Embeddings

Create vector embeddings for input text.

Create embeddings

post

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

Authorizations

AuthorizationstringRequired

Bearer authentication header of the form Bearer <token>.

Body

modelstringRequiredExample: Text Embedding 3 Large

inputone ofOptional

Input text to get embeddings for.

stringOptionalExample: The food was delicious and the waiter...

or

string[]OptionalExample: ["The food was delicious","The waiter was friendly"]

or

integer[]OptionalExample: [1,2,3,4,5]

or

encoding_formatstring · enumOptional

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

Default: floatPossible values:

dimensionsinteger · min: 1Optional

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

Example: 1536

Responses

200

Represents an embedding response returned by model, based on the provided input.

application/json

objectstringOptional

The object type, which is always "list"

Example: list

modelstringOptional

The model used for generating embeddings

400

Invalid request data.

402

The company has run out of AI credits. Returned when the company's budget limit has been reached.

application/json

500

Server error.

post/v1/embeddings

POST /v1/embeddings HTTP/1.1
Host: api.nexos.ai
Authorization: Bearer YOUR_SECRET_TOKEN
Content-Type: application/json
Accept: */*
Content-Length: 98

{
  "model": "Text Embedding 3 Large",
  "input": "There are three letters 'r' in the word 'strawberry'."
}

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        0.0023064255,
        -0.009327292
      ],
      "index": 0
    }
  ],
  "model": "text",
  "usage": {
    "prompt_tokens": 8,
    "total_tokens": 8,
    "nexos_credits_cost": 0.000016
  }
}