format

Enhance StoryList component with dynamic bottom padding
- Introduced useMemo to calculate bottom padding based on the visibility of the StoryTrackEditor and FloatingGenerateBox. - Updated imports to include useStory hook for fetching the current story data. - Adjusted the StoryList layout to accommodate the new padding logic, improving UI consistency.
2026-09-27 22:25:15 -07:00 · 2026-02-03 06:45:35 -08:00 · 2026-02-03 06:36:09 -08:00 · 2026-02-03 06:33:24 -08:00 · 2026-02-03 06:25:27 -08:00 · 2026-02-03 06:07:19 -08:00
168 changed files with 14318 additions and 1570 deletions
@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.1.10
+current_version = 0.1.13
 commit = True
 tag = True
 tag_name = v{new_version}
@@ -0,0 +1,55 @@
+# Dependencies
+node_modules/
+__pycache__/
+*.pyc
+*.pyo
+*.pyd
+.Python
+env/
+venv/
+
+# Build outputs
+build/
+*.egg-info/
+.eggs/
+target/
+
+# Keep web/dist for the Docker image
+!web/dist
+
+# Development
+.git/
+.github/
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+
+# Data and logs
+data/
+*.log
+*.sqlite
+*.db
+
+# OS
+.DS_Store
+Thumbs.db
+
+# Documentation
+docs/
+landing/
+mlx-test/
+
+# Test files
+*.test.ts
+*.test.tsx
+*.spec.ts
+*.spec.tsx
+
+# Keep these out
+.env
+.env.local
+*.pem
+*.key
+credentials.json
@@ -4,9 +4,153 @@ on:
  workflow_dispatch:
  push:
    tags:
-      - 'v*'
+      - "v*"
+
+env:
+  PROVIDER_VERSION: "1.0.0"

 jobs:
+  # ============================================
+  # Build TTS Providers (uploaded to R2, not GitHub)
+  # ============================================
+  build-providers:
+    runs-on: ${{ matrix.platform }}
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          # PyTorch CPU provider (Windows)
+          - platform: "windows-latest"
+            provider: "pytorch-cpu"
+            python-version: "3.12"
+          # PyTorch CUDA provider (Windows) - large binary, uploaded to R2
+          - platform: "windows-latest"
+            provider: "pytorch-cuda"
+            python-version: "3.12"
+          # PyTorch CPU provider (Linux)
+          - platform: "ubuntu-22.04"
+            provider: "pytorch-cpu"
+            python-version: "3.12"
+          # PyTorch CUDA provider (Linux) - large binary, uploaded to R2
+          - platform: "ubuntu-22.04"
+            provider: "pytorch-cuda"
+            python-version: "3.12"
+          # PyTorch CPU provider (macOS Apple Silicon)
+          - platform: "macos-latest"
+            provider: "pytorch-cpu"
+            python-version: "3.12"
+          # PyTorch CPU provider (macOS Intel)
+          - platform: "macos-15-intel"
+            provider: "pytorch-cpu"
+            python-version: "3.12"
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Install dependencies (ubuntu only)
+        if: matrix.platform == 'ubuntu-22.04'
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y llvm-dev
+
+      - name: Setup Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+          cache: "pip"
+
+      - name: Install CPU-only torch (Linux)
+        if: matrix.provider == 'pytorch-cpu' && matrix.platform == 'ubuntu-22.04'
+        run: |
+          python -m pip install --upgrade pip
+          pip install pyinstaller
+          pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
+          pip install -r providers/pytorch-cpu/requirements.txt
+          pip install -r backend/requirements.txt
+
+      - name: Install Python dependencies (CPU - non-Linux)
+        if: matrix.provider == 'pytorch-cpu' && matrix.platform != 'ubuntu-22.04'
+        run: |
+          python -m pip install --upgrade pip
+          pip install pyinstaller
+          pip install -r providers/pytorch-cpu/requirements.txt
+          pip install -r backend/requirements.txt
+
+      - name: Install Python dependencies (CUDA)
+        if: matrix.provider == 'pytorch-cuda'
+        run: |
+          python -m pip install --upgrade pip
+          pip install pyinstaller
+          pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
+          pip install -r providers/pytorch-cuda/requirements.txt
+          pip install -r backend/requirements.txt
+
+      - name: Build provider binary
+        shell: bash
+        run: |
+          cd providers/${{ matrix.provider }}
+          python build.py
+
+      - name: Package provider for distribution
+        shell: bash
+        run: |
+          cd providers/${{ matrix.provider }}/dist
+
+          # Add platform suffix for archive name
+          if [ "${{ matrix.platform }}" == "windows-latest" ]; then
+            ARCHIVE_NAME="tts-provider-${{ matrix.provider }}-windows.zip"
+            # On Windows, zip the directory
+            powershell Compress-Archive -Path "tts-provider-${{ matrix.provider }}/*" -DestinationPath "$ARCHIVE_NAME"
+          elif [ "${{ matrix.platform }}" == "macos-latest" ]; then
+            ARCHIVE_NAME="tts-provider-${{ matrix.provider }}-macos-arm64.tar.gz"
+            tar -czf "$ARCHIVE_NAME" tts-provider-${{ matrix.provider }}/
+          elif [ "${{ matrix.platform }}" == "macos-15-intel" ]; then
+            ARCHIVE_NAME="tts-provider-${{ matrix.provider }}-macos-x64.tar.gz"
+            tar -czf "$ARCHIVE_NAME" tts-provider-${{ matrix.provider }}/
+          else
+            ARCHIVE_NAME="tts-provider-${{ matrix.provider }}-linux.tar.gz"
+            tar -czf "$ARCHIVE_NAME" tts-provider-${{ matrix.provider }}/
+          fi
+
+          echo "Created archive: $ARCHIVE_NAME"
+          ls -lh "$ARCHIVE_NAME"
+
+      - name: Upload provider to R2
+        shell: bash
+        env:
+          R2_ACCESS_KEY_ID: ${{ secrets.R2_ACCESS_KEY_ID }}
+          R2_SECRET_ACCESS_KEY: ${{ secrets.R2_SECRET_ACCESS_KEY }}
+          R2_ENDPOINT: ${{ secrets.R2_ENDPOINT }}
+        run: |
+          # Install AWS CLI (compatible with R2)
+          pip install awscli
+
+          # Configure AWS CLI for R2
+          aws configure set aws_access_key_id $R2_ACCESS_KEY_ID
+          aws configure set aws_secret_access_key $R2_SECRET_ACCESS_KEY
+          aws configure set region auto
+
+          # Determine archive name based on platform
+          if [ "${{ matrix.platform }}" == "windows-latest" ]; then
+            ARCHIVE_NAME="tts-provider-${{ matrix.provider }}-windows.zip"
+          elif [ "${{ matrix.platform }}" == "macos-latest" ]; then
+            ARCHIVE_NAME="tts-provider-${{ matrix.provider }}-macos-arm64.tar.gz"
+          elif [ "${{ matrix.platform }}" == "macos-15-intel" ]; then
+            ARCHIVE_NAME="tts-provider-${{ matrix.provider }}-macos-x64.tar.gz"
+          else
+            ARCHIVE_NAME="tts-provider-${{ matrix.provider }}-linux.tar.gz"
+          fi
+
+          # Upload to R2 (bucket: voicebox)
+          aws s3 cp "providers/${{ matrix.provider }}/dist/$ARCHIVE_NAME" \
+            "s3://voicebox/providers/v${{ env.PROVIDER_VERSION }}/$ARCHIVE_NAME" \
+            --endpoint-url "$R2_ENDPOINT"
+
+          echo "Uploaded $ARCHIVE_NAME to R2"
+
+  # ============================================
+  # Build Main App (without bundled TTS on Win/Linux)
+  # ============================================
  release:
    permissions:
      contents: write
@@ -14,22 +158,26 @@ jobs:
      fail-fast: false
      matrix:
        include:
-          - platform: 'macos-latest'
-            args: '--target aarch64-apple-darwin'
-            python-version: '3.12'
-            backend: 'mlx'
-          - platform: 'macos-15-intel'
-            args: '--target x86_64-apple-darwin'
-            python-version: '3.12'
-            backend: 'pytorch'
-          # - platform: 'ubuntu-22.04'
-          #   args: ''
-          #   python-version: '3.12'
-          #   backend: 'pytorch'
-          - platform: 'windows-latest'
-            args: ''
-            python-version: '3.12'
-            backend: 'pytorch'
+          # macOS Apple Silicon - MLX bundled (works out of the box)
+          - platform: "macos-latest"
+            args: "--target aarch64-apple-darwin"
+            python-version: "3.12"
+            backend: "mlx"
+          # macOS Intel - PyTorch bundled (smaller user base, keep simple)
+          - platform: "macos-15-intel"
+            args: "--target x86_64-apple-darwin"
+            python-version: "3.12"
+            backend: "pytorch"
+          # Linux - No TTS bundled, providers downloaded separately
+          - platform: "ubuntu-22.04"
+            args: ""
+            python-version: "3.12"
+            backend: "none"
+          # Windows - PyTorch CPU bundled (works out of the box)
+          - platform: "windows-latest"
+            args: ""
+            python-version: "3.12"
+            backend: "pytorch"

    runs-on: ${{ matrix.platform }}

@@ -40,7 +188,7 @@ jobs:
        if: matrix.platform == 'ubuntu-22.04'
        run: |
          sudo apt-get update
-          sudo apt-get install -y libwebkit2gtk-4.1-dev libappindicator3-dev librsvg2-dev patchelf llvm-dev
+          sudo apt-get install -y libwebkit2gtk-4.1-dev libappindicator3-dev librsvg2-dev patchelf llvm-dev libasound2-dev

      - name: Install LLVM (macOS)
        if: matrix.platform == 'macos-latest' || matrix.platform == 'macos-15-intel'
@@ -53,14 +201,24 @@ jobs:
        uses: actions/setup-python@v5
        with:
          python-version: ${{ matrix.python-version }}
-          cache: 'pip'
+          cache: "pip"

-      - name: Install Python dependencies
+      - name: Install Python dependencies (with TTS)
+        if: matrix.backend != 'none'
        run: |
          python -m pip install --upgrade pip
          pip install pyinstaller
          pip install -r backend/requirements.txt

+      - name: Install Python dependencies (without TTS)
+        if: matrix.backend == 'none'
+        run: |
+          python -m pip install --upgrade pip
+          pip install pyinstaller
+          # Install base requirements without PyTorch/Qwen-TTS
+          pip install fastapi uvicorn sqlalchemy librosa soundfile numpy httpx
+          pip install huggingface_hub  # For Whisper downloads
+
      - name: Install MLX dependencies (Apple Silicon only)
        if: matrix.backend == 'mlx'
        run: |
@@ -100,7 +258,7 @@ jobs:
      - name: Rust cache
        uses: swatinem/rust-cache@v2
        with:
-          workspaces: './tauri/src-tauri -> target'
+          workspaces: "./tauri/src-tauri -> target"

      - name: Install dependencies
        run: bun install
@@ -136,19 +294,90 @@ jobs:
        with:
          projectPath: tauri
          tagName: v__VERSION__
-          releaseName: 'voicebox v__VERSION__'
+          releaseName: "voicebox v__VERSION__"
          releaseBody: |
            ## What's Changed
            See the assets below to download and install this version.

