Overview Use Cases Connectors Authentication Getting Started with the Python SDK API Reference ai_agents ai_chat algorithm annotations application_connectors batch_prediction code_completion custom_loss_function custom_metric database_connectors dataset deployment deployment_conversations docstore document_retrievers documentation eda external_app feature_drift feature_group feature_group_row_process feature_group_template file_connectors graph_dashboard holdout_analysis llm_apps model model_monitoring module natural_language_explanation organization pipelines predict checkConstraints classifyImage classifyPDF describeImage executeAgent executeAgentWithBinaryData executeConversationAgent generateImage getAlternativeAssignments getAnomalies getAssignments getChatResponse getChatResponseWithBinaryData getClassification getCluster getCompletion getConversationResponse getConversationResponseWithBinaryData getEntailment getEntitiesFromPDF getEventAnomalyScore getForecast getKNearest getLabels getMatrixAgentSchema getMultipleKNearest getObjectsFromImage getPersonalizedRanking getRankedItems getRecommendations getRelatedItems getSearchResults getSentiment getSummary getTextFromDocument getTimeseriesAnomalies isAnomaly lookupFeatures lookupMatches pauseAutonomousAgent predict predictChurn predictClass predictFraud predictFromDatasets predictLanguage predictLead predictMultiple predictTakeover predictTarget predictWithBinaryData scoreImage startAutonomousAgent transcribeAudio transferStyle prediction_operator project python_function refresh secrets streaming streaming_connectors upload webhooks API Classes API Inputs Documentation Chat Bot API Search Video Tutorials ChatLLM

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: