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Thanks! Yeah that would be pretty cool, but continuous indexing would be pretty expensive now, because the model's in public preview and there are no local alternatives afaik.

This very well might be a reality in a couple years though!

Totally valid concern. Right now the cost ($2.50/hr) and latency make continuous real-time indexing impractical, but that won't always be the case. This is one of the reasons I'd want to see open-weight local models for this, keeps the indexing on your own hardware with no footage leaving your machine. But you're right that the broader trajectory here is worth thinking carefully about.

Show HN: Gemini can now natively embed video, so I built sub-second video search

Gemini Embedding 2 can project raw video directly into a 768-dimensional vector space alongside text. No transcription, no frame captioning, no intermediate text. A query like "green car cutting me off" is directly comparable to a 30-second video clip at the vector level.

I used this to build a CLI that indexes hours of footage into ChromaDB, then searches it with natural language and auto-trims the matching clip. Demo video on the GitHub README.
Indexing costs ~$2.50/hr of footage. Still-frame detection skips idle chunks, so security camera / sentry mode footage is much cheaper.

https://github.com/ssrajadh/sentrysearch

GitHub - ssrajadh/sentrysearch: Semantic search over videos using Gemini Embedding 2.

Semantic search over videos using Gemini Embedding 2. - ssrajadh/sentrysearch

GitHub