Configure the web application

Caution: Document AI Warehouse is deprecated and will no longer be available on Google Cloud after January 16, 2025. To safeguard your data, migrate any documents currently saved in Document AI Warehouse to an alternative like Cloud Storage. Verify that your data migration is completed before the discontinuation date to prevent any data loss. See Deprecations for details.

Preview

This feature is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the Service Specific Terms. Pre-GA features are available "as is" and might have limited support. For more information, see the launch stage descriptions.

Before you begin

1. You need to be the administrator of your project to configure the web application.

2. Follow the quick start guide to set up necessary APIs, grant permissions, and provision the instances for your project.

3. To get access to the web application, complete the following form.

Configure the project with Google Cloud console

1. In the Document AI Warehouse settings view, which is the final view after provisioning, click Show Details.

   

2. Go to the third step. Select Yes.

   1. If your project is provisioned with the document-level access control mode, you need to create a service account and key:

      1. Click Create to create a service account.

         

      2. After the service account is created, click Create to create a service account key.

         

      3. You can click the download button to save the key credentials. Then click Grant to grant your account and the service account the Content Warehouse Admin role.

         

      4. Click Save Config to save the config.

         

   2. If your project uses the universal access mode, directly click Save Config:

      

3. After the config is saved, then go to the last step to open the link.

   

4. In the opened window, be sure to log in.

   

5. Give Document AI Warehouse access to your Google Cloud data by checking the first checkbox.

   

6. If you're getting CODE 400 (invalid argument) or 401 (insufficient authentication scopes), log out by clicking on the user section at the top right, and log in again to be sure you have OAuth permissions.

   

7. If you cannot open the project as expected, refresh the page after 3 to 5 minutes. The saved configuration takes time to propagate.

   

Set up project-level access controls

Note: Document AI Warehouse users and groups are authenticated by Cloud Identity. All Document AI Warehouse users and groups must be in Cloud Identity. IAM supports synchronizing users and groups from customer's LDAP and Active Directory. For more information, see Federating Google Cloud with Active Directory.

Grant project-level access controls (ACLs) to users. There are four Document AI Warehouse roles, including Document Creator, Document Viewer, Document Editor, and Document Admin. The following information about the roles is important:

• The Document Creator role is typically granted to all users, which lets the users create documents.

  • We recommend that you assign this role to a group of users, such as Doc Owners, who are expected to create documents in Document AI Warehouse and manage the group.
  • The creator is automatically granted the document-level Document Admin role on documents they create by default.

• The Document Viewer, Document Editor, and Document Admin roles must be used with caution and granted only to select administrators. It is recommended to grant operators temporarily for cleanup or audit needs. As with these roles, the users have permissions to view, edit, share, or delete all documents in the project.

• Document level ACLs can be granted later by Document Admin of each document.

Note: Be sure to grant your account the project-level Document Admin access in the Access tab.

Configure schemas

Configure the schema for documents and folders. A document schema is used to define the document structure in Document AI Warehouse. For more information about document schemas, see Manage document schemas.

(Optional) Process documents using Document AI

Customers can map the Document AI processors to the Document AI Warehouse schema, and use Document AI processors to extract text and data. By doing so, when documents are uploaded with specific Document AI Warehouse schema, Document AI Warehouse uses the corresponding Document AI processor to extract the document properties based on the mapping. For this to work, here are the requirements and recommendations:

• This requires the Document AI processors in the same project.

• To make uploaded documents full-text-searchable, we recommend using the Document AI OCR processor for PDF doc-types that don't have specialized processors. They are then full-text searchable in Document AI Warehouse.

• Multiple processors can be mapped to a schema, the user can specify which processor to use for extraction when uploading documents.

  

• The throughput quota for Document AI processors is lower (around 10 qps). Therefore, the batch pipelines or multiple concurrent user upload scenarios run slower than typical ingests throughput that is supported by Document AI Warehouse Create API.

• If you need to use custom models for classification and extraction, convert the extracted data into a Document AI Warehouse API JSON format and ingest the data using the Create API.

  

Troubleshooting

• For non-admin users to access to the Document AI Warehouse web application, ask your admin to add you to the allowlist group.

• If you see messages like "you do not have access to Partner Dash", follow this step to resolve the issue.

Next steps

For more information, learn how to upload documents.