Hi all!
I am integrating a custom ML backend with Label Studio to auto-suggest labels during annotation. 
It works well for simple single-label tasks; but when using overlapping labels (multi-label classification); the predictions are inconsistent sometimes only one label shows up / confidence scores are missing entirely. 
I suspect the issue might be with how the backend formats multiple predicted labels or with how Label Studio interprets overlapping annotations from the model. 
I followed the ML backend example, but the docs don’t cover multi-label /overlapping scenarios in depth. Checked Label Studio Documentation — Write your own ML backend with JIRA Course documentation guide for reference.
Has anyone successfully set up a backend that returns multiple predicted regions or tags for the same object/text span? Would love a working example or advice on the right payload format to ensure consistency in pre-labeling.
Thank you !!