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MRR Reranker

This reranker uses the Mean Reciprocal Rank (MRR) algorithm to combine and rerank search results from vector and full-text search. You can use this reranker by passing MRRReranker() to the rerank() method. The MRR algorithm calculates the average of reciprocal ranks across different search results, providing a balanced way to merge results from multiple ranking systems.

Note: Supported query types – Hybrid and Multivector search.

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Accepted Arguments

Note: weight_vector + weight_fts must equal 1.0. For multivector reranking, input result sets need _rowid so LanceDB can identify the same row across the ranked lists. Add .with_row_id(True) to each vector search before passing the results to the reranker.

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Supported Scores for each query type

You can specify the type of scores you want the reranker to return. The following are the supported scores for each query type:

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Hybrid Search

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Multivector Search