Hello everyone,
I’m currently working with the Message Filtering Extension and would really appreciate some clarification around its performance and operational constraints. While the extension is extremely powerful and useful, I’ve found that some important details are either unclear or not well covered in the available documentation.
There are two main areas I’m trying to understand better:
- Machine learning model constraints within the extension
In our case, we already have an existing ML model that classifies messages (and are not dependant on Apple's built-in models). We’re evaluating whether and how it can be used inside the extension.
Specifically, I’m trying to understand:
- Are there documented limits on the size of an ML model (e.g., maximum bundle size or model file size in MB)?
- What are the memory constraints for a model once loaded into memory by the extension?
- Under what conditions would the system terminate or “kick out” the extension due to memory or performance pressure?
- Message processing timeouts and execution constraints
- What is the timeout for processing a single received message?
- At what point will the OS stop waiting for the extension’s response and allow the message by default (for example, if the extension does not respond in time)?
Any guidance, official references, or practical experience from Apple engineers or other developers would be greatly appreciated.
Thanks in advance for your help,