Create Embedding

Create embeddings for text using various AI models

POST /v1/embeddings

Create embedding

cURL

curl --request POST \
  --url https://router.requesty.ai/v1/embeddings \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "input": "<string>",
  "model": "openai/text-embedding-3-small",
  "dimensions": 123,
  "encoding_format": "float",
  "user": "<string>"
}
'

200

{
  "data": [
    {
      "embedding": [
        123
      ],
      "index": 123,
      "object": "<string>"
    }
  ],
  "model": "<string>",
  "object": "<string>",
  "usage": {
    "prompt_tokens": 123,
    "total_tokens": 123
  }
}

Authorizations

Authorization · string · header · required

API key for authentication

Body

application/json

input · string string[] integer<int64>[] integer<int64>[][] · required

Input text to embed, encoded as a string, array of strings, array of tokens, or array of token arrays

model · string · required

The model name to use for embedding generation

Example:

"openai/text-embedding-3-small"

dimensions · integer<int64>

The number of dimensions the resulting output embeddings should have

encoding_format · enum<string> · default: float

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

Available options: float, base64

user · string

A unique identifier representing your end-user.

Response

200

application/json

Embedding response

data · object[] · required

The list of embeddings generated by the model

Show child attributes

model · string · required

The name of the model used to generate the embedding

object · string · required

The object type, which is always 'list'

usage · object · required

Show child attributes