Pot să vibecodez Shade?

Ce construiești

Walk my drives, pull keyframes and transcripts, embed both with CLIP and whisper into a local vector index, then search the whole library in plain English.

ce îți trebuie

• ffmpeg
• a CLIP model via transformers.js or Python
• whisper.cpp
• sqlite-vec or another local vector store
• a GPU, or patience measured in nights

Semantic search over your own footage is the strongest DIY case in post right now · the collaboration wrapper is what you are actually renting.

Promptul

Un weekend cu un agent de coding. Golurile care rămân sunt mai jos, la „ce pierzi”.

Build me a semantic search engine for my own footage to replace Shade. Requirements:

- A Python CLI plus a small FastAPI web UI on localhost. SQLite with sqlite-vec for
  the vectors and the metadata, one file at ~/FootageIndex/index.db.
- `index <folder>` walks the tree, and for every video ffmpeg pulls a keyframe every
  5 seconds plus one at each scene cut detected by the ffmpeg scene filter.
- Each keyframe is embedded with open_clip (ViT-B/32) and stored with its timestamp.
  Stills and photos get the same treatment as a single frame.
- Audio goes through whisper.cpp for a transcript with word timestamps, chunked into
  30-second windows and embedded with sentence-transformers for text search.
- The search box takes a plain sentence and searches image and transcript vectors
  together, returning ranked results as thumbnail, filename, and timecode. Clicking
  one opens the clip at that exact frame in a player.
- Indexing is incremental and resumable, keyed on file path plus mtime plus size, and
  prints a running count so an overnight run is checkable in the morning.
- Everything runs on my machine, models included · no accounts, no cloud, no
  telemetry, no API keys. Files are read only, never moved or renamed.
- Out of scope: face recognition, sharing links, review and comments, and team sync.
  Do not build auth or a server deployment, this is a single-user local tool.
- README: installing ffmpeg and whisper.cpp, first-run model downloads, an honest
  estimate of indexing hours per TB on CPU versus GPU, and how to reset the index.

Ce pierzi

• cloud streaming of full-res files without downloading them first
• guest links with per-link permissions and roles
• built-in review, approval, and commenting
• face recognition and shot-type tagging that improves without your involvement
• team sync, so everyone searches the same index
• the NLE plugins and Slack integration

De ce se plătește în continuare

They pay because the search only matters if the whole team gets it. A local index that only lives on the editor's machine solves the editor's problem and nobody else's, and the person who most needs to find the clip is usually the one furthest from the storage. Shade sells the index plus the delivery of what the index found, and the second half is the expensive one.

moat: Colaborare Scara infrastructurii Modele proprietare ce e un moat

cloud streaming/collaboration/model pipeline

Alternative gratuite

N-ai chef să ți-o construiești? Astea există deja, sunt gratuite sau open source, și le-am verificat una câte una.

Cine l-a construit deja

Să pornești de aici e tot vibecoding: promptul e pentru când o vrei exact în felul tău.

• Immich (se deschide într-o filă nouă) — Self-hosted photo and video library with CLIP semantic search and face recognition already built in. The closest working proof the search half is solved. (alive)
• PhotoPrism (se deschide într-o filă nouă) — Self-hosted AI-tagged media library with local indexing and search. Photo-first, but the same pattern. (alive)

Cât costă într-un an

Ești de acord?

Aplicații similare

Iconik 65 $ NU CHIAR Frame.io 25 $ CAM AȘA Descript 24 $ CAM AȘA