            ### Installation
-            - **macOS (Apple Silicon)**: Download the `aarch64.dmg` file - uses MLX for fast native inference
+            - **macOS (Apple Silicon)**: Download the `aarch64.dmg` file - uses MLX for fast native inference (works out of the box)
            - **macOS (Intel)**: Download the `x64.dmg` file - uses PyTorch
-            - **Windows**: Download the `.msi` installer
-            - **Linux**: Download the `.AppImage` or `.deb` package
+            - **Windows**: Download the `.msi` installer - requires downloading a TTS provider on first use
+            - **Linux**: Download the `.AppImage` or `.deb` package - requires downloading a TTS provider on first use
+
+            ### TTS Providers
+            Windows and Linux users will be prompted to download a TTS provider on first launch:
+            - **Windows**: PyTorch CPU (~300MB) or PyTorch CUDA (~2.4GB for NVIDIA GPUs)
+            - **Linux**: PyTorch CUDA (~2.4GB) - requires NVIDIA GPU

            The app includes automatic updates - future updates will be installed automatically.
          releaseDraft: true
          prerelease: false
          args: ${{ matrix.args }}
          includeUpdaterJson: true
+
+  # ============================================
+  # Build and Push Docker Images
+  # ============================================
+  docker:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      packages: write
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Login to GitHub Container Registry
+        uses: docker/login-action@v3
+        with:
+          registry: ghcr.io
+          username: ${{ github.actor }}
+          password: ${{ secrets.GITHUB_TOKEN }}
+
+      - name: Setup Bun
+        uses: oven-sh/setup-bun@v2
+
+      - name: Install dependencies and build web UI
+        run: |
+          bun install
+          cd web
+          bun run build
+
+      - name: Extract version from tag
+        id: version
+        run: |
+          if [[ $GITHUB_REF == refs/tags/v* ]]; then
+            VERSION=${GITHUB_REF#refs/tags/v}
+          else
+            VERSION="dev"
+          fi
+          echo "version=$VERSION" >> $GITHUB_OUTPUT
+
+      - name: Build and push CPU image
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          file: ./Dockerfile
+          platforms: linux/amd64,linux/arm64
+          push: true
+          tags: |
+            ghcr.io/jamiepine/voicebox:latest
+            ghcr.io/jamiepine/voicebox:${{ steps.version.outputs.version }}
+          cache-from: type=gha
+          cache-to: type=gha,mode=max
+
+      - name: Build and push CUDA image
+        uses: docker/build-push-action@v5
+        with:
+          context: .
+          file: ./Dockerfile.cuda
+          platforms: linux/amd64
+          push: true
+          tags: |
+            ghcr.io/jamiepine/voicebox:latest-cuda
+            ghcr.io/jamiepine/voicebox:${{ steps.version.outputs.version }}-cuda
+          cache-from: type=gha
+          cache-to: type=gha,mode=max
@@ -15,6 +15,7 @@ dist/
 build/
 *.egg-info/
 *.egg
+*.spec
 target/
 *.app
 *.dmg
@@ -53,6 +53,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0

 ## [Unreleased]

+### Fixed
+- Audio export failing when Tauri save dialog returns object instead of string path
+
 ### Added
 - **Makefile** - Comprehensive development workflow automation with commands for setup, development, building, testing, and code quality checks
  - Includes Python version detection and compatibility warnings
@@ -14,16 +14,19 @@ Thank you for your interest in contributing to Voicebox! This document provides
 ### Prerequisites

 - **[Bun](https://bun.sh)** - Fast JavaScript runtime and package manager
+
  ```bash
  curl -fsSL https://bun.sh/install | bash
  ```

 - **[Python 3.11+](https://python.org)** - For backend development
+
  ```bash
  python --version  # Should be 3.11 or higher
  ```

 - **[Rust](https://rustup.rs)** - For Tauri desktop app (installed automatically by Tauri CLI)
+
  ```bash
  rustc --version  # Check if installed
  ```
@@ -37,41 +40,46 @@ Thank you for your interest in contributing to Voicebox! This document provides
 **Manual setup (required for Windows):**

 1. **Fork and clone the repository**
+
   ```bash
   git clone https://github.com/YOUR_USERNAME/voicebox.git
   cd voicebox
   ```

 2. **Install JavaScript dependencies**
+
   ```bash
   bun install
   ```
+
   This installs dependencies for:
+
   - `app/` - Shared React frontend
   - `tauri/` - Tauri desktop wrapper
   - `web/` - Web deployment wrapper

 3. **Set up Python backend**
+
   ```bash
   cd backend
-   
+
   # Create virtual environment
   python -m venv venv
-   
+
   # Activate virtual environment
   source venv/bin/activate  # On macOS/Linux
   # or
   venv\Scripts\activate  # On Windows
-   
+
   # Install Python dependencies
   pip install -r requirements.txt
-   
+
   # Install MLX dependencies (Apple Silicon only - for faster inference)
   # On Apple Silicon, this enables native Metal acceleration
   if [[ $(uname -m) == "arm64" ]]; then
     pip install -r requirements-mlx.txt
   fi
-   
+
   # Install Qwen3-TTS (required for voice synthesis)
   pip install git+https://github.com/QwenLM/Qwen3-TTS.git
   ```
@@ -81,19 +89,24 @@ Thank you for your interest in contributing to Voicebox! This document provides
   Development requires two terminals: one for the Python backend, one for the Tauri app.

   **Terminal 1: Backend server** (start this first)
+
   ```bash
   cd backend
   source venv/bin/activate  # Activate venv if not already active
   bun run dev:server
   # Or manually: uvicorn main:app --reload --port 17493
   ```
+
   Backend will be available at `http://localhost:17493`

   **Terminal 2: Desktop app**
+
   ```bash
   bun run dev
   ```
+
   This will:
+
   - Create a placeholder sidecar binary (for Tauri compilation)
   - Start Vite dev server on port 5173
   - Launch Tauri window pointing to localhost:5173
@@ -104,26 +117,133 @@ Thank you for your interest in contributing to Voicebox! This document provides
   > The bundled server binary is only used in production builds.

   **Optional: Web app**
+
   ```bash
   bun run dev:web
   ```
+
   Web app will be available at `http://localhost:5174`

 ### Model Downloads

 Models are automatically downloaded from HuggingFace Hub on first use:
+
 - **Whisper** (transcription): Auto-downloads on first transcription
 - **Qwen3-TTS** (voice cloning): Auto-downloads on first generation (~2-4GB)

 First-time usage will be slower due to model downloads, but subsequent runs will use cached models.

+### TTS Provider Development
+
+Voicebox uses a modular provider system to support different inference backends. Understanding this architecture is important when working on TTS features.
+
+#### Provider Types
+
+**Bundled Providers** — Included with the app binary:
+
+- `apple-mlx` — Bundled with macOS Apple Silicon builds (`.dmg` for aarch64)
+  - Uses MLX for native Metal acceleration
+  - Configured in `.github/workflows/release.yml` with `backend: "mlx"`
+
+**Hybrid Provider:**
+
+- `pytorch-cpu` — Can be bundled OR downloaded depending on platform
+  - **Bundled** with Windows and macOS Intel builds
+    - macOS Intel: `.dmg` for x64 with `backend: "pytorch"`
+    - Windows: `.exe` installer with PyTorch CPU included
+  - **Downloaded** on first use for Linux builds (~300MB)
+  - Falls back to bundled version if external binary not found
+
+**External-Only Providers:**
+
+- `pytorch-cuda` — NVIDIA GPU-accelerated provider (~2.4GB)
+  - Windows/Linux only (no NVIDIA GPUs on macOS)
+  - Downloaded on demand, not bundled
+  - Optional for users with CUDA-capable GPUs
+
+#### Provider Architecture
+
+```
+backend/providers/
+├── __init__.py         # ProviderManager - lifecycle management
+├── base.py             # TTSProvider protocol
+├── bundled.py          # BundledProvider - wraps built-in backends
+├── local.py            # LocalProvider - wraps external subprocess
+├── installer.py        # Download and install external providers
+└── types.py            # Provider type definitions
+
+providers/
+├── pytorch-cpu/        # External PyTorch CPU provider
+│   ├── main.py         # FastAPI server
+│   ├── build.py        # PyInstaller build script
+│   └── build_and_install.py  # Build and install locally
+└── pytorch-cuda/       # External PyTorch CUDA provider
+    ├── main.py
+    ├── build.py
+    └── build_and_install.py
+```
+
+**How it works:**
+
+1. **Bundled providers** run in-process within the main backend
+2. **External providers** run as separate subprocess servers
+3. **LocalProvider** communicates with external providers via HTTP
+4. **ProviderManager** handles starting/stopping and health checks
+
+#### Building Providers Locally
+
+When developing provider features, you'll need to build and test external providers:
+
+**Build a single provider:**
+
+```bash
+cd providers/pytorch-cpu
+python build_and_install.py
+```
+
+**Build all providers:**
+
+```bash
+bun run build:providers
+```
+
+This script:
+
+- Builds the provider binary with PyInstaller
+- Detects your platform (Windows/macOS/Linux)
+- Copies to the correct location:
+  - macOS: `~/Library/Application Support/voicebox/providers/`
+  - Windows: `%APPDATA%\voicebox\providers\`
+  - Linux: `~/.local/share/voicebox/providers/`
+- Sets executable permissions on Unix
+
+**Testing provider changes:**
+
+1. Make changes to `providers/pytorch-cpu/main.py`
+2. Run `bun run build:providers`
+3. Restart the Voicebox app
+4. Select the provider in Settings → TTS Provider
+
+#### Provider Binary Distribution
+
+For production releases, provider binaries are:
+
+1. Built by GitHub Actions for all platforms
+2. Uploaded to Cloudflare R2 at `downloads.voicebox.sh/providers/v{VERSION}/`
+3. Downloaded on-demand by users based on their platform and GPU
+
+See `.github/workflows/release.yml` for the build matrix.
+
 ### Building

 **Build everything (recommended):**
+
 ```bash
 bun run build
 ```
+
 This automatically:
+
 1. Builds the Python server binary (`./scripts/build-server.sh`)
 2. Builds the Tauri desktop app (`cd tauri && bun run tauri build`)

@@ -132,13 +252,23 @@ Creates platform-specific installers (`.dmg`, `.msi`, `.AppImage`) in `tauri/src
 **Note:** The build process detects your platform and includes the appropriate backend (MLX for Apple Silicon, PyTorch for others).

 **Build server binary only:**
+
 ```bash
 bun run build:server
 # or
 ./scripts/build-server.sh
 ```
+
 Creates platform-specific binary in `tauri/src-tauri/binaries/`

+**Build provider binaries (for development):**
+
+```bash
+bun run build:providers
+```
+
+Builds all external provider binaries and installs them to the system provider directory. See [TTS Provider Development](#tts-provider-development) for details.
+
 **Building with local Qwen3-TTS development version:**

 If you're actively developing or modifying the Qwen3-TTS library, set the `QWEN_TTS_PATH` environment variable to point to your local clone:
@@ -151,34 +281,41 @@ bun run build:server
 This makes PyInstaller use your local qwen-tts version instead of the pip-installed package. Useful when testing changes to the TTS library before they're published to PyPI or when using an editable install (`pip install -e`).

 **Build web app:**
+
 ```bash
 cd web
 bun run build
 ```
+
 Output in `web/dist/`

 ### Generate OpenAPI Client

 After starting the backend server:
+
 ```bash
 ./scripts/generate-api.sh
 ```
+
 This downloads the OpenAPI schema and generates the TypeScript client in `app/src/lib/api/`

 ### Convert Assets to Web Formats

 To optimize images and videos for the web, run:
+
 ```bash
 bun run convert:assets
 ```

 This script:
+
 - Converts PNG → WebP (better compression, same quality)
 - Converts MOV → WebM (VP9 codec, smaller file size)
 - Processes files in `landing/public/` and `docs/public/`
 - **Deletes original files** after successful conversion

