The way that semantic search works, they don't cap a relevance score (since it's all relative), and they don't allow you to sort through some kind of time index either.
Generation is usually fast, but prompt processing is the main limitation with local agents. I also have a 128 GB M4 Max. How is the prompt processing on long prompts? processing the system prompt for Goose always takes quite a while for me. I haven't been able to download the 120B yet, but I'm looking to switch to either that or the GLM-4.5-Air for my main driver.
Frigate has been an overweight nightmare for me to work with. Trying to detect wildlife that are not in their classification models is basically impossible. I've been better off using motion / motioneye for a lightweight and practical approach
Writing to catalogs is still pretty new. Databricks has recently been pushing delta-kernel-rs that DuckDb has a connector set up for, and there’s support for writing via Python with the Polars package through delta-rs. For small-time developers this has been pretty helpful for me and influential in picking delta lake over iceberg.