April 2025

2025.4.29

Fix: Tweak the calculation of Deep Structure Stability in the SQS report for more consistent scores.
Feature: Added new task for running the full sample-to-dataset pipeline.
Feature: Adds support for users to provide their own test holdout dataset for safe synthetic data evaluation.
Feature: Adds support for subcategory type sampling columns to the magic interface.
Feature: Train and holdout dataset splits are now accessible as CSV outputs.
Fix: Add display_name as an additional field to v2 report headers.
Feature: Addition of data_designer_object.info.model_suite to display info of model suite selected for the current data designer object
Fix: Model configs provided are now also validated upon calling data_designer_ojbect.validate()
Fix: In cases when a person object has phone_number = None, None will be a NoneType rather than a string, consistent with how we treat email_address.
Feature: A new "reasoning" model alias is now available for use within each model suite in data designer.
Fix: Fixes a bug with the TextFT task config not picking up certain generation parameters
Feature: Add configuration option to specify entity list for use in Transform NER functions.
Fix: Format change to evaluation report.
Task: Enforce a minimum of 200 input records or 10 holdout records for performing the holdout step in Workflows.
Fix: Fixes bug where int holdout values greater than 1 would be cast to floats, causing holdout sampling to fail.
Fix: Fixes two small typing related bugs in report column view and AIA calculations.
Fix: Fixes a bad call on a default empty dictionary in the dataset designer report calculations.

2025.4.21

Task: Fully wires in support for Transform sections of Multimodal report. Also updates the safe synthetics evaluate task to detect if transform and/or synthesis tasks were run in the workflow.
Feature: Add optional Transform rule "description" field.
Fix: Fixes an issue with the format for writing a report file in the client
Feature: Adds a status field to the workflow run object
Fix: Fix transform progress log off-by-one error

2025.4.16

Feature: Free-tier users will now be given a one time allocation of 50 credits.
Feature: Can now properly edit sampling configurations when using magic.add_sampling_column
Feature: For the US locale, you can now filter on state.
Bugfix: Support pandas Int64 and numpy bool_ dtypes for input columns for TabularFT
Feature: New validate method on the DataDesigner object, which performs a task-level validation (by attempting to build the workflow) and a wholistic semantic validation of all the column definitions.
Task: This changes the error messages users see, but not fundamentally a new feature or something that operates differently.
Fix: Reduce the of assistant-like responses for the apache-2.0 suite.
Fix: Expression columns now appear in the table when you call display_sample_record.
Feature: Introduces designer.magic.refine_prompt, a tool for quickly iterating on LLM generation column prompt templates. Vary an existing prompt while keeping its intent with designer.magic.refine_prompt("my_column"). Instruct a specific change to the prompt with deisgner.magic.refine_prompt("my_column", "Ensure that the outputs are in Old English.").
Task: Updates the multimodal report to show more relevant v2 workflow identifier info in the overview section.
Fix: The error message for workflow step failure has been better standardized.
Feature: Adds designer.magic.extend_columns(name, n) which can be used to increase the number of possible sampling values for a category.
Fix: Fixes an issue with hybrid workflows not properly authenticating
Fix: Remove experimental warnings from magic.refine_prompt and magic.extend_category.
Fix: Minor update to how generation summaries are logged to the user with verbose_logging=True in AIDD.
Feature: Release note: Update AIDD apache-2.0 suite to use newer models
Fix: Magic llm columns now show up in aidd repr and display_sample_record.
Fix: Fix for crashing bug preventing structured data references in Jinja templates for generated structured columns in Data Designer.
Task: Renames the evaluate_dd_dataset task to evaluate_data_designer_dataset. Addresses serialization issues/requirements.
Fix: Word-wraps REPR HTML displays to make notebook display of Data Designer columns more legible.

