POST
/
v3
/
openai
/
embeddings
curl --request POST \
  --url https://api.novita.ai/v3/openai/embeddings \
  --header 'Authorization: <authorization>' \
  --header 'Content-Type: <content-type>' \
  --data '{
  "input": {},
  "model": {},
  "encoding_format": "<string>"
}'
{
  "object": "<string>",
  "data": [
    {
      "index": 123,
      "embedding": [
        {}
      ],
      "object": "<string>"
    }
  ],
  "model": "<string>",
  "usage": {
    "prompt_tokens": 123,
    "total_tokens": 123
  }
}

Creates an embedding vector representing the input text.

​
Request Headers

​
Content-Type
string
required

Enum: application/json

​
Authorization
string
required

Bearer authentication format, for example: Bearer {{API Key}}.

​
Request Body

​
input
string | arrary
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.

​
model
enum<string>
required

ID of the model to use. Enum: baai/bge-m3.

​
encoding_format
string

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

​
Response

​
object
string
required

Fixed as list

​
data
array
required

List of embeddings vectors generated by the model.

​
index
integer
required

The index of the embedding vector.

​
embedding
array
required

The embedding vector.

​
object
string
required

Fixed as embedding

​
model
string
required

The ID of the model used.

​
usage
object
required

Usage information.

​
prompt_tokens
integer
required

The number of prompt tokens.

​
total_tokens
integer
required

The number of total tokens.

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