API Reference

Embeddings

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Create embeddings

client.Embeddings.New(ctx, body) (*CreateEmbeddingResponse, error)

POST/embeddings

Creates an embedding vector representing the input text.

ParametersExpand Collapse

body EmbeddingNewParams

Input param.Field[EmbeddingNewParamsInputUnion]

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 all embedding models), cannot be an empty string, and any array must be 2048 dimensions or less. Example Python code for counting tokens. In addition to the per-input token limit, all embedding models enforce a maximum of 300,000 tokens summed across all inputs in a single request.

Model param.Field[EmbeddingModel]

ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.

Dimensions param.Field[int64]Optional

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

minimum1

EncodingFormat param.Field[EmbeddingNewParamsEncodingFormat]Optional

The format to return the embeddings in. Can be either float or base64.

User param.Field[string]Optional

A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.

ReturnsExpand Collapse

type CreateEmbeddingResponse struct{…}

Data []Embedding

The list of embeddings generated by the model.

Model string

The name of the model used to generate the embedding.

Object List

The object type, which is always “list”.

Usage CreateEmbeddingResponseUsage

The usage information for the request.

Create embeddings

Go

HTTP

Python

TypeScript

Go

Ruby

Java

CLI Tool

package main

import (
  "context"
  "fmt"

  "github.com/openai/openai-go"
  "github.com/openai/openai-go/option"
)

func main() {
  client := openai.NewClient(
    option.WithAPIKey("My API Key"),
  )
  createEmbeddingResponse, err := client.Embeddings.New(context.TODO(), openai.EmbeddingNewParams{
    Input: openai.EmbeddingNewParamsInputUnion{
      OfString: openai.String("The quick brown fox jumped over the lazy dog"),
    },
    Model: openai.EmbeddingModelTextEmbedding3Small,
  })
  if err != nil {
    panic(err.Error())
  }
  fmt.Printf("%+v\n", createEmbeddingResponse.Data)
}

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        0.0023064255,
        -0.009327292,
        .... (1536 floats total for ada-002)
        -0.0028842222,
      ],
      "index": 0
    }
  ],
  "model": "text-embedding-ada-002",
  "usage": {
    "prompt_tokens": 8,
    "total_tokens": 8
  }
}

Returns Examples

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        0.0023064255,
        -0.009327292,
        .... (1536 floats total for ada-002)
        -0.0028842222,
      ],
      "index": 0
    }
  ],
  "model": "text-embedding-ada-002",
  "usage": {
    "prompt_tokens": 8,
    "total_tokens": 8
  }
}