cosineSimilarity()

When you want to compare the similarity of embeddings, standard vector similarity metrics like cosine similarity are often used.

cosineSimilarity calculates the cosine similarity between two vectors. A high value (close to 1) indicates that the vectors are very similar, while a low value (close to -1) indicates that they are different.

import { cosineSimilarity, embedMany } from 'ai';

const { embeddings } = await embedMany({
  model: 'openai/text-embedding-3-small',
  values: ['sunny day at the beach', 'rainy afternoon in the city'],
});

console.log(
  `cosine similarity: ${cosineSimilarity(embeddings[0], embeddings[1])}`,
);

Import

<Snippet text={import { cosineSimilarity } from "ai"} prompt={false} />

API Signature

Parameters

<PropertiesTable content={[ { name: 'vector1', type: 'number[]', description: 'The first vector to compare', }, { name: 'vector2', type: 'number[]', description: 'The second vector to compare', }, ]} />

Returns

A number between -1 and 1 representing the cosine similarity between the two vectors.