DescribeSong

Describe a song in plain words — instruments, mood, tempo, era, where you heard it — and get its name.

A community index of how songs sound. Nobody uploads audio: your browser reads your files, identifies each one by acoustic fingerprint (AcoustID + MusicBrainz), and boils it down to a 2 KB vector (LAION CLAP, run in the browser with WebGPU). Only the vector and the artist / title / album text are sent. Searching turns your sentence into the same kind of vector and ranks every stored song against it.

What the server stores, and what it never stores: web/legal.html.

Layout

• web/ — the site. app.js (search + folder scan), worker.js (Chromaprint via WASM + CLAP via transformers.js), tones.js (the two-tone technicolor palette), water.js (a port of hyprwater), wasm/ (the fingerprinter).
• server/ — FastAPI. SQLite, a brute-force vector index in RAM, the CLAP text tower on ONNX Runtime (CPU). Runs on a Raspberry Pi.
• fingerprint-wasm/ — Chromaprint (rusty-chromaprint) compiled to WebAssembly.
• deploy/ — the Pi install script and systemd unit.
• QUEUE.md — the working log: every decision, measurement and landmine, in order.

Run it

cd server && python -m venv .venv && .venv/bin/pip install -r requirements.txt
VIBEFIND_DATA=../data ACOUSTID_KEY=<your key from acoustid.org/new-application> .venv/bin/python -m uvicorn app:app --port 8080

Open http://localhost:8080. The text model (~240 MB) downloads on the first search; the browser downloads the audio model (~143 MB) on the first scan.

On a Raspberry Pi: deploy/pi-install.sh, then the unit in deploy/describesong.service.

Licences

• Code: AGPL-3.0. If you run a modified copy as a service, you must offer its source to your users.
• The database of vectors and labels: ODbL — use it for anything, share improvements to the database itself alike.
• Model weights: LAION CLAP (CC0). Fingerprints: Chromaprint (LGPL) via rusty-chromaprint.