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How to Combine Multiple `$vectorSearch` Queries

The MongoDB $rankFusion aggregation stage supports $vectorSearch inside the input pipeline. You can use $rankFusion to combine multiple $vectorSearch queries against the same collection in the same pipeline. $rankFusion first executes all input pipelines independently, and then de-duplicates and combines the input pipeline results into a final ranked results set. To run multiple $vectorSearch queries against multiple collections in a single pipeline, use $unionWith.

Use Cases and Benefits

You can run the following types of $vectorSearch queries by using the $rankFusion pipeline:

Run multiple $vectorSearch queries for similar terms against the same field.

This allows you to perform a comprehensive search of your dataset for similar terms in the same query.
Run multiple $vectorSearch queries for the same term against multiple fields.

This allows you to search multiple fields in your dataset to determine which fields return the best results for the query.
Run multiple $vectorSearch queries for the same term against embeddings from different embedding models.

This allows you to search embeddings from different embedding models to determine the semantic interpretation differences between the different models.

About the Tutorial

This tutorial demonstrates how to run different $vectorSearch queries against the embedded_movies collection in the sample_mflix database. This collection includes the following fields:

plot_embedding, which contains embeddings created by using OpenAI's text-embedding-ada-002 embedding model.
plot_embedding_voyage_4_large, which contains embeddings created by using Voyage AI's voyage-4-large embedding model. You use this field for all sample queries in this tutorial.

For the second query listed in Use Cases and Benefits, you must generate embeddings for another field. To try the sample query for this use case, complete the steps in Generate the Embeddings.

This tutorial walks you through the following steps:

Set up a MongoDB Vector Search index on the sample_mflix.embedded_movies collection.
Run $vectorSearch query with $rankFusion to perform the following searches:
- Search the plot_embedding_voyage_4_large field for movie plots that contain movies with plots similar to light-hearted comedy with ghosts and slapstick humor with paranormal events.
- Search the plot_embedding_voyage_4_large and title_embedding fields for movies with plots similar to battle between good and evil using embeddings from Voyage AI.
- Search the plot_embedding and plot_embedding_voyage_4_large fields for movies with plots similar to journey across lands using embeddings from OpenAI and Voyage AI respectively.

Before you begin, ensure that your cluster meets the requirements described in the Prerequisites.

Note

To run a $vectorSearch query with $rankFusion, your cluster must run MongoDB v8.0 or higher.

Generate the Embeddings

To query for the same term against multiple fields, you must prepare the dataset to include embeddings for different fields. This section demonstrates how to generate embeddings for the title field in the collection by using Voyage AI's voyage-4-large embedding model.

You can skip this section if you want to only try the other sample use cases.

Prerequisites

An environment to run interactive Python notebooks such as VS Code or Colab.
API key for Voyage AI embedding models.

Procedure

In this section, you generate embeddings for the title field in the embedded_movies collection by using Voyage AI's voyage-4-large embedding model.

Set up the environment.

Create an interactive Python notebook by saving a file with the .ipynb extension, and then run the following command in the notebook to install the dependencies:

pip install --quiet voyageai pymongo

Define and use a function to generate vector embeddings.

Paste and run the following code in your notebook after replacing the following placeholder values:

`<api-key>`	Your Voyage AI API key (line 6).
`<connection-string>`	Your MongoDB cluster connection string (line 18).

The following code defines a function that generates vector embeddings by using a proprietary embedding model from Voyage AI. Specifically, this code does the following:

Specifies the voyage-4-large embedding model.
Creates a function named get_embedding() that calls the model's API to generate 2048 dimension embedding for a given text input.
Connects to the cluster and fetches 3500 documents from the sample_mflix.embedded_movies namespace.
Generates embeddings from each document's title field by using the get_embedding() function.
Updates each document with a new field named title_embedding_voyage_4_large that contains the embedding value by using the MongoDB PyMongo Driver.

1 import os
2 import pymongo
3 import voyageai
4 
5 # Specify your Voyage API key and embedding model
6 os.environ["VOYAGE_API_KEY"] = "<api-key>"
7 
8 model = "voyage-4-large"
9 outputDimension = 2048
10 vo = voyageai.Client()
11 # Define a function to generate embeddings
12 def get_embedding(data, input_type = "document"):
13   embeddings = vo.embed(
14       data, model = model, output_dimension = outputDimension, input_type = input_type
15   ).embeddings
16   return embeddings[0]
17 
18 # Connect to your MongoDB Atlas cluster
19 mongo_client = pymongo.MongoClient("<connection-string>")
20 db = mongo_client["sample_mflix"]
21 collection = db["embedded_movies"]
22 
23 # Filter to exclude null or empty plot fields
24 filter = {"title": {"$nin": [None, ""]}}
25 
26 # Get a subset of documents in the collection
27 documents = collection.find(filter).limit(3500)
28 
29 # Update each document with a new embedding field
30 updated_doc_count = 0
31 for doc in documents:
32     embedding = get_embedding(doc["title"])
33     if embedding is not None:
34         collection.update_one({"_id": doc["_id"]}, {"$set": {"title_embedding_voyage_4_large": embedding}})
35         updated_doc_count += 1
36 
37 print(f"Updated {updated_doc_count} documents.")

Updated 3500 documents.

Note

It might take up to 15 minutes for the operation to complete.

Create the MongoDB Vector Search Index

In this section, you create a MongoDB Vector Search index on the sample_mflix.embedded_movies namespace. The section demonstrates an index definition that can be used for running various queries. Before creating the index, complete the procedure to generate the embeddings.

Connect to the cluster using `mongosh`.

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

Switch to the database that contains the collection for which you want to create the index.

Example

use sample_mflix

switched to db sample_mflix

Run the `db.collection.createSearchIndex()` method.

1 db.embedded_movies.createSearchIndex(
2   "multiple-vector-search", 
3   "vectorSearch", 
4   {
5     "fields": [
6       {
7         "type": "vector",
8         "path": "plot_embedding",
9         "numDimensions": 1536,
10         "similarity": "dotProduct"
11       },
12       {
13         "type": "vector",
14         "path": "plot_embedding_voyage_4_large",
15         "numDimensions": 2048,
16         "similarity": "dotProduct"
17       },
18       {
19         "type": "vector",
20         "path": "title_embedding_voyage_4_large",
21         "numDimensions": 2048,
22         "similarity": "dotProduct"
23       }
24     ]
25   }
26 );

This index definition indexes the following fields:

plot_embedding field as the vector type. This field contains vector embeddings that represent the summary of a movie's plot. The index definition:
- Specifies 1536 vector dimensions.
- Measures similarity using dotProduct similarity.
This field mapping is required for the third use case.
plot_embedding_voyage_4_large field as the vector type. This field contains vector embeddings that represent the summary of a movie's plot. The index definition:
- Specifies 2048 vector dimensions.
- Measures similarity using dotProduct similarity.
This field mapping is required all the queries in this tutorial.
title_embedding_voyage_4_large field as the vector type. This field contains vector embeddings that represent the title of the movie. The index definition:
- Specifies 2048 vector dimensions.
- Measures similarity using dotProduct similarity.
This field mapping is required for the second use case.

Run the MongoDB Vector Search Queries

In this section, you query the embedded_movies collection in the sample_mflix database by using the index named multiple-vector-search that you created on the collection.

Create a file for the embeddings to use in the query.

Create a file named embeddings.js.
touch embeddings.js

Copy and paste the following embeddings into the embeddings.js file.

This file contains embeddings for the query terms used in the queries. The following table shows the query term, the variable that contains the embeddings for the query term, the embedding model used to generate the embeddings, and the number of dimensions.

Query Phrase	Variable	Embedding Model	Dimensions
light-hearted comedy with ghosts	COMEDY_INVOLVING_GHOSTS	Voyage AI's `voyage-4-large`	2048
slapstick humor with paranormal events	HUMOR_INVOLVING_PARANORMAL	Voyage AI's `voyage-4-large`	2048
battle between good and evil	BATTLE_GOOD_EVIL	Voyage AI's `voyage-4-large`	2048
journey across lands	JOURNEY_ACROSS_LANDS_VOYAGEAI	Voyage AI's `voyage-4-large`	2048
journey across lands	JOURNEY_ACROSS_LANDS_OPENAI	OpenAI's `text-embedding-ada-002`	1536

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Save and close the file.

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.

Use the `sample_mflix` database.

Run the following command in the mongosh prompt:

use sample_mflix

Load the embeddings to use in the query.

Run the following command to load the embeddings in the embeddings.js file after replacing <path-to-file> with the absolute path to your embeddings.js file.
load('/<path-to-file>/embeddings.js';
true
Verify that the embeddings loaded successfully.
You can verify by running a command similar to the following:
COMEDY_INVOLVING_GHOSTS.length
2048

Run the MongoDB Vector Search queries against the `embedded_movies` collection.

Multiple Query Vectors Against a Single Document Vector

Perform a comprehensive search of the dataset for semantically similar terms to determine which query term returns the best results.

1 db.embedded_movies.aggregate([
2   {
3     $rankFusion: {
4       input: {
5         pipelines: {
6           vectorPipeline1: [
7             {
8               "$vectorSearch": {
9                 "index": "multiple-vector-search",
10                 "path": "plot_embedding_voyage_4_large",
11                 "queryVector": COMEDY_INVOLVING_GHOSTS,
12                 "numCandidates": 2000,
13                 "limit": 50
14               }
15             }
16           ],
17           vectorPipeline2: [
18             {
19               "$vectorSearch": {
20                 "index": "multiple-vector-search",
21                 "path": "plot_embedding_voyage_4_large",
22                 "queryVector": HUMOR_INVOLVING_PARANORMAL,
23                 "numCandidates": 2000,
24                 "limit": 50
25               }
26             }
27           ]
28         }
29       },
30       combination: {
31         weights: {
32           vectorPipeline1: 0.5,
33           vectorPipeline2: 0.5
34         }
35       },
36       "scoreDetails": true
37     }
38   },
39   {
40     "$project": {
41       _id: 1,
42       title: 1,
43       plot: 1,
44       scoreDetails: {"$meta": "scoreDetails"}
45     }
46   },
47   {
48     "$limit": 20
49   }
50 ]);

[
  {
    _id: ObjectId('573a139af29313caabcef0a4'),
    plot: 'A paranormal expert and his daughter bunk in an abandoned house populated by 3 mischievous ghosts and one friendly one.',
    title: 'Casper',
    scoreDetails: {
      value: 0.01639344262295082,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 1,
          weight: 0.5,
          value: 0.7622715830802917,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 1,
          weight: 0.5,
          value: 0.7325888276100159,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13b3f29313caabd3e8a1'),
    plot: 'A folk tale - supernatural love story about a ghost who falls in love with a newlywed woman.',
    title: 'Paheli',
    scoreDetails: {
      value: 0.015640273704789834,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 2,
          weight: 0.5,
          value: 0.7293232679367065,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 6,
          weight: 0.5,
          value: 0.7031921148300171,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1398f29313caabce912c'),
    plot: 'Three unemployed parapsychology professors set up shop as a unique ghost removal service.',
    title: 'Ghostbusters',
    scoreDetails: {
      value: 0.015625,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 4,
          weight: 0.5,
          value: 0.7225469946861267,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 4,
          weight: 0.5,
          value: 0.7111413478851318,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1398f29313caabceace9'),
    plot: 'A couple of recently deceased ghosts contract the services of a "bio-exorcist" in order to remove the obnoxious new owners of their house.',
    title: 'Beetlejuice',
    scoreDetails: {
      value: 0.01518288474810214,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 3,
          weight: 0.5,
          value: 0.7231436371803284,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 9,
          weight: 0.5,
          value: 0.6983412504196167,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1398f29313caabce9a71'),
    plot: 'Peanut butter is the secret ingredient for magic potions made by two friendly ghosts. Eleven-year-old Michael loses all of his hair when he gets a fright and uses the potion to get his hair...',
    title: 'The Peanut Butter Solution',
    scoreDetails: {
      value: 0.015154994259471873,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 7,
          weight: 0.5,
          value: 0.7036163806915283,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 5,
          weight: 0.5,
          value: 0.7067587375640869,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13d3f29313caabd96a55'),
    plot: 'A teacher with paranormal abilities helps a group of ghosts graduate high school.',
    title: 'Ghost Graduation',
    scoreDetails: {
      value: 0.014835164835164835,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 5,
          weight: 0.5,
          value: 0.7210001945495605,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 10,
          weight: 0.5,
          value: 0.6979111433029175,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1399f29313caabced85b'),
    plot: 'A comical Gothic horror-movie-type family tries to rescue their beloved uncle from his gold-digging new love.',
    title: 'Addams Family Values',
    scoreDetails: {
      value: 0.01316017316017316,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 15,
          weight: 0.5,
          value: 0.687480628490448,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 17,
          weight: 0.5,
          value: 0.6881510019302368,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13a8f29313caabd1db7e'),
    plot: 'Kung-Fu Action / Comedy / Horror / Musical about the second coming.',
    title: 'Jesus Christ Vampire Hunter',
    scoreDetails: {
      value: 0.012781497261107728,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 46,
          weight: 0.5,
          value: 0.6382369995117188,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 2,
          weight: 0.5,
          value: 0.720718264579773,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13b5f29313caabd41f29'),
    plot: '14-year-old Lulu moves to a small provincial town with her mother and younger brother. One night, her brother is struck by a beam of white light - actually the spirit of Herman Hartmann ...',
    title: 'Island of Lost Souls',
    scoreDetails: {
      value: 0.012579113924050634,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 20,
          weight: 0.5,
          value: 0.680338978767395,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 19,
          weight: 0.5,
          value: 0.6868098974227905,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13b0f29313caabd3380e'),
    plot: 'After a failed suicide attempt, a pregnant woman gains the ability to see ghosts.',
    title: 'The Eye 2',
    scoreDetails: {
      value: 0.012361402457296973,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 11,
          weight: 0.5,
          value: 0.6916752457618713,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 34,
          weight: 0.5,
          value: 0.6768500208854675,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13bdf29313caabd58274'),
    plot: 'Banku, his mother, Anjali Sharma and father move in to their new house -- the Nath villa, unaware of the fact that the house is inhabited by a ghost. It is learnt the ghost is not too happy...',
    title: 'Bhoothnath',
    scoreDetails: {
      value: 0.012352941176470587,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 8,
          weight: 0.5,
          value: 0.7026016712188721,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 40,
          weight: 0.5,
          value: 0.6747320294380188,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1398f29313caabcebb96'),
    plot: "A mother/daughter pair of witches descend on a yuppie family's home and cause havoc, one at a time since they share one body & the other must live in a cat the rest of the time. Now it's up...",
    title: 'Wicked Stepmother',
    scoreDetails: {
      value: 0.012207602339181285,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 35,
          weight: 0.5,
          value: 0.6473828554153442,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 12,
          weight: 0.5,
          value: 0.6947218179702759,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13a0f29313caabd056df'),
    plot: "A girl calls on her brother's imaginary friend to banish a mischievous boogeyman who has framed her for his pranks.",
    title: "Don't Look Under the Bed",
    scoreDetails: {
      value: 0.012196892696384493,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 37,
          weight: 0.5,
          value: 0.6451717019081116,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 11,
          weight: 0.5,
          value: 0.696073055267334,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13b0f29313caabd34285'),
    plot: 'After a failed suicide attempt, a pregnant woman gains the ability to see ghosts.',
    title: 'The Eye 2',
    scoreDetails: {
      value: 0.012046485260770973,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 12,
          weight: 0.5,
          value: 0.6906752586364746,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 38,
          weight: 0.5,
          value: 0.6758197546005249,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13bdf29313caabd5a0d9'),
    plot: 'A haunting ghost story spanning two worlds, two centuries apart. When 13 year old Tolly finds he can mysteriously travel between the two, he begins an adventure that unlocks family secrets laid buried for generations.',
    title: 'From Time to Time',
    scoreDetails: {
      value: 0.011611125688795592,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 14,
          weight: 0.5,
          value: 0.6898269057273865,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 43,
          weight: 0.5,
          value: 0.6731695532798767,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139af29313caabcf0f06'),
    plot: 'The wry, comic romantic tale follows the Owens sisters, Sally and Gillian, as they struggle to use their hereditary gift for practical magic to overcome the obstacles in discovering true love.',
    title: 'Practical Magic',
    scoreDetails: {
      value: 0.011564171122994652,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 25,
          weight: 0.5,
          value: 0.6609134078025818,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 28,
          weight: 0.5,
          value: 0.679317831993103,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1398f29313caabceaf10'),
    plot: "When Peter Plunkett's Irish castle turned hotel is about to be repossesed, he decides to spice up the attraction a bit for the 'Yanks' by having his staff pretend to haunt the castle. The ...",
    title: 'High Spirits',
    scoreDetails: {
      value: 0.011379618974555684,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 19,
          weight: 0.5,
          value: 0.6816859245300293,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 39,
          weight: 0.5,
          value: 0.6753329634666443,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13a3f29313caabd0cd93'),
    plot: "A simple funeral turns a man's world topsy turvy.",
    title: 'Monday',
    scoreDetails: {
      value: 0.010752688172043012,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 33,
          weight: 0.5,
          value: 0.6509981751441956,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 33,
          weight: 0.5,
          value: 0.6770291328430176,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13c0f29313caabd627c4'),
    plot: 'An adventure set in the early part of the 20th century and focused on a popular novelist and her dealings with would-be suitors, the cops, monsters, and other distractions.',
    title: 'The Extraordinary Adventures of Adèle Blanc-Sec',
    scoreDetails: {
      value: 0.009495949594959495,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 50,
          weight: 0.5,
          value: 0.636377215385437,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 41,
          weight: 0.5,
          value: 0.6734551787376404,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13d9f29313caabda92a9'),
    plot: 'The misadventures of a teenager girl in her new life as zombie.',
    title: "Daddy, I'm a Zombie",
    scoreDetails: {
      value: 0.009391534391534392,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 45,
          weight: 0.5,
          value: 0.6392303705215454,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 48,
          weight: 0.5,
          value: 0.6711602210998535,
          details: []
        }
      ]
    }
  }
]