 **Requirements:** Install `webp` and `ffmpeg`:
+
 ```bash
 brew install webp ffmpeg
 ```
@@ -225,6 +362,7 @@ git push origin feature/your-feature-name
 ```

 Then create a pull request on GitHub with:
+
 - Clear description of changes
 - Screenshots (for UI changes)
 - Reference to related issues
@@ -370,21 +508,23 @@ Currently, testing is primarily manual. When adding tests:
 Releases are managed by maintainers:

 1. **Bump version using bumpversion:**
+
   ```bash
   # Install bumpversion (if not already installed)
   pip install bumpversion
-   
+
   # Bump patch version (0.1.0 -> 0.1.1)
   bumpversion patch
-   
+
   # Or bump minor version (0.1.0 -> 0.2.0)
   bumpversion minor
-   
+
   # Or bump major version (0.1.0 -> 1.0.0)
   bumpversion major
   ```
-   
+
   This automatically:
+
   - Updates version numbers in all files (`tauri.conf.json`, `Cargo.toml`, all `package.json` files, `backend/main.py`)
   - Creates a git commit with the version bump
   - Creates a git tag (e.g., `v0.1.1`, `v0.2.0`)
@@ -392,6 +532,7 @@ Releases are managed by maintainers:
 2. **Update CHANGELOG.md** with release notes

 3. **Push commits and tags:**
+
   ```bash
   git push
   git push --tags
@@ -0,0 +1,43 @@
+# Base Dockerfile for Voicebox (CPU-only)
+# For GPU support, use Dockerfile.cuda
+
+FROM python:3.12-slim
+
+# Prevent interactive prompts during build
+ENV DEBIAN_FRONTEND=noninteractive
+ENV TZ=UTC
+
+WORKDIR /app
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    ffmpeg \
+    curl \
+    tzdata \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy backend
+COPY backend/ /app/backend/
+COPY providers/ /app/providers/
+
+# Copy pre-built web UI
+COPY web/dist/ /app/web/dist/
+
+# Install Python dependencies (without PyTorch - will be downloaded via provider system)
+RUN python -m pip install --upgrade pip && \
+    pip install --no-cache-dir \
+    fastapi uvicorn[standard] pydantic sqlalchemy alembic \
+    librosa soundfile numpy python-multipart Pillow \
+    huggingface_hub transformers accelerate
+
+# Create data directory for profiles/generations
+RUN mkdir -p /app/data
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --retries=3 --start-period=40s \
+  CMD curl -f http://localhost:8000/health || exit 1
+
+EXPOSE 8000
+
+# Run server with web UI
+CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]
@@ -0,0 +1,58 @@
+# Dockerfile for Voicebox with NVIDIA GPU support (CUDA)
+
+FROM nvidia/cuda:12.1.1-runtime-ubuntu22.04
+
+# Prevent interactive prompts during build
+ENV DEBIAN_FRONTEND=noninteractive
+ENV TZ=UTC
+
+WORKDIR /app
+
+# Install Python 3.12
+RUN apt-get update && apt-get install -y \
+    software-properties-common \
+    && add-apt-repository ppa:deadsnakes/ppa \
+    && apt-get update && apt-get install -y \
+    python3.12 \
+    python3.12-dev \
+    python3.12-venv \
+    ffmpeg \
+    curl \
+    tzdata \
+    && rm -rf /var/lib/apt/lists/*
+
+# Set Python 3.12 as default and bootstrap pip
+RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.12 1 && \
+    update-alternatives --install /usr/bin/python python /usr/bin/python3.12 1 && \
+    python3.12 -m ensurepip --upgrade && \
+    python3.12 -m pip install --upgrade pip
+
+# Copy backend
+COPY backend/ /app/backend/
+COPY providers/ /app/providers/
+
+# Copy pre-built web UI
+COPY web/dist/ /app/web/dist/
+
+# Install PyTorch with CUDA support first
+RUN pip install --no-cache-dir \
+    torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
+
+# Install remaining dependencies
+RUN pip install --no-cache-dir \
+    fastapi uvicorn[standard] pydantic sqlalchemy alembic \
+    transformers accelerate huggingface_hub \
+    librosa soundfile numpy python-multipart Pillow \
+    qwen-tts
+
+# Create data directory
+RUN mkdir -p /app/data
+
+# Health check
+HEALTHCHECK --interval=30s --timeout=10s --retries=3 --start-period=40s \
+  CMD curl -f http://localhost:8000/health || exit 1
+
+EXPOSE 8000
+
+# Run server with web UI
+CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]
@@ -59,7 +59,7 @@

 ## What is Voicebox?

-Voicebox is a **local-first voice cloning studio** with DAW-like features for professional voice synthesis. Think of it as the **Ollama for voice** — download models, clone voices, and generate speech entirely on your machine.
+Voicebox is a **local-first voice cloning studio** with DAW-like features for professional voice synthesis. Think of it as a **local, free and open-source alternative to ElevenLabs** — download models, clone voices, and generate speech entirely on your machine.

 Unlike cloud services that lock your voice data behind subscriptions, Voicebox gives you:

@@ -68,6 +68,7 @@ Unlike cloud services that lock your voice data behind subscriptions, Voicebox g
 - **Model flexibility** — currently powered by Qwen3-TTS, with support for XTTS, Bark, and other models coming soon
 - **API-first** — use the desktop app or integrate voice synthesis into your own projects
 - **Native performance** — built with Tauri (Rust), not Electron
+- **Super fast on Mac** — MLX backend with native Metal acceleration for 4-5x faster inference on Apple Silicon

 Download a voice model, clone any voice from a few seconds of audio, and compose multi-voice projects with studio-grade editing tools. No Python install required, no cloud dependency, no limits.

@@ -75,16 +76,39 @@ Download a voice model, clone any voice from a few seconds of audio, and compose

 ## Download

-Voicebox is available now for macOS and Windows.
+### Desktop App

-| Platform | Download |
-|----------|----------|
-| macOS (Apple Silicon) | [voicebox_aarch64.app.tar.gz](https://github.com/jamiepine/voicebox/releases/download/v0.1.0/voicebox_aarch64.app.tar.gz) |
-| macOS (Intel) | [voicebox_x64.app.tar.gz](https://github.com/jamiepine/voicebox/releases/download/v0.1.0/voicebox_x64.app.tar.gz) |
-| Windows (MSI) | [voicebox_0.1.0_x64_en-US.msi](https://github.com/jamiepine/voicebox/releases/download/v0.1.0/voicebox_0.1.0_x64_en-US.msi) |
-| Windows (Setup) | [voicebox_0.1.0_x64-setup.exe](https://github.com/jamiepine/voicebox/releases/download/v0.1.0/voicebox_0.1.0_x64-setup.exe) |
+| Platform              | Download                                                                                                                    |
+| --------------------- | --------------------------------------------------------------------------------------------------------------------------- |
+| macOS (Apple Silicon) | [Download latest release](https://github.com/jamiepine/voicebox/releases/latest)   |
+| macOS (Intel)         | [Download latest release](https://github.com/jamiepine/voicebox/releases/latest)           |
+| Windows (MSI)         | [Download latest release](https://github.com/jamiepine/voicebox/releases/latest) |
+| Windows (Setup)       | [Download latest release](https://github.com/jamiepine/voicebox/releases/latest) |
+| Linux (AppImage)      | [Download latest release](https://github.com/jamiepine/voicebox/releases/latest) |
+| Linux (Deb)           | [Download latest release](https://github.com/jamiepine/voicebox/releases/latest) |

-> **Linux builds coming soon** — Currently blocked by GitHub runner disk space limitations.
+### Docker
+
+Run Voicebox with the web UI in Docker - perfect for servers and headless deployments:
+
+```bash
+# CPU-only (supports amd64 and arm64)
+docker run -p 8000:8000 -v voicebox-data:/app/data \
+  ghcr.io/jamiepine/voicebox:latest
+
+# NVIDIA GPU (recommended for performance)
+docker run --gpus all -p 8000:8000 -v voicebox-data:/app/data \
+  ghcr.io/jamiepine/voicebox:latest-cuda
+```
+
+Or use Docker Compose:
+```bash
+docker compose up -d
+```
+
+Open http://localhost:8000 to access the web UI.
+
+See [Docker Deployment Guide](docs/overview/docker.mdx) for cloud deployments, GPU setup, and more.

 ---

@@ -97,6 +121,7 @@ Powered by Alibaba's **Qwen3-TTS** — a breakthrough model that achieves near-p
 - **Instant cloning** — Upload a sample, get a voice profile
 - **High fidelity** — Natural prosody, emotion, and cadence
 - **Multi-language** — English, Chinese, and more coming
+- **Lightning fast on Mac** — MLX backend leverages Apple Silicon's Neural Engine for super fast generation

 ### Voice Profile Management

@@ -135,9 +160,10 @@ Create multi-voice narratives, podcasts, and conversations with a timeline-based

 ### Flexible Deployment

- **Local mode** — Everything runs on your machine
- **Remote mode** — Connect to a GPU server on your network
- **One-click server** — Turn any machine into a Voicebox server
+- **Desktop app** — Native apps for macOS, Windows, and Linux
+- **Docker** — Deploy to servers with the web UI included
+- **Remote mode** — Connect desktop app to a remote GPU server
+- **Cloud ready** — Deploy to AWS, GCP, DigitalOcean, or any cloud provider

 ---

@@ -174,17 +200,17 @@ Full API documentation available at `http://localhost:8000/docs` when running.

 ## Tech Stack

-| Layer | Technology |
-|-------|------------|
-| Desktop App | Tauri (Rust) |
-| Frontend | React, TypeScript, Tailwind CSS |
-| State | Zustand, React Query |
-| Backend | FastAPI (Python) |
-| Voice Model | Qwen3-TTS (PyTorch or MLX) |
-| Transcription | Whisper (PyTorch or MLX) |
+| Layer            | Technology                                          |
+| ---------------- | --------------------------------------------------- |
+| Desktop App      | Tauri (Rust)                                        |
+| Frontend         | React, TypeScript, Tailwind CSS                     |
+| State            | Zustand, React Query                                |
+| Backend          | FastAPI (Python)                                    |
+| Voice Model      | Qwen3-TTS (PyTorch or MLX)                          |
+| Transcription    | Whisper (PyTorch or MLX)                            |
 | Inference Engine | MLX (Apple Silicon) / PyTorch (Windows/Linux/Intel) |
-| Database | SQLite |
-| Audio | WaveSurfer.js, librosa |
+| Database         | SQLite                                              |
+| Audio            | WaveSurfer.js, librosa                              |

 **Why this stack?**

@@ -192,6 +218,26 @@ Full API documentation available at `http://localhost:8000/docs` when running.
 - **FastAPI** — Async Python with automatic OpenAPI schema generation
 - **Type-safe end-to-end** — Generated TypeScript client from OpenAPI spec

+### TTS Provider Architecture
+
+Voicebox uses a modular provider system to support different inference backends:
+
+- **`apple-mlx`** — Bundled with macOS Apple Silicon builds
+
+  - Uses MLX with native Metal acceleration (4-5x faster)
+  - Works out of the box, no download required
+
+- **`pytorch-cpu`** — Universal CPU provider (bundled or downloaded)
+
+  - Bundled with Windows and macOS Intel builds
+  - Downloaded on first use for Linux (~300MB)
+
+- **`pytorch-cuda`** — Optional NVIDIA GPU-accelerated provider
+  - Windows/Linux only (~2.4GB)
+  - 4-5x faster inference on CUDA-capable GPUs
+
+macOS and Windows builds work out of the box with bundled providers. Linux users download a provider on first launch. The app automatically detects your hardware and recommends the best option. All downloadable providers are distributed via Cloudflare R2 for fast, global delivery.
+
 ---

 ## Roadmap
@@ -200,13 +246,13 @@ Voicebox is the beginning of something bigger. Here's what's coming:

 ### Coming Soon

-| Feature | Description |
-|---------|-------------|
-| **Real-time Synthesis** | Stream audio as it generates, word by word |
-| **Conversation Mode** | Multi-speaker dialogues with automatic turn-taking |
-| **Voice Effects** | Pitch shift, reverb, M3GAN-style effects |
-| **Timeline Editor** | Audio studio with word-level precision editing |
-| **More Models** | XTTS, Bark, and other open-source voice models |
+| Feature                 | Description                                        |
+| ----------------------- | -------------------------------------------------- |
+| **Real-time Synthesis** | Stream audio as it generates, word by word         |
+| **Conversation Mode**   | Multi-speaker dialogues with automatic turn-taking |
+| **Voice Effects**       | Pitch shift, reverb, M3GAN-style effects           |
+| **Timeline Editor**     | Audio studio with word-level precision editing     |
+| **More Models**         | XTTS, Bark, and other open-source voice models     |

