feat: add meeting transcription app scaffolding

- Add Python backend structure with FastAPI for transcription/summarization
- Add React UI with audio recording, transcript, and summary views
- Configure Tauri to manage Python backend lifecycle
- Set up Windows cross-compilation with cargo-xwin
- Add Gitea CI workflow for lint, test, and multi-platform builds
- Configure ESLint, Prettier, and Vitest for code quality

Note: App scaffolding only - Python env and models not yet set up

scripts/build_windows.py

@@ -0,0 +1,128 @@
+"""Build script to create a Windows executable with bundled Python environment.
+
+This script should be run ON WINDOWS, not cross-compiled from Linux.
+"""
+
+import shutil
+import subprocess
+import sys
+from pathlib import Path
+
+
+def main():
+    """Create a Windows executable bundle for Chronara."""
+    project_root = Path(__file__).parent.parent
+    dist_dir = project_root / "dist-bundle"
+
+    print("🔨 Chronara Windows Build Script")
+    print("=" * 50)
+    print("\n⚠️  NOTE: This script must be run on Windows!")
+    print("    Cross-compilation from Linux is not supported.\n")
+
+    if sys.platform != "win32":
+        print("❌ This script must be run on Windows.")
+        print("   Please run this on a Windows machine or in a Windows VM.")
+        sys.exit(1)
+
+    # Clean previous builds
+    if dist_dir.exists():
+        print("Cleaning previous build...")
+        shutil.rmtree(dist_dir)
+
+    dist_dir.mkdir(exist_ok=True)
+
+    # Step 1: Create Python bundle using PyInstaller
+    print("\n📦 Creating Python bundle...")
+
+    # Create a temporary spec file for PyInstaller
+    spec_content = f"""
+# -*- mode: python ; coding: utf-8 -*-
+
+a = Analysis(
+    ['{project_root / "src" / "backend" / "main.py"}'],
+    pathex=['{project_root / "src"}'],
+    binaries=[],
+    datas=[
+        ('{project_root / "models" / "*.gguf"}', 'models'),
+    ],
+    hiddenimports=['uvicorn', 'fastapi', 'whisperx', 'llama_cpp'],
+    hookspath=[],
+    hooksconfig={{}},
+    runtime_hooks=[],
+    excludes=[],
+    noarchive=False,
+)
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    a.binaries,
+    a.datas,
+    [],
+    name='chronara-backend',
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=False,
+    upx_exclude=[],
+    runtime_tmpdir=None,
+    console=True,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None,
+)
+"""
+
+    spec_path = project_root / "chronara-backend.spec"
+    spec_path.write_text(spec_content)
+
+    try:
+        subprocess.run([
+            sys.executable,
+            "-m",
+            "PyInstaller",
+            str(spec_path),
+            "--clean",
+            "--noconfirm",
+            "--distpath", str(dist_dir / "backend")
+        ], check=True)
+    except subprocess.CalledProcessError:
+        print("⚠️  PyInstaller not found. Installing...")
+        subprocess.run([sys.executable, "-m", "pip", "install", "pyinstaller"], check=True)
+        subprocess.run([
+            sys.executable,
+            "-m",
+            "PyInstaller",
+            str(spec_path),
+            "--clean",
+            "--noconfirm",
+            "--distpath", str(dist_dir / "backend")
+        ], check=True)
+
+    # Clean up spec file
+    spec_path.unlink()
+
+    # Step 2: Build Tauri app (creates NSIS installer on Windows)
+    print("\n🦀 Building Tauri app with NSIS installer...")
+    subprocess.run(
+        "pnpm tauri build",
+        cwd=project_root,
+        check=True,
+        shell=True
+    )
+
+    print("\n✅ Build complete!")
+    print("\nWindows installer (.exe) location:")
+    print("  src-tauri/target/release/bundle/nsis/Chronara_0.1.0_x64_en-US.exe")
+    print("\nThis installer includes:")
+    print("  - Tauri app with React frontend")
+    print("  - Python backend (bundled)")
+    print("  - Llama model files")
+    print("  - All dependencies")
+
+
+if __name__ == "__main__":
+    main()