This sample query uses the $rankFusion with the following input pipeline stages:

$vectorSearch

Searches the plot_embedding_voyage_4_large field for the phrase light-hearted comedy with ghosts, specified in the queryVector field of the query as vector embeddings by using the COMEDY_INVOLVING_GHOSTS variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results from this stage to 50 documents.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

$vectorSearch

Performs a sequential vector search on the plot_embedding_voyage_4_large field for the phrase slapstick humor with paranormal events, specified in the queryVector field as vector embeddings by using the HUMOR_INVOLVING_PARANORMAL variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results from this stage to 50 documents.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

The sample query also specifies the following pipeline stages.

`$project`	Includes only the `plot` and `title` fields in the results. Adds a field named `scoreDetails` in the results.
`$limit`	Limits the returned results to 20 documents.

MongoDB Vector Search merges the results for both the queries into a single result set. In the results:

The scoreDetails.value shows the raw score from that pipeline before it is weighted and combined by using reciprocal rank fusion.
The score.details.rank shows the rank of the document in the results of the pipeline.
The scoreDetails.details.value contains the weighted reciprocal rank score.

You can do the following:

Adjust the weights assigned to each pipeline in the query to further refine the results.
Increase the number of documents in the results if you see disjoint results.

Same Term Query Vector Against Multiple Document Vectors

Search multiple fields in the dataset to determine which fields return the best results for the same query.

1 db.embedded_movies.aggregate([
2   {
3     $rankFusion: {
4       input: {
5         pipelines: {
6           vectorPipeline1: [
7             {
8               "$vectorSearch": {
9                 "index": "multiple-vector-search",
10                 "path": "plot_embedding_voyage_4_large",
11                 "queryVector": BATTLE_GOOD_EVIL,
12                 "numCandidates": 2000,
13                 "limit": 200
14               }
15             }
16           ],
17           vectorPipeline2: [
18             {
19               "$vectorSearch": {
20                 "index": "multiple-vector-search",
21                 "path": "title_embedding_voyage_4_large",
22                 "queryVector": BATTLE_GOOD_EVIL,
23                 "numCandidates": 2000,
24                 "limit": 200
25               }
26             }
27           ]
28         }
29       },
30       combination: {
31         weights: {
32           vectorPipeline1: 0.5,
33           vectorPipeline2: 0.5
34         }
35       },
36       "scoreDetails": true
37     }
38   },
39   {
40     "$project": {
41       _id: 1,
42       title: 1,
43       plot: 1,
44       scoreDetails: {"$meta": "scoreDetails"}
45     }
46   },
47   {
48     "$limit": 20
49   }
50 ]);

[
  {
    plot: 'A team of police hunt down a villain.',
    title: 'Nowhere to Hide',
    scoreDetails: {
      value: 0.004273504273504274,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 57,
          weight: 0.5,
          value: 0.6504640579223633,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Childhood friends continue their battle against a dangerous cult.',
    title: '20th Century Boys 2: The Last Hope',
    scoreDetails: {
      value: 0.007462686567164179,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 7,
          weight: 0.5,
          value: 0.6790846586227417,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'The Addams Family goes on a search for their relatives.',
    title: 'Addams Family Reunion',
    scoreDetails: {
      value: 0.005813953488372093,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 26,
          weight: 0.5,
          value: 0.5182114243507385,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'An attempt to transform a Roman Western into a Greek tragedy.',
    title: 'Instructions for a Light and Sound Machine',
    scoreDetails: {
      value: 0.003968253968253968,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 66,
          weight: 0.5,
          value: 0.5156481266021729,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A gang of ex-cons rob a casino during Elvis convention week.',
    title: '3000 Miles to Graceland',
    scoreDetails: {
      value: 0.005154639175257732,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 37,
          weight: 0.5,
          value: 0.5178723335266113,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Three freedom fighters attack a large corporation to prevent a future apocalypse.',
    title: 'T2 3-D: Battle Across Time',
    scoreDetails: {
      value: 0.003937007874015748,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 67,
          weight: 0.5,
          value: 0.6470792889595032,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "Teenage twins battle dark forces hidden beneath Auckland's volcanoes.",
    title: 'Under the Mountain',
    scoreDetails: {
      value: 0.004310344827586207,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 56,
          weight: 0.5,
          value: 0.6506195068359375,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "A simple funeral turns a man's world topsy turvy.",
    title: 'Monday',
    scoreDetails: {
      value: 0.007692307692307693,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 5,
          weight: 0.5,
          value: 0.5210264325141907,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "Two teenage girls discover a mermaid in their beach club's swimming pool.",
    title: 'Aquamarine',
    scoreDetails: {
      value: 0.003816793893129771,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 71,
          weight: 0.5,
          value: 0.5154338479042053,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Seven warriors come together to protect a village from a diabolical General.',
    title: 'Seven Swords',
    scoreDetails: {
      value: 0.005050505050505051,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 39,
          weight: 0.5,
          value: 0.6564368009567261,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Mystical martial artist/environmental agent takes on a ruthless oil corporation.',
    title: 'On Deadly Ground',
    scoreDetails: {
      value: 0.004807692307692308,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 44,
          weight: 0.5,
          value: 0.6541689038276672,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A super powered vigilante defies the law using extreme violence to fight crime.',
    title: 'The Flying Man',
    scoreDetails: {
      value: 0.0032258064516129032,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 95,
          weight: 0.5,
          value: 0.638878583908081,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A rag doll fights a monster that has been stealing the souls of his people.',
    title: '9',
    scoreDetails: {
      value: 0.005,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 40,
          weight: 0.5,
          value: 0.6557563543319702,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A man receives a distressing phone call from a woman who has been kidnapped.',
    title: 'Connected',
    scoreDetails: {
      value: 0.004807692307692308,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 44,
          weight: 0.5,
          value: 0.5171101093292236,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'The misadventures of a teenager girl in her new life as zombie.',
    title: "Daddy, I'm a Zombie",
    scoreDetails: {
      value: 0.00684931506849315,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 13,
          weight: 0.5,
          value: 0.5196477770805359,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A troubled writer moves into a haunted house after inheriting it from his aunt.',
    title: 'House',
    scoreDetails: {
      value: 0.003424657534246575,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 86,
          weight: 0.5,
          value: 0.5150279998779297,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A dramatization of the World War II Battle of Iwo Jima.',
    title: 'Sands of Iwo Jima',
    scoreDetails: {
      value: 0.0031446540880503146,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 99,
          weight: 0.5,
          value: 0.5144232511520386,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Kung-Fu Action / Comedy / Horror / Musical about the second coming.',
    title: 'Jesus Christ Vampire Hunter',
    scoreDetails: {
      value: 0.0045871559633027525,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 49,
          weight: 0.5,
          value: 0.652422308921814,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'An All-American trucker gets dragged into a centuries-old mystical battle in Chinatown.',
    title: 'Big Trouble in Little China',
    scoreDetails: {
      value: 0.00684931506849315,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 13,
          weight: 0.5,
          value: 0.6701953411102295,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A group of assassins come together for a suicide mission to kill an evil lord.',
    title: '13 Assassins',
    scoreDetails: {
      value: 0.003703703703703704,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 75,
          weight: 0.5,
          value: 0.6449810266494751,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  }
]

This sample query uses the $rankFusion with the following input pipeline stages:

$vectorSearch

Searches the plot_embedding_voyage_4_large field for the phrase battle between good and evil, specified in the queryVector field of the query as vector embeddings by using the BATTLE_GOOD_EVIL variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results to 200 documents only.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

$vectorSearch

Performs a sequential vector search on the title_embedding_voyage_4_large field for the string battle between good and evil, specified in the queryVector field as vector embeddings by using the BATTLE_GOOD_EVIL variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results to 200 documents only.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

The sample query also specifies the following pipeline stages.

