Starting in v8.1, 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 a field named
plot_embedding
, which contains embeddings created by using OpenAI's
text-embedding-ada-002
embedding model. You use this field for all
sample queries in this tutorial.
For the second and third query types listed in Use Cases and Benefits, you must generate embeddings for another field and from another embedding model, respectively. To run the sample queries for these use cases, complete the steps in Generate the Embeddings.
This tutorial walks you through the following steps:
Set up an Atlas Vector Search index on the
sample_mflix.embedded_movies
collection.Run
$vectorSearch
query with$rankFusion
to perform the following searches:Search the
plot_embedding
field for movie plots that contain movies with plots similar tolight-hearted comedy with ghosts
andslapstick humor with paranormal events
.Search the
plot_embedding
andtitle_embedding
fields for movies with plots similar tobattle between good and evil
using embeddings from OpenAI.Search the
plot_embedding
andplot_voyageai_embedding
fields for movies with plots similar tojourney across lands
using embeddings from OpenAI and Voyage AI respectively.
Before you begin, ensure that your Atlas cluster meets the requirements described in the Prerequisites.
Note
To run a $vectorSearch
query with $rankFusion
,
your cluster must run MongoDB v8.1 or higher.
Generate the Embeddings
To query for the same term against multiple fields and to query for the same term against embeddings from different embedding models, you must prepare the dataset to include embeddings for different fields and from different embedding models. This section demonstrates how to generate embeddings for the following:
Field Name | Embedding Model | Query Type |
---|---|---|
| OpenAI's | Run a comprehensive query for the same term against the |
| VoyageAI's | Run a query for the same term against VoyageAI's
|
You can skip this section if you want to run
$vectorSearch
queries against only the plot_embedding
field.
Prerequisites
Procedure
In this section, you generate embeddings by using OpenAI and Voyage AI models so you can run the following example queries:
Same Query Term Against Different Fields: For this query, you generate embeddings for the
title
field in theembedded_movies
collection by using OpenAI'stext-embedding-3-large
embedding model.Same Query Term Against Different Embedding Models: For this query, you generate embeddings for the
plot
field in theembedded_movies
collection by using Voyage AI'svoyage-3-large
embedding model.
Define and use a function to generate vector embeddings.
Paste and run the following code in your notebook after replacing the following placeholder values:
| Your OpenAI API key (line 6). |
| Your MongoDB cluster connection string (line 18). |
The following code defines a function that generates vector embeddings by using a proprietary embedding model from OpenAI. Specifically, this code does the following:
Specifies the
text-embedding-3-large
embedding model.Creates a function named
get_embedding
that calls the model's API to generate an embedding for a given text input.Connects to the Atlas cluster and fetches
3500
documents from thesample_mflix.embedded_movies
namespace.Generates embeddings from each document's
title
field by using theget_embedding
function.Updates each document with a new field named
title_embedding
that contains the embedding value by using the MongoDB PyMongo Driver.
1 import os 2 from openai import OpenAI 3 import pymongo 4 5 # Specify your OpenAI API key and embedding model 6 os.environ["OPENAI_API_KEY"] = "<api-key>" 7 model = "text-embedding-3-large" 8 openai_client = OpenAI() 9 10 # Define a function to generate embeddings 11 def get_embedding(text): 12 """Generates vector embeddings for the given text.""" 13 14 embedding = openai_client.embeddings.create(input = [text], model=model).data[0].embedding 15 return embedding 16 17 # Connect to your Atlas cluster 18 mongo_client = pymongo.MongoClient("<connection-string>") 19 db = mongo_client["sample_mflix"] 20 collection = db["embedded_movies"] 21 22 # Filter to exclude null or empty summary fields 23 filter = { "title": {"$nin": [ None, "" ]} } 24 25 # Get a subset of documents in the collection 26 documents = collection.find(filter).limit(3500) 27 28 # Update each document with a new embedding field 29 updated_doc_count = 0 30 for doc in documents: 31 embedding = get_embedding(doc["title"]) 32 collection.update_one( { "_id": doc["_id"] }, { "$set": { "title_embedding": embedding } } ) 33 updated_doc_count += 1 34 35 print(f"Updated {updated_doc_count} documents.")
