58faa83cb3
- PyInstaller frozen sidecar: spec file, build script, and ffmpeg path resolver for self-contained distribution without Python prerequisites - Dual-mode sidecar launcher: frozen binary (production) with dev mode fallback - Parallel transcription + diarization pipeline (~30-40% faster) - GPU auto-detection for diarization (CUDA when available) - Async run_pipeline command for real-time progress event delivery - Web Audio API backend for instant playback and seeking - OpenAI-compatible provider replacing LiteLLM client-side routing - Cross-platform RAM detection (Linux/macOS/Windows) - Settings: speaker count hint, token reveal toggles, dark dropdown styling - Loading splash screen, flexbox layout fix for viewport overflow - Gitea Actions CI/CD pipeline (Linux, Windows, macOS ARM) - Updated README and CLAUDE.md documentation Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
93 lines
3.1 KiB
Markdown
93 lines
3.1 KiB
Markdown
# Voice to Notes
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A desktop application that transcribes audio/video recordings with speaker identification, producing editable transcriptions with synchronized audio playback.
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## Features
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- **Speech-to-Text Transcription** — Accurate transcription via faster-whisper (Whisper models) with word-level timestamps
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- **Speaker Identification (Diarization)** — Detect and distinguish between speakers using pyannote.audio
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- **Synchronized Playback** — Click any word to seek to that point in the audio (Web Audio API for instant playback)
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- **AI Integration** — Ask questions about your transcript via OpenAI, Anthropic, or any OpenAI-compatible API (LiteLLM proxies, Ollama, vLLM)
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- **Export Formats** — SRT, WebVTT, ASS captions, plain text, and Markdown with speaker labels
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- **Cross-Platform** — Builds for Linux, Windows, and macOS (Apple Silicon)
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## Platform Support
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| Platform | Architecture | Status |
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|----------|-------------|--------|
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| Linux | x86_64 | Supported |
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| Windows | x86_64 | Supported |
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| macOS | ARM (Apple Silicon) | Supported |
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## Tech Stack
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- **Desktop shell:** Tauri v2 (Rust backend + Svelte 5 / TypeScript frontend)
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- **ML pipeline:** Python sidecar (faster-whisper, pyannote.audio) — frozen via PyInstaller for distribution
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- **Audio playback:** wavesurfer.js with Web Audio API backend
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- **AI providers:** OpenAI, Anthropic, OpenAI-compatible endpoints (local or remote)
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- **Local AI:** Bundled llama-server (llama.cpp)
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- **Caption export:** pysubs2
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## Development
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### Prerequisites
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- Node.js 20+
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- Rust (stable)
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- Python 3.11+ with ML dependencies
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- System: `libgtk-3-dev`, `libwebkit2gtk-4.1-dev` (Linux)
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### Getting Started
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```bash
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# Install frontend dependencies
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npm install
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# Install Python sidecar dependencies
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cd python && pip install -e . && cd ..
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# Run in dev mode (uses system Python for the sidecar)
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npm run tauri:dev
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```
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### Building for Distribution
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```bash
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# Build the frozen Python sidecar
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npm run sidecar:build
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# Build the Tauri app (requires sidecar in src-tauri/binaries/)
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npm run tauri build
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```
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### CI/CD
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Gitea Actions workflows are in `.gitea/workflows/`. The build pipeline:
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1. **Build sidecar** — PyInstaller-frozen Python binary per platform (CPU-only PyTorch)
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2. **Build Tauri app** — Bundles the sidecar via `externalBin`, produces .deb/.AppImage (Linux), .msi (Windows), .dmg (macOS)
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#### Required Secrets
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| Secret | Purpose | Required? |
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|--------|---------|-----------|
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| `TAURI_SIGNING_PRIVATE_KEY` | Signs Tauri update bundles | Optional (for auto-updates) |
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No other secrets are needed for building. AI provider API keys and HuggingFace tokens are configured by end users in the app's Settings.
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### Project Structure
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```
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src/ # Svelte 5 frontend
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src-tauri/ # Rust backend (Tauri commands, sidecar manager, SQLite)
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python/ # Python sidecar (transcription, diarization, AI)
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voice_to_notes/ # Python package
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build_sidecar.py # PyInstaller build script
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voice_to_notes.spec # PyInstaller spec
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.gitea/workflows/ # Gitea Actions CI/CD
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```
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## License
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MIT
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