`$project`	Includes only the `plot` and `title` fields in the results. Adds a field named `scoreDetails` in the results.
`$limit`	Limits the returned results to 20 documents.

MongoDB Vector Search merges the results for both the queries into a single result set. In the results:

The scoreDetails.value shows the raw score from that pipeline before it is weighted and combined by using reciprocal rank fusion.
The score.details.rank shows the rank of the document in the results of the pipeline.
The scoreDetails.details.value contains the weighted reciprocal rank score, which shows which fields return the most relevant result for the query term.

For example, the first and fourth documents in the results suggest a significant match for the term in the plot field while the second and fifth documents suggest a significant match in the title field. You can do the following:

Adjust the weights assigned to each pipeline in the query to further refine the results.
Increase the number of documents in the results if you see disjoint results.

Same Term Query Using Multiple Models

Search embeddings from different embedding models to determine the semantic interpretation differences between the different models.

1 db.embedded_movies.aggregate([
2   {
3     $rankFusion: {
4       input: {
5         pipelines: {
6           vectorPipeline1: [
7             {
8               "$vectorSearch": {
9                 "index": "multiple-vector-search",
10                 "path": "plot_embedding",
11                 "queryVector": JOURNEY_ACROSS_LANDS_OPENAI,
12                 "numCandidates": 2000,
13                 "limit": 100
14               }
15             }
16           ],
17           vectorPipeline2: [
18             {
19               "$vectorSearch": {
20                 "index": "multiple-vector-search",
21                 "path": "plot_embedding_voyage_4_large",
22                 "queryVector": JOURNEY_ACROSS_LANDS_VOYAGEAI,
23                 "numCandidates": 2000,
24                 "limit": 100
25               }
26             }
27           ]
28         }
29       },
30       combination: {
31         weights: {
32           vectorPipeline1: 0.5,
33           vectorPipeline2: 0.5
34         }
35       },
36       "scoreDetails": true
37     }
38   },
39   {
40     "$project": {
41       _id: 1,
42       title: 1,
43       plot: 1,
44       scoreDetails: {"$meta": "scoreDetails"}
45     }
46   },
47   {
48     "$limit": 20
49   }
50 ]);

[
  {
    _id: ObjectId('573a13e8f29313caabdc9e14'),
    plot: 'A young Scottish man travels across America in pursuit of the woman he loves, attracting the attention of an outlaw who is willing to serve as a guide.',
    title: 'Slow West',
    scoreDetails: {
      value: 0.016129032258064516,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 2,
          weight: 0.5,
          value: 0.9210423827171326,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 2,
          weight: 0.5,
          value: 0.6790797114372253,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13b6f29313caabd48c52'),
    plot: 'In a mythical land, a man and a young boy investigate a series of unusual occurrences.',
    title: 'Tales from Earthsea',
    scoreDetails: {
      value: 0.015873015873015872,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 3,
          weight: 0.5,
          value: 0.9192964434623718,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 3,
          weight: 0.5,
          value: 0.6772182583808899,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139af29313caabcefa6c'),
    plot: 'A Englishman returns after a long time abroad and tells his strange stories about the lands he visited which are allegories about the real world.',
    title: "Gulliver's Travels",
    scoreDetails: {
      value: 0.015549662487945998,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 8,
          weight: 0.5,
          value: 0.9156127572059631,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 1,
          weight: 0.5,
          value: 0.6862039566040039,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a1391f29313caabcd91dc'),
    plot: 'Breck Coleman leads hundreds of settlers in covered wagons from the Mississippi River to their destiny out West.',
    title: 'The Big Trail',
    scoreDetails: {
      value: 0.014854753521126762,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 4,
          weight: 0.5,
          value: 0.9187002182006836,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 11,
          weight: 0.5,
          value: 0.6496086120605469,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13d0f29313caabd8bfb8'),
    plot: 'A young man crosses over North and South Korea to deliver the pain and longings of separated families.',
    title: 'Poongsan',
    scoreDetails: {
      value: 0.01482213438735178,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 6,
          weight: 0.5,
          value: 0.9168118238449097,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 9,
          weight: 0.5,
          value: 0.6547074913978577,
          details: []
        }
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    }
  },
  {
    _id: ObjectId('573a13b6f29313caabd46ae0'),
    plot: "In a countryside town bordering on a magical land, a young man makes a promise to his beloved that he'll retrieve a fallen star by venturing into the magical realm.",
    title: 'Stardust',
    scoreDetails: {
      value: 0.01436956081764825,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 1,
          weight: 0.5,
          value: 0.9228402376174927,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 21,
          weight: 0.5,
          value: 0.6418390274047852,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a13f7f29313caabde65b4'),
    plot: 'Our figurine sized supermen hero embarks on an epic surreal journey that will take him across the Ethiopian post apocalyptic landscape in search of a way to get on the hovering spacecraft that for years has become a landmark in the skies.',
    title: 'Crumbs',
    scoreDetails: {
      value: 0.014202256244963738,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 13,
          weight: 0.5,
          value: 0.9113836288452148,
          details: []
        },
        {
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          rank: 8,
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          details: []
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      ]
    }
  },
  {
    _id: ObjectId('573a13d4f29313caabd99ec6'),
    plot: "A ten-year-old cartographer secretly leaves his family's ranch in Montana where he lives with his cowboy father and scientist mother and travels across the country aboard a freight train to receive an award at the Smithsonian Institute.",
    title: 'The Young and Prodigious T.S. Spivet',
    scoreDetails: {
      value: 0.013789868667917449,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 22,
          weight: 0.5,
          value: 0.9102069735527039,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 5,
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          value: 0.6698448657989502,
          details: []
        }
      ]
    }
  },
  {
    _id: ObjectId('573a139af29313caabcf0e95'),
    plot: 'A man, having fallen in love with the wrong woman, is sent by the sultan himself on a diplomatic mission to a distant land as an ambassador. Stopping at a Viking village port to restock on supplies, he finds himself unwittingly embroiled on a quest to banish a mysterious threat in a distant Viking land.',
    title: 'The 13th Warrior',
    scoreDetails: {
      value: 0.012854317732366513,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 14,
          weight: 0.5,
          value: 0.911109983921051,
          details: []
        },
        {
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  },
  {
    _id: ObjectId('573a139af29313caabcef85f'),
    plot: "After the death of his mother, a young Brazilian decides to leave his country and travel to his mother's native land. In a foreign land, he finds love and danger.",
    title: 'Foreign Land',
    scoreDetails: {
      value: 0.012562421972534332,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 12,
          weight: 0.5,
          value: 0.9135410785675049,
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        {
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      ]
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  },
  {
    _id: ObjectId('573a1395f29313caabce2911'),
    plot: "Upon finding a book that relates his grandfather's story, an officer ventures through Spain meeting a wide array of characters, most of whom have a story of their own to tell.",
    title: 'The Saragossa Manuscript',
    scoreDetails: {
      value: 0.012260765550239234,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
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          rank: 28,
          weight: 0.5,
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  },
  {
    _id: ObjectId('573a13c9f29313caabd792a8'),
    plot: 'Settlers traveling through the Oregon desert in 1845 find themselves stranded in harsh conditions.',
    title: "Meek's Cutoff",
    scoreDetails: {
      value: 0.011997226074895978,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 10,
          weight: 0.5,
          value: 0.9155632257461548,
          details: []
        },
        {
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      ]
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  },
  {
    _id: ObjectId('573a1392f29313caabcdaa70'),
    plot: 'Leo Vincey, told by his dying uncle of a lost land visited 500 years ago by his ancestor, heads out with family friend Horace Holly to try to discover the land and its secret of immortality...',
    title: 'She',
    scoreDetails: {
      value: 0.01198581560283688,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 15,
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      ]
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  },
  {
    _id: ObjectId('573a1397f29313caabce8828'),
    plot: 'A warrior seeks his true origins in a seemingly prehistoric wasteland.',
    title: 'Yor, the Hunter from the Future',
    scoreDetails: {
      value: 0.011944214305440487,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 11,
          weight: 0.5,
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  },
  {
    _id: ObjectId('573a13f3f29313caabddf32e'),
    plot: 'In a dry and dusty post-apocalyptic world, two wayfarers wander aimlessly until Leif finds a copy of The Wonderful Wizard of Oz. Using the world around him to interpret what he reads, Leif ...',
    title: 'OzLand',
    scoreDetails: {
      value: 0.011777438248026482,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
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  },
  {
    _id: ObjectId('573a13d8f29313caabda5a4e'),
    plot: 'A savage warrior escapes slavery and hunted by his former masters, begins a perilous journey back to his homeland and his wife.',
    title: 'The Dragonphoenix Chronicles: Indomitable',
    scoreDetails: {
      value: 0.0116999747027574,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 7,
          weight: 0.5,
          value: 0.9163008332252502,
          details: []
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        {
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          rank: 58,
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  },
  {
    _id: ObjectId('573a139af29313caabcf02db'),
    plot: 'Chris embarks on an odyssey of self-discovery that spans the globe. Kidnapped and enslaved by gun smugglers, sold by pirates and thrust into the murky underworld of gambling and kickboxing,...',
    title: 'The Quest',
    scoreDetails: {
      value: 0.011512297226582941,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 18,
          weight: 0.5,
          value: 0.910321056842804,
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      ]
    }
  },
  {
    _id: ObjectId('573a1398f29313caabceb40c'),
    plot: "Epic story about two former Texas rangers who decide to move cattle from the south to Montana. Augustus McCrae and Woodrow Call run into many problems on the way, and the journey doesn't ...",
    title: 'Lonesome Dove',
    scoreDetails: {
      value: 0.011017628205128204,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 96,
          weight: 0.5,
          value: 0.9035773277282715,
          details: []
        },
        {
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          rank: 4,
          weight: 0.5,
          value: 0.6702411770820618,
          details: []
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      ]
    }
  },
  {
    _id: ObjectId('573a1395f29313caabce1fb7'),
    plot: 'The dying words of a thief spark a madcap cross-country rush to find some treasure.',
    title: "It's a Mad, Mad, Mad, Mad World",
    scoreDetails: {
      value: 0.010528600890046674,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 51,
          weight: 0.5,
          value: 0.9072262048721313,
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        {
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          rank: 23,
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          value: 0.640996515750885,
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      ]
    }
  },
  {
    _id: ObjectId('573a1396f29313caabce491f'),
    plot: 'A god-fearing Ohio boy dodging the Civil War draft arrives in Jefferson City where he joins up with a hardscrabble group of like runaways heading west.',
    title: 'Bad Company',
    scoreDetails: {
      value: 0.010272536687631027,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 46,
          weight: 0.5,
          value: 0.9078546166419983,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 30,
          weight: 0.5,
          value: 0.6375589966773987,
          details: []
        }
      ]
    }
  }
]