Updated 3500 documents.
Note
It might take up to 15 minutes for the operation to complete.
Define and use a function to generate vector embeddings.
Paste and run the following code in your notebook after replacing the following placeholder values:
| Your VoyageAI API key (line 6). |
| Your MongoDB cluster connection string (line 18). |
The following code defines a function that generates vector embeddings by using a proprietary embedding model from VoyageAI. Specifically, this code does the following:
Specifies the
voyage-3-large
embedding model.Creates a function named
get_embedding
that calls the model's API to generate an embedding for a given text input.Connects to the Atlas cluster and fetches
3500
documents from thesample_mflix.embedded_movies
namespace.Generates embeddings from each document's
plot
field by using theget_embedding
function.Updates each document with a new field named
plot_voyageai_embedding
that contains the embedding value by using the MongoDB PyMongo Driver.
1 import os 2 import pymongo 3 import voyageai 4 5 # Specify your Voyage API key and embedding model 6 os.environ["VOYAGE_API_KEY"] = "<api-key>" 7 8 model = "voyage-3-large" 9 vo = voyageai.Client() 10 # Define a function to generate embeddings 11 def get_embedding(data, input_type = "document"): 12 embeddings = vo.embed( 13 data, model = model, input_type = input_type 14 ).embeddings 15 return embeddings[0] 16 17 # Connect to your MongoDB Atlas cluster 18 mongo_client = pymongo.MongoClient("<connection-string>") 19 db = mongo_client["sample_mflix"] 20 collection = db["embedded_movies"] 21 22 # Filter to exclude null or empty plot fields 23 filter = {"plot": {"$nin": [None, ""]}} 24 25 # Get a subset of documents in the collection 26 documents = collection.find(filter).limit(3500) 27 28 # Update each document with a new embedding field 29 updated_doc_count = 0 30 for doc in documents: 31 embedding = get_embedding(doc["plot"]) 32 if embedding is not None: 33 collection.update_one({"_id": doc["_id"]}, {"$set": {"plot_voyageai_embedding": embedding}}) 34 updated_doc_count += 1 35 36 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 Atlas Vector Search Index
In this section, you create an Atlas 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 Atlas cluster using mongosh
.
Open mongosh
in a terminal window and connect to your Atlas
cluster. For detailed instructions on connecting, see
Connect via mongosh.
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_voyageai_embedding", 15 "numDimensions": 1024, 16 "similarity": "dotProduct" 17 }, 18 { 19 "type": "vector", 20 "path": "title_embedding", 21 "numDimensions": 3072, 22 "similarity": "dotProduct" 23 } 24 ] 25 } 26 );
This index definition indexes the following fields:
plot_embedding
field as thevector
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 all the queries in this tutorial.
plot_voyageai_embedding
field as thevector
type. This field contains vector embeddings that represent the summary of a movie's plot. The index definition:Specifies
1024
vector dimensions.Measures similarity using
dotProduct
similarity.
This field mapping is required for the second use case.
title_embedding
field as thevector
type. This field contains vector embeddings that represent the title of the movie. The index definition:Specifies
3072
vector dimensions.Measures similarity using
dotProduct
similarity.
This field mapping is required for the third use case.