 ### Future Vision

@@ -258,9 +304,10 @@ cd backend && pip install -r requirements.txt && cd ..
 bun run dev
 ```

-**Prerequisites:** [Bun](https://bun.sh), [Rust](https://rustup.rs), [Python 3.11+](https://python.org). 
+**Prerequisites:** [Bun](https://bun.sh), [Rust](https://rustup.rs), [Python 3.11+](https://python.org).
+
+**Performance:**

-**Performance:** 
 - **Apple Silicon (M1/M2/M3)**: Uses MLX backend with native Metal acceleration for 4-5x faster inference
 - **Windows/Linux/Intel Mac**: Uses PyTorch backend (CUDA GPU recommended, CPU supported but slower)

@@ -1,6 +1,6 @@
 {
  "name": "@voicebox/app",
-  "version": "0.1.10",
+  "version": "0.1.13",
  "private": true,
  "type": "module",
  "scripts": {
@@ -17,6 +17,10 @@
    "@dnd-kit/sortable": "^10.0.0",
    "@dnd-kit/utilities": "^3.2.2",
    "@hookform/resolvers": "^3.9.0",
+    "@hugeicons/core-free-icons": "^3.1.1",
+    "@hugeicons/react": "^1.1.4",
+    "@iconify-json/svg-spinners": "^1.2.4",
+    "@iconify/react": "^6.0.2",
    "@radix-ui/react-alert-dialog": "^1.1.1",
    "@radix-ui/react-avatar": "^1.1.0",
    "@radix-ui/react-dialog": "^1.1.1",
@@ -24,6 +28,7 @@
    "@radix-ui/react-label": "^2.1.0",
    "@radix-ui/react-popover": "^1.1.1",
    "@radix-ui/react-progress": "^1.1.0",
+    "@radix-ui/react-radio-group": "^1.2.0",
    "@radix-ui/react-scroll-area": "^1.1.0",
    "@radix-ui/react-select": "^2.1.1",
    "@radix-ui/react-separator": "^1.1.0",
@@ -43,7 +48,6 @@
    "clsx": "^2.1.1",
    "date-fns": "^3.6.0",
    "framer-motion": "^12.29.0",
-    "lucide-react": "^0.454.0",
    "motion": "^12.29.0",
    "react": "^18.3.0",
    "react-dom": "^18.3.0",
@@ -1,16 +1,12 @@
-import { useEffect, useRef, useState } from 'react';
 import { RouterProvider } from '@tanstack/react-router';
+import { useEffect, useRef, useState } from 'react';
 import voiceboxLogo from '@/assets/voicebox-logo.png';
 import ShinyText from '@/components/ShinyText';
 import { TitleBarDragRegion } from '@/components/TitleBarDragRegion';
+import { useAutoUpdater } from '@/hooks/useAutoUpdater';
 import { TOP_SAFE_AREA_PADDING } from '@/lib/constants/ui';
-import {
-  isTauri,
-  setKeepServerRunning,
-  setupWindowCloseHandler,
-  startServer,
-} from '@/lib/tauri';
 import { cn } from '@/lib/utils/cn';
+import { usePlatform } from '@/platform/PlatformContext';
 import { router } from '@/router';
 import { useServerStore } from '@/stores/serverStore';

@@ -38,29 +34,45 @@ const LOADING_MESSAGES = [
 ];

 function App() {
+  const platform = usePlatform();
  const [serverReady, setServerReady] = useState(false);
  const [loadingMessageIndex, setLoadingMessageIndex] = useState(0);
  const serverStartingRef = useRef(false);

+  // Automatically check for app updates on startup and show toast notifications
+  useAutoUpdater(true);
+
  // Sync stored setting to Rust on startup
  useEffect(() => {
-    if (isTauri()) {
+    if (platform.metadata.isTauri) {
      const keepRunning = useServerStore.getState().keepServerRunningOnClose;
-      setKeepServerRunning(keepRunning).catch((error) => {
+      platform.lifecycle.setKeepServerRunning(keepRunning).catch((error) => {
        console.error('Failed to sync initial setting to Rust:', error);
      });
    }
-  }, []);
+    // Empty dependency array - platform is stable from context, only run once
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.metadata.isTauri, platform.lifecycle]);
+
+  // Setup lifecycle callbacks
+  useEffect(() => {
+    platform.lifecycle.onServerReady = () => {
+      setServerReady(true);
+    };
+    // Empty dependency array - platform is stable from context, only run once
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.lifecycle]);

  // Setup window close handler and auto-start server when running in Tauri (production only)
  useEffect(() => {
-    if (!isTauri()) {
+    if (!platform.metadata.isTauri) {
+      setServerReady(true); // Web assumes server is running
      return;
    }

    // Setup window close handler to check setting and stop server if needed
    // This works in both dev and prod, but will only stop server if it was started by the app
-    setupWindowCloseHandler().catch((error) => {
+    platform.lifecycle.setupWindowCloseHandler().catch((error) => {
      console.error('Failed to setup window close handler:', error);
    });

@@ -70,8 +82,7 @@ function App() {
      console.log('Dev mode: Skipping auto-start of server (run it separately)');
      setServerReady(true); // Mark as ready so UI doesn't show loading screen
      // Mark that server was not started by app (so we don't try to stop it on close)
-      // @ts-expect-error - adding property to window
-      window.__voiceboxServerStartedByApp = false;
+      (window as any).__voiceboxServerStartedByApp = false;
      return;
    }

@@ -83,19 +94,20 @@ function App() {
    serverStartingRef.current = true;
    console.log('Production mode: Starting bundled server...');

-    startServer(false)
+    platform.lifecycle
+      .startServer(false)
      .then((serverUrl) => {
        console.log('Server is ready at:', serverUrl);
        // Update the server URL in the store with the dynamically assigned port
        useServerStore.getState().setServerUrl(serverUrl);
        setServerReady(true);
        // Mark that we started the server (so we know to stop it on close)
-        window.__voiceboxServerStartedByApp = true;
+        (window as any).__voiceboxServerStartedByApp = true;
      })
      .catch((error) => {
        console.error('Failed to auto-start server:', error);
        serverStartingRef.current = false;
-        window.__voiceboxServerStartedByApp = false;
+        (window as any).__voiceboxServerStartedByApp = false;
      });

    // Cleanup: stop server on actual unmount (not StrictMode remount)
@@ -104,11 +116,13 @@ function App() {
      // Window close event handles server shutdown based on setting
      serverStartingRef.current = false;
    };
-  }, []);
+    // Empty dependency array - platform is stable from context, only run once
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.metadata.isTauri, platform.lifecycle]);

  // Cycle through loading messages every 3 seconds
  useEffect(() => {
-    if (!isTauri() || serverReady) {
+    if (!platform.metadata.isTauri || serverReady) {
      return;
    }

@@ -117,10 +131,10 @@ function App() {
    }, 3000);

    return () => clearInterval(interval);
-  }, [serverReady]);
+  }, [serverReady, platform.metadata.isTauri]);

  // Show loading screen while server is starting in Tauri
-  if (isTauri() && !serverReady) {
+  if (platform.metadata.isTauri && !serverReady) {
    return (
      <div
        className={cn(
@@ -1,17 +1,18 @@
 import { useQuery } from '@tanstack/react-query';
-import { invoke } from '@tauri-apps/api/core';
-import { Pause, Play, Repeat, Volume2, VolumeX, X } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { PauseIcon, PlayIcon, RepeatIcon, VolumeHighIcon, VolumeMuteIcon, Cancel01Icon } from '@hugeicons/core-free-icons';
 import { useEffect, useMemo, useRef, useState } from 'react';
 import WaveSurfer from 'wavesurfer.js';
 import { Button } from '@/components/ui/button';
 import { Slider } from '@/components/ui/slider';
 import { apiClient } from '@/lib/api/client';
-import { isTauri } from '@/lib/tauri';
 import { formatAudioDuration } from '@/lib/utils/audio';
 import { debug } from '@/lib/utils/debug';
 import { usePlayerStore } from '@/stores/playerStore';
+import { usePlatform } from '@/platform/PlatformContext';

 export function AudioPlayer() {
+  const platform = usePlatform();
  const {
    audioUrl,
    audioId,
@@ -39,7 +40,7 @@ export function AudioPlayer() {
      if (!profileId) return { channel_ids: [] };
      return apiClient.getProfileChannels(profileId);
    },
-    enabled: !!profileId && isTauri(),
+    enabled: !!profileId && platform.metadata.isTauri,
  });

  const { data: channels } = useQuery({
@@ -50,7 +51,7 @@ export function AudioPlayer() {

  // Determine if we should use native playback
  const useNativePlayback = useMemo(() => {
-    if (!isTauri() || !profileChannels || !channels) {
+    if (!platform.metadata.isTauri || !profileChannels || !channels) {
      return false;
    }

@@ -195,7 +196,7 @@ export function AudioPlayer() {
        let runtimeProfileChannels = null;
        let runtimeChannels = null;

-        if (isTauri() && currentProfileId) {
+        if (platform.metadata.isTauri && currentProfileId) {
          try {
            runtimeProfileChannels = await apiClient.getProfileChannels(currentProfileId);
            debug.log('Runtime profileChannels:', runtimeProfileChannels);
@@ -210,7 +211,7 @@ export function AudioPlayer() {
        }

        debug.log('Auto-play check:', {
-          isTauri: isTauri(),
+          isTauri: platform.metadata.isTauri,
          currentAudioUrl,
          currentProfileId,
          hasProfileChannels: !!runtimeProfileChannels,
@@ -218,7 +219,7 @@ export function AudioPlayer() {
        });

        if (
-          isTauri() &&
+          platform.metadata.isTauri &&
          currentAudioUrl &&
          currentProfileId &&
          runtimeProfileChannels &&
@@ -229,7 +230,7 @@ export function AudioPlayer() {
          // Stop any existing native playback first
          if (isUsingNativePlaybackRef.current) {
            try {
-              await invoke('stop_audio_playback');
+              platform.audio.stopPlayback();
              debug.log('Stopped existing native playback before starting new one');
            } catch (error) {
              debug.error('Failed to stop existing playback:', error);
@@ -279,11 +280,8 @@ export function AudioPlayer() {
                // Play via native audio
                debug.log('Invoking play_audio_to_devices...');
                try {
-                  const result = await invoke('play_audio_to_devices', {
-                    audioData: Array.from(audioData),
-                    deviceIds: deviceIds,
-                  });
-                  debug.log('play_audio_to_devices completed successfully, result:', result);
+                  await platform.audio.playToDevices(audioData, deviceIds);
+                  debug.log('play_audio_to_devices completed successfully');

                  // Mark that we're using native playback
                  isUsingNativePlaybackRef.current = true;
@@ -462,7 +460,7 @@ export function AudioPlayer() {
    // Use double requestAnimationFrame to ensure DOM is fully rendered
    let rafId1: number;
    let rafId2: number;
-    let timeoutId: number | null = null;
+    let timeoutId: ReturnType<typeof setTimeout> | null = null;

    rafId1 = requestAnimationFrame(() => {
      rafId2 = requestAnimationFrame(() => {
@@ -516,15 +514,13 @@ export function AudioPlayer() {
    }

    // Stop native playback if it was active
-    if (isUsingNativePlaybackRef.current && isTauri()) {
-      (async () => {
-        try {
-          await invoke('stop_audio_playback');
-          debug.log('Stopped native audio playback');
-        } catch (error) {
-          debug.error('Failed to stop native playback:', error);
-        }
-      })();
+    if (isUsingNativePlaybackRef.current && platform.metadata.isTauri) {
+      try {
+        platform.audio.stopPlayback();
+        debug.log('Stopped native audio playback');
+      } catch (error) {
+        debug.error('Failed to stop native playback:', error);
+      }
    }

    // Reset native playback flag when loading new audio
@@ -711,7 +707,7 @@ export function AudioPlayer() {
      if (isPlaying) {
        // Pause: stop native playback and pause WaveSurfer visualization
        try {
-          await invoke('stop_audio_playback');
+          platform.audio.stopPlayback();
          debug.log('Stopped native audio playback');
        } catch (error) {
          debug.error('Failed to stop native playback:', error);
@@ -724,7 +720,7 @@ export function AudioPlayer() {
      try {
        // Stop any existing native playback first
        try {
-          await invoke('stop_audio_playback');
+          platform.audio.stopPlayback();
        } catch (_error) {
          // Ignore errors when stopping (might not be playing)
          debug.log('No existing playback to stop');
@@ -742,10 +738,7 @@ export function AudioPlayer() {
          const audioData = new Uint8Array(await response.arrayBuffer());

          // Play via native audio
-          await invoke('play_audio_to_devices', {
-            audioData: Array.from(audioData),
-            deviceIds: deviceIds,
-          });
+          await platform.audio.playToDevices(audioData, deviceIds);

          // Mark that we're using native playback
          isUsingNativePlaybackRef.current = true;
@@ -806,10 +799,12 @@ export function AudioPlayer() {

  const handleClose = () => {
    // Stop any native playback
-    if (isUsingNativePlaybackRef.current && isTauri()) {
-      invoke('stop_audio_playback').catch((error) => {
+    if (isUsingNativePlaybackRef.current && platform.metadata.isTauri) {
+      try {
+        platform.audio.stopPlayback();
+      } catch (error) {
        debug.error('Failed to stop native playback:', error);
-      });
+      }
    }
    // Stop WaveSurfer
    if (wavesurferRef.current) {
@@ -838,7 +833,7 @@ export function AudioPlayer() {
            className="shrink-0"
            title={duration === 0 && !isLoading ? 'Audio not loaded' : ''}
          >
-            {isPlaying ? <Pause className="h-5 w-5" /> : <Play className="h-5 w-5" />}
