Embeddings

Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.

Related guide: Embeddings

Create embeddings

POST https://api.openai.com/v1/embeddings

Creates an embedding vector representing the input text.

Request body

---

modelstringRequired

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.

---

inputstring or arrayRequired

Input text to get embeddings for, encoded as a string or array of tokens. To get embeddings for multiple inputs in a single request, pass an array of strings or array of token arrays. Each input must not exceed 8192 tokens in length.

---

userstringOptional

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

---

Example request:

curl:

curl https://api.openai.com/v1/embeddings \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": "The food was delicious and the waiter...",
    "model": "text-embedding-ada-002"
  }'

python:

import os
import openai
openai.api_key = os.getenv("OPENAI_API_KEY")
openai.Embedding.create(
  model="text-embedding-ada-002",
  input="The food was delicious and the waiter..."
)

node.js:

const { Configuration, OpenAIApi } = require("openai");
const configuration = new Configuration({
  apiKey: process.env.OPENAI_API_KEY,
});
const openai = new OpenAIApi(configuration);
const response = await openai.createEmbedding({
  model: "text-embedding-ada-002",
  input: "The food was delicious and the waiter...",
});

Parameters:

{
  "model": "text-embedding-ada-002",
  "input": "The food was delicious and the waiter..."
}

Response:

{
  "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
  }
}