Run the Atlas 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 PhraseVariableEmbedding ModelDimensionslight-hearted comedy with ghosts
COMEDY_INVOLVING_GHOSTS
OpenAI's
text-embedding-ada-002
1536
slapstick humor with paranormal events
HUMOR_INVOLVING_PARANORMAL
OpenAI's
text-embedding-ada-002
1536
journey across lands
JOURNEY_ACROSS_LANDS_VOYAGEAI
VoyageAI's
voyage-3-large
1024
journey across lands
JOURNEY_ACROSS_LANDS_OPENAI
OpenAI's
text-embedding-ada-002
1536
battle between good and evil
BATTLE_GOOD_EVIL_TITLE_SEARCH
OpenAI's
text-embedding-3-large
3072
battle between good and evil
BATTLE_GOOD_EVIL_PLOT_SEARCH
OpenAI's
text-embedding-ada-002
1536
COMEDY_INVOLVING_GHOSTS=[0.004941695835441351, -0.02559443935751915, 0.005922815762460232, -0.00457746721804142, 0.015435416251420975, 0.004721845965832472, -0.00922712404280901, -0.03711850196123123, -0.005847345106303692, -0.018559250980615616, 0.015540419146418571, 0.014175382442772388, -0.01201626192778349, -0.014949778094887733, 0.01496290322393179, -0.01627543941140175, 0.037801019847393036, -0.014608519151806831, 0.012226266786456108, -0.02979455329477787, -0.008072092197835445, 0.006520019378513098, -0.007862087339162827, -0.0045380908995866776, 0.013145041652023792, 0.0033420431427657604, 0.02821951173245907, -0.01892676018178463, -0.017417345196008682, 0.0041902693919837475, 0.012659403495490551, -0.018703630194067955, -0.016380442306399345, -0.01016558613628149, -0.012994100339710712, -0.012705342844128609, -0.012305019423365593, -0.002349438378587365, 0.009824327193200588, -0.0038588540628552437, -0.014674145728349686, 0.00844616536051035, -0.010749665088951588, 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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 yourembeddings.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 1536
Run the Atlas Vector Search queries against the embedded_movies
collection.
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": COMEDY_INVOLVING_GHOSTS, 12 "numCandidates": 2000, 13 "limit": 50 14 } 15 } 16 ], 17 vectorPipeline2: [ 18 { 19 "$vectorSearch": { 20 "index": "multiple-vector-search", 21 "path": "plot_embedding", 22 "queryVector": HUMOR_INVOLVING_PARANORMAL, 23 "numCandidates": 2000, 24 "limit": 50 25 } 26 } 27 ] 28 } 29 }, 30 combination: { 31 weights: { 32 vectorPipeline1: 0.5, 33 vectorPipeline2: 0.5 34 } 35 }, 36 "scoreDetails": true 37 } 38 }, 39 { 40 "$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: 0.9327191114425659, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 1, weight: 0.5, value: 0.9237540364265442, details: [] } ] } }, { _id: ObjectId('573a13d3f29313caabd96a55'), plot: 'A teacher with paranormal abilities helps a group of ghosts graduate high school.', title: 'Ghost Graduation', scoreDetails: { value: 0.015512265512265512, 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: 0.9280960559844971, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 6, weight: 0.5, value: 0.9170590043067932, details: [] } ] } }, { _id: ObjectId('573a13abf29313caabd24011'), plot: 'A real-time dark comedy about a science geek who tangles with a clutch of Russian gangsters after he delivers them the wrong computer disk.', title: 'Nicotina', scoreDetails: { value: 0.014306006493506494, 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: 0.9196028709411621, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 4, weight: 0.5, value: 0.9184012413024902, details: [] } ] } }, { _id: ObjectId('573a13c6f29313caabd72c06'), plot: "Two exorcists literally remove the skeletons from the cupboards from people's homes. Some fairly embarrassing secrets are revealed along the way. A case where the skeletons have hidden themselves turns the lives of all those involved.", title: 'Skeletons', scoreDetails: { value: 0.013986697965571206, 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: 0.9218283891677856, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 12, weight: 0.5, value: 0.9145868420600891, details: [] } ] } }, { _id: ObjectId('573a1398f29313caabcebf6f'), plot: 'After an accident leaves a young man dead, his spirit stays behind to warn his lover of impending danger, with the help of a reluctant psychic.', title: 'Ghost', scoreDetails: { value: 0.013748597081930415, 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: 0.9261202812194824, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 21, weight: 0.5, value: 0.9131492376327515, 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: 0.013574660633484163, 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: 0.9271853566169739, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 25, weight: 0.5, value: 0.912155270576477, 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: 0.013486782952706347, 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: 0.9257347583770752, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 23, weight: 0.5, value: 0.9131345152854919, details: [] } ] } }, { _id: ObjectId('573a13acf29313caabd281b1'), plot: 'Will and Jake Grimm are traveling con-artists who encounter a genuine fairy-tale curse which requires true courage instead of their usual bogus exorcisms.', title: 'The Brothers Grimm', scoreDetails: { value: 0.01324561403508772, 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: 