+            {isPlaying ? <HugeiconsIcon icon={PauseIcon} size={20} className="h-5 w-5" /> : <HugeiconsIcon icon={PlayIcon} size={20} className="h-5 w-5" />}
          </Button>

          {/* Waveform */}
@@ -879,7 +874,7 @@ export function AudioPlayer() {
            className={isLooping ? 'text-primary' : ''}
            title="Toggle loop"
          >
-            <Repeat className="h-4 w-4" />
+            <HugeiconsIcon icon={RepeatIcon} size={16} className="h-4 w-4" />
          </Button>

          {/* Volume Control */}
@@ -890,7 +885,7 @@ export function AudioPlayer() {
              onClick={() => setVolume(volume > 0 ? 0 : 1)}
              className="h-8 w-8"
            >
-              {volume > 0 ? <Volume2 className="h-4 w-4" /> : <VolumeX className="h-4 w-4" />}
+              {volume > 0 ? <HugeiconsIcon icon={VolumeHighIcon} size={16} className="h-4 w-4" /> : <HugeiconsIcon icon={VolumeMuteIcon} size={16} className="h-4 w-4" />}
            </Button>
            <Slider
              value={[volume * 100]}
@@ -909,7 +904,7 @@ export function AudioPlayer() {
            className="shrink-0"
            title="Close player"
          >
-            <X className="h-5 w-5" />
+            <HugeiconsIcon icon={Cancel01Icon} size={20} className="h-5 w-5" />
          </Button>
        </div>
      </div>
@@ -1,6 +1,6 @@
 import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
-import { invoke } from '@tauri-apps/api/core';
-import { Check, CheckCircle2, Edit, Plus, Speaker, Trash2 } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { CheckmarkCircle01Icon, CheckmarkCircle02Icon, Edit01Icon, Add01Icon, SpeakerIcon, Delete01Icon } from '@hugeicons/core-free-icons';
 import { useState } from 'react';
 import { Badge } from '@/components/ui/badge';
 import { Button } from '@/components/ui/button';
@@ -23,9 +23,9 @@ import {
 } from '@/components/ui/select';
 import { apiClient } from '@/lib/api/client';
 import { BOTTOM_SAFE_AREA_PADDING } from '@/lib/constants/ui';
-import { isTauri } from '@/lib/tauri';
 import { cn } from '@/lib/utils/cn';
 import { usePlayerStore } from '@/stores/playerStore';
+import { usePlatform } from '@/platform/PlatformContext';

 interface AudioDevice {
  id: string;
@@ -34,6 +34,7 @@ interface AudioDevice {
 }

 export function AudioTab() {
+  const platform = usePlatform();
  const [createDialogOpen, setCreateDialogOpen] = useState(false);
  const [editingChannel, setEditingChannel] = useState<string | null>(null);
  const [selectedChannelId, setSelectedChannelId] = useState<string | null>(null);
@@ -49,18 +50,17 @@ export function AudioTab() {
  const { data: devices, isLoading: devicesLoading } = useQuery({
    queryKey: ['audio-devices'],
    queryFn: async () => {
-      if (!isTauri()) {
+      if (!platform.metadata.isTauri) {
        return [];
      }
      try {
-        const result = await invoke<AudioDevice[]>('list_audio_output_devices');
-        return result;
+        return await platform.audio.listOutputDevices();
      } catch (error) {
        console.error('Failed to list audio devices:', error);
        return [];
      }
    },
-    enabled: isTauri(),
+    enabled: platform.metadata.isTauri,
  });

  const { data: profiles } = useQuery({
@@ -136,7 +136,7 @@ export function AudioTab() {
      <div className="flex items-center justify-between mb-6 shrink-0">
        <h2 className="text-2xl font-bold">Audio Channels</h2>
        <Button onClick={() => setCreateDialogOpen(true)}>
-          <Plus className="h-4 w-4 mr-2" />
+          <HugeiconsIcon icon={Add01Icon} size={16} className="h-4 w-4 mr-2" />
          New Channel
        </Button>
      </div>
@@ -151,13 +151,13 @@ export function AudioTab() {
        >
          {allChannels.length === 0 ? (
            <div className="flex flex-col items-center justify-center py-12 border-2 border-dashed border-muted rounded-md">
-              <Speaker className="h-12 w-12 text-muted-foreground mb-4" />
+              <HugeiconsIcon icon={SpeakerIcon} size={48} className="h-12 w-12 text-muted-foreground mb-4" />
              <p className="text-muted-foreground mb-4">
                No audio channels yet. Create your first channel to route voices to specific
                devices.
              </p>
              <Button onClick={() => setCreateDialogOpen(true)}>
-                <Plus className="h-4 w-4 mr-2" />
+                <HugeiconsIcon icon={Add01Icon} size={16} className="h-4 w-4 mr-2" />
                Create Channel
              </Button>
            </div>
@@ -179,7 +179,7 @@ export function AudioTab() {
                      <div className="flex-1 min-w-0">
                        <div className="flex items-center gap-2 mb-3">
                          <div className="h-8 w-8 rounded-lg bg-muted flex items-center justify-center shrink-0">
-                            <Speaker className="h-4 w-4 text-muted-foreground" />
+                            <HugeiconsIcon icon={SpeakerIcon} size={16} className="h-4 w-4 text-muted-foreground" />
                          </div>
                          <div className="flex items-center gap-2 min-w-0">
                            <h3 className="font-semibold text-base truncate">{channel.name}</h3>
@@ -236,7 +236,7 @@ export function AudioTab() {
                              setEditingChannel(channel.id);
                            }}
                          >
-                            <Edit className="h-4 w-4" />
+                            <HugeiconsIcon icon={Edit01Icon} size={16} className="h-4 w-4" />
                          </Button>
                          <Button
                            variant="ghost"
@@ -249,7 +249,7 @@ export function AudioTab() {
                              }
                            }}
                          >
-                            <Trash2 className="h-4 w-4" />
+                            <HugeiconsIcon icon={Delete01Icon} size={16} className="h-4 w-4" />
                          </Button>
                        </div>
                      )}
@@ -326,10 +326,10 @@ export function AudioTab() {
                          isConnected ? 'bg-accent border-accent' : 'border-muted-foreground/30',
                        )}
                      >
-                        {isConnected && <Check className="h-3 w-3 text-accent-foreground" />}
+                        {isConnected && <HugeiconsIcon icon={CheckmarkCircle01Icon} size={12} className="h-3 w-3 text-accent-foreground" />}
                      </div>
                    ) : device.is_default ? (
-                      <CheckCircle2 className="h-4 w-4 text-primary shrink-0" />
+                      <HugeiconsIcon icon={CheckmarkCircle02Icon} size={16} className="h-4 w-4 text-primary shrink-0" />
                    ) : null}
                    <span className={cn('truncate flex-1', device.is_default && 'font-medium')}>
                      {device.name}
@@ -340,9 +340,9 @@ export function AudioTab() {
            </div>
          ) : (
            <div className="flex flex-col items-center justify-center py-12 border-2 border-dashed border-muted rounded-md">
-              <CheckCircle2 className="h-12 w-12 text-muted-foreground mb-4" />
+              <HugeiconsIcon icon={CheckmarkCircle02Icon} size={48} className="h-12 w-12 text-muted-foreground mb-4" />
              <p className="text-muted-foreground text-center">
-                {isTauri() ? 'No audio devices found' : 'Audio device selection requires Tauri'}
+                {platform.metadata.isTauri ? 'No audio devices found' : 'Audio device selection requires Tauri'}
              </p>
            </div>
          )}
@@ -495,7 +495,7 @@ function CreateChannelDialog({ open, onOpenChange, devices, onCreate }: CreateCh
                          setSelectedDevices(selectedDevices.filter((id) => id !== deviceId))
                        }
                      >
-                        <Trash2 className="h-3 w-3" />
+                        <HugeiconsIcon icon={Delete01Icon} size={12} className="h-3 w-3" />
                      </Button>
                    </div>
                  );
@@ -603,7 +603,7 @@ function EditChannelDialog({
                          setSelectedDevices(selectedDevices.filter((id) => id !== deviceId))
                        }
                      >
-                        <Trash2 className="h-3 w-3" />
+                        <HugeiconsIcon icon={Delete01Icon} size={12} className="h-3 w-3" />
                      </Button>
                    </div>
                  );
@@ -649,7 +649,7 @@ function EditChannelDialog({
                          setSelectedVoices(selectedVoices.filter((id) => id !== profileId))
                        }
                      >
-                        <Trash2 className="h-3 w-3" />
+                        <HugeiconsIcon icon={Delete01Icon} size={12} className="h-3 w-3" />
                      </Button>
                    </div>
                  );
@@ -1,6 +1,8 @@
+import { SparklesIcon, TextSquareIcon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Icon } from '@iconify/react';
 import { useMatchRoute } from '@tanstack/react-router';
 import { AnimatePresence, motion } from 'framer-motion';
-import { Loader2, MessageSquare, Sparkles } from 'lucide-react';
 import { useEffect, useRef, useState } from 'react';
 import { Button } from '@/components/ui/button';
 import { Form, FormControl, FormField, FormItem, FormMessage } from '@/components/ui/form';
@@ -187,7 +189,7 @@ export function FloatingGenerateBox({
      }}
    >
      <motion.div
-        className="bg-background/30 backdrop-blur-2xl border border-accent/20 rounded-[2rem] shadow-2xl hover:bg-background/40 hover:border-accent/20 transition-all duration-300 overflow-hidden p-3"
+        className="bg-background/30 backdrop-blur-2xl border border-accent/20 rounded-[2rem] shadow-2xl hover:bg-background/40 hover:border-accent/20 transition-all duration-300 p-3"
        transition={{ duration: 0.6, ease: 'easeInOut' }}
      >
        <Form {...form}>
@@ -274,7 +276,7 @@ export function FloatingGenerateBox({
                                  field.ref(node);
                                }
                              }}
-                              placeholder="Add delivery instructions..."
+                              placeholder="e.g. very happy and excited"
                              className="resize-none bg-transparent border-none focus-visible:ring-0 focus-visible:ring-offset-0 focus:outline-none focus:ring-0 outline-none ring-0 rounded-2xl text-sm placeholder:text-muted-foreground/60 w-full"
                              style={{
                                minHeight: isExpanded ? '100px' : '32px',
@@ -294,18 +296,27 @@ export function FloatingGenerateBox({
              </motion.div>

              <div className="relative shrink-0">
-                <Button
-                  type="submit"
-                  disabled={isPending || !selectedProfileId}
-                  className="h-10 w-10 rounded-full bg-accent hover:bg-accent/90 hover:scale-105 text-accent-foreground shadow-lg hover:shadow-accent/50 transition-all duration-200"
-                  size="icon"
-                >
-                  {isPending ? (
-                    <Loader2 className="h-4 w-4 animate-spin" />
-                  ) : (
-                    <Sparkles className="h-4 w-4" />
-                  )}
-                </Button>
+                <div className="group relative">
+                  <Button
+                    type="submit"
+                    disabled={isPending || !selectedProfileId}
+                    className="h-10 w-10 rounded-full bg-accent hover:bg-accent/90 hover:scale-105 text-accent-foreground shadow-lg transition-all duration-200"
+                    size="icon"
+                  >
+                    {isPending ? (
+                      <Icon icon="svg-spinners:ring-resize" className="h-4 w-4 animate-spin" />
+                    ) : (
+                      <HugeiconsIcon icon={SparklesIcon} size={16} className="h-4 w-4" />
+                    )}
+                  </Button>
+                  <span className="pointer-events-none absolute bottom-full left-1/2 -translate-x-1/2 mb-2 whitespace-nowrap rounded-md bg-popover px-3 py-1.5 text-xs text-popover-foreground border border-border opacity-0 transition-opacity group-hover:opacity-100 z-[9999]">
+                    {isPending
+                      ? 'Generating...'
+                      : !selectedProfileId
+                        ? 'Select a voice profile first'
+                        : 'Generate speech'}
+                  </span>
+                </div>
                <AnimatePresence>
                  {isExpanded && (
                    <motion.div
@@ -315,20 +326,25 @@ export function FloatingGenerateBox({
                      transition={{ duration: 0.2 }}
                      className="absolute top-0 right-[calc(100%+0.5rem)]"
                    >
-                      <Button
-                        type="button"
-                        variant="ghost"
-                        size="icon"
-                        onClick={() => setIsInstructMode(!isInstructMode)}
-                        className={cn(
-                          'h-10 w-10 rounded-full transition-all duration-200',
-                          isInstructMode
-                            ? 'bg-accent text-accent-foreground border border-accent hover:bg-accent/90'
