Improved the Textual NER model throughput on long strings that contain a large number of detected entities.
Added support to store dataset files in a specified S3 bucket, instead of in the Textual application database.
When Textual replaces first name values, it now attempts to use a name with the same gender.
For the DOB (date of birth) entity type, you can now configure synthesis options. You can set how to shift the date.
You can now configure the entity type handling for a dataset before you upload the dataset files.
You can now provide added and excluded entity values when you use the SDK to redact individual strings and files.
Added a new method to the SDK. redact_xml works similarly to redact_json. To produce a redacted output, you pass in a redact_xml string.
Removed support for en_core_web_trf and en_core_web_lg auxiliary models. Disabled model inference for ORGANIZATION, PERSON, LOCATION, and MONEY entity types. Updated the auxiliary model configuration environmental variables to have new default values:TEXTUAL_AUX_MODEL_GPU: falseTEXTUAL_AUX_MODEL: en_core_web_sm
Fixed a redaction issue that was caused by a regression from v140.
Improved the Textual NER model, specifically for datetime values and and electronic health records.
Fix for correctly re-synthesizing files as part of pipelines
When you call the dataset.add_file method in the Textual SDK, you can now pass in IO bytes.
You can now specify a list of additional values to include for each entity in a datasets. This allows Textual to identify values that it might not identify because they are specific to your organization or industry. The list can contain both specific values and regular expressions.
Improved the file list display for datasets to better accommodate longer file names.
For an uploaded file pipeline, added a Back to Files breadcrumb to return the user to the main file list.
On the dataset details page, the bulk edit function for entity type handling is now a dropdown instead of separate buttons.
You can now use the Python SDK to delete files from a dataset.
To improve performance, enabled date synthesis inference on GPU. Added the environment variable TEXTUAL_DATE_ SYNTH_ GPU to manage whether to use it.
Renamed the following environment variables:
SOLAR_PREFER_GPUtoTEXTUAL_AUX_MODEL_GPUSOLAR_AUX_MODELtoTEXTUAL_AUX_MODEL
