
    54
    55title: "Shaolin Soccer"
    56score: 0.7660527229309082
    57year: 2001
    58plot: "A young Shaolin follower reunites with his discouraged brothers to for…"
    59genres: Array (3)

Note

The Pipeline Output pane displays the results of your query.

5

The Atlas UI might not display all the values in the documents it returns. To view all the values for the fields that you searched in the query path, expand the fields in the documents.

1

Open mongosh in a terminal window and connect to your cluster. For detailed instructions on connecting, see Connect via mongosh.

2
use sample_mflix
switched to db sample_mflix
3

The following queries use the $vectorSearch pipeline stage to search for movies that match the specified vector embeddings. Note that the queries use ada-002-text embedding, which is the same as the vector embedding in the plot_embedding field. 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 _id field and include only the title, genres, plot, and year fields in the results.

  • Add a field named score that shows the vector search score for each document in the results.

The following query searches the plot_embedding field using the vector embeddings for the string historical heist. The query uses ada-002-text embedding, which is the same as the vector embedding in the plot_embedding field. 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 genres field to find movies that aren't in the drama, western, or crime genre, but in the action, adventure, or family genre.

  • Filter by the year field to find movies that were released between the years 1960 and 2000, both inclusive.