-                            : 'bg-card border border-border hover:bg-background/50',
-                        )}
-                      >
-                        <MessageSquare className="h-4 w-4" />
-                      </Button>
+                      <div className="group relative">
+                        <Button
+                          type="button"
+                          variant="ghost"
+                          size="icon"
+                          onClick={() => setIsInstructMode(!isInstructMode)}
+                          className={cn(
+                            'h-10 w-10 rounded-full transition-all duration-200',
+                            isInstructMode
+                              ? 'bg-accent text-accent-foreground border border-accent hover:bg-accent/90'
+                              : 'bg-card border border-border hover:bg-background/50',
+                          )}
+                        >
+                          <HugeiconsIcon icon={TextSquareIcon} size={16} className="h-4 w-4" />
+                        </Button>
+                        <span className="pointer-events-none absolute bottom-full left-1/2 -translate-x-1/2 mb-2 whitespace-nowrap rounded-md bg-popover px-3 py-1.5 text-xs text-popover-foreground border border-border opacity-0 transition-opacity group-hover:opacity-100 z-[9999]">
+                          Fine tune instructions
+                        </span>
+                      </div>
                    </motion.div>
                  )}
                </AnimatePresence>
@@ -1,4 +1,6 @@
-import { Loader2, Mic } from 'lucide-react';
+import { Mic01Icon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Icon } from '@iconify/react';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
 import {
@@ -46,7 +48,11 @@ export function GenerationForm() {
              <FormLabel>Voice Profile</FormLabel>
              {selectedProfile ? (
                <div className="mt-2 p-3 border rounded-md bg-muted/50 flex items-center gap-2">
-                  <Mic className="h-4 w-4 text-muted-foreground" />
+                  <HugeiconsIcon
+                    icon={Mic01Icon}
+                    size={16}
+                    className="h-4 w-4 text-muted-foreground"
+                  />
                  <span className="font-medium">{selectedProfile.name}</span>
                  <span className="text-sm text-muted-foreground">{selectedProfile.language}</span>
                </div>
@@ -170,14 +176,10 @@ export function GenerationForm() {
              />
            </div>

-            <Button
-              type="submit"
-              className="w-full"
-              disabled={isPending || !selectedProfileId}
-            >
+            <Button type="submit" className="w-full" disabled={isPending || !selectedProfileId}>
              {isPending ? (
                <>
-                  <Loader2 className="mr-2 h-4 w-4 animate-spin" />
+                  <Icon icon="svg-spinners:ring-resize" className="mr-2 h-4 w-4 animate-spin" />
                  Generating...
                </>
              ) : (
@@ -1,4 +1,13 @@
-import { AudioWaveform, Download, FileArchive, MoreHorizontal, Play, Trash2 } from 'lucide-react';
+import {
+  Archive01Icon,
+  Delete01Icon,
+  Download01Icon,
+  MoreHorizontalIcon,
+  PlayIcon,
+  WaveIcon,
+} from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Icon } from '@iconify/react';
 import { useEffect, useRef, useState } from 'react';
 import { Button } from '@/components/ui/button';
 import {
@@ -18,6 +27,7 @@ import {
 import { Textarea } from '@/components/ui/textarea';
 import { useToast } from '@/components/ui/use-toast';
 import { apiClient } from '@/lib/api/client';
+import type { HistoryResponse } from '@/lib/api/types';
 import { BOTTOM_SAFE_AREA_PADDING } from '@/lib/constants/ui';
 import {
  useDeleteGeneration,
@@ -33,18 +43,29 @@ import { usePlayerStore } from '@/stores/playerStore';
 // OLD TABLE-BASED COMPONENT - REMOVED (can be found in git history)
 // This is the new alternate history view with fixed height rows

-// NEW ALTERNATE HISTORY VIEW - FIXED HEIGHT ROWS
+// NEW ALTERNATE HISTORY VIEW - FIXED HEIGHT ROWS WITH INFINITE SCROLL
 export function HistoryTable() {
-  const [page, _setPage] = useState(0);
+  const [page, setPage] = useState(0);
+  const [allHistory, setAllHistory] = useState<HistoryResponse[]>([]);
+  const [total, setTotal] = useState(0);
  const [isScrolled, setIsScrolled] = useState(false);
  const scrollRef = useRef<HTMLDivElement>(null);
+  const loadMoreRef = useRef<HTMLDivElement>(null);
  const fileInputRef = useRef<HTMLInputElement>(null);
  const [importDialogOpen, setImportDialogOpen] = useState(false);
  const [selectedFile, setSelectedFile] = useState<File | null>(null);
+  const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
+  const [generationToDelete, setGenerationToDelete] = useState<{ id: string; name: string } | null>(
+    null,
+  );
  const limit = 20;
  const { toast } = useToast();

-  const { data: historyData, isLoading } = useHistory({
+  const {
+    data: historyData,
+    isLoading,
+    isFetching,
+  } = useHistory({
    limit,
    offset: page * limit,
  });
@@ -60,6 +81,56 @@ export function HistoryTable() {
  const audioUrl = usePlayerStore((state) => state.audioUrl);
  const isPlayerVisible = !!audioUrl;

+  // Update accumulated history when new data arrives
+  useEffect(() => {
+    if (historyData?.items) {
+      setTotal(historyData.total);
+      if (page === 0) {
+        // Reset to first page
+        setAllHistory(historyData.items);
+      } else {
+        // Append new items, avoiding duplicates
+        setAllHistory((prev) => {
+          const existingIds = new Set(prev.map((item) => item.id));
+          const newItems = historyData.items.filter((item) => !existingIds.has(item.id));
+          return [...prev, ...newItems];
+        });
+      }
+    }
+  }, [historyData, page]);
+
+  // Reset to page 0 when deletions or imports occur
+  useEffect(() => {
+    if (deleteGeneration.isSuccess || importGeneration.isSuccess) {
+      setPage(0);
+      setAllHistory([]);
+    }
+  }, [deleteGeneration.isSuccess, importGeneration.isSuccess]);
+
+  // Intersection Observer for infinite scroll
+  useEffect(() => {
+    const loadMoreEl = loadMoreRef.current;
+    if (!loadMoreEl) return;
+
+    const observer = new IntersectionObserver(
+      (entries) => {
+        const target = entries[0];
+        if (target.isIntersecting && !isFetching && allHistory.length < total) {
+          setPage((prev) => prev + 1);
+        }
+      },
+      {
+        root: scrollRef.current,
+        rootMargin: '100px',
+        threshold: 0.1,
+      },
+    );
+
+    observer.observe(loadMoreEl);
+    return () => observer.disconnect();
+  }, [isFetching, allHistory.length, total]);
+
+  // Track scroll position for gradient effect
  useEffect(() => {
    const scrollEl = scrollRef.current;
    if (!scrollEl) return;
@@ -113,24 +184,16 @@ export function HistoryTable() {
    );
  };

-  const _handleImportClick = () => {
-    file_handleImportClickk.click();
+  const handleDeleteClick = (generationId: string, profileName: string) => {
+    setGenerationToDelete({ id: generationId, name: profileName });
+    setDeleteDialogOpen(true);
  };

-  const _handleFileChange = (_e: React.ChangeEvent<HTMLInputElement>) => {
-    cons_handleFileChangeet.files?.[0];
-    if (file) {
-      // Validate file extension
-      if (!file.name.endsWith('.voicebox.zip')) {
-        toast({
-          title: 'Invalid file type',
-          description: 'Please select a valid .voicebox.zip file',
-          variant: 'destructive',
-        });
-        return;
-      }
-      setSelectedFile(file);
-      setImportDialogOpen(true);
+  const handleDeleteConfirm = () => {
+    if (generationToDelete) {
+      deleteGeneration.mutate(generationToDelete.id);
+      setDeleteDialogOpen(false);
+      setGenerationToDelete(null);
    }
  };

@@ -159,13 +222,19 @@ export function HistoryTable() {
    }
  };

-  if (isLoading) {
-    return null;
+  if (isLoading && page === 0) {
+    return (
+      <div className="flex items-center justify-center h-full">
+        <Icon
+          icon="svg-spinners:ring-resize"
+          className="h-8 w-8 animate-spin text-muted-foreground"
+        />
+      </div>
+    );
  }

-  const history = historyData?.items || [];
-  const total = historyData?.total || 0;
-  const _hasMore = history.length === limit && (page + 1) * limit < total;
+  const history = allHistory;
+  const hasMore = allHistory.length < total;

  return (
    <div className="flex flex-col h-full min-h-0 relative">
@@ -205,7 +274,11 @@ export function HistoryTable() {
                >
                  {/* Waveform icon */}
                  <div className="flex items-center shrink-0">
-                    <AudioWaveform className="h-5 w-5 text-muted-foreground" />
+                    <HugeiconsIcon
+                      icon={WaveIcon}
+                      size={20}
+                      className="h-5 w-5 text-muted-foreground"
+                    />
                  </div>

                  {/* Left side - Meta information */}
@@ -229,6 +302,7 @@ export function HistoryTable() {
                    <Textarea
                      value={gen.text}
                      className="flex-1 resize-none text-sm text-muted-foreground select-text"
+                      readOnly
                    />
                  </div>

@@ -246,36 +320,35 @@ export function HistoryTable() {
                          className="h-8 w-8"
                          aria-label="Actions"
                        >
-                          <MoreHorizontal className="h-4 w-4" />
+                          <HugeiconsIcon icon={MoreHorizontalIcon} size={16} className="h-4 w-4" />
                        </Button>
                      </DropdownMenuTrigger>
                      <DropdownMenuContent align="end">
                        <DropdownMenuItem
                          onClick={() => handlePlay(gen.id, gen.text, gen.profile_id)}
                        >
-                          <Play className="mr-2 h-4 w-4" />
+                          <HugeiconsIcon icon={PlayIcon} size={16} className="mr-2 h-4 w-4" />
                          Play
                        </DropdownMenuItem>
                        <DropdownMenuItem
                          onClick={() => handleDownloadAudio(gen.id, gen.text)}
                          disabled={exportGenerationAudio.isPending}
                        >
-                          <Download className="mr-2 h-4 w-4" />
+                          <HugeiconsIcon icon={Download01Icon} size={16} className="mr-2 h-4 w-4" />
                          Export Audio
                        </DropdownMenuItem>
                        <DropdownMenuItem
                          onClick={() => handleExportPackage(gen.id, gen.text)}
                          disabled={exportGeneration.isPending}
                        >
-                          <FileArchive className="mr-2 h-4 w-4" />
+                          <HugeiconsIcon icon={Archive01Icon} size={16} className="mr-2 h-4 w-4" />
                          Export Package
                        </DropdownMenuItem>
                        <DropdownMenuItem
-                          onClick={() => deleteGeneration.mutate(gen.id)}
+                          onClick={() => handleDeleteClick(gen.id, gen.profile_name)}
                          disabled={deleteGeneration.isPending}
-                          className="text-destructive focus:text-destructive"
                        >
-                          <Trash2 className="mr-2 h-4 w-4" />
+                          <HugeiconsIcon icon={Delete01Icon} size={16} className="mr-2 h-4 w-4" />
                          Delete
                        </DropdownMenuItem>
                      </DropdownMenuContent>
@@ -284,10 +357,59 @@ export function HistoryTable() {
                </div>
              );
            })}
+
+            {/* Load more trigger element */}
+            {hasMore && (
+              <div ref={loadMoreRef} className="flex items-center justify-center py-4">
+                {isFetching && (
+                  <Icon
+                    icon="svg-spinners:ring-resize"
+                    className="h-6 w-6 animate-spin text-muted-foreground"
+                  />
+                )}
+              </div>
+            )}
+
+            {/* End of list indicator */}
+            {!hasMore && history.length > 0 && (
+              <div className="text-center py-4 text-xs text-muted-foreground">
+                You've reached the end
+              </div>
+            )}
          </div>
        </>
      )}

+      <Dialog open={deleteDialogOpen} onOpenChange={setDeleteDialogOpen}>
+        <DialogContent>
+          <DialogHeader>
+            <DialogTitle>Delete Generation</DialogTitle>
+            <DialogDescription>
+              Are you sure you want to delete this generation from "{generationToDelete?.name}"?
+              This action cannot be undone.
+            </DialogDescription>
+          </DialogHeader>
+          <DialogFooter>
+            <Button
+              variant="outline"
+              onClick={() => {
+                setDeleteDialogOpen(false);
+                setGenerationToDelete(null);
+              }}
+            >
+              Cancel
+            </Button>
