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>

python/voice_to_notes/providers/__init__.py

@@ -0,0 +1 @@
+"""AI provider adapters — local (llama-server), LiteLLM, OpenAI, Anthropic."""

python/voice_to_notes/providers/anthropic_provider.py

@@ -0,0 +1,5 @@
+"""Anthropic provider — direct Anthropic SDK integration."""
+
+from __future__ import annotations
+
+# TODO: Implement Anthropic provider

python/voice_to_notes/providers/base.py

@@ -0,0 +1,23 @@
+"""Abstract base class for AI providers."""
+
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from collections.abc import AsyncIterator
+from typing import Any
+
+
+class AIProvider(ABC):
+    """Base interface for all AI providers."""
+
+    @abstractmethod
+    async def chat(self, messages: list[dict[str, Any]], config: dict[str, Any]) -> str:
+        """Send a chat completion request and return the response."""
+        ...
+
+    @abstractmethod
+    async def stream(
+        self, messages: list[dict[str, Any]], config: dict[str, Any]
+    ) -> AsyncIterator[str]:
+        """Send a streaming chat request, yielding tokens as they arrive."""
+        ...

python/voice_to_notes/providers/litellm_provider.py

@@ -0,0 +1,5 @@
+"""LiteLLM provider — multi-provider gateway."""
+
+from __future__ import annotations
+
+# TODO: Implement LiteLLM provider

python/voice_to_notes/providers/local_provider.py

@@ -0,0 +1,9 @@
+"""Local AI provider — bundled llama-server (OpenAI-compatible API)."""
+
+from __future__ import annotations
+
+
+# TODO: Implement local provider
+# - Connect to llama-server on localhost:{port}
+# - Use openai SDK with custom base_url
+# - Support chat and streaming

python/voice_to_notes/providers/openai_provider.py

@@ -0,0 +1,5 @@
+"""OpenAI provider — direct OpenAI SDK integration."""
+
+from __future__ import annotations
+
+# TODO: Implement OpenAI provider