# Product

Whisper Web — on-device speech-to-text. A browser-first transcription app powered by OpenAI Whisper,
running through [Transformers.js](https://github.com/huggingface/transformers) (`@huggingface/transformers`).
(Moved here from the original `docs/CLAUDE.md` §1.)

## Audience

**Primary: non-technical people** who want Whisper transcription without reading docs or setting up
any ML tooling themselves. **Also: technical people**, who must be able to do what they want and need
with it — the same control they'd have running Whisper on their own device.

What that means for the UI and its copy:
- **Works with zero knowledge.** Defaults are good enough to just drop a file or press record and get a
  transcript. No step should require knowing what a backend, dtype, or quantization is.
- **Plain language first.** Labels, statuses, and errors say what is happening and what to do next in
  everyday words ("Downloading the model (~44 MB, one time)", not "Fetching ONNX weights").
- **Control is there, not in the way.** Technical choices (model size/variant, backend, language, task,
  timestamps, export formats, storage) stay available and honest, but visually secondary — never
  hidden behind a "simple mode" that removes them, and never required.
- **Technical truth on demand.** Where a technical term is the real answer (WebGPU, WASM, model ids),
  show it alongside the plain description rather than replacing it.

## Users and what they get

**Anonymous users (no login) can:**
- Run Whisper models fully in the browser — no audio or transcript leaves the device.
- Choose which Whisper model to use (tiny → large, English-only and multilingual, quantized variants).
- Keep working when the network — or our own server — is offline (installable PWA + cached model weights).
- Accelerate inference with WebNN or WebGPU (auto-selected in that order, D-017; never WebGPU on
  Firefox, D-026), falling back to WASM automatically.
- Transcribe an uploaded audio/video file, or live from the microphone (D-016).
- Export transcripts as `.txt` / `.srt` and manage cached model storage.

**Logged-in users (Passport.js, when `AUTH_ENABLED`) get all of the above, plus:**
- A toggle to choose where inference runs: **their own device** (browser engine) or **the server**
  (server engine).
- The server engine MUST use [faster-whisper](https://github.com/SYSTRAN/faster-whisper) (CTranslate2) —
  not Transformers.js (D-013). faster-whisper cannot run in a browser, so the browser engine stays on
  Transformers.js.

## Product principles (from `docs/Architecture.md` §5)

- **Privacy:** browser-engine audio never touches the network.
- **Anonymous-first:** login only unlocks the server engine; nothing else is gated.
- **Offline-first:** app shell + previously downloaded models work with no network.
- **Honest status:** the UI must not claim a state it isn't in — e.g. "Downloading" vs "Loading model
  from cache" (D-033), no "Listening" before the model is ready (D-034).
- **User-initiated downloads:** selecting a model never downloads it (D-020); large models on mobile
  get a warn/confirm gate (D-027–D-029).

## Out of scope (from `docs/WorkBreakdown.md`)

Arbitrary Hub model ids, OAuth providers, multi-user transcript storage, whisper.cpp server backend,
i18n of the UI.