Phase 1 foundation: Tauri shell, Python sidecar, SQLite database
Tauri v2 + Svelte + TypeScript frontend:
- App shell with workspace layout (waveform, transcript, speakers, AI chat)
- Placeholder components for all major UI areas
- Typed stores (project, transcript, playback, AI)
- TypeScript interfaces matching the database schema
- Tauri bridge service with typed invoke wrappers
- svelte-check passes with 0 errors
Rust backend:
- Tauri v2 app entry point with command registration
- SQLite database layer (rusqlite with bundled SQLite)
- Full schema: projects, media_files, speakers, segments, words,
ai_outputs, annotations (with indexes)
- Model structs with serde serialization
- CRUD queries for projects, speakers, segments, words
- Segment text editing preserves original text
- Schema versioning for future migrations
- 6 tests passing
- Command stubs for project, transcribe, export, AI, settings, system
- App state management
Python sidecar:
- JSON-line IPC protocol (stdin/stdout)
- Message types: IPCMessage, progress, error, ready
- Handler registry with routing and error handling
- Ping/pong handler for connectivity testing
- Service stubs: transcribe, diarize, pipeline, AI, export
- Provider stubs: local (llama-server), OpenAI, Anthropic, LiteLLM
- Hardware detection stubs
- 14 tests passing, ruff clean
Also adds:
- Testing strategy document (docs/TESTING.md)
- Validation script (scripts/validate.sh)
- Updated .gitignore for Svelte, Rust, Python artifacts
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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python/voice_to_notes/services/export.py
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python/voice_to_notes/services/export.py
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"""Export service — caption and text document generation."""
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from __future__ import annotations
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class ExportService:
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"""Handles export to SRT, WebVTT, ASS, plain text, and Markdown."""
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# TODO: Implement pysubs2 integration
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# - SRT with [Speaker]: prefix
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# - WebVTT with <v Speaker> voice tags
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# - ASS with named styles per speaker
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# - Plain text and Markdown with speaker labels
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pass
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