# MeetRec for Android

Native Android app with the same functionality as the desktop meetrec:
record meetings and transcribe them on-device with Whisper. Nothing leaves
the phone — no cloud, no telemetry.

Status: **M0 (engine proof)** — the app can download a GGML model, load it
via JNI (whisper.cpp, CPU/NEON) and transcribe a picked WAV file. Recording,
live transcript, and output files arrive in later milestones (see the
milestone plan in the project docs).

## Requirements

- Android Studio (or: SDK Platform 36, Build Tools 36, NDK 27.1, CMake 3.22.1)
- JDK 17+
- Device running Android 10+ (developed against a Fairphone 6 / Snapdragon
  7s Gen 3, Android 15+)

## Build

```sh
cd android
./tools/fetch-whisper.sh     # vendors whisper.cpp v1.9.3 into third_party/
./gradlew :app:assembleDebug # or open the android/ folder in Android Studio
adb install -r app/build/outputs/apk/debug/app-debug.apk
```

`third_party/whisper.cpp` is gitignored — the fetch script pins the exact
release tag so the JNI layer never breaks on upstream churn.

## Test on device (M0)

1. Launch **MeetRec**, pick a model (`tiny` is fine for a first test) and tap
   **Download** (model comes from Hugging Face; tiny is ~75 MB).
2. Tap **Load engine**.
3. Tap **Pick WAV file** and choose a 16 kHz mono WAV for best results
   (other PCM WAVs are resampled automatically).
4. Tap **Transcribe** — segments with timestamps appear; share via the
   share sheet.

Expect roughly realtime transcription with `tiny`/`base` on the
Fairphone 6's CPU; `small` is noticeably slower — use it for final passes
only (the live/final split comes with the recorder milestones).

## Performance notes

- The engine runs on CPU via NEON, using up to 4 threads.
- GPU/NPU acceleration (e.g. Snapdragon NPU via the QNN backend) is a
  stretch goal, not wired up yet.

## Module layout

```
app/          Compose UI (model download, WAV picker, transcript view)
core/whisper/ whisper.cpp JNI wrapper: CMake build + LibWhisper.kt +
              WhisperEngine.kt (the on-device transcription API)
tools/        fetch-whisper.sh — vendor the pinned whisper.cpp release
```

Models live in the app's private storage (`filesDir/models`), shared files
with the desktop app's `~/.cache/meetrec/whisper-cpp` naming
(ggml-tiny.bin … ggml-large-v3.bin).