`embedMany()`

Embed several values using an embedding model. The type of the value is defined by the embedding model.

embedMany automatically splits large requests into smaller chunks if the model has a limit on how many embeddings can be generated in a single call.

import { openai } from '@ai-sdk/openai';
import { embedMany } from 'ai';

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

Import

import { embedMany } from "ai"

API Signature

Parameters

model:

EmbeddingModel

The embedding model to use. Example: openai.embedding('text-embedding-3-small')

values:

Array<VALUE>

The values to embed. The type depends on the model.

maxRetries?:

number

Maximum number of retries. Set to 0 to disable retries. Default: 2.

abortSignal?:

AbortSignal

An optional abort signal that can be used to cancel the call.

headers?:

Record<string, string>

Additional HTTP headers to be sent with the request. Only applicable for HTTP-based providers.

experimental_telemetry?:

TelemetrySettings

Telemetry configuration. Experimental feature.

TelemetrySettings

isEnabled?:

boolean

Enable or disable telemetry. Disabled by default while experimental.

functionId?:

string

Identifier for this function. Used to group telemetry data by function.

metadata?:

Additional information to include in the telemetry data.

Returns

values:

Array<VALUE>

The values that were embedded.

embeddings:

number[][]

The embeddings. They are in the same order as the values.

usage:

EmbeddingTokenUsage

The token usage for generating the embeddings.

EmbeddingTokenUsage

tokens:

number

The total number of input tokens.