Function: embed()

function embed<TAdapter>(options): Promise<EmbeddingResult>;

Defined in: packages/ai/src/activities/embed/index.ts:189

Embed activity - generates embedding vectors from text and image inputs.

Accepts a single item or an array of items; the result always carries an embeddings array with one vector per input item, in input order.

Type Parameters

TAdapter

TAdapter extends EmbeddingAdapter<string, any, any, any>

Parameters

options

EmbedOptions<TAdapter>

Returns

Promise<EmbeddingResult>

Examples

Embed a single text

import { embed } from '@tanstack/ai'
import { openaiEmbedding } from '@tanstack/ai-openai'

const result = await embed({
  adapter: openaiEmbedding('text-embedding-3-small'),
  input: 'a red guitar',
})

console.log(result.embeddings[0].vector)

Batch with requested dimensions

const result = await embed({
  adapter: openaiEmbedding('text-embedding-3-large'),
  input: ['a red guitar', 'a blue drum kit'],
  dimensions: 1024,
})

Multimodal embedding (text + image fused into one vector)

import { cohereEmbedding } from '@tanstack/ai-cohere'

// A nested array of parts fuses them into a single vector. The outer array
// is the item list, so this embeds one fused item into one vector.
const result = await embed({
  adapter: cohereEmbedding('embed-v4.0'),
  input: [
    [
      { type: 'text', content: 'product photo' },
      { type: 'image', source: { type: 'data', value: base64, mimeType: 'image/png' } },
    ],
  ],
  modelOptions: { inputType: 'search_document' },
})