Something which I can query later - Like when brainstorming with Claude "I wanna make some videos of the Luxury rooms in the lodge" and it knows what all videos could help here (going through the files).
There's also a folder root level files that aggregates the text descriptions to make it easier to find.
I've just attached an image in the blog showing an example - https://blog.simbastack.com/_media/gvcycx2n.png
2) No - nothing from DaVinci Resolve. Framedex is a standalone pipeline. Resolve isn't involved.
Faces come from insightface (the open-source buffalo_l pack - RetinaFace for detection), running locally on CPU. For each clip it detects faces in the sampled frames, embeds them, and writes rows to ~/.framedex/faces.db.
Tbh, this part I know it's building up in my local DB but I haven't tested how good is it. Will check them out properly soon.
But yeah, on your broader point that's why framedex deliberately does not ask the LLM to handle faces or locations.
----
Faces → insightface / ArcFace embeddings. Deterministic, comparable across clips. The vision model only contributes a rough people_count; it never tries to identify anyone.
Locations → EXIF GPS via exiftool, reverse-geocoded through Nominatim/OpenStreetMap. Hard metadata, not a guess.
The LLM only does what it's good at: scene description, mood, shot type, keywords, keep/review/cull rating (this last part is also debatable though).