2025.4.9

Fix: Change behavior of magic.add_sampling_column and magic.add_column to update existing columns (where possible) rather than raising an error.
Fix: Improve error and status reporting for DataDesigner magic operations.
Fix: Fix Text Metrics Failure for Multi-Metrics Report.
Fix: Improve error reporting for Jinja specification errors when using DataDesigner.
Fix: Any code language can now be specified for LLM generation columns in DataDesigner.
Feature: Rename task from evaluate_ss_dataset to evaluate_safe_synthetics_dataset.
Fix: Address an issue with jobs failing due to heartbeat issues.
Feature: Add support for the following Jinja filters when writing expressions or prompt templates: abs, capitalize, first, float, int, items, last, length, list, lower, max, min, random, replace, reverse, round, sort, string, title, trim, truncate, unique, urlencode.
Fix: Fix a bug in which workflows fail validation when globals are not provided.
Fix: Fix for null values when attempting to reference LLM-generated structured data fields with ExpressionColumn.
Feature: An error will now be thrown if the user tries to add a column with the same name as a latent person sampler.
Feature: Person samplers now have an optional age_range argument, which defaults to adult ages.
Fix: Fix a bug that crashed Data Designer jobs when sequence of Structured Output -> Expression -> Expression/LLMPrompt existed in the workflow.

2025.4.3-3

Fix: Internal config updates.

2025.4.3-2

Fix: Internal config updates.

2025.4.3-1

Fix: Internal config updates.

2025.4.3

Feature: Two new samplers have been added to AI Data Designer: Bernoulli Exponential and Bernoulli X (where X is any Scipy distribution).
Feature: ModelAlias.NATURAL_LANGUAGE has been renamed to ModelAlias.TEXT.
Feature: The AI Data Designer object __repr__ method now includes all column types.
Feature: Enable stop-params in Default TabFT Config for improved inference efficiency.
Fix: AIDD requirements update in gretel-client.
Fix: Fix a regression with use_structured_generation.
Fix: Support downloading CSV version of dataset task outputs.
Fix: Fix a warning when importing the gretel_client in Python 3.12.
Fix: Correct unicode handling for parsed outputs in Magic and Structured column generation.
Fix: Bernoulli and BernoulliMixture will now work client side. This required a bug fix in a helper function.
Fix: Update the print displays of column configurations when using magic to be copy-pasteable to facilitate easier editing.
Fix: Fix a bug where pre-existing seed dataset columns would be dropped from the DataDesigner object after DataDesigner.magic.add_sampling_columns was used.
Fix: Remove extraneous enum warnings from DataDesigner preview operations.
Fix: Fix a bug where the DataDesigner's model_suite wasn't being respected when using magic to add LLM generation columns.

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2025.4.29

Fix: Tweak the calculation of Deep Structure Stability in the SQS report for more consistent scores.

Feature: Added new task for running the full sample-to-dataset pipeline.

Feature: Adds support for users to provide their own test holdout dataset for safe synthetic data evaluation.

Feature: Adds support for subcategory type sampling columns to the magic interface.

Feature: Train and holdout dataset splits are now accessible as CSV outputs.

Fix: Add display_name as an additional field to v2 report headers.

Feature: Addition of data_designer_object.info.model_suite to display info of model suite selected for the current data designer object

Fix: Model configs provided are now also validated upon calling data_designer_ojbect.validate()

Fix: In cases when a person object has phone_number = None, None will be a NoneType rather than a string, consistent with how we treat email_address.

Feature: A new "reasoning" model alias is now available for use within each model suite in data designer.

Fix: Fixes a bug with the TextFT task config not picking up certain generation parameters

Feature: Add configuration option to specify entity list for use in Transform NER functions.

Fix: Format change to evaluation report.

Task: Enforce a minimum of 200 input records or 10 holdout records for performing the holdout step in Workflows.

Fix: Fixes bug where int holdout values greater than 1 would be cast to floats, causing holdout sampling to fail.

Fix: Fixes two small typing related bugs in report column view and AIA calculations.

Fix: Fixes a bad call on a default empty dictionary in the dataset designer report calculations.

2025.4.21

Task: Fully wires in support for Transform sections of Multimodal report. Also updates the safe synthetics evaluate task to detect if transform and/or synthesis tasks were run in the workflow.

Feature: Add optional Transform rule "description" field.

Fix: Fixes an issue with the format for writing a report file in the client

Feature: Adds a status field to the workflow run object

Fix: Fix transform progress log off-by-one error

2025.4.16

Feature: Free-tier users will now be given a one time allocation of 50 credits.

Feature: Can now properly edit sampling configurations when using magic.add_sampling_column

Feature: For the US locale, you can now filter on state.

Bugfix: Support pandas Int64 and numpy bool_ dtypes for input columns for TabularFT

Feature: New validate method on the DataDesigner object, which performs a task-level validation (by attempting to build the workflow) and a wholistic semantic validation of all the column definitions.

Task: This changes the error messages users see, but not fundamentally a new feature or something that operates differently.

Fix: Reduce the of assistant-like responses for the apache-2.0 suite.

Fix: Expression columns now appear in the table when you call display_sample_record.

Feature: Introduces designer.magic.refine_prompt, a tool for quickly iterating on LLM generation column prompt templates. Vary an existing prompt while keeping its intent with designer.magic.refine_prompt("my_column"). Instruct a specific change to the prompt with deisgner.magic.refine_prompt("my_column", "Ensure that the outputs are in Old English.").

Task: Updates the multimodal report to show more relevant v2 workflow identifier info in the overview section.

Fix: The error message for workflow step failure has been better standardized.

Feature: Adds designer.magic.extend_columns(name, n) which can be used to increase the number of possible sampling values for a category.

Fix: Fixes an issue with hybrid workflows not properly authenticating

Fix: Remove experimental warnings from magic.refine_prompt and magic.extend_category.

Fix: Minor update to how generation summaries are logged to the user with verbose_logging=True in AIDD.

Feature: Release note: Update AIDD apache-2.0 suite to use newer models

Fix: Magic llm columns now show up in aidd repr and display_sample_record.

Fix: Fix for crashing bug preventing structured data references in Jinja templates for generated structured columns in Data Designer.

Task: Renames the evaluate_dd_dataset task to evaluate_data_designer_dataset. Addresses serialization issues/requirements.

Fix: Word-wraps REPR HTML displays to make notebook display of Data Designer columns more legible.

2025.4.9

Fix: Change behavior of magic.add_sampling_column and magic.add_column to update existing columns (where possible) rather than raising an error.

Fix: Improve error and status reporting for DataDesigner magic operations.

Fix: Fix Text Metrics Failure for Multi-Metrics Report.

Fix: Improve error reporting for Jinja specification errors when using DataDesigner.

Fix: Any code language can now be specified for LLM generation columns in DataDesigner.

Feature: Rename task from evaluate_ss_dataset to evaluate_safe_synthetics_dataset.

Fix: Address an issue with jobs failing due to heartbeat issues.

Feature: Add support for the following Jinja filters when writing expressions or prompt templates: abs, capitalize, first, float, int, items, last, length, list, lower, max, min, random, replace, reverse, round, sort, string, title, trim, truncate, unique, urlencode.

Fix: Fix a bug in which workflows fail validation when globals are not provided.

Fix: Fix for null values when attempting to reference LLM-generated structured data fields with ExpressionColumn.

Feature: An error will now be thrown if the user tries to add a column with the same name as a latent person sampler.

Feature: Person samplers now have an optional age_range argument, which defaults to adult ages.

Fix: Fix a bug that crashed Data Designer jobs when sequence of Structured Output -> Expression -> Expression/LLMPrompt existed in the workflow.

2025.4.3

Feature: Two new samplers have been added to AI Data Designer: Bernoulli Exponential and Bernoulli X (where X is any Scipy distribution).

Feature: ModelAlias.NATURAL_LANGUAGE has been renamed to ModelAlias.TEXT.

Feature: The AI Data Designer object __repr__ method now includes all column types.

Feature: Enable stop-params in Default TabFT Config for improved inference efficiency.

Fix: AIDD requirements update in gretel-client.

Fix: Fix a regression with use_structured_generation.

Fix: Support downloading CSV version of dataset task outputs.

Fix: Fix a warning when importing the gretel_client in Python 3.12.

Fix: Correct unicode handling for parsed outputs in Magic and Structured column generation.

Fix: Bernoulli and BernoulliMixture will now work client side. This required a bug fix in a helper function.

Fix: Update the print displays of column configurations when using magic to be copy-pasteable to facilitate easier editing.

Fix: Fix a bug where pre-existing seed dataset columns would be dropped from the DataDesigner object after DataDesigner.magic.add_sampling_columns was used.

Fix: Remove extraneous enum warnings from DataDesigner preview operations.

Fix: Fix a bug where the DataDesigner's model_suite wasn't being respected when using magic to add LLM generation columns.