Get Started With Native Reranking

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Get Started With Native Reranking

The [$rerank](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/rerank.md#mongodb-pipeline-pipe.-rerank aggregation stage reorders input documents using [Voyage AI reranking models](https://www.mongodb.com/docs/voyageai/models/rerankers.md#std-label-voyage-rerankers and returns the same documents sorted by relevance to the query. The $rerank stage can appear anywhere in an aggregation pipeline.

You don't need to create an index to run [$rerank](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/rerank.md#mongodb-pipeline-pipe.-rerank queries. However, MongoDB recommends using [$rerank](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/rerank.md#mongodb-pipeline-pipe.-rerank after a [$vectorSearch](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/vector-search-stage.md#mongodb-pipeline-pipe.-vectorSearch, [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search, [$rankFusion](https://www.mongodb.com/docs/manual/reference/operator/aggregation/rankFusion.md#mongodb-pipeline-pipe.-rankFusion, or [$scoreFusion](https://www.mongodb.com/docs/manual/reference/operator/aggregation/scoreFusion.md#mongodb-pipeline-pipe.-scoreFusion stage, which require creating a [MongoDB Vector Search](https://www.mongodb.com/docs/vector-search/indexes/vector-search-type.md#std-label-avs-types-vector-search or [MongoDB Search](https://www.mongodb.com/docs/search/indexes/manage-indexes.md#std-label-ref-create-index index on your collection.

This quickstart demonstrates how to enable and use Native Reranking in Atlas by using the [$rerank](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/rerank.md#mongodb-pipeline-pipe.-rerank aggregation stage on queries against the [sample_mflix](https://www.mongodb.com/docs/manual/sample-data/sample-mflix.md#std-label-sample-mflix dataset.

Prerequisites

Before you begin, complete the following tasks:

  • Deploy a Atlas cluster with MongoDB 8.3 or later by selecting Latest Version with Auto-Upgrades in the Atlas UI Cluster Builder page.

To learn more about an Atlas cluster, see [Create a Cluster](https://www.mongodb.com/docs/atlas/tutorial/create-new-cluster.md#std-label-create-new-cluster. Native reranking is not available for self-managed deployments.

  • Load the [sample_mflix](https://www.mongodb.com/docs/manual/sample-data/sample-mflix.md#std-label-sample-mflix dataset into your cluster.

To learn more, see [Load Sample Data.](https://www.mongodb.com/docs/atlas/import/load-sample-data.md#std-label-load-sample-data

  • Download and install [mongosh.](https://www.mongodb.com/docs/mongodb-shell.md#mongodb-binary-bin.mongosh

To learn more, see Install the MongoDB Shell.

To learn more about the compatibility and requirements for using $rerank, see [Considerations](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/rerank.md#std-label-rerank-considerations. The rerank-3 and rerank-3-lite models require a dedicated cluster running MongoDB 9.0 or later. To learn more, see [Requirements.](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/rerank.md#std-label-rerank-requirements

Procedure

To get started with native reranking, follow these steps:

  1. Enable Native Reranking.

In Atlas, go to the Project Settings page.

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

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

In the sidebar, click the icon next to Project Overview.

The Project Settings page displays.

  1. Scroll down to the Native Reranking section and toggle Enable Native Reranking to On.

  2. Click Confirm.

  3. Run a Native Reranking query.

The following query uses the [$rerank](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/rerank.md#mongodb-pipeline-pipe.-rerank stage to find the top ten movies that are most relevant to the query for martial arts.

Switch to the sample_mflix database:

javascript use sample_mflix

Run a Native Reranking query.

The following query uses the [$rerank](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/rerank.md#mongodb-pipeline-pipe.-rerank stage to return movies that are most relevant to the query for martial arts using the rerank-2.5 model. The query prioritizes films about martial arts training and tournaments. It uses the following pipeline stages:

Pipeline Stage Description
[$match](https://www.mongodb.com/docs/manual/reference/operator/aggregation/match.md#mongodb-pipeline-pipe.-match Filters the documents to include only documents that have a fullplot field of type string.
[$sort](https://www.mongodb.com/docs/manual/reference/operator/aggregation/sort.md#mongodb-pipeline-pipe.-sort Sorts the documents in descending order of the released field to ensure deterministic ordering.
[$rerank](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/rerank.md#mongodb-pipeline-pipe.-rerank Reorders the documents to match the query using the rerank-2.5 reranker model. The numDocsToRerank parameter specifies the maximum number of documents to consider for reranking. The path parameter specifies the field to use for reranking.
[$addFields](https://www.mongodb.com/docs/manual/reference/operator/aggregation/addFields.md#mongodb-pipeline-pipe.-addFields Adds a field named rerankScore to the documents.
[$limit](https://www.mongodb.com/docs/manual/reference/operator/aggregation/limit.md#mongodb-pipeline-pipe.-limit Limits the output to 10 documents.
[$project](https://www.mongodb.com/docs/manual/reference/operator/aggregation/project.md#mongodb-pipeline-pipe.-project Excludes all fields except title, fullplot, and rerankScore from the documents in the results.

json db.embedded_movies.aggregate([ { "$match": { "fullplot": { "$exists": true, "$type": "string" } } }, { "$sort": { "released": -1 } }, { "$rerank": { "model": "rerank-2.5", "query": { "text": "martial arts; prioritize films about martial arts training and tournaments" }, "path": "fullplot", "numDocsToRerank": 100 } }, { "$addFields": { "rerankScore": { "$meta": "score" } } }, { "$limit": 10 }, { "$project": { "_id": 0, "title": 1, "fullplot": 1, "rerankScore": 1 } } ])

