I’m expecting Apple to introduce their own local LLM model and API built into MacOS and iOS within the next two years. From the rumors I’ve read, I don’t think it’ll make it in time for this year’s WWDC (but you never know). I’m guessing at that point it’ll be good enough for Devon Technologies, but who knows. (IMO, small models will get there but I’m unsure when due to the amount of resources required to properly train small models.)
I’ve used DevonThink off and on for over a decade. I find that I like the idea of note taking and storing items more than my ability to actually do those tasks as part of my workflow. Being able to query data via an LLM does make me lean more towards using those. I just moved to Bear from Obsidian due to my brain liking the old Notational Velocity method of note taking and searching vs the links/backlinks/etc method. Obsidian does have a lot of nice power features, but it also has more of an overhead than I want to deal with.
I haven’t looked into what DT provides scripting/plugin wise. I just made a todo for me to look into that and seeing what it’d take to pull the data into a vector database. I’m guessing if we want this anytime soon someone will need to implement something to regularly go through devonthink and make it easy to use with a LLM. If I end up doing this, it’ll most likely be something with RayCast.