Skip to main content
POST
/
embeddings
curl https://api.portkey.ai/v1/embeddings \
  -H "x-portkey-api-key: $PORTKEY_API_KEY" \
  -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": "The food was delicious and the waiter...",
    "model": "text-embedding-ada-002",
    "encoding_format": "float"
  }'
{
  "data": [
    {
      "index": 123,
      "embedding": [
        123
      ],
      "object": "embedding"
    }
  ],
  "model": "<string>",
  "object": "list",
  "usage": {
    "prompt_tokens": 123,
    "total_tokens": 123
  }
}

Authorizations

​
x-portkey-api-key
string
header
required
​
x-portkey-virtual-key
string
header
required

Body

application/json
​
input
default:""
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 for counting tokens.

Example:

"The quick brown fox jumped over the lazy dog"

​
model
required

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.

Example:

"text-embedding-3-small"

​
encoding_format
enum<string>
default:float

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

Available options:
float,
base64
Example:

"float"

​
dimensions
integer

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

Required range: x >= 1
​
user
string

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

Example:

"user-1234"

Response

200 - application/json

OK

​
data
object[]
required

The list of embeddings generated by the model.

​
model
string
required

The name of the model used to generate the embedding.

​
object
enum<string>
required

The object type, which is always "list".

Available options:
list
​
usage
object
required

The usage information for the request.

Last modified on April 27, 2026