Hi @ShamenParis , your suggestions mostly make sense, but unfortunately, I'm still struggling with the same issue. I updated the `ingestion_type` in both the {source}_schemas.py and the _generated_{source}_python_source.py files. Below are my attempts based on your suggestions:

1. Trigger a Full Refresh:
   • No difference
   • It's still showing up with the old `ingestion_type`
2. Use Editable Install:
   • ModuleNotFoundError: No module named 'databricks.labs.community_connector.pipeline'
   • Added `-e ` prior to my current dependencies but got above ERROR
3. Develop Interactively (Best for Live Testing):
   • This one doesn't make too much sense to me..
   • Even after running the commands, I'm not sure how a notebook connected to all-purpose compute is supposed to run the Lakeflow Connect pipeline logic.

Out of all these options, the 2nd one seems like it holds the most promise.. but I'm not sure how to get past the No module error.