scripts/download_models.py

@@ -0,0 +1,90 @@
+"""Download required models for Chronara."""
+
+import os
+import sys
+from pathlib import Path
+from urllib.request import urlretrieve
+
+# Model download URLs
+MODELS = {
+    "llama-3.2-1B": {
+        "url": "https://huggingface.co/bartowski/Llama-3.2-1B-Instruct-GGUF/resolve/main/Llama-3.2-1B-Instruct-Q4_K_M.gguf",
+        "filename": "llama-3.2-1B-instruct-Q4_K_M.gguf",
+        "size": "1.2GB",
+    },
+    "llama-3.2-3B": {
+        "url": "https://huggingface.co/bartowski/Llama-3.2-3B-Instruct-GGUF/resolve/main/Llama-3.2-3B-Instruct-Q4_K_M.gguf",
+        "filename": "llama-3.2-3B-instruct-Q4_K_M.gguf",
+        "size": "2.5GB",
+    },
+}
+
+
+def download_with_progress(url: str, filepath: Path):
+    """Download file with progress bar."""
+
+    def _progress(block_num, block_size, total_size):
+        downloaded = block_num * block_size
+        percent = min(downloaded * 100 / total_size, 100)
+        progress = int(50 * percent / 100)
+        sys.stdout.write(
+            f"\r[{'=' * progress}{' ' * (50 - progress)}] {percent:.1f}%"
+        )
+        sys.stdout.flush()
+
+    print(f"Downloading {filepath.name}...")
+    urlretrieve(url, filepath, reporthook=_progress)
+    print()  # New line after progress bar
+
+
+def main():
+    """Download all required models."""
+    # Get project root
+    project_root = Path(__file__).parent.parent
+    models_dir = project_root / "models"
+    models_dir.mkdir(exist_ok=True)
+
+    print("🤖 Chronara Model Downloader")
+    print("=" * 50)
+
+    # Ask which model to download
+    print("\nWhich Llama model would you like to use?")
+    print("1. Llama 3.2 1B (1.2GB) - Faster, good for basic summaries")
+    print("2. Llama 3.2 3B (2.5GB) - Better quality summaries")
+    print("3. Both models")
+
+    choice = input("\nEnter your choice (1/2/3): ").strip()
+
+    models_to_download = []
+    if choice == "1":
+        models_to_download = ["llama-3.2-1B"]
+    elif choice == "2":
+        models_to_download = ["llama-3.2-3B"]
+    elif choice == "3":
+        models_to_download = ["llama-3.2-1B", "llama-3.2-3B"]
+    else:
+        print("Invalid choice!")
+        return
+
+    # Download selected models
+    for model_name in models_to_download:
+        model_info = MODELS[model_name]
+        filepath = models_dir / model_info["filename"]
+
+        if filepath.exists():
+            print(f"\n✓ {model_name} already downloaded")
+            continue
+
+        print(f"\n📥 Downloading {model_name} ({model_info['size']})...")
+        try:
+            download_with_progress(model_info["url"], filepath)
+            print(f"✓ Downloaded {model_name} successfully!")
+        except Exception as e:
+            print(f"✗ Failed to download {model_name}: {e}")
+
+    print("\n✨ Model download complete!")
+    print("\nNote: WhisperX models will be downloaded automatically on first run.")
+
+
+if __name__ == "__main__":
+    main()

scripts/start_backend.py

@@ -0,0 +1,24 @@
+"""Start the Chronara backend server."""
+
+import os
+import sys
+import subprocess
+from pathlib import Path
+
+# Add src directory to Python path
+src_path = Path(__file__).parent.parent / "src"
+sys.path.insert(0, str(src_path))
+
+# Set environment for bundled deployment
+os.environ["CHRONARA_BUNDLED"] = "1"
+
+# Start the FastAPI server
+subprocess.run([
+    sys.executable,
+    "-m",
+    "uvicorn",
+    "backend.main:app",
+    "--host", "127.0.0.1",
+    "--port", "8000",
+    "--reload" if os.environ.get("CHRONARA_DEV") else ""
+])