+            <Button
+              variant="destructive"
+              onClick={handleDeleteConfirm}
+              disabled={deleteGeneration.isPending}
+            >
+              {deleteGeneration.isPending ? 'Deleting...' : 'Delete'}
+            </Button>
+          </DialogFooter>
+        </DialogContent>
+      </Dialog>
+
      <Dialog open={importDialogOpen} onOpenChange={setImportDialogOpen}>
        <DialogContent>
          <DialogHeader>
@@ -1,4 +1,5 @@
-import { Sparkles, Upload } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { SparklesIcon, Upload01Icon } from '@hugeicons/core-free-icons';
 import { useRef, useState } from 'react';
 import { FloatingGenerateBox } from '@/components/Generation/FloatingGenerateBox';
 import { HistoryTable } from '@/components/History/HistoryTable';
@@ -89,7 +90,7 @@ export function MainEditor() {
            <h2 className="text-2xl font-bold">Voicebox</h2>
            <div className="flex gap-2">
              <Button variant="outline" onClick={handleImportClick}>
-                <Upload className="mr-2 h-4 w-4" />
+                <HugeiconsIcon icon={Upload01Icon} size={16} className="mr-2 h-4 w-4" />
                Import Voice
              </Button>
              <input
@@ -100,7 +101,7 @@ export function MainEditor() {
                className="hidden"
              />
              <Button onClick={() => setDialogOpen(true)}>
-                <Sparkles className="mr-2 h-4 w-4" />
+                <HugeiconsIcon icon={SparklesIcon} size={16} className="mr-2 h-4 w-4" />
                Create Voice
              </Button>
            </div>
@@ -17,7 +17,7 @@ import { Input } from '@/components/ui/input';
 import { Checkbox } from '@/components/ui/checkbox';
 import { useToast } from '@/components/ui/use-toast';
 import { useServerStore } from '@/stores/serverStore';
-import { setKeepServerRunning } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';

 const connectionSchema = z.object({
  serverUrl: z.string().url('Please enter a valid URL'),
@@ -26,6 +26,7 @@ const connectionSchema = z.object({
 type ConnectionFormValues = z.infer<typeof connectionSchema>;

 export function ConnectionForm() {
+  const platform = usePlatform();
  const serverUrl = useServerStore((state) => state.serverUrl);
  const setServerUrl = useServerStore((state) => state.setServerUrl);
  const keepServerRunningOnClose = useServerStore((state) => state.keepServerRunningOnClose);
@@ -89,7 +90,7 @@ export function ConnectionForm() {
              checked={keepServerRunningOnClose}
              onCheckedChange={(checked: boolean) => {
                setKeepServerRunningOnClose(checked);
-                setKeepServerRunning(checked).catch((error) => {
+                platform.lifecycle.setKeepServerRunning(checked).catch((error) => {
                  console.error('Failed to sync setting to Rust:', error);
                });
                toast({
@@ -0,0 +1,112 @@
+import { Folder01Icon, FolderOpenIcon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Icon } from '@iconify/react';
+import { Button } from '@/components/ui/button';
+import { Card, CardContent, CardDescription, CardHeader, CardTitle } from '@/components/ui/card';
+import { Input } from '@/components/ui/input';
+import { useSystemFolders } from '@/lib/hooks/useSystemFolders';
+import { usePlatform } from '@/platform/PlatformContext';
+
+interface FolderRowProps {
+  label: string;
+  description: string;
+  path: string | undefined;
+  isLoading: boolean;
+  canOpen: boolean;
+  onOpen: () => void;
+}
+
+function FolderRow({ label, description, path, isLoading, canOpen, onOpen }: FolderRowProps) {
+  return (
+    <div className="space-y-1.5">
+      <div className="flex items-center justify-between">
+        <div>
+          <div className="text-sm font-medium">{label}</div>
+          <div className="text-xs text-muted-foreground">{description}</div>
+        </div>
+        {canOpen && path && (
+          <Button
+            variant="outline"
+            size="sm"
+            onClick={onOpen}
+            disabled={isLoading || !path}
+            className="shrink-0"
+          >
+            <HugeiconsIcon icon={FolderOpenIcon} size={16} className="h-4 w-4 mr-2" />
+            Open
+          </Button>
+        )}
+      </div>
+      <Input
+        value={isLoading ? 'Loading...' : path || 'Not available'}
+        readOnly
+        className="font-mono text-xs text-muted-foreground select-all cursor-text"
+      />
+    </div>
+  );
+}
+
+export function DataFolders() {
+  const { data: folders, isLoading, error } = useSystemFolders();
+  const platform = usePlatform();
+  const isTauri = platform.metadata.isTauri;
+
+  const handleOpenFolder = async (path: string | undefined) => {
+    if (!path) return;
+    const success = await platform.filesystem.openFolder(path);
+    if (!success && isTauri) {
+      console.error('Failed to open folder:', path);
+    }
+  };
+
+  return (
+    <Card>
+      <CardHeader>
+        <CardTitle className="flex items-center gap-2">
+          <HugeiconsIcon icon={Folder01Icon} size={20} className="h-5 w-5" />
+          Data Folders
+        </CardTitle>
+        <CardDescription>
+          {isTauri
+            ? 'Click "Open" to view folders in your file explorer, or copy the paths below.'
+            : 'These are the server-side folder paths where your data is stored.'}
+        </CardDescription>
+      </CardHeader>
+      <CardContent className="space-y-4">
+        {error ? (
+          <div className="flex items-center gap-2 text-sm text-destructive">
+            <Icon icon="lucide:alert-circle" className="h-4 w-4" />
+            <span>Failed to load folder paths: {error.message}</span>
+          </div>
+        ) : (
+          <>
+            <FolderRow
+              label="App Data"
+              description="Voices, generations, and app database"
+              path={folders?.data_dir}
+              isLoading={isLoading}
+              canOpen={isTauri}
+              onOpen={() => handleOpenFolder(folders?.data_dir)}
+            />
+            <FolderRow
+              label="Models"
+              description="Downloaded AI models from HuggingFace Hub"
+              path={folders?.models_dir}
+              isLoading={isLoading}
+              canOpen={isTauri}
+              onOpen={() => handleOpenFolder(folders?.models_dir)}
+            />
+            <FolderRow
+              label="Providers"
+              description="External TTS provider binaries (PyTorch CPU/CUDA)"
+              path={folders?.providers_dir}
+              isLoading={isLoading}
+              canOpen={isTauri}
+              onOpen={() => handleOpenFolder(folders?.providers_dir)}
+            />
+          </>
+        )}
+      </CardContent>
+    </Card>
+  );
+}
@@ -1,6 +1,8 @@
+import { Delete01Icon, Download01Icon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Icon } from '@iconify/react';
 import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
-import { Download, Loader2, Trash2 } from 'lucide-react';
-import { useState } from 'react';
+import { useCallback, useState } from 'react';
 import {
  AlertDialog,
  AlertDialogAction,
@@ -17,7 +19,6 @@ import { Card, CardContent, CardDescription, CardHeader, CardTitle } from '@/com
 import { useToast } from '@/components/ui/use-toast';
 import { apiClient } from '@/lib/api/client';
 import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
-import { ModelProgress } from './ModelProgress';

 export function ModelManagement() {
  const { toast } = useToast();
@@ -27,15 +28,36 @@ export function ModelManagement() {

  const { data: modelStatus, isLoading } = useQuery({
    queryKey: ['modelStatus'],
-    queryFn: () => apiClient.getModelStatus(),
+    queryFn: async () => {
+      console.log('[Query] Fetching model status');
+      const result = await apiClient.getModelStatus();
+      console.log('[Query] Model status fetched:', result);
+      return result;
+    },
    refetchInterval: 5000, // Refresh every 5 seconds
  });

+  // Callbacks for download completion
+  const handleDownloadComplete = useCallback(() => {
+    console.log('[ModelManagement] Download complete, clearing state');
+    setDownloadingModel(null);
+    setDownloadingDisplayName(null);
+    queryClient.invalidateQueries({ queryKey: ['modelStatus'] });
+  }, [queryClient]);
+
+  const handleDownloadError = useCallback(() => {
+    console.log('[ModelManagement] Download error, clearing state');
+    setDownloadingModel(null);
+    setDownloadingDisplayName(null);
+  }, []);
+
  // Use progress toast hook for the downloading model
  useModelDownloadToast({
    modelName: downloadingModel || '',
    displayName: downloadingDisplayName || '',
    enabled: !!downloadingModel && !!downloadingDisplayName,
+    onComplete: handleDownloadComplete,
+    onError: handleDownloadError,
  });

  const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
@@ -45,44 +67,69 @@ export function ModelManagement() {
    sizeMb?: number;
  } | null>(null);

-  const downloadMutation = useMutation({
-    mutationFn: (modelName: string) => {
+  const handleDownload = async (modelName: string) => {
+    console.log('[Download] Button clicked for:', modelName, 'at', new Date().toISOString());
+
+    // Find display name
+    const model = modelStatus?.models.find((m) => m.model_name === modelName);
+    const displayName = model?.display_name || modelName;
+
+    try {
+      // IMPORTANT: Call the API FIRST before setting state
+      // Setting state enables the SSE EventSource in useModelDownloadToast,
+      // which can block/delay the download fetch due to HTTP/1.1 connection limits
+      console.log('[Download] Calling download API for:', modelName);
+      const result = await apiClient.triggerModelDownload(modelName);
+      console.log('[Download] Download API responded:', result);
+
+      // NOW set state to enable SSE tracking (after download has started on backend)
      setDownloadingModel(modelName);
-      // Find display name from model status
-      const model = modelStatus?.models.find((m) => m.model_name === modelName);
-      setDownloadingDisplayName(model?.display_name || modelName);
-      return apiClient.triggerModelDownload(modelName);
-    },
-    onSuccess: () => {
-      // Download completed - clear state and refetch status
-      setDownloadingModel(null);
-      setDownloadingDisplayName(null);
+      setDownloadingDisplayName(displayName);
+
+      // Download initiated successfully - state will be cleared when SSE reports completion
+      // or by the polling interval detecting the model is downloaded
      queryClient.invalidateQueries({ queryKey: ['modelStatus'] });
-    },
-    onError: (error: Error) => {
+    } catch (error) {
+      console.error('[Download] Download failed:', error);
      setDownloadingModel(null);
      setDownloadingDisplayName(null);
      toast({
        title: 'Download failed',
-        description: error.message,
+        description: error instanceof Error ? error.message : 'Unknown error',
        variant: 'destructive',
      });
-    },
-  });
+    }
+  };

  const deleteMutation = useMutation({
-    mutationFn: (modelName: string) => apiClient.deleteModel(modelName),
-    onSuccess: () => {
+    mutationFn: async (modelName: string) => {
+      console.log('[Delete] Deleting model:', modelName);
+      const result = await apiClient.deleteModel(modelName);
+      console.log('[Delete] Model deleted successfully:', modelName);
+      return result;
+    },
+    onSuccess: async (_data, _modelName) => {
+      console.log('[Delete] onSuccess - showing toast and invalidating queries');
      toast({
        title: 'Model deleted',
        description: `${modelToDelete?.displayName || 'Model'} has been deleted successfully.`,
      });
      setDeleteDialogOpen(false);
      setModelToDelete(null);
-      // Refetch status to update UI
-      queryClient.invalidateQueries({ queryKey: ['modelStatus'] });
+      // Invalidate AND explicitly refetch to ensure UI updates
+      // Using refetchType: 'all' ensures we refetch even if the query is stale
+      console.log('[Delete] Invalidating modelStatus query');
+      await queryClient.invalidateQueries({
+        queryKey: ['modelStatus'],
+        refetchType: 'all',
+      });
+      // Also explicitly refetch to guarantee fresh data
+      console.log('[Delete] Explicitly refetching modelStatus query');
+      await queryClient.refetchQueries({ queryKey: ['modelStatus'] });
+      console.log('[Delete] Query refetched');
    },
    onError: (error: Error) => {
+      console.log('[Delete] onError:', error);
      toast({
        title: 'Delete failed',
        description: error.message,
@@ -108,7 +155,10 @@ export function ModelManagement() {
      <CardContent className="space-y-4">
        {isLoading ? (
          <div className="flex items-center justify-center py-8">
-            <Loader2 className="h-6 w-6 animate-spin text-muted-foreground" />
+            <Icon
+              icon="svg-spinners:ring-resize"
+              className="h-6 w-6 animate-spin text-muted-foreground"
+            />
          </div>
        ) : modelStatus ? (
          <div className="space-y-4">
@@ -124,7 +174,7 @@ export function ModelManagement() {
                    <ModelItem
                      key={model.model_name}
                      model={model}
-                      onDownload={() => downloadMutation.mutate(model.model_name)}
