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Or is there a way to force a set of users into a certain variation within an experiment based on an attribute? Seems like you can only do this separately with a force rule.

Hi Shayla. @freezing-postman-69602 may be able to help you with the SDK question

@fresh-football-47124 Thanks so much! @freezing-postman-69602 Are you able to answer my question by any chance?

are you using the latest sdk? if yes, you should get the ruleId when you do,

evalFeature('feature_name').ruleId

Which version is the current version? We are on

1.1.0

@freezing-postman-69602

1.2.1

is the latest

@freezing-postman-69602 Is there any documentation that shows the changes from 1.1.0 to 1.2.1?

We're as of now, working on updating the docs. The most significant changes include, growthbook_client, that lets you use the same growthbook instance with various attributes targeting at the time of feature evaluation with enhanced thread safety and performance. Alternatively, you can see the changelog tagged in the release.