# Voice to Notes

A desktop application that transcribes audio/video recordings with speaker identification, producing editable transcriptions with synchronized audio playback.

## Features

- **Speech-to-Text Transcription** — Accurate transcription via faster-whisper (Whisper models) with word-level timestamps
- **Speaker Identification (Diarization)** — Detect and distinguish between speakers using pyannote.audio
- **Synchronized Playback** — Click any word to seek to that point in the audio (Web Audio API for instant playback)
- **AI Integration** — Ask questions about your transcript via OpenAI, Anthropic, or any OpenAI-compatible API (LiteLLM proxies, Ollama, vLLM)
- **Export Formats** — SRT, WebVTT, ASS captions, plain text, and Markdown with speaker labels
- **Cross-Platform** — Builds for Linux, Windows, and macOS (Apple Silicon)

## Platform Support

| Platform | Architecture | Status |
|----------|-------------|--------|
| Linux    | x86_64      | Supported |
| Windows  | x86_64      | Supported |
| macOS    | ARM (Apple Silicon) | Supported |

## Tech Stack

- **Desktop shell:** Tauri v2 (Rust backend + Svelte 5 / TypeScript frontend)
- **ML pipeline:** Python sidecar (faster-whisper, pyannote.audio) — frozen via PyInstaller for distribution
- **Audio playback:** wavesurfer.js with Web Audio API backend
- **AI providers:** OpenAI, Anthropic, OpenAI-compatible endpoints (local or remote)
- **Local AI:** Bundled llama-server (llama.cpp)
- **Caption export:** pysubs2

## Development

### Prerequisites

- Node.js 20+
- Rust (stable)
- Python 3.11+ with ML dependencies
- System: `libgtk-3-dev`, `libwebkit2gtk-4.1-dev` (Linux)

### Getting Started

```bash
# Install frontend dependencies
npm install

# Install Python sidecar dependencies
cd python && pip install -e . && cd ..

# Run in dev mode (uses system Python for the sidecar)
npm run tauri:dev
```

### Building for Distribution

```bash
# Build the frozen Python sidecar
npm run sidecar:build

# Build the Tauri app (requires sidecar in src-tauri/binaries/)
npm run tauri build
```

### CI/CD

Gitea Actions workflows are in `.gitea/workflows/`. The build pipeline:

1. **Build sidecar** — PyInstaller-frozen Python binary per platform (CPU-only PyTorch)
2. **Build Tauri app** — Bundles the sidecar via `externalBin`, produces .deb/.AppImage (Linux), .msi (Windows), .dmg (macOS)

#### Required Secrets

| Secret | Purpose | Required? |
|--------|---------|-----------|
| `TAURI_SIGNING_PRIVATE_KEY` | Signs Tauri update bundles | Optional (for auto-updates) |

No other secrets are needed for building. AI provider API keys and HuggingFace tokens are configured by end users in the app's Settings.

### Project Structure

```
src/                    # Svelte 5 frontend
src-tauri/              # Rust backend (Tauri commands, sidecar manager, SQLite)
python/                 # Python sidecar (transcription, diarization, AI)
  voice_to_notes/       # Python package
  build_sidecar.py      # PyInstaller build script
  voice_to_notes.spec   # PyInstaller spec
.gitea/workflows/       # Gitea Actions CI/CD
```

## License

MIT