0.9197224974632263, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 15, weight: 0.5, value: 0.9143059849739075, details: [] } ] } }, { _id: ObjectId('573a139af29313caabcf0859'), plot: 'A man struggles with memories of his past, including a wife he cannot remember, in a nightmarish world with no sun and run by beings with telekinetic powers who seek the souls of humans.', title: 'Dark City', scoreDetails: { value: 0.013167013167013167, 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: 0.9192354083061218, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 14, weight: 0.5, value: 0.9144110083580017, details: [] } ] } }, { _id: ObjectId('573a13bcf29313caabd566d2'), plot: "A hotel handyman's life changes when the lavish bedtime stories he tells his niece and nephew start to magically come true.", title: 'Bedtime Stories', scoreDetails: { value: 0.01250758035172832, 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: 0.9158861041069031, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 8, weight: 0.5, value: 0.9161232709884644, 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: 0.012404870624048707, 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: 0.9203757643699646, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 30, weight: 0.5, value: 0.9115088582038879, details: [] } ] } }, { _id: ObjectId('573a1398f29313caabce9fd5'), plot: 'A troubled writer moves into a haunted house after inheriting it from his aunt.', title: 'House', 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: 12, weight: 0.5, value: 0.9210504293441772, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 35, weight: 0.5, value: 0.9111618995666504, details: [] } ] } }, { _id: ObjectId('573a13a8f29313caabd1db7e'), plot: 'Kung-Fu Action / Comedy / Horror / Musical about the second coming.', title: 'Jesus Christ Vampire Hunter', scoreDetails: { value: 0.012193362193362194, 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: 0.9157752990722656, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 10, weight: 0.5, value: 0.9146226644515991, details: [] } ] } }, { _id: ObjectId('573a1398f29313caabce98c8'), plot: 'The planned reburial of a village elder goes awry as the corpse resurrects into a hopping, bloodthirsty vampire, threatening mankind. Therefore, a Taoist Priest and his two disciples attempt to stop the terror.', title: 'Mr. Vampire', scoreDetails: { value: 0.0115210355987055, 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: 0.9200190305709839, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 43, weight: 0.5, value: 0.9108449220657349, details: [] } ] } }, { _id: ObjectId('573a1397f29313caabce784b'), plot: "The bizarre and musical tale of a girl who travels to another dimension through the gateway found in her family's basement.", title: 'Forbidden Zone', scoreDetails: { value: 0.011160714285714284, 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: 0.916013240814209, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 24, weight: 0.5, value: 0.913086473941803, details: [] } ] } }, { _id: ObjectId('573a1398f29313caabce912c'), plot: 'Three unemployed parapsychology professors set up shop as a unique ghost removal service.', title: 'Ghostbusters', scoreDetails: { value: 0.010583778966131907, 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: 42, weight: 0.5, value: 0.9153138995170593, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 28, weight: 0.5, value: 0.9117591381072998, details: [] } ] } }, { _id: ObjectId('573a1398f29313caabcea63f'), plot: 'A group of people stop by a mansion during a storm and discover two magical toy makers, and their haunted collection of dolls.', title: 'Dolls', scoreDetails: { value: 0.010081053698074976, 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: 0.9147992730140686, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 34, weight: 0.5, value: 0.9112522006034851, details: [] } ] } }, { _id: ObjectId('573a13f3f29313caabddfde0'), plot: 'Two siblings discover a supernatural escape from a troubled home, but find their bond tested when reality threatens to tear their family apart.', title: 'One and Two', scoreDetails: { value: 0.010064412238325281, 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: 32, weight: 0.5, value: 0.9163687229156494, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 48, weight: 0.5, value: 0.9105724096298218, details: [] } ] } }, { _id: ObjectId('573a13b5f29313caabd44e20'), plot: 'While sorting the affairs of his late Uncle, a man accidentally stumbles across a series of dark secrets connected to an ancient horror waiting to be freed.', title: 'The Call of Cthulhu', scoreDetails: { value: 0.009441524895341587, 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: 43, weight: 0.5, value: 0.9152694344520569, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 49, weight: 0.5, value: 0.9104976654052734, 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: 0.008064516129032258, 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: 0.9308393001556396, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 0, weight: 0.5 } ] } } ]
This sample query uses the $rankFusion
with the
following input pipeline stages:
| |
|
The sample query also specifies the following pipeline stages.