This sample query uses the $rankFusion with the following input pipeline stages:

$vectorSearch

Searches the plot_embedding field for the string journey across lands specified in the queryVector field of the query as vector embeddings by using the JOURNEY_ACROSS_LANDS_OPENAI variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results to 100 documents.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

$vectorSearch

Performs a sequential vector search on the plot_embedding_voyage_4_large field for the string journey across lands, specified in the queryVector field as vector embeddings by using the JOURNEY_ACROSS_LANDS_VOYAGEAI variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results to 100 documents.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

The sample query also specifies the following pipeline stages.

`$project`	Includes only the `plot` and `title` fields in the results. Adds a field named `scoreDetails` in the results.
`$limit`	Limits the returned results to 20 documents.

MongoDB Vector Search merges the results for both the queries into a single result set. In the results:

The scoreDetails.value shows the raw score from that pipeline before it is weighted and combined by using reciprocal rank fusion.
The score.details.rank shows the rank of the document in the results of the pipeline.
The scoreDetails.details.value contains the weighted reciprocal rank score, which shows the strengths and differences in the semantic interpretation of the query term by the different embedding models.

For example, the first and fifth documents in the results suggest more similar semantic representation by the model used in the vectorPipeline2 while the second and fourth document in the results suggest closer semantic interpretation by the model used in the vectorPipeline1.

Reorder the Results

In this section, you reorder the results of the query by using the $rerank stage.

Run the following query to reorder the results.

Multiple Query Vectors Against a Single Document Vector

Reorder the results of your comprehensive search of the dataset for semantically similar terms to determine which query term returns the best results.

1 db.embedded_movies.aggregate([
2   {
3     $rankFusion: {
4       input: {
5         pipelines: {
6           vectorPipeline1: [
7             {
8               "$vectorSearch": {
9                 "index": "multiple-vector-search",
10                 "path": "plot_embedding_voyage_4_large",
11                 "queryVector": COMEDY_INVOLVING_GHOSTS,
12                 "numCandidates": 2000,
13                 "limit": 50
14               }
15             }
16           ],
17           vectorPipeline2: [
18             {
19               "$vectorSearch": {
20                 "index": "multiple-vector-search",
21                 "path": "plot_embedding_voyage_4_large",
22                 "queryVector": HUMOR_INVOLVING_PARANORMAL,
23                 "numCandidates": 2000,
24                 "limit": 50
25               }
26             }
27           ]
28         }
29       },
30       combination: {
31         weights: {
32           vectorPipeline1: 0.5,
33           vectorPipeline2: 0.5
34         }
35       },
36       "scoreDetails": true
37     }
38   },
39   {
40     "$project": {
41       _id: 1,
42       title: 1,
43       plot: 1,
44       scoreDetails: {"$meta": "scoreDetails"}
45     }
46   },
47   {
48     "$limit": 50
49   },
50   {
51     "$rerank": {
52       "model": "rerank-2.5",
53       "query": {
54         "text": "light-hearted comedy with ghosts"
55       },
56       "path": "plot",
57       "numDocsToRerank": 50
58     }
59   },
60   {
61     "$addFields": {
62       "rerankScore": { "$meta": "score" }
63     }
64   },
65   {
66     "$limit": 20
67   },
68   {
69     "$project": {
70       _id: 0,
71       title: 1,
72       plot: 1,
73       scoreDetails: 1,
74       rerankScore: 1
75     }
76   }
77 ]);

