Document Automation v.32 release
- 最終更新日2024/07/22
Document Automation v.32 release
Review what's new and changed, and the fixes and limitations in Document Automation for the v.32 release.
Document Automation
| What's new |
|---|
| Manage
validation feedback using lock - unlock feedback
feature You can now lock the validation feedback for a learning instance using the Lock - Unlock feedback feature. With this feature enabled, you cannot provide any further validation feedback to respective learning instance. 注: You can use this feature only when the Improve
accuracy using validation option is
enabled. |
| Document Automation
Cloud capabilities for On-Premises deployment You can now
leverage Cloud capabilities for Automation 360
On-Premises deployment. With this feature,
you can use the following features for On-Premises deployment:
Enable generative AI and other external connections to Document Automation |
| Improved user
experience through multi-table support in a learning
instance As a Document Automation user, you can now create multiple custom tables in a learning instance. With this feature, you can add custom tables while creating and editing a learning instance for all document types. Create a learning instance in Document Automation | 非構造化ドキュメント向けの generative AI を備えたラーニングインスタンスを作成する |
| Data extraction enhancement with
GenAI for table fields We have extended data
extraction with GenAI support for table fields as well. This
capability can be availed for unstructured and
semi-structured documents from this release. You can extract
table data efficiently using simple natural language
queries, making document processing faster and more
accurate. 注: This feature is
available on Cloud and On-Premises. |
| Bring your own license (BYOL)
support for MS OpenAI We offer the BYOL option to our users to allow them to retain access and control of their data by using their own account while continuing to use the features and capability of Document Automation. When you use the action in a Task Bot, you can extract data from documents by using Google Document AI or MS OpenAI services. You already have the option to use your own license key when using the Google Document AI services. From this release, we bring you the option to use your own license and credentials for using MS OpenAI services. For MS OpenAI services, you would provide the Endpoint URLs and the Service accounts for the GPT and Embedding models, for connecting to Document Automation. [データの抽出] action | Document Automation - generative AI を使用したデータ抽出 |
| What's changed |
|---|
| Korean languages support for Standard Forms We now support Korean language along with associated locale for the Standard Forms. This enhancement enables you to process the documents and extract data in Korean language. |
| Fixes |
|---|
| You can now use
multiple field rules to replace characters that appear more than
once in a string. Previously, only the last field rule was applied. Service Cloud Case ID: 02124562 |
| You can now create a Standard Forms model and use the same model to create a learning instance when the instance is set up with proxy. |
| On the Learning instances page, the Google Document AI provider icon is now visible for Google CDE learning instances. |
| When a user applies a formula validation across multiple columns in table to validate a value at form field level (Example, Sub Total) and if the user deletes one or more rows and resets the value of form field to match with the present rows, the validation error no longer exists. Also, no error message is displayed. |
| With improved table extraction for Google OCR, user can no longer view the extra symbol after extraction and the document is now extracted correctly. |
| When you extract a
document that contains table data, the data is extracted
correctly with enhanced table extraction. Previously, in such cases, users were facing table data extraction issue. |
| When a user connects and processes a document with IQ Bot learning instance that contains non-English characters in document type (such as Arabic and Chinese characters) and is connected to Document Automation, the license consumption is now tracked in the for such connected learning instances. |
| When a user deletes a parser from Parser configuration page and if a user creates a learning instance later, the Document type drop-down no longer shows the domain associated with the deleted parser. |
| When you configure a
parser and select the Japanese language,
the Locale field shows the associated and
correct locale (Japanese (Japan)) value.
Previously, in such cases, the Locale field showed the English (United States) value. |
| As per the
required use case, users can now move the field rules up and
down while creating a learning instance, and change the field
rule order successfully. Service Cloud Case ID: 01996145 |
| With improved logic for
the Update document data
action, users can now view all the table data
provided through multiple rows in the input JSON file. It is
applicable to DocumentJson and
DictionaryType document data
inputs. Previously, in such cases, data only from the first row was populated in the table. |
| The text within the
buttons no longer appear compressed in Community Edition. Also, the text padding is now
consistent for all the buttons. Previously, compressed appearance and inconsistent text padding led to bad user experience. |
| The SIR generation no
longer changes after every feedback and you now get the
consistent extraction results. Service Cloud Case ID: 02107121 |
| When you create two
parsers with the same Provider and
Document type but with different
languages, you can now delete both the (first and second)
parsers. Previously, you were unable to delete parsers in such a scenario. |
| Limitations |
|---|
| When user processes a document to a learning instance that is imported into Document Automation using IQ Bot - DA Bridge package from classic IQ Bot, the extraction fails if the classic learning instance is created with check box fields and the Improve accuracy using validation option is enabled. |
| When user processes a document on custom process learning instance, the validate document count is not updated post extraction. Also, if user submits the document, the validate document count is updated with the negative value. |
| When you process a document with a learning instance that contains multi-tables, the validation feedback does not work for any of the multi-tables. |
| For bridged learning instances, if
training is not provided in IQ Bot or table column headings are
not mapped to column fields in Document Automation correctly,
the validation feedback is not working for default or custom
table fields. Workaround: To fix this issue, perform
one of the following steps:
|
| When using Control Room version .31 or earlier with the Document Automation
package version .32, the extraction might fail
with newly created learning Instances. Workaround: To
process the documents without errors, perform the following
steps:
|
| Limitations from previous releases |
|---|
|
When you process a document using Google CDE with bring your own key (BYOK) setup and the corresponding processor is using foundational model, the document processing fails due to transformational failure. Workaround: To fix this issue, use the custom model instead of foundational model in Google console. |
|
For a public process, you might encounter an error message in
the following scenarios:
注: No error message is
displayed for the private process. |
| No error message is displayed to an user when the IQ Bot learning instance has already been bridged by another user. |
| When you process a document and if
it is sent to the validator, you might encounter an issue with
decimal numbers (such as .78, .99) for the number data
type. Workaround: To fix this issue, you must enter the decimal numbers as 0.78 or 0.99. |