| |
Limits the returned results to 20 documents. |
Atlas 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.
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": BATTLE_GOOD_EVIL_PLOT_SEARCH, 12 "numCandidates": 2000, 13 "limit": 200 14 } 15 } 16 ], 17 vectorPipeline2: [ 18 { 19 "$vectorSearch": { 20 "index": "multiple-vector-search", 21 "path": "title_embedding", 22 "queryVector": BATTLE_GOOD_EVIL_TITLE_SEARCH, 23 "numCandidates": 2000, 24 "limit": 200 25 } 26 } 27 ] 28 } 29 }, 30 combination: { 31 weights: { 32 vectorPipeline1: 0.5, 33 vectorPipeline2: 0.5 34 } 35 }, 36 "scoreDetails": true 37 } 38 }, 39 { 40 "$project": { 41 _id: 1, 42 title: 1, 43 plot: 1, 44 scoreDetails: {"$meta": "scoreDetails"} 45 } 46 }, 47 { 48 "$limit": 20 49 } 50 ]);
[ { _id: ObjectId('573a13b8f29313caabd4c898'), plot: 'Perseus, mortal son of Zeus, battles the minions of the underworld to stop them from conquering heaven and earth.', title: 'Clash of the Titans', scoreDetails: { value: 0.013814698839565298, 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: 29, weight: 0.5, value: 0.9173959493637085, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 1, weight: 0.5, value: 0.70682692527771, details: [] } ] } }, { _id: ObjectId('573a139af29313caabcef692'), plot: 'The angel Gabriel comes to Earth to collect a soul which will end the stalemated war in Heaven, and only a former priest and a little girl can stop him.', title: 'The Prophecy', scoreDetails: { value: 0.013575490735644836, 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: 0.9186791181564331, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 9, weight: 0.5, value: 0.6911849975585938, details: [] } ] } }, { _id: ObjectId('573a1398f29313caabce8f83'), plot: 'A small group of human resistance fighters fight a desperate guerilla war against the genocidal extra-terrestrials who dominate Earth.', title: 'V: The Final Battle', scoreDetails: { value: 0.013167013167013167, 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: 0.9201459884643555, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 18, weight: 0.5, value: 0.6841024160385132, details: [] } ] } }, { _id: ObjectId('573a139af29313caabcf0e15'), plot: 'A young boy is whisked away to the mythical land of Tao where he becomes the center of a conflict between an evil lord and a group of animal warriors.', title: 'Warriors of Virtue', scoreDetails: { value: 0.011963357943669675, 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: 9, weight: 0.5, value: 0.9214991927146912, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 46, weight: 0.5, value: 0.6675300002098083, details: [] } ] } }, { _id: ObjectId('573a13c6f29313caabd72148'), plot: "Frankenstein's creature finds himself caught in an all-out, centuries old war between two immortal clans.", title: 'I, Frankenstein', scoreDetails: { value: 0.011489173663278833, 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: 0.9267290830612183, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 86, weight: 0.5, value: 0.6572250127792358, details: [] } ] } }, { _id: ObjectId('573a13b3f29313caabd3c719'), plot: "The warrior Beowulf must fight and defeat the monster Grendel who is terrorizing towns, and later, Grendel's mother, who begins killing out of revenge.", title: 'Beowulf', scoreDetails: { value: 0.011074800290486565, 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: 42, weight: 0.5, value: 0.9154369831085205, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 21, weight: 0.5, value: 0.6825653910636902, details: [] } ] } }, { _id: ObjectId('573a13b6f29313caabd467f5'), plot: "Story centers on a battle during China's Warring States Period, a series of civil wars, which spanned from the 5th to the 3rd century B.C. Based on a popular Japanese manga, which was in turn based a Japanese novel inspired by Warring States history in China.", title: 'Battle of the Warriors', 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: 0.9106720685958862, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 4, weight: 0.5, value: 0.7059011459350586, details: [] } ] } }, { _id: ObjectId('573a1397f29313caabce7dba'), plot: 'A film adaption of the myth of Perseus and his quest to battle both Medusa and the Kraken monster to save the Princess Andromeda.', title: 'Clash of the Titans', scoreDetails: { value: 0.01092896174863388, 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: 