def client():
client = Client()
return client
if not model_id:
raise ValueError('A modelId is needed for prediction, input modelId directly or MODEL_ID to env')
response = las_client.create_prediction(
document_id=document_id,
model_id=model_id,
max_pages=event.get('maxPages', 1),
auto_rotate=event.get('autoRotate', False),
)
return response
if __name__ == '__main__':
las_client = Client()
transition_id = os.environ['TRANSITION_ID']
execution_id = os.environ['EXECUTION_ID']
logging.info(f'Execute {execution_id} of transition {transition_id}')
try:
execution = las_client.get_transition_execution(transition_id, execution_id=execution_id)
event = execution['input']
logging.info(f'event: {event}')
output = handler(las_client, event, environ=os.environ)
las_client.update_transition_execution(
transition_id=transition_id,
execution_id=execution_id,
status='succeeded',
output=output,
)
'documentId': response['documentId'],
}
if model_id:
content['modelId'] = model_id
response = client.execute_workflow(workflow_id, content)
logging.info(f'{json.dumps(response, indent=2)}')
if __name__ == '__main__':
parser = ArgumentParser()
parser.add_argument('document')
parser.add_argument('--workflow-id')
parser.add_argument('--model-id')
parser.add_argument('--content-type', default='application/pdf')
parser.add_argument('--profile')
args = parser.parse_args()
if args.profile:
credentials = Credentials(*read_from_file(section=args.profile))
client = Client(credentials)
else:
client = Client()
main(client=client,
workflow_id=args.workflow_id,
document_path=args.document,
content_type=args.content_type,
model_id=args.model_id)