Reranking

Reranking is a technique used to improve search relevance by reordering a set of documents based on their relevance to a query. Unlike embedding-based similarity search, reranking models are specifically trained to understand the relationship between queries and documents, often producing more accurate relevance scores.

Reranking Documents

The AI SDK provides the rerank function to rerank documents based on their relevance to a query. You can use it with reranking models, e.g. cohere.reranking('rerank-v3.5') or bedrock.reranking('cohere.rerank-v3-5:0').

import { rerank } from 'ai';
import { cohere } from '@ai-sdk/cohere';

const documents = [
  'sunny day at the beach',
  'rainy afternoon in the city',
  'snowy night in the mountains',
];

const { ranking } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents,
  query: 'talk about rain',
  topN: 2, // Return top 2 most relevant documents
});

console.log(ranking);
// [
//   { originalIndex: 1, score: 0.9, document: 'rainy afternoon in the city' },
//   { originalIndex: 0, score: 0.3, document: 'sunny day at the beach' }
// ]

Working with Object Documents

Reranking also supports structured documents (JSON objects), making it ideal for searching through databases, emails, or other structured content:

import { rerank } from 'ai';
import { cohere } from '@ai-sdk/cohere';

const documents = [
  {
    from: 'Paul Doe',
    subject: 'Follow-up',
    text: 'We are happy to give you a discount of 20% on your next order.',
  },
  {
    from: 'John McGill',
    subject: 'Missing Info',
    text: 'Sorry, but here is the pricing information from Oracle: $5000/month',
  },
];

const { ranking, rerankedDocuments } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents,
  query: 'Which pricing did we get from Oracle?',
  topN: 1,
});

console.log(rerankedDocuments[0]);
// { from: 'John McGill', subject: 'Missing Info', text: '...' }

Understanding the Results

The rerank function returns a comprehensive result object:

import { cohere } from '@ai-sdk/cohere';
import { rerank } from 'ai';

const { ranking, rerankedDocuments, originalDocuments } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents: ['sunny day at the beach', 'rainy afternoon in the city'],
  query: 'talk about rain',
});

// ranking: sorted array of { originalIndex, score, document }
// rerankedDocuments: documents sorted by relevance (convenience property)
// originalDocuments: original documents array

Each item in the ranking array contains:

originalIndex: Position in the original documents array
score: Relevance score (typically 0-1, where higher is more relevant)
document: The original document

Settings

Top-N Results

Use topN to limit the number of results returned. This is useful for retrieving only the most relevant documents:

import { cohere } from '@ai-sdk/cohere';
import { rerank } from 'ai';

const { ranking } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents: ['doc1', 'doc2', 'doc3', 'doc4', 'doc5'],
  query: 'relevant information',
  topN: 3, // Return only top 3 most relevant documents
});

Provider Options

Reranking model settings can be configured using providerOptions for provider-specific parameters:

import { cohere } from '@ai-sdk/cohere';
import { rerank } from 'ai';

const { ranking } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents: ['sunny day at the beach', 'rainy afternoon in the city'],
  query: 'talk about rain',
  providerOptions: {
    cohere: {
      maxTokensPerDoc: 1000, // Limit tokens per document
    },
  },
});

Retries

The rerank function accepts an optional maxRetries parameter of type number that you can use to set the maximum number of retries for the reranking process. It defaults to 2 retries (3 attempts in total). You can set it to 0 to disable retries.

import { cohere } from '@ai-sdk/cohere';
import { rerank } from 'ai';

const { ranking } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents: ['sunny day at the beach', 'rainy afternoon in the city'],
  query: 'talk about rain',
  maxRetries: 0, // Disable retries
});

Abort Signals and Timeouts

The rerank function accepts an optional abortSignal parameter of type AbortSignal that you can use to abort the reranking process or set a timeout.

import { cohere } from '@ai-sdk/cohere';
import { rerank } from 'ai';

const { ranking } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents: ['sunny day at the beach', 'rainy afternoon in the city'],
  query: 'talk about rain',
  abortSignal: AbortSignal.timeout(5000), // Abort after 5 seconds
});

Custom Headers

The rerank function accepts an optional headers parameter of type Record<string, string> that you can use to add custom headers to the reranking request.

import { cohere } from '@ai-sdk/cohere';
import { rerank } from 'ai';

const { ranking } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents: ['sunny day at the beach', 'rainy afternoon in the city'],
  query: 'talk about rain',
  headers: { 'X-Custom-Header': 'custom-value' },
});

Response Information

The rerank function returns response information that includes the raw provider response:

import { cohere } from '@ai-sdk/cohere';
import { rerank } from 'ai';

const { ranking, response } = await rerank({
  model: cohere.reranking('rerank-v3.5'),
  documents: ['sunny day at the beach', 'rainy afternoon in the city'],
  query: 'talk about rain',
});

console.log(response); // { id, timestamp, modelId, headers, body }

Reranking Providers & Models

Several providers offer reranking models:

Provider	Model
Cohere	`rerank-v3.5`
Cohere	`rerank-english-v3.0`
Cohere	`rerank-multilingual-v3.0`
Amazon Bedrock	`amazon.rerank-v1:0`
Amazon Bedrock	`cohere.rerank-v3-5:0`
Together.ai	`Salesforce/Llama-Rank-v1`
Together.ai	`mixedbread-ai/Mxbai-Rerank-Large-V2`