123, weight: 0.5, value: 0.9083951115608215, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 1, weight: 0.5, value: 0.70682692527771, details: [] } ] } }, { _id: ObjectId('573a139af29313caabcf0e61'), plot: 'A sci-fi update of the famous 6th Century poem. In a beseiged land, Beowulf must battle against the hideous creature Grendel and his vengeance seeking mother.', title: 'Beowulf', scoreDetails: { value: 0.010718294051627384, 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: 0.9144304394721985, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 21, weight: 0.5, value: 0.6825653910636902, details: [] } ] } }, { _id: ObjectId('573a13acf29313caabd274f4'), plot: "It's a high-kicking battle on the dark side when an ace vampire slayer and his beautiful sidekicks wage the ultimate martial-arts showdown with one of the most dangerous of the undead.", title: 'Vampire Effect', scoreDetails: { value: 0.009985688264376789, 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: 0.9257449507713318, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 184, weight: 0.5, value: 0.6469712853431702, details: [] } ] } }, { _id: ObjectId('573a13b2f29313caabd385df'), plot: "A young boy is chosen as the defender of good and must team up with Japan's ancient spirits and creatures of lore to destroy the forces of evil.", title: 'The Great Yokai War', scoreDetails: { value: 0.009706875383670963, 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: 0.9209381341934204, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 121, weight: 0.5, value: 0.6517701148986816, details: [] } ] } }, { _id: ObjectId('573a13cbf29313caabd7ec91'), plot: 'A vengeful fairy is driven to curse an infant princess, only to discover that the child may be the one person who can restore peace to their troubled land.', title: 'Maleficent', scoreDetails: { value: 0.009554985402105635, 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: 0.9130404591560364, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 29, weight: 0.5, value: 0.676243782043457, details: [] } ] } }, { _id: ObjectId('573a139ff29313caabd000f6'), plot: 'After enslavement & near extermination by an alien race in the year 3000, humanity begins to fight back.', title: 'Battlefield Earth', scoreDetails: { value: 0.009166125892277742, 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: 74, weight: 0.5, value: 0.9121060371398926, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 32, weight: 0.5, value: 0.6739504933357239, details: [] } ] } }, { _id: ObjectId('573a13c2f29313caabd67b22'), plot: '"An Epic Battle for World Domination: In the faraway land of Mirabillis, the warlord Dragon-a Eye has unleashed his terrifying forces to hunt down the source of all power, a legendary ...', title: 'Knights of Bloodsteel', scoreDetails: { value: 0.009083069847657374, 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: 0.9210658073425293, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 185, weight: 0.5, value: 0.646918773651123, details: [] } ] } }, { _id: ObjectId('573a13daf29313caabdad051'), plot: 'Bilbo and Company are forced to engage in a war against an array of combatants and keep the Lonely Mountain from falling into the hands of a rising darkness.', title: 'The Hobbit: The Battle of the Five Armies', 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: 0.916031539440155, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 77, weight: 0.5, value: 0.6581593751907349, details: [] } ] } }, { _id: ObjectId('573a139af29313caabcef28d'), plot: 'A young prince fights to free his people with the help of his family mascot, a small dragon who grows upon eating metal.', title: 'The Legend of Galgameth', scoreDetails: { value: 0.008791371158392434, 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: 0.9167085886001587, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 84, weight: 0.5, value: 0.6572535037994385, details: [] } ] } }, { _id: ObjectId('573a139af29313caabcf06fe'), plot: 'A young prince fights to free his people with the help of his family mascot, a small dragon who grows upon eating metal.', title: 'The Legend of Galgameth', scoreDetails: { value: 0.008791371158392434, 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: 0.9167085886001587, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 84, weight: 0.5, value: 0.6572535037994385, details: [] } ] } }, { _id: