Text reranking v7

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Use the aidb.rerank_text() function to reorder a set of candidate text passages by their relevance to a query. Reranking is typically applied as a post-retrieval step — after an initial set of candidates has been retrieved from a knowledge base — to surface the most relevant results at the top.

Step 1: Register a reranking model

SELECT aidb.create_model(
    'my_reranker',
    'nim_reranking',
    config => aidb.nim_reranking_config(
        api_key => 'nvapi-...',
        model   => 'nvidia/nv-rerankqa-mistral-4b-v3'
    )
);

Step 2: Rerank a set of candidates

SELECT * FROM aidb.rerank_text(
    query   => 'What is retrieval-augmented generation?',
    inputs  => ARRAY[
        'RAG combines retrieval and generation to produce grounded answers.',
        'Vector databases store high-dimensional embeddings for similarity search.',
        'RAG systems retrieve relevant documents before generating a response.'
    ],
    options => '{"model": "my_reranker"}'
)
ORDER BY relevance_score DESC;
Output
 id | relevance_score
----+-----------------
  2 |        0.97
  0 |        0.91
  1 |        0.43
(3 rows)

The id column corresponds to the zero-based index of each string in the inputs array, allowing you to join back to the original data.

For the full parameter reference, see Models reference.

Using reranking after knowledge base retrieval

A typical pattern is to retrieve an initial candidate set from a knowledge base and then rerank the results:

WITH candidates AS (
    SELECT
        source_id,
        content
    FROM aidb.retrieve_text('my_kb', 'What is RAG?', 20)
    JOIN my_source_table ON source_id = id::TEXT
)
SELECT
    c.source_id,
    c.content,
    r.relevance_score
FROM candidates c
JOIN aidb.rerank_text(
    query   => 'What is RAG?',
    inputs  => ARRAY(SELECT content FROM candidates),
    options => '{"model": "my_reranker"}'
) r ON r.id = (
    SELECT array_position(ARRAY(SELECT content FROM candidates), c.content) - 1
)
ORDER BY r.relevance_score DESC
LIMIT 5;
Note

Reranking models score passages against a query but don't generate text. To register a reranking model, use the appropriate model config helper for your provider — for example, aidb.nim_reranking_config() for NVIDIA NIM reranking endpoints.

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