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v171

latestOpenAPI 3.1.0raw.githubusercontent.com2026-08-0726249111.7 MB
Embeddings

Create embeddings

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

post/v2/router/embeddings

Request body

dimensionsinteger

The number of dimensions the resulting output embeddings should have.

encoding_format'float' | 'base64'

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

modelstring required

ID of the model to use.

namestring

The name to display on the trace. If not specified, the default system name will be used.

userstring

A unique identifier representing your end-user.

Example request

{
  "orq": {
    "identity": {
      "id": "contact_01ARZ3NDEKTSV4RRFFQ69G5FAV",
      "display_name": "Jane Doe",
      "email": "jane.doe@example.com",
      "metadata": [
        {
          "department": "Engineering",
          "role": "Senior Developer"
        }
      ],
      "logo_url": "https://example.com/avatars/jane-doe.jpg",
      "tags": [
        "hr",
        "engineering"
      ]
    }
  }
}

Response

Returns the embedding vector.

modelstring required

ID of the model used.

object'list' required

Always "list".