ObjectId('573a139ef29313caabcfbd25'), plot: 'A demon, raised from infancy after being conjured by and rescued from the Nazis, grows up to become a defender against the forces of darkness.', title: 'Hellboy', scoreDetails: { value: 0.008647627352663324, 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: 0.9158757328987122, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 79, weight: 0.5, value: 0.6577332615852356, details: [] } ] } }, { _id: ObjectId('573a13ecf29313caabdd205d'), plot: 'An orphan, whose father has been killed by dark power, attempts to bring justice back to the town.', title: 'Rise of the Legend', scoreDetails: { value: 0.008620689655172414, 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: 0.9139308929443359, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 56, weight: 0.5, value: 0.6645089387893677, details: [] } ] } }, { _id: ObjectId('573a13b0f29313caabd3505e'), plot: 'The mythical world starts a rebellion against humanity in order to rule the Earth, so Hellboy and his team must save the world from the rebellious creatures.', title: 'Hellboy II: The Golden Army', scoreDetails: { value: 0.008435282945086867, 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: 0.9181161522865295, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 161, weight: 0.5, value: 0.6486427783966064, details: [] } ] } } ]
This sample query uses the $rankFusion
with the
following input pipeline stages:
| |
|
The sample query also specifies the following pipeline stages.
| |
Limits the returned results to 20 documents. |
Atlas 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 second documents in the results
suggest a significant match for the term 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.
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 "$vectorSearch": { 20 "index": "multiple-vector-search", 21 "path": "plot_voyageai_embedding", 22 "queryVector": JOURNEY_ACROSS_LANDS_VOYAGEAI, 23 "numCandidates": 2000, 24 "limit": 100 25 } 26 } 27 ] 28 } 29 }, 30 combination: { 31 weights: { 32 vectorPipeline1: 0.5, 33 vectorPipeline2: 0.5 34 } 35 }, 36 "scoreDetails": true 37 } 38 }, 39 { 40 "$project": { 41 _id: 1, 42 title: 1, 43 plot: 1, 44 scoreDetails: {"$meta": "scoreDetails"} 45 } 46 }, 47 { 48 "$limit": 20 49 } 50 ]);
[ { _id: ObjectId('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: 0.7671917676925659, 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: 0.015512265512265512, 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: 3, weight: 0.5, value: 0.7560752630233765, 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: 0.014785823005001086, 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: 13, weight: 0.5, value: 0.7426372170448303, details: [] } ] } }, { _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: 0.014407131011608624, 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, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 7, weight: 0.5, value: 0.746292233467102, details: [] } ] } }, { _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: 0.014162077104642014, 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: 2, weight: 0.5, value: 0.760703444480896, details: [] } ] } }, { _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: 0.013811642565813867, 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: 27, weight: 0.5, value: 0.7315881848335266, 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: 0.013606071825249907, 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: [] }, { inputPipelineName: 'vectorPipeline2', rank: 14, weight: 0.5, value: 0.7411826848983765, details: [] } ] } }, { _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: 0.013494318181818182, 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: 28, weight: 0.5, value: 0.9088537693023682, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 4, weight: 0.5, value: 0.7538963556289673, details: [] } ] } }, { _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: 0.01324561403508772, 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: 0.910618782043457, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 16, weight: 0.5, value: 0.7397823333740234, 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: 0.012714460784313725, 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: 42, weight: 0.5, value: 0.72636878490448, 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: 0.012639109697933228, 