Document Automation v.40 release

Review what's new and changed, and the fixes and limitations in Document Automation for the v.40 release.

What's new

Update extraction models in 표준 양식 learning instances

You can now change the extraction model for an existing learning instance by copying the learning instance and changing it to the required extraction model. To use a different extraction model, you no longer need to create a new learning instance and manually recreate configurations such as field mappings and validation rules.

Copy a learning instance in 표준 양식

Copy or delete projects in 표준 양식
You can now copy or delete projects when using 표준 양식.
  • Copy a project when you want to preserve the configuration of an existing project. You can use the copied project to update and test the project without affecting the original project.
  • Delete redundant or unused projects.

Copy projects in 표준 양식 | 표준 양식에서 프로젝트 삭제

What's changed

Import and export learning instances using 모델 연결

When you import or export a learning instance, the 모델 연결 configuration is included in the learning instance. When you import a learning instance that was using a 모델 연결, the Include the 생성형 AI 모델 연결 option is introduced on the Import Learning Instances page to review the 모델 연결 option before importing the learning instance.

학습 인스턴스 내보내기 및 가져오기

Enhanced zoom controls when validating documents

Users validating documents can now zoom in on documents up to 500 percent and select specific zoom levels. Users can also continue to use the zoom in and zoom out controls, and the selected zoom level is reflected in the drop-down option.

Automation Co-Pilot 유효성 검사기를 통한 문서 유효성 검사

Fixes

The alignment of IF and THEN conditions in field rules is now displayed correctly.

Previously, these conditions were misaligned.
Correct label is displayed for the Confidence option when the Control Room is set to a language other than English.

Previously, the label was incorrectly displayed in certain languages.
In the Advanced training settings option, the table fields that are not selected for validation feedback are no longer displayed in the Primary Column drop-down.

Previously, such table fields were displayed in the Primary Column drop-down in certain scenarios.
Data extraction will no longer fail when you copy a learning instance that is using a third-party parser configured in Document Automation and process documents using the copied learning instance.

Previously, data extraction failed in such a scenario.
When creating or editing a learning instance, field properties are now retained after changing the data type before entering a label for a field.

Previously, changing the data type reset all configured field properties.

Limitations

When you create and process a document using a learning instance in the private repository, move the associated process to the public repository, and then submit the document from the validator, the Download data automation will fail.
Limitations from previous releases
When you try to check in a process without having the required permissions, the audit log entry for this event will include Source as Control Room instead of Document Workspace and Item name as Unknown instead of <learning-instance-name>.
When you use a regular expression for a table field without defining an alias, the regular expression might not be considered for extracting the data.

Workaround: Define an alias for the table field before using a regular expression.
When you process documents containing multiple tables in 표준 양식, the order of the tables extracted is reversed.
Document extraction will fail with the error “500: Internal Failure , Failed to initialize ABBYY’ when you change the default path (C:/ProgramData/AutomationAnywhere/GlobalCache) of Global Cache Location for your devices.
When you edit and check in a process linked to a public learning instance that is using 클라우드 추출 서비스, the extraction 봇 might not be visible in dependencies, and document processing might fail.
Workaround: Use one of the following options:
  • Update to the v.39 release
  • Use the default process or copy the learning instance to create a new process and then publish the learning instance before processing documents
When you process documents with file names greater than or equal to 75 characters in test mode, you might not see improvements in the reprocessing time for such documents.
If you have disabled the OCR provider in the administrator settings and if you are using a language other than English for your Control Room, you will see an error to enable the OCR provider settings in English in the following scenarios:
  • When you create a learning instance that is using an OCR provider
  • When you change the OCR provider for an existing learning instance
When you use the 문서 분류기 작업 (Classify, Classify documents, and Train Classifier) and Extract Data 작업 in the 문서 추출 패키지 together in a 봇, the 봇 will fail to execute.

Workaround: Ensure that you create separate Bot when using any of the 작업 from the 문서 분류기 패키지 and the Extract Data 작업 of the 문서 추출 패키지. If you need to execute these Bot in a sequence, include these Bot in an Automation Co-Pilot process.
When a user processes a document on a custom process learning instance, the validate document count is not updated post extraction. Also, if the user submits the document, the validate document count is updated with a negative value.
A user with the Automation Co-Pilot administrator permissions is unable to view the Document Automation tasks that are assigned or requested and are in pending or complete status.
When you are using the IQ Bot Pre-processor 패키지 작업 and if the Output folder path contains Japanese characters, you will see an error when processing documents.

Workaround: Create an output folder in a folder path that does not contain any Japanese characters and provide the path in the output folder path field.