[
  {
    plot: 'Two ghosts walk along the Camino of Santiago.',
    title: 'Finisterrae',
    scoreDetails: {
      value: 0.007142857142857143,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 10,
          weight: 0.5,
          value: 0.694494366645813,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A teenage boy is cursed with periodically turning into an sheepdog.',
    title: 'The Shaggy Dog',
    scoreDetails: {
      value: 0.006172839506172839,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 21,
          weight: 0.5,
          value: 0.6834555864334106,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Two cops are brought back to life to chase down supernatural criminals.',
    title: 'Dead Heat',
    scoreDetails: {
      value: 0.006578947368421052,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 16,
          weight: 0.5,
          value: 0.6887474060058594,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "A simple funeral turns a man's world topsy turvy.",
    title: 'Monday',
    scoreDetails: {
      value: 0.010752688172043012,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 33,
          weight: 0.5,
          value: 0.6509981751441956,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 33,
          weight: 0.5,
          value: 0.6770291328430176,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A teacher with paranormal abilities helps a group of ghosts graduate high school.',
    title: 'Ghost Graduation',
    scoreDetails: {
      value: 0.014835164835164835,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 5,
          weight: 0.5,
          value: 0.7210001945495605,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 10,
          weight: 0.5,
          value: 0.6979111433029175,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A public housing tenement is plunged into a dark storm of supernatural chaos.',
    title: 'Rigor Mortis',
    scoreDetails: {
      value: 0.006666666666666667,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 15,
          weight: 0.5,
          value: 0.6895216703414917,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Kung-Fu Action / Comedy / Horror / Musical about the second coming.',
    title: 'Jesus Christ Vampire Hunter',
    scoreDetails: {
      value: 0.012781497261107728,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 46,
          weight: 0.5,
          value: 0.6382369995117188,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 2,
          weight: 0.5,
          value: 0.720718264579773,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'After a failed suicide attempt, a pregnant woman gains the ability to see ghosts.',
    title: 'The Eye 2',
    scoreDetails: {
      value: 0.012361402457296973,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 11,
          weight: 0.5,
          value: 0.6916752457618713,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 34,
          weight: 0.5,
          value: 0.6768500208854675,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'The misadventures of a teenager girl in her new life as zombie.',
    title: "Daddy, I'm a Zombie",
    scoreDetails: {
      value: 0.009391534391534392,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 45,
          weight: 0.5,
          value: 0.6392303705215454,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 48,
          weight: 0.5,
          value: 0.6711602210998535,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'After a failed suicide attempt, a pregnant woman gains the ability to see ghosts.',
    title: 'The Eye 2',
    scoreDetails: {
      value: 0.012046485260770973,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 12,
          weight: 0.5,
          value: 0.6906752586364746,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 38,
          weight: 0.5,
          value: 0.6758197546005249,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Five bizarre stories, with no apparently connections, get intertwined resulting in a surreal situation.',
    title: 'Survive Style 5+',
    scoreDetails: {
      value: 0.005952380952380952,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 24,
          weight: 0.5,
          value: 0.6814087629318237,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Three unemployed parapsychology professors set up shop as a unique ghost removal service.',
    title: 'Ghostbusters',
    scoreDetails: {
      value: 0.015625,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 4,
          weight: 0.5,
          value: 0.7225469946861267,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 4,
          weight: 0.5,
          value: 0.7111413478851318,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'The funny misadventures of a dating duo of film stunt professionals in France.',
    title: 'Animal',
    scoreDetails: {
      value: 0.006756756756756757,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 14,
          weight: 0.5,
          value: 0.6896277666091919,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A folk tale - supernatural love story about a ghost who falls in love with a newlywed woman.',
    title: 'Paheli',
    scoreDetails: {
      value: 0.015640273704789834,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 2,
          weight: 0.5,
          value: 0.7293232679367065,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 6,
          weight: 0.5,
          value: 0.7031921148300171,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Bank clerk Stanley Ipkiss is transformed into a manic super-hero when he wears a mysterious mask.',
    title: 'The Mask',
    scoreDetails: {
      value: 0.00684931506849315,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 13,
          weight: 0.5,
          value: 0.6942293047904968,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A lonely landscape architect falls for the spirit of the beautiful woman who used to live in his new apartment.',
    title: 'Just Like Heaven',
    scoreDetails: {
      value: 0.006172839506172839,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 21,
          weight: 0.5,
          value: 0.6797891855239868,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "While attending his brother's wedding, a serial womanizer is haunted by the ghosts of his past girlfriends.",
    title: 'Ghosts of Girlfriends Past',
    scoreDetails: {
      value: 0.006578947368421052,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 16,
          weight: 0.5,
          value: 0.6873041391372681,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Ho Sheung Sang finds himself wrapped up in another cat-and-mouse game, this time against a tricky magician.',
    title: 'Running Out of Time 2',
    scoreDetails: {
      value: 0.005747126436781609,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 27,
          weight: 0.5,
          value: 0.6800718903541565,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A veteran of the Chechen War is helped by the ghosts of his two fallen comrades to leave the war behind.',
    title: 'Alive',
    scoreDetails: {
      value: 0.005952380952380952,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 24,
          weight: 0.5,
          value: 0.6612753868103027,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Adaption of the famous Oscar Wilde tale about a young American girl that helps a British ghost find rest and forgiveness.',
    title: 'The Canterville Ghost',
    scoreDetails: {
      value: 0.007575757575757576,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 6,
          weight: 0.5,
          value: 0.7143866419792175,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  }
]

This sample query uses the $rankFusion with the following input pipeline stages:

$vectorSearch

Searches the plot_embedding_voyage_4_large field for the phrase light-hearted comedy with ghosts, specified in the queryVector field of the query as vector embeddings by using the COMEDY_INVOLVING_GHOSTS variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results from this stage to 50 documents.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

$vectorSearch

Performs a sequential vector search on the plot_embedding_voyage_4_large field for the phrase slapstick humor with paranormal events, specified in the queryVector field as vector embeddings by using the HUMOR_INVOLVING_PARANORMAL variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results from this stage to 50 documents.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

The sample query also specifies the following pipeline stages.

`$project`	Includes only the `plot` and `title` fields in the results. Adds a field named `scoreDetails` in the results.
`$limit`	Limits the returned results to 50 documents.

MongoDB Vector Search merges the results for both the queries into a single result set. It then reorders the results by using the $rerank stage. The $rerank stage reorders the results by relevance to the query term light-hearted comedy with ghosts. In the results, the $rerank stage adds a field named rerankScore that shows the score after reordering. The reordered results are more relevant to the query term.

Same Term Query Vector Against Multiple Document Vectors

Reorder the results of the search on multiple fields in the dataset to determine which fields return the best results for the same query.

1 db.embedded_movies.aggregate([
2   {
3     $rankFusion: {
4       input: {
5         pipelines: {
6           vectorPipeline1: [
7             {
8               "$vectorSearch": {
9                 "index": "multiple-vector-search",
10                 "path": "plot_embedding_float32",
11                 "queryVector": BATTLE_GOOD_EVIL,
12                 "numCandidates": 2000,
13                 "limit": 200
14               }
15             }
16           ],
17           vectorPipeline2: [
18             {
19               "$vectorSearch": {
20                 "index": "multiple-vector-search",
21                 "path": "title_embedding_voyage_4_large",
22                 "queryVector": BATTLE_GOOD_EVIL,
23                 "numCandidates": 2000,
24                 "limit": 200
25               }
26             }
27           ]
28         }
29       },
30       combination: {
31         weights: {
32           vectorPipeline1: 0.5,
33           vectorPipeline2: 0.5
34         }
35       },
36       "scoreDetails": true
37     }
38   },
39   {
40     "$project": {
41       _id: 1,
42       title: 1,
43       plot: 1,
44       scoreDetails: {"$meta": "scoreDetails"}
45     }
46   },
47   {
48     "$limit": 200
49   },
50   {
51     "$match": {
52       "plot": { "$exists": true, "$type": "string" }
53     }
54   },
55   {
56     "$rerank": {
57       "model": "rerank-2.5",
58       "query": {
59         "text": "battle between good and evil"
60       },
61       "path": "plot",
62       "numDocsToRerank": 200
63     }
64   },
65   {
66     "$addFields": {
67       "rerankScore": { "$meta": "score" }
68     }
69   },
70   {
71     "$limit": 20
72   },
73   {
74     "$project": {
75       "_id": 0,
76       "title": 1,
77       "plot": 1,
78       "scoreDetails": 1,
79       "rerankScore": 1
80     }
81   }
82 ]);

[
  {
    plot: 'A team of police hunt down a villain.',
    title: 'Nowhere to Hide',
    scoreDetails: {
      value: 0.004273504273504274,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 57,
          weight: 0.5,
          value: 0.6504640579223633,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Childhood friends continue their battle against a dangerous cult.',
    title: '20th Century Boys 2: The Last Hope',
    scoreDetails: {
      value: 0.007462686567164179,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 7,
          weight: 0.5,
          value: 0.6790846586227417,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'The Addams Family goes on a search for their relatives.',
    title: 'Addams Family Reunion',
    scoreDetails: {
      value: 0.005813953488372093,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 26,
          weight: 0.5,
          value: 0.5182114243507385,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'An attempt to transform a Roman Western into a Greek tragedy.',
    title: 'Instructions for a Light and Sound Machine',
    scoreDetails: {
      value: 0.003968253968253968,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 66,
          weight: 0.5,
          value: 0.5156481266021729,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A gang of ex-cons rob a casino during Elvis convention week.',
    title: '3000 Miles to Graceland',
    scoreDetails: {
      value: 0.005154639175257732,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 37,
          weight: 0.5,
          value: 0.5178723335266113,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Three freedom fighters attack a large corporation to prevent a future apocalypse.',
    title: 'T2 3-D: Battle Across Time',
    scoreDetails: {
      value: 0.003937007874015748,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 67,
          weight: 0.5,
          value: 0.6470792889595032,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "Teenage twins battle dark forces hidden beneath Auckland's volcanoes.",
    title: 'Under the Mountain',
    scoreDetails: {
      value: 0.004310344827586207,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 56,
          weight: 0.5,
          value: 0.6506195068359375,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "A simple funeral turns a man's world topsy turvy.",
    title: 'Monday',
    scoreDetails: {
      value: 0.007692307692307693,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 5,
          weight: 0.5,
          value: 0.5210264325141907,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "Two teenage girls discover a mermaid in their beach club's swimming pool.",
    title: 'Aquamarine',
    scoreDetails: {
      value: 0.003816793893129771,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 71,
          weight: 0.5,
          value: 0.5154338479042053,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Seven warriors come together to protect a village from a diabolical General.',
    title: 'Seven Swords',
    scoreDetails: {
      value: 0.005050505050505051,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 39,
          weight: 0.5,
          value: 0.6564368009567261,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Mystical martial artist/environmental agent takes on a ruthless oil corporation.',
    title: 'On Deadly Ground',
    scoreDetails: {
      value: 0.004807692307692308,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 44,
          weight: 0.5,
          value: 0.6541689038276672,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A super powered vigilante defies the law using extreme violence to fight crime.',
    title: 'The Flying Man',
    scoreDetails: {
      value: 0.0032258064516129032,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 95,
          weight: 0.5,
          value: 0.638878583908081,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A rag doll fights a monster that has been stealing the souls of his people.',
    title: '9',
    scoreDetails: {
      value: 0.005,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 40,
          weight: 0.5,
          value: 0.6557563543319702,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A man receives a distressing phone call from a woman who has been kidnapped.',
    title: 'Connected',
    scoreDetails: {
      value: 0.004807692307692308,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 44,
          weight: 0.5,
          value: 0.5171101093292236,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'The misadventures of a teenager girl in her new life as zombie.',
    title: "Daddy, I'm a Zombie",
    scoreDetails: {
      value: 0.00684931506849315,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 13,
          weight: 0.5,
          value: 0.5196477770805359,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A troubled writer moves into a haunted house after inheriting it from his aunt.',
    title: 'House',
    scoreDetails: {
      value: 0.003424657534246575,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 86,
          weight: 0.5,
          value: 0.5150279998779297,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A dramatization of the World War II Battle of Iwo Jima.',
    title: 'Sands of Iwo Jima',
    scoreDetails: {
      value: 0.0031446540880503146,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 99,
          weight: 0.5,
          value: 0.5144232511520386,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Kung-Fu Action / Comedy / Horror / Musical about the second coming.',
    title: 'Jesus Christ Vampire Hunter',
    scoreDetails: {
      value: 0.0045871559633027525,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 49,
          weight: 0.5,
          value: 0.652422308921814,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'An All-American trucker gets dragged into a centuries-old mystical battle in Chinatown.',
    title: 'Big Trouble in Little China',
    scoreDetails: {
      value: 0.00684931506849315,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 13,
          weight: 0.5,
          value: 0.6701953411102295,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A group of assassins come together for a suicide mission to kill an evil lord.',
    title: '13 Assassins',
    scoreDetails: {
      value: 0.003703703703703704,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 75,
          weight: 0.5,
          value: 0.6449810266494751,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  }
]