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: [] }, { inputPipelineName: 'vectorPipeline2', rank: 25, weight: 0.5, value: 0.732880175113678, details: [] } ] } }, { _id: ObjectId('573a13aaf29313caabd218b4'), plot: 'An adventurous girl finds another world that is a strangely idealized version of her frustrating home, but it has sinister secrets.', title: 'Coraline', scoreDetails: { value: 0.012270400481782595, 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: 0.9102445840835571, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 22, weight: 0.5, value: 0.736004650592804, details: [] } ] } }, { _id: ObjectId('573a13c9f29313caabd792a8'), plot: 'Settlers traveling through the Oregon desert in 1845 find themselves stranded in harsh conditions.', title: "Meek's Cutoff", scoreDetails: { value: 0.011859838274932614, 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: 46, weight: 0.5, value: 0.7261408567428589, details: [] } ] } }, { _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: 0.011845039018952062, 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, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 32, weight: 0.5, value: 0.7292750477790833, details: [] } ] } }, { _id: ObjectId('573a1394f29313caabcdee62'), plot: 'The success of the journey focuses on keeping the Indian girl alive as well as themselves to complete trade with the Blackfeet.', title: 'The Big Sky', scoreDetails: { value: 0.01136950904392765, 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: 30, weight: 0.5, value: 0.9088267087936401, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 26, weight: 0.5, value: 0.732370138168335, details: [] } ] } }, { _id: ObjectId('573a13d6f29313caabd9eb15'), plot: 'A tribe of Norse warriors traipse across a barren land after battle. Bloodied and wounded, their chief is near death. He is about to hand over power to his son when an army of a completely different kind descends upon them.', title: 'Tumult', scoreDetails: { value: 0.010817307692307692, 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: 0.9174321293830872, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 100, weight: 0.5, value: 0.7155807614326477, details: [] } ] } }, { _id: ObjectId('573a13aef29313caabd2c923'), plot: 'A Chinese emissary is sent to the Gobi desert to execute a renegade soldier. When a caravan transporting a Buddhist monk and a valuable treasure is threatened by thieves, however, the two warriors might unite to protect the travelers.', title: 'Warriors of Heaven and Earth', scoreDetails: { value: 0.010793399638336348, 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: 0.9103184342384338, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 52, weight: 0.5, value: 0.7232900261878967, details: [] } ] } }, { _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: 0.010695187165775402, 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: 59, weight: 0.5, value: 0.9061647653579712, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 17, weight: 0.5, value: 0.7394661903381348, details: [] } ] } }, { _id: ObjectId('573a139af29313caabcf0e15'), plot: 'A young boy is whisked away to the mythical land of Tao where he becomes the center of a conflict between an evil lord and a group of animal warriors.', title: 'Warriors of Virtue', scoreDetails: { value: 0.010690045248868778, 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: 0.9092057943344116, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 44, weight: 0.5, value: 0.7262298464775085, details: [] } ] } }, { _id: ObjectId('573a1398f29313caabceb2b3'), plot: 'When two girls move to the country to be near their ailing mother, they have adventures with the wonderous forest spirits who live nearby.', title: 'My Neighbor Totoro', scoreDetails: { value: 0.010009008107296567, 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: 43, weight: 0.5, value: 0.9080972671508789, details: [] }, { inputPipelineName: 'vectorPipeline2', rank: 37, weight: 0.5, value: 0.7281997203826904, details: [] } ] } } ]
This sample query uses the $rankFusion
with the
following input pipeline stages:
| |
|
The sample query also specifies the following pipeline stages.
| |
Limits the returned results to 20 documents. |
Atlas 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 seconds documents in the results
suggest closer semantic interpretation by the model used in the
vectorPipeline2
.