I am trying to run the demo code given in PDF parsing of GCP document AI. To run the code, exporting Google credentials as a command line works fine. The problem comes when the code needs to run in memory and hence no credential files are allowed to be accessed from disk. Is there a way to pass the credentials in the document ai parsing function?
The sample code of Google:
def main(project_id='YOUR_PROJECT_ID',
input_uri='gs://cloud-samples-data/documentai/invoice.pdf'):
"""Process a single document with the Document AI API, including
text extraction and entity extraction."""
client = documentai.DocumentUnderstandingServiceClient()
gcs_source = documentai.types.GcsSource(uri=input_uri)
# mime_type can be application/pdf, image/tiff,
# and image/gif, or application/json
input_config = documentai.types.InputConfig(
gcs_source=gcs_source, mime_type='application/pdf')
# Location can be 'us' or 'eu'
parent = 'projects/{}/locations/us'.format(project_id)
request = documentai.types.ProcessDocumentRequest(
parent=parent,
input_config=input_config)
document = client.process_document(request=request)
# All text extracted from the document
print('Document Text: {}'.format(document.text))
def _get_text(el):
"""Convert text offset indexes into text snippets.
"""
response = ''
# If a text segment spans several lines, it will
# be stored in different text segments.
for segment in el.text_anchor.text_segments:
start_index = segment.start_index
end_index = segment.end_index
response += document.text[start_index:end_index]
return response
for entity in document.entities:
print('Entity type: {}'.format(entity.type))
print('Text: {}'.format(_get_text(entity)))
print('Mention text: {}\n'.format(entity.mention_text))