This sample query uses the $rankFusion with the following input pipeline stages:

$vectorSearch

Searches the plot_embedding_voyage_4_large field for the phrase battle between good and evil, specified in the queryVector field of the query as vector embeddings by using the BATTLE_GOOD_EVIL variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results to 200 documents only.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

$vectorSearch

Performs a sequential vector search on the title_embedding_voyage_4_large field for the string battle between good and evil, specified in the queryVector field as vector embeddings by using the BATTLE_GOOD_EVIL variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results to 200 documents only.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

The sample query also specifies the following pipeline stages.

`$project`	Includes only the `plot` and `title` fields in the results. Adds a field named `scoreDetails` in the results.
`$limit`	Limits the returned results to 200 documents.

MongoDB Vector Search merges the results for both the queries into a single result set. It then reorders the results by using the $rerank stage. The $match stage filters the documents to include only documents that have a plot field of type string. The $rerank stage reorders the results by relevance to the query term battle between good and evil. In the results, the $rerank stage adds a field named rerankScore that shows the score after reordering.

Same Term Query Using Multiple Models

Reorder the results of the search on embeddings from different embedding models to determine the semantic interpretation differences between the different models.

1 db.embedded_movies.aggregate([
2   {
3     $rankFusion: {
4       input: {
5         pipelines: {
6           vectorPipeline1: [
7             {
8               "$vectorSearch": {
9                 "index": "multiple-vector-search",
10                 "path": "plot_embedding",
11                 "queryVector": JOURNEY_ACROSS_LANDS_OPENAI,
12                 "numCandidates": 2000,
13                 "limit": 100
14               }
15             }
16           ],
17           vectorPipeline2: [
18             {
19               "$vectorSearch": {
20                 "index": "multiple-vector-search",
21                 "path": "plot_embedding_voyage_4_large",
22                 "queryVector": JOURNEY_ACROSS_LANDS_VOYAGEAI,
23                 "numCandidates": 2000,
24                 "limit": 100
25               }
26             }
27           ]
28         }
29       },
30       combination: {
31         weights: {
32           vectorPipeline1: 0.5,
33           vectorPipeline2: 0.5
34         }
35       },
36       "scoreDetails": true
37     }
38   },
39   {
40     "$project": {
41       _id: 1,
42       title: 1,
43       plot: 1,
44       scoreDetails: {"$meta": "scoreDetails"}
45     }
46   },
47   {
48     "$limit": 100
49   },
50   {
51     "$rerank": {
52       "model": "rerank-2.5",
53       "query": {
54         "text": "journey across lands"
55       },
56       "path": "plot",
57       "numDocsToRerank": 100
58     }
59   },
60   {
61     "$addFields": {
62       "rerankScore": { "$meta": "score" }
63     }
64   },
65   {
66     "$limit": 20
67   },
68   {
69     "$project": {
70       _id: 0,
71       title: 1,
72       plot: 1,
73       scoreDetails: 1,
74       rerankScore: 1
75     }
76   }
77 ]);

[
  {
    plot: 'A warrior seeks his true origins in a seemingly prehistoric wasteland.',
    title: 'Yor, the Hunter from the Future',
    scoreDetails: {
      value: 0.011944214305440487,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 11,
          weight: 0.5,
          value: 0.9153545498847961,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 42,
          weight: 0.5,
          value: 0.6328363418579102,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A wide variety of eccentric competitors participate in a wild and illegal cross-country car race.',
    title: 'The Cannonball Run',
    scoreDetails: {
      value: 0.0043859649122807015,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 54,
          weight: 0.5,
          value: 0.6279412508010864,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'In a mythical land, a man and a young boy investigate a series of unusual occurrences.',
    title: 'Tales from Earthsea',
    scoreDetails: {
      value: 0.015873015873015872,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 3,
          weight: 0.5,
          value: 0.9192964434623718,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 3,
          weight: 0.5,
          value: 0.6772182583808899,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'The dying words of a thief spark a madcap cross-country rush to find some treasure.',
    title: "It's a Mad, Mad, Mad, Mad World",
    scoreDetails: {
      value: 0.010528600890046674,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 51,
          weight: 0.5,
          value: 0.9072262048721313,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 23,
          weight: 0.5,
          value: 0.640996515750885,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'An urban husband and wife travel to the jungle and learn just how precious their relationship is.',
    title: 'Nymph',
    scoreDetails: {
      value: 0.010015634160641,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 26,
          weight: 0.5,
          value: 0.909113883972168,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 59,
          weight: 0.5,
          value: 0.6264784336090088,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A Civil War veteran embarks on a journey to rescue his niece from an Indian tribe.',
    title: 'The Searchers',
    scoreDetails: {
      value: 0.006493506493506494,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 17,
          weight: 0.5,
          value: 0.9103956818580627,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A man shuffles through a dream meeting various people and discussing the meanings and purposes of the universe.',
    title: 'Waking Life',
    scoreDetails: {
      value: 0.004464285714285714,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 52,
          weight: 0.5,
          value: 0.6300867795944214,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A young man crosses over North and South Korea to deliver the pain and longings of separated families.',
    title: 'Poongsan',
    scoreDetails: {
      value: 0.01482213438735178,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 6,
          weight: 0.5,
          value: 0.9168118238449097,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 9,
          weight: 0.5,
          value: 0.6547074913978577,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Settlers traveling through the Oregon desert in 1845 find themselves stranded in harsh conditions.',
    title: "Meek's Cutoff",
    scoreDetails: {
      value: 0.011997226074895978,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 10,
          weight: 0.5,
          value: 0.9155632257461548,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 43,
          weight: 0.5,
          value: 0.6323773860931396,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'Breck Coleman leads hundreds of settlers in covered wagons from the Mississippi River to their destiny out West.',
    title: 'The Big Trail',
    scoreDetails: {
      value: 0.014854753521126762,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 4,
          weight: 0.5,
          value: 0.9187002182006836,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 11,
          weight: 0.5,
          value: 0.6496086120605469,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A young woman must journey through the seasons to rescue her boyfriend who has been kidnapped by the evil Snow Queen.',
    title: 'Snow Queen',
    scoreDetails: {
      value: 0.004672897196261682,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 47,
          weight: 0.5,
          value: 0.6311054229736328,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A young woman must journey through the seasons to rescue her boyfriend who has been kidnapped by the evil Snow Queen.',
    title: 'Snow Queen',
    scoreDetails: {
      value: 0.004672897196261682,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 47,
          weight: 0.5,
          value: 0.6311054229736328,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "The life of an immigrant family from Sweden in the Minnesota's forests, during mid 19th century",
    title: 'The New Land',
    scoreDetails: {
      value: 0.008857968369829683,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 36,
          weight: 0.5,
          value: 0.9085773825645447,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 77,
          weight: 0.5,
          value: 0.6231112480163574,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "The life of an immigrant family from Sweden in the Minnesota's forests, during mid 19th century",
    title: 'The New Land',
    scoreDetails: {
      value: 0.008967731829573933,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 36,
          weight: 0.5,
          value: 0.9085773825645447,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 73,
          weight: 0.5,
          value: 0.6232647895812988,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "The life of an immigrant family from Sweden in the Minnesota's forests, during mid 19th century",
    title: 'The New Land',
    scoreDetails: {
      value: 0.008967731829573933,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 36,
          weight: 0.5,
          value: 0.9085773825645447,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 73,
          weight: 0.5,
          value: 0.6232647895812988,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "The life of an immigrant family from Sweden in the Minnesota's forests, during mid 19th century",
    title: 'The New Land',
    scoreDetails: {
      value: 0.008967731829573933,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 36,
          weight: 0.5,
          value: 0.9085773825645447,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 73,
          weight: 0.5,
          value: 0.6232647895812988,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "The life of an immigrant family from Sweden in the Minnesota's forests, during mid 19th century",
    title: 'The New Land',
    scoreDetails: {
      value: 0.009078547432410815,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 34,
          weight: 0.5,
          value: 0.9086182713508606,
          details: []
        },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 73,
          weight: 0.5,
          value: 0.6232647895812988,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: "An account of Baron Munchausen's supposed travels and fantastical experiences with his band of misfits.",
    title: 'The Adventures of Baron Munchausen',
    scoreDetails: {
      value: 0.006493506493506494,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 17,
          weight: 0.5,
          value: 0.6459617614746094,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A young boy accidentally joins a band of dwarves as they jump from era to era looking for treasure to steal.',
    title: 'Time Bandits',
    scoreDetails: {
      value: 0.006944444444444444,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        { inputPipelineName: 'vectorPipeline1', rank: 'NA' },
        {
          inputPipelineName: 'vectorPipeline2',
          rank: 12,
          weight: 0.5,
          value: 0.6489611864089966,
          details: []
        }
      ]
    },
    rerankScore: 0.5986876487731934
  },
  {
    plot: 'A troubled young man is drawn to a mythical place called Midian where a variety of monsters are hiding from humanity.',
    title: 'Nightbreed',
    scoreDetails: {
      value: 0.005,
      description: 'value output by reciprocal rank fusion algorithm, computed as sum of (weight * (1 / (60 + rank))) across input pipelines from which this document is output, from:',
      details: [
        {
          inputPipelineName: 'vectorPipeline1',
          rank: 40,
          weight: 0.5,
          value: 0.9085456132888794,
          details: []
        },
        { inputPipelineName: 'vectorPipeline2', rank: 'NA' }
      ]
    },
    rerankScore: 0.5986876487731934
  }
]

