Sign in

v1

latestOpenAPI 3.0.32026-07-2659199427.5 KB
Create predictions

Model predictions by use case

This is an all-purpose prediction endpoint you can use by specifying a USE_CASE and MODEL_ID. Upon submission, the API responds with a unique predictionId and a status. The predictionId can be used later in the GET request to retrieve the results.

IMPORTANT: The available use cases are detailed in their own section in this specification.

post/ai/async-prediction/{USE_CASE}/{MODEL_ID}

Path parameters

USE_CASEstring required

The name of the use case for the model. Use the Use Case API to get the list of supported use cases.

Headers

Authorizationstring required

Bearer token used for authentication. Format: Authorization: Bearer ACCESS_TOKEN.

Content-Typestring

application/json

Request body

chunkerConfigobject

This parameter contains fields that determine how the text is split and the size of text chunks created.

IMPORTANT: Specific information is detailed in each use case.

Example request

{
  "batch": [
    {
      "text": "The content to be split into chunks. "
    }
  ],
  "modelConfig": {
    "vectorQuantizationMethod": "min-max",
    "dimReductionSize": 256
  },
  "useCaseConfig": {
    "dataType": "query"
  }
}

Response

OK

chunkingIdstring uuid

The universal unique identifier (UUID) returned in the POST request. This UUID is required in the GET request to retrieve results.

statusstring

The current status of the request. Allowed values are:

  • SUBMITTED - The POST request was successful and the response has returned the chunkingId and status that is used by the GET request.

  • ERROR - An error was generated when the GET request was sent.

  • READY - The results associated with the chunkingId are available and ready to be retrieved.

  • RETRIEVED - The results associated with the chunkingId are returned successfully when the GET request was sent.

Example response

{
  "chunkingId": "441eb3be-7de6-470a-8141-e416a15c7db1",
  "status": "SUBMITTED"
}