provider Embeddings POST /embeddings
@utdk/openai /embeddings
Creates an embedding vector representing the input text.

Try it

Authentication
Configure credentials for OpenAI API
createembedding
POST/embeddings

Input

required

Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for `text-embedding-ada-002`), cannot be an empty string, and any array must be 2048 dimensions or less. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens. Some models may also impose a limit on total number of tokens summed across inputs.

required

ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](/docs/models) for descriptions of them.

The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/).

The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices#end-user-ids).

Configure credentials above to enable sending.

Code snippet
Updates live as you fill in the form above.

TypeScript

import openai from '@utdk/openai';

await openai.createembedding({
  "encoding_format": "float"
})