Output:

javascript [ { title: 'Ti mene nosis', fullplot: 'No treason, no surrender.', rerankScore: 0.5986876487731934 }, { title: 'The Real Miyagi', fullplot: 'The life of the greatest karate master of a generation.', rerankScore: 0.5986876487731934 }, { title: 'Peter Pan Live!', fullplot: 'A live telecast of the beloved J. M. Barrie story.', rerankScore: 0.5986876487731934 }, { title: "Why Don't You Play in Hell?", fullplot: 'A renegade film crew becomes embroiled with a yakuza clan feud.', rerankScore: 0.5986876487731934 }, { fullplot: "A French police magistrate spends years trying to take down one of the country's most powerful drug rings.", title: 'The Connection', rerankScore: 0.5986876487731934 }, { title: 'Anomalisa', fullplot: "Charlie Kaufman's first stop-motion film about a man crippled by the mundanity of his life.", rerankScore: 0.5986876487731934 }, { title: 'The Master Plan', fullplot: 'Charles Ingvar Jènsson gathers three criminals to take vengeance upon the people who killed his uncle.', rerankScore: 0.5986876487731934 }, { title: 'Redeemer', fullplot: 'A former hit-man for a drug cartel becomes a vigilante to pay for his sins and find redemption.', rerankScore: 0.5986876487731934 }, { title: 'Rise of the Legend', fullplot: 'An orphan, whose father has been killed by dark power, attempts to bring justice back to the town.', rerankScore: 0.5986876487731934 }, { title: 'Darkness on the Edge of Town', fullplot: 'A troubled teenage sharpshooter decides to avenge the death of her estranged sister after she is found murdered in a public bathroom.', rerankScore: 0.5986876487731934 } ]

  1. Create the indexes for running Native Reranking queries with $vectorSearch and $search.

MongoDB recommends using [$rerank](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/rerank.md#mongodb-pipeline-pipe.-rerank after a [$vectorSearch](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/vector-search-stage.md#mongodb-pipeline-pipe.-vectorSearch, [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search, [$rankFusion](https://www.mongodb.com/docs/manual/reference/operator/aggregation/rankFusion.md#mongodb-pipeline-pipe.-rankFusion, or [$scoreFusion](https://www.mongodb.com/docs/manual/reference/operator/aggregation/scoreFusion.md#mongodb-pipeline-pipe.-scoreFusion stage. To do so, create a MongoDB Vector Search and MongoDB Search index on your collection to run the [$vectorSearch](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/vector-search-stage.md#mongodb-pipeline-pipe.-vectorSearch and [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search stages.

To try the sample queries that use the [$vectorSearch](https://www.mongodb.com/docs/vector-search/query/aggregation-stages/vector-search-stage.md#mongodb-pipeline-pipe.-vectorSearch and [$search](https://www.mongodb.com/docs/search/query/aggregation-stages/search.md#mongodb-pipeline-pipe.-search stages in this quickstart, you must create a MongoDB Vector Search and MongoDB Search index on your collection.

##### Create a MongoDB Vector Search index

###### Create a MongoDB Vector Search index on the plot_embedding_voyage_4_large field.

To create the index, complete the following steps:

Click Search & Vector Search in the sidebar.

Click Create Index.

Start your index configuration:

  • Select Vector Search as the index type.

  • Enter vector_index as the name of the index.

  • Select the sample_mflix.embedded_movies collection.

  • Select JSON Editor as the editor type.

Click Next and paste the following index definition in the JSON editor:

json { "fields": [ { "type": "vector", "path": "plot_embedding_voyage_4_large", "numDimensions": 2048, "similarity": "dotProduct" } ] }

Click Next, then click Create Index.

##### Create a MongoDB Search index

###### Create a MongoDB Search index on the ``fullplot`` field.

To create the index, complete the following steps:

Click Search & Vector Search in the sidebar.

Click Create Index.

Start your index configuration:

  • Select Search as the index type.

  • Enter search_index as the name of the index.

  • Select the sample_mflix.embedded_movies collection.

  • Select JSON Editor as the editor type.

Click Next and paste the following index definition in the JSON editor:

json { "mappings": { "dynamic": true } }

Click Next, then click Create Index.

  1. Prepare to run $vectorSearch and $search queries with Native Reranking.

Connect to your cluster using [mongosh.](https://www.mongodb.com/docs/mongodb-shell.md#mongodb-binary-bin.mongosh

Create a file named embeddings.js to store the embeddings to use in the queries.

Copy and paste the following embeddings into the file.

```javascript MARTIAL_ARTS_EMBEDDINGS=[0.02218237891793251, -0.007462590467184782, -0.01691064052283764, 0.0072914301417768, -0.011365045793354511, -0.045186325907707214, -6.846413452876732e-05, -0.0034916705917567015, 0.009995763190090656, 0.025742514058947563, -0.002481824718415737, -0.0029268416110426188, 0.0023106643930077553, -0.04135233536362648, -0.019717669114470482, -0.024510158225893974, -0.008729176595807076, -0.001048356993123889, 0.01033808384090662, 0.008900336921215057, -0.00797607097774744, 0.03258892521262169, 0.00766798248514533, 0.010406548157334328, 0.04107847809791565, -0.020128455013036728, -0.03833991289138794, 0.018348386511206627, -0.01533596497029066, 0.042995475232601166, 0.020813096314668655, -0.0016260230913758278, -0.004364588297903538, -0.011159653775393963, -0.03436899557709694, 0.010817333124577999, -0.0008900337270461023, -0.012118151411414146, -0.0156782865524292, 0.04381704330444336, -0.013350505381822586, 0.003851107321679592, 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