This quickstart shows you how to process documents (invoices) from a source Cloud Storage bucket and store the processed document (JSON file) in a target bucket by using the batch processing capability of Document AI API through the SAP BTP edition of ABAP SDK for Google Cloud.
Before you begin
Before you run this quickstart, make sure that you or your administrators have completed the following prerequisites:
You have a Google Cloud account and project.
Billing is enabled for your project. See how to confirm that billing is enabled for your project.
The SAP BTP edition of ABAP SDK for Google Cloud is installed and configured. See how to install and configure the SAP BTP edition of ABAP SDK for Google Cloud.
Authentication to access Google Cloud APIs is set up. See how to set up authentication.
You have access to the SAP BTP, ABAP environment.
You have downloaded and installed the latest ABAP Development Tools (ADT) on the latest Eclipse platform.
You have created an ABAP Cloud Project.
Make sure the Document AI API is enabled in your Google Cloud project.
In the Document AI Workbench, create a processor with type
INVOICE_PROCESSOR
. For more information, see Creating and managing processors.In Cloud Storage, create a source bucket to store the invoices for processing and place the invoices in this bucket. For more information, see Create buckets.
In Cloud Storage, create a target bucket to store the processed files.
Create an ABAP class to process documents
Create a package:
- In ADT, go to the Project Explorer.
- Right-click the package
ZLOCAL
, and select New > ABAP Package. Enter the following details for your package:
- Name: enter
ZABAPSDK_TEST
. - Description: enter
ABAP SDK Test Package
.
- Name: enter
Click Next.
In the Select a Transport Request dialog, select the Create a new request checkbox.
Enter a description for the transport request.
Click Finish.
Create an ABAP class to call the Document AI API:
- Right-click your ABAP package and select New > ABAP Class.
Enter the following details for your ABAP class:
- Name: enter
ZGOOG_CL_QS_DOCUMENT_AI
. - Description: enter
Quick start for Document AI API
.
- Name: enter
Click Next.
Select a transport request and click Finish.
In the code editor, replace the default code with the following code snippet:
Replace the following:
DEMO_DOC_PROCESSING
: the client key name.PROJECT_ID
: the ID of the Google Cloud project that has the Document AI API enabled.LOCATION_ID
: the processor's location.PROCESSOR_ID
: the ID of the processor.SOURCE_BUCKET_URI
: the URI of the Cloud Storage bucket folder where source documents are kept for processing.TARGET_BUCKET_URI
: the URI of the Cloud Storage bucket where the processed document (JSON file) would be stored.
Save and activate the changes.
Run your application:
- Select the ABAP class
ZGOOG_CL_QS_DOCUMENT_AI
. - Click Run > Run As > ABAP Application (Console).
Alternatively, press
F9
.
- Select the ABAP class
To validate the results, follow these steps:
In the Google Cloud console, go to Cloud Storage Buckets page.
Open the target bucket. The processed document is stored in the form of a JSON file.
What's next
- Read the guide Application development with the SAP BTP edition of ABAP SDK for Google Cloud.
- View the code samples.
- Ask your questions and discuss ABAP SDK for Google Cloud with the community on Cloud Forums.