jevreel

What it is

A zero-embedding approach to video intelligence, using Jev.

What the README says it does

• Your question, not a fixed notion of "similar". An embedding index decides at index time what
• Every second, cheaply. Jev charges for input tokens only, and output is free. A contact sheet
• Questions are nearly free, so ask many. Lenses add your own typed questions to every minute
• The expensive model only sees what passed. Your agent gets the few moments that matter, as
• Typed answers, not just rankings. Yes/no with the second it happens, one of your options, or a

From the project’s README.

Getting started

From the README:

uv tool install "jevreel[all]"
export TYPESAFE_API_KEY=...
jevreel index talk.mp4                       # prints the video id
jevreel ask talk "a slide with a bar chart"  # id, id prefix, path or title all work

Where the decision sits

jevreel calls the hosted decision API rather than running its own weights. That keeps the project small and means its behaviour moves whenever the vendor ships a new model version. It also means an API key and a network round trip sit in the path of every decision.

Models it references: Jev, jev.

How active it is

Created 2026-10-15, last pushed 2026-10-29, 51 stars and 5 forks when we read it on 2026-11-02. Everything in this category is weeks old at most, so a stale push date means something different here than it would on a mature project. Check the repository before you depend on it.