Indexing a year of video locally on a 2021 MacBook with Gemma4-31B (50GB swap)

UPDATE: Quickly created a repo for this - https://github.com/Simbastack-hq/framedex (MIT License)

It's not tested properly after I genericized it. Will try to go through it properly and add more updates.

Two big things on my TODO: 1) Make use of this indexing and using Claude's help, make video editing faster with Davinci Resolve (now that I have a good index of all the content)

2) I currently did this for videos, but I want to add more things to this for my thousands of still images of my camera - need to make sense of them. So I'll be working on this as well.

> The skill is open at ~/.claude/skills/video-index/. If you're working on something similar (indexing personal archives, getting a local model to do real archival work, building agents that drive editing tools), I'd be glad to compare notes.

When your Claude wrote this post they might not have selected the right URL to share, unless your home folder is exposed. Care to share the skill files?

Thanks for the article! I have a beefy M5 Pro and I'm eagerly looking around for ways to use local models (specifically Gemma4 & Qwen3.6).

This is an excellent thing to do. Especially that LLMs excel at batching thus you can index multiple photos and videos in parallel for no performance penalty.

I ran Gemma on a 2015 thinkpad to do something similar. Fortunately, I could upgrade the memory otherwise it would have been a painful exercise.

Not gonna lie, llama.cpp had the fans spinning at max speed. But it worked and I got the job done.

> generative AI video has no place on a real travel brand

I am pretty sure that the vast majority of Airbnb hosts would not agree with you.

> equals TripAdvisor crucifixion

I have no idea how the Airbnb hosts with fake listings survive, really.

Two questions:

1. What is the search index?

2. The "description.md" example has things like "faces -> cluster_id". Is this from Davinci Resolve's face index? Things like faces+names and locations are really important with photo collections, but general LLMs don't handle them so well.

Awesome. Say, this is very comprehensive.

I was vaguely aware of all these pieces existing (except for running a facial recognition database at home o_o), but it's really neat to put them all together like that.

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