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Method

getEntitiesFromPDF POST

Copy POST

Extracts text from the provided PDF and returns a list of recognized labels and their scores.

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.
No	pdf	bytes	(Optional) The pdf to predict on. One of pdf or docId must be specified.
No	docId	str	(Optional) The pdf to predict on. One of pdf or docId must be specified.
No	returnExtractedFeatures	bool	(Optional) If True, will return all extracted features (e.g. all tokens in a page) from the PDF. Default is False.
No	verbose	bool	(Optional) If True, will return all the extracted tokens probabilities for all the trained labels. Default is False.
No	saveExtractedFeatures	bool	(Optional) If True, will save extracted features (i.e. page tokens) so that they can be fetched using the prediction docId. Default is False.

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.
DataNotFoundError	`docId` is not found.

Language: