❖ Constraint Augmented Generation (CAG)

❖ SDV Enterprise bundle. This feature is available for purchase as an SDV Enterprise bundle. For more information, visit our page to Explore SDV.

Constraint Augmented Generation (CAG) is a powerful system that allows you to input business logic into your complex schemas. Fast, easy, and flexible, CAG patterns allow you to create synthetic data that conforms to your logic, 100% of the time.

⭐️ Apply patterns across multiple tables. Add business logic that determines the connections between tables, or the type of data that linked tables are allowed to have.

⭐️ Access complex, powerful algorithms with simple APIs. CAG supports patterns that are more complex, often incorporating different algorithms to get you the data you need. The best part? There's one, simple API to denote your data pattern.

Usage

This functionality is in Beta. At this time, select SDV Enterprise users have been invited to use this feature.

To use CAG, define your CAG pattern and add it to any SDV single or multi-table synthesizer.

from sdv.cag import PrimaryToPrimaryKey

# define your CAG pattern
my_pattern = PrimaryToPrimaryKey(
    table_names=['Accounts', 'Supplemental_Account_Info']
)

# add it to any multi-table synthesizer
synthesizer = HSASynthesizer(metadata)
synthesizer.add_cag(patterns=[my_pattern])

synthesizer.fit(data)
synthetic_data = synthesizer.sample()

<synthesizer>.add_cag

Use this function to add CAG patterns to any single- or multi-table synthesizer that uses AI-generation techniques.

Parameters:

• (required) patterns: A list of CAG pattern objects (explore the CAG patterns below)

Output (None)

synthesizer.add_cag(patterns=[my_pattern1, my_pattern2, ...])

<synthesizer>.get_cag

Get all the CAG pattern objects that are attached to your synthesizer.

Parameters: None

Output: A list of CAG pattern objects that the synthesizer uses, in order of use

patterns = synthesizer.get_cag()

<synthesizer>.get_metadata

Use this function to access the metadata object that you have included for the synthesizer

Parameters

• version: The version of metadata that you are requesting. The metadata may change between before vs. after applying the CAG algorithms

  • (default) 'original': Return the original metadata that you used to instantiate the synthesizer

  • 'modified': Return the metadata that will be created after applying the CAG patterns. If there are CAG patterns present, then it will be different from the original metadata. Otherwise, it will be the same.

Explore CAG Patterns

Pattern Name	Description
❖ CarryOverColumns	The same columns are present in a parent table and a child table, and the values of those columns have to match up according to the connection.
❖ CompositeKey	[Coming soon!] Multiple columns together form a primary key and foreign key connection.
❖ ForeignToPrimaryKeySubset	[Coming soon!] You have a 1-to-many connection between tables, but only certain values are allowed to have connections.
❖ PrimaryToPrimaryKey	You have an exact 1-to-1 connection between the primary keys of two or more tables.
❖ PrimaryToPrimaryKeySubset	You have a 1-to-1 connection between the primary keys of two or more tables but only certain values are allowed to have connections.
❖ UniqueBridgeTable	[Coming soon!] You have a bridge table that records a many-to-many relationship between two other tabes, and the connections have to be unique

FAQs

What is the difference between a CAG pattern and a constraint?

CAG is an entirely new, more powerful system for handling constraints. The older constraint sytem is only able to handle simple logic that happens within a table. Meanwhile, CAG can handle business logic that happens in between multiple tables, and determine better connections between the tables.

In terms of the product API, our team is working to align both the CAG patterns and constraints in future iterations.