Predict API

Once your model is trained, you must deploy the model on Abacus.AI platform to generate predictions. You can use the prediction dashboard to generate the predictions from the trained model. In this section the underlying prediction API and all other additional prediction API methods are discussed for the use case in consideration:

Method
getLabels POST
Copy POST

Returns a list of scored labels for a document.

Arguments:

REQUIRED KEY TYPE DESCRIPTION
Yes deploymentToken str The deployment token to authenticate access to created deployments. This token is only authorized to predict on deployments in this project, so it is safe to embed this model inside of an application or website.
Yes deploymentId str The unique identifier to a deployment created under the project.
Yes queryData dict Dictionary where key is "Content" and value is the text from which entities are to be extracted.
No returnExtractedEntities bool (Optional) If True, will return the extracted entities in simpler format
Note: The arguments for the API methods follow camelCase but for Python SDK underscore_case is followed.

Response:

KEY TYPE DESCRIPTION
success Boolean true if the call succeeded, false if there was an error
List[EntityRecognitionPrediction]

Exceptions:

TYPE WHEN
DataNotFoundError

deploymentId is not found.

Language: