voice-to-notes/CLAUDE.md

# Voice to Notes — Project Guidelines

## Project Overview
Desktop app for transcribing audio/video with speaker identification. Runs locally on user's computer. See `docs/ARCHITECTURE.md` for full architecture.

## Tech Stack
- **Desktop shell:** Tauri v2 (Rust backend + Svelte/TypeScript frontend)
- **ML pipeline:** Python sidecar process (faster-whisper, pyannote.audio, wav2vec2)
- **Database:** SQLite (via rusqlite in Rust)
- **Local AI:** Bundled llama-server (llama.cpp) — default, no install needed
- **Cloud AI providers:** LiteLLM, OpenAI, Anthropic (optional, user-configured)
- **Caption export:** pysubs2 (Python)
- **Audio UI:** wavesurfer.js
- **Transcript editor:** TipTap (ProseMirror)

## Key Architecture Decisions
- Python sidecar communicates with Rust via JSON-line IPC (stdin/stdout)
- All ML models must work on CPU. GPU (CUDA) is optional acceleration.
- AI cloud providers are optional. Bundled llama-server (llama.cpp) is the default local AI — no separate install needed.
- Rust backend manages llama-server lifecycle (start/stop/port allocation).
- Project is open source (MIT license).
- SQLite database is per-project, stored alongside media files.
- Word-level timestamps are required for click-to-seek playback sync.

## Directory Structure
```
src/                    # Svelte frontend source
src-tauri/              # Rust backend source
python/                 # Python sidecar source
  voice_to_notes/       # Python package
  tests/                # Python tests
docs/                   # Architecture and design documents
```

## Conventions
- Rust: follow standard Rust conventions, use `cargo fmt` and `cargo clippy`
- Python: Python 3.11+, use type hints, follow PEP 8, use `ruff` for linting
- TypeScript: strict mode, prefer Svelte stores for state management
- IPC messages: JSON-line format, each message has `id`, `type`, `payload` fields
- Database: UUIDs as primary keys (TEXT type in SQLite)
- All timestamps in milliseconds (integer) relative to media file start

## Platform Targets
- Linux (primary development target)
- Windows (must work, tested before release)
- macOS (future, not yet targeted)