This sample query uses the $rankFusion with the following input pipeline stages:

$vectorSearch

Searches the plot_embedding field for the string journey across lands specified in the queryVector field of the query as vector embeddings by using the JOURNEY_ACROSS_LANDS_OPENAI variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results to 100 documents.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

$vectorSearch

Performs a sequential vector search on the plot_embedding_voyage_4_large field for the string journey across lands, specified in the queryVector field as vector embeddings by using the JOURNEY_ACROSS_LANDS_VOYAGEAI variable.
Specifies a search for up to 2000 nearest neighbors.
Limits the results to 100 documents.
Specifies a weight of 0.5 to influence that pipeline's rank contribution to the final score.

The sample query also specifies the following pipeline stages.

`$project`	Includes only the `plot` and `title` fields in the results. Adds a field named `scoreDetails` in the results.
`$limit`	Limits the returned results to 100 documents.

MongoDB Vector Search merges the results for both the queries into a single result set. It then reorders the results by using the $rerank stage. The $rerank stage reorders the results by relevance to the query term journey across lands. In the results, the $rerank stage adds a field named rerankScore that shows the score after reordering.

Back

Combined Vector Search and Full-Text Search

Review Deployment Options

1	import os
2	import pymongo
3	import voyageai
4
5	# Specify your Voyage API key and embedding model
6	os.environ["VOYAGE_API_KEY"] = "<api-key>"
7
8	model = "voyage-4-large"
9	outputDimension = 2048
10	vo = voyageai.Client()
11	# Define a function to generate embeddings
12	def get_embedding(data, input_type = "document"):
13	embeddings = vo.embed(
14	data, model = model, output_dimension = outputDimension, input_type = input_type
15	).embeddings
16	return embeddings[0]
17
18	# Connect to your MongoDB Atlas cluster
19	mongo_client = pymongo.MongoClient("<connection-string>")
20	db = mongo_client["sample_mflix"]
21	collection = db["embedded_movies"]
22
23	# Filter to exclude null or empty plot fields
24	filter = {"title": {"$nin": [None, ""]}}
25
26	# Get a subset of documents in the collection
27	documents = collection.find(filter).limit(3500)
28
29	# Update each document with a new embedding field
30	updated_doc_count = 0
31	for doc in documents:
32	embedding = get_embedding(doc["title"])
33	if embedding is not None:
34	collection.update_one({"_id": doc["_id"]}, {"$set": {"title_embedding_voyage_4_large": embedding}})
35	updated_doc_count += 1
36
37	print(f"Updated {updated_doc_count} documents.")

1	db.embedded_movies.createSearchIndex(
2	"multiple-vector-search",
3	"vectorSearch",
4	{
5	"fields": [
6	{
7	"type": "vector",
8	"path": "plot_embedding",
9	"numDimensions": 1536,
10	"similarity": "dotProduct"
11	},
12	{
13	"type": "vector",
14	"path": "plot_embedding_voyage_4_large",
15	"numDimensions": 2048,
16	"similarity": "dotProduct"
17	},
18	{
19	"type": "vector",
20	"path": "title_embedding_voyage_4_large",
21	"numDimensions": 2048,
22	"similarity": "dotProduct"
23	}
24	]
25	}
26	);

1	db.embedded_movies.aggregate([
2	{
3	$rankFusion: {
4	input: {
5	pipelines: {
6	vectorPipeline1: [
7	{
8	"$vectorSearch": {
9	"index": "multiple-vector-search",
10	"path": "plot_embedding_voyage_4_large",
11	"queryVector": COMEDY_INVOLVING_GHOSTS,
12	"numCandidates": 2000,
13	"limit": 50
14	}
15	}
16	],
17	vectorPipeline2: [
18	{
19	"$vectorSearch": {
20	"index": "multiple-vector-search",
21	"path": "plot_embedding_voyage_4_large",
22	"queryVector": HUMOR_INVOLVING_PARANORMAL,
23	"numCandidates": 2000,
24	"limit": 50
25	}
26	}
27	]
28	}
29	},
30	combination: {
31	weights: {
32	vectorPipeline1: 0.5,
33	vectorPipeline2: 0.5
34	}
35	},
36	"scoreDetails": true
37	}
38	},
39	{
40	"$project": {
41	_id: 1,
42	title: 1,
43	plot: 1,
44	scoreDetails: {"$meta": "scoreDetails"}
45	}
46	},
47	{
48	"$limit": 20
49	}
50	]);

How to Combine Multiple $vectorSearch Queries

Use Cases and Benefits

About the Tutorial

Note

Generate the Embeddings

Prerequisites

Procedure

Set up the environment.

Define and use a function to generate vector embeddings.

Note

Create the MongoDB Vector Search Index

Connect to the cluster using mongosh.

Switch to the database that contains the collection for which you want to create the index.

Example

Run the db.collection.createSearchIndex() method.

Run the MongoDB Vector Search Queries

Create a file for the embeddings to use in the query.

Connect to your cluster in mongosh.

Use the sample_mflix database.

Load the embeddings to use in the query.

Run the MongoDB Vector Search queries against the embedded_movies collection.

Multiple Query Vectors Against a Single Document Vector

Same Term Query Vector Against Multiple Document Vectors

Same Term Query Using Multiple Models

Reorder the Results

Multiple Query Vectors Against a Single Document Vector

Same Term Query Vector Against Multiple Document Vectors

Same Term Query Using Multiple Models

How to Combine Multiple `$vectorSearch` Queries

Connect to the cluster using `mongosh`.

Run the `db.collection.createSearchIndex()` method.

Connect to your cluster in `mongosh`.

Use the `sample_mflix` database.

Run the MongoDB Vector Search queries against the `embedded_movies` collection.