+                      onDownload={() => handleDownload(model.model_name)}
                      onDelete={() => {
                        setModelToDelete({
                          name: model.model_name,
@@ -152,7 +202,7 @@ export function ModelManagement() {
                    <ModelItem
                      key={model.model_name}
                      model={model}
-                      onDownload={() => downloadMutation.mutate(model.model_name)}
+                      onDownload={() => handleDownload(model.model_name)}
                      onDelete={() => {
                        setModelToDelete({
                          name: model.model_name,
@@ -167,22 +217,6 @@ export function ModelManagement() {
                  ))}
              </div>
            </div>
-
-            {/* Progress indicators */}
-            <div className="pt-4 border-t">
-              <h3 className="text-sm font-semibold mb-3 text-muted-foreground">
-                Download Progress
-              </h3>
-              <div className="space-y-2">
-                {modelStatus.models.map((model) => (
-                  <ModelProgress
-                    key={model.model_name}
-                    modelName={model.model_name}
-                    displayName={model.display_name}
-                  />
-                ))}
-              </div>
-            </div>
          </div>
        ) : null}
      </CardContent>
@@ -216,7 +250,7 @@ export function ModelManagement() {
            >
              {deleteMutation.isPending ? (
                <>
-                  <Loader2 className="h-4 w-4 mr-2 animate-spin" />
+                  <Icon icon="svg-spinners:ring-resize" className="h-4 w-4 mr-2 animate-spin" />
                  Deleting...
                </>
              ) : (
@@ -235,16 +269,20 @@ interface ModelItemProps {
    model_name: string;
    display_name: string;
    downloaded: boolean;
+    downloading?: boolean; // From server - true if download in progress
    size_mb?: number;
    loaded: boolean;
  };
  onDownload: () => void;
  onDelete: () => void;
-  isDownloading: boolean;
+  isDownloading: boolean; // Local state - true if user just clicked download
  formatSize: (sizeMb?: number) => string;
 }

 function ModelItem({ model, onDownload, onDelete, isDownloading, formatSize }: ModelItemProps) {
+  // Use server's downloading state OR local state (for immediate feedback before server updates)
+  const showDownloading = model.downloading || isDownloading;
+
  return (
    <div className="flex items-center justify-between p-3 border rounded-lg">
      <div className="flex-1">
@@ -255,20 +293,21 @@ function ModelItem({ model, onDownload, onDelete, isDownloading, formatSize }: M
              Loaded
            </Badge>
          )}
-          {model.downloaded && !model.loaded && (
+          {/* Only show Downloaded if actually downloaded AND not downloading */}
+          {model.downloaded && !model.loaded && !showDownloading && (
            <Badge variant="secondary" className="text-xs">
              Downloaded
            </Badge>
          )}
        </div>
-        {model.downloaded && model.size_mb && (
+        {model.downloaded && model.size_mb && !showDownloading && (
          <div className="text-xs text-muted-foreground mt-1">
            Size: {formatSize(model.size_mb)}
          </div>
        )}
      </div>
      <div className="flex items-center gap-2">
-        {model.downloaded ? (
+        {model.downloaded && !showDownloading ? (
          <div className="flex items-center gap-2">
            <div className="flex items-center gap-1 text-sm text-muted-foreground">
              <span>Ready</span>
@@ -280,22 +319,18 @@ function ModelItem({ model, onDownload, onDelete, isDownloading, formatSize }: M
              disabled={model.loaded}
              title={model.loaded ? 'Unload model before deleting' : 'Delete model'}
            >
-              <Trash2 className="h-4 w-4" />
+              <HugeiconsIcon icon={Delete01Icon} size={16} className="h-4 w-4" />
            </Button>
          </div>
+        ) : showDownloading ? (
+          <Button size="sm" variant="outline" disabled>
+            <Icon icon="svg-spinners:ring-resize" className="h-4 w-4 mr-2 animate-spin" />
+            Downloading...
+          </Button>
        ) : (
-          <Button size="sm" onClick={onDownload} disabled={isDownloading} variant="outline">
-            {isDownloading ? (
-              <>
-                <Loader2 className="h-4 w-4 mr-2 animate-spin" />
-                Downloading...
-              </>
-            ) : (
-              <>
-                <Download className="h-4 w-4 mr-2" />
-                Download
-              </>
-            )}
+          <Button size="sm" onClick={onDownload} variant="outline">
+            <HugeiconsIcon icon={Download01Icon} size={16} className="h-4 w-4 mr-2" />
+            Download
          </Button>
        )}
      </div>
@@ -1,4 +1,6 @@
-import { Loader2, XCircle } from 'lucide-react';
+import { CancelCircleIcon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Icon } from '@iconify/react';
 import { useEffect, useState } from 'react';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
 import { Progress } from '@/components/ui/progress';
@@ -8,14 +10,27 @@ import { useServerStore } from '@/stores/serverStore';
 interface ModelProgressProps {
  modelName: string;
  displayName: string;
+  /** Only connect to SSE when actively downloading - prevents connection exhaustion */
+  isDownloading?: boolean;
 }

-export function ModelProgress({ modelName, displayName }: ModelProgressProps) {
+export function ModelProgress({
+  modelName,
+  displayName,
+  isDownloading = false,
+}: ModelProgressProps) {
  const [progress, setProgress] = useState<ModelProgressType | null>(null);
  const serverUrl = useServerStore((state) => state.serverUrl);

  useEffect(() => {
-    if (!serverUrl) return;
+    // IMPORTANT: Only connect to SSE when this specific model is downloading
+    // Opening SSE connections for all models exhausts HTTP/1.1 connection limits (6 per origin)
+    // which causes other fetches (like the download trigger) to be queued/blocked
+    if (!serverUrl || !isDownloading) {
+      return;
+    }
+
+    console.log(`[ModelProgress] Connecting SSE for ${modelName}`);

    // Subscribe to progress updates via Server-Sent Events
    const eventSource = new EventSource(`${serverUrl}/models/progress/${modelName}`);
@@ -27,6 +42,7 @@ export function ModelProgress({ modelName, displayName }: ModelProgressProps) {

        // Close connection if complete or error
        if (data.status === 'complete' || data.status === 'error') {
+          console.log(`[ModelProgress] Download ${data.status} for ${modelName}, closing SSE`);
          eventSource.close();
        }
      } catch (error) {
@@ -35,14 +51,15 @@ export function ModelProgress({ modelName, displayName }: ModelProgressProps) {
    };

    eventSource.onerror = (error) => {
-      console.error('SSE error:', error);
+      console.error(`[ModelProgress] SSE error for ${modelName}:`, error);
      eventSource.close();
    };

    return () => {
+      console.log(`[ModelProgress] Cleanup - closing SSE for ${modelName}`);
      eventSource.close();
    };
-  }, [serverUrl, modelName]);
+  }, [serverUrl, modelName, isDownloading]);

  // Don't render if no progress or if complete/error and some time has passed
  if (
@@ -63,10 +80,12 @@ export function ModelProgress({ modelName, displayName }: ModelProgressProps) {
  const getStatusIcon = () => {
    switch (progress.status) {
      case 'error':
-        return <XCircle className="h-4 w-4 text-destructive" />;
+        return (
+          <HugeiconsIcon icon={CancelCircleIcon} size={16} className="h-4 w-4 text-destructive" />
+        );
      case 'downloading':
      case 'extracting':
-        return <Loader2 className="h-4 w-4 animate-spin" />;
+        return <Icon icon="svg-spinners:ring-resize" className="h-4 w-4 animate-spin" />;
      default:
        return null;
    }
@@ -0,0 +1,400 @@
+import { Delete01Icon, Download01Icon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Icon } from '@iconify/react';
+import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
+import { useCallback, useState } from 'react';
+import {
+  AlertDialog,
+  AlertDialogAction,
+  AlertDialogCancel,
+  AlertDialogContent,
+  AlertDialogDescription,
+  AlertDialogFooter,
+  AlertDialogHeader,
+  AlertDialogTitle,
+} from '@/components/ui/alert-dialog';
+import { Button } from '@/components/ui/button';
+import { Card, CardContent, CardDescription, CardHeader, CardTitle } from '@/components/ui/card';
+import { Label } from '@/components/ui/label';
+import { RadioGroup, RadioGroupItem } from '@/components/ui/radio-group';
+import { useToast } from '@/components/ui/use-toast';
+import { apiClient } from '@/lib/api/client';
+import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
+
+const isMacOS = () => navigator.platform.toLowerCase().includes('mac');
+const isWindows = () => navigator.platform.toLowerCase().includes('win');
+const getPlatformName = () => {
+  if (isMacOS()) return 'macOS';
+  if (isWindows()) return 'Windows';
+  return 'Linux';
+};
+
+type ProviderType =
+  | 'auto'
+  | 'apple-mlx'
+  | 'bundled-pytorch'
+  | 'pytorch-cpu'
+  | 'pytorch-cuda'
+  | 'remote'
+  | 'openai';
+
+export function ProviderSettings() {
+  const { toast } = useToast();
+  const queryClient = useQueryClient();
+  const [downloadingProvider, setDownloadingProvider] = useState<string | null>(null);
+
+  const { data: providersData, isLoading } = useQuery({
+    queryKey: ['providers'],
+    queryFn: async () => {
+      return await apiClient.listProviders();
+    },
+    refetchInterval: 5000,
+  });
+
+  const { data: activeProvider } = useQuery({
+    queryKey: ['activeProvider'],
+    queryFn: async () => {
+      return await apiClient.getActiveProvider();
+    },
+    refetchInterval: 5000,
+  });
+
+  // Callbacks for download completion
+  const handleDownloadComplete = useCallback(() => {
+    setDownloadingProvider(null);
+    queryClient.invalidateQueries({ queryKey: ['providers'] });
+  }, [queryClient]);
+
+  const handleDownloadError = useCallback(() => {
+    setDownloadingProvider(null);
+  }, []);
+
+  // Use progress toast hook for the downloading provider
+  useModelDownloadToast({
+    modelName: downloadingProvider || '',
+    displayName: downloadingProvider || '',
+    enabled: !!downloadingProvider,
+    onComplete: handleDownloadComplete,
+    onError: handleDownloadError,
+  });
+
+  const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
+  const [providerToDelete, setProviderToDelete] = useState<string | null>(null);
+
+  const downloadMutation = useMutation({
+    mutationFn: async (providerType: string) => {
+      return await apiClient.downloadProvider(providerType);
+    },
+    onSuccess: (_, providerType) => {
+      setDownloadingProvider(providerType);
+      queryClient.invalidateQueries({ queryKey: ['providers'] });
+    },
+    onError: (error: Error) => {
+      toast({
+        title: 'Download failed',
+        description: error.message,
+        variant: 'destructive',
+      });
+    },
+  });
+
+  const startMutation = useMutation({
+    mutationFn: async (providerType: string) => {
+      return await apiClient.startProvider(providerType);
+    },
+    onSuccess: () => {
+      queryClient.invalidateQueries({ queryKey: ['activeProvider'] });
+      toast({
+        title: 'Provider started',
+        description: 'The provider has been started successfully',
+      });
+    },
+    onError: (error: Error) => {
+      toast({
+        title: 'Failed to start provider',
+        description: error.message,
+        variant: 'destructive',
+      });
+    },
+  });
+
+  const deleteMutation = useMutation({
+    mutationFn: async (providerType: string) => {
+      return await apiClient.deleteProvider(providerType);
+    },
+    onSuccess: () => {
+      queryClient.invalidateQueries({ queryKey: ['providers'] });
+      toast({
+        title: 'Provider deleted',
+        description: 'The provider has been deleted successfully',
+      });
+    },
+    onError: (error: Error) => {
+      toast({
+        title: 'Failed to delete provider',
+        description: error.message,
+        variant: 'destructive',
+      });
+    },
+  });
+
+  const handleDownload = async (providerType: string) => {
+    downloadMutation.mutate(providerType);
+  };
+
+  const handleStart = async (providerType: string) => {
+    startMutation.mutate(providerType);
+  };
+
+  const handleDelete = (providerType: string) => {
+    setProviderToDelete(providerType);
+    setDeleteDialogOpen(true);
+  };
+
+  const confirmDelete = () => {
+    if (providerToDelete) {
+      deleteMutation.mutate(providerToDelete);
+      setDeleteDialogOpen(false);
+      setProviderToDelete(null);
+    }
+  };
+
+  if (isLoading) {
+    return (
+      <Card>
+        <CardHeader>
+          <CardTitle>TTS Provider</CardTitle>
+          <CardDescription>Choose how Voicebox generates speech</CardDescription>
+        </CardHeader>
+        <CardContent>
+          <div className="flex items-center justify-center py-8">
+            <Icon icon="svg-spinners:ring-resize" className="h-6 w-6 animate-spin" />
+          </div>
+        </CardContent>
+      </Card>
+    );
+  }
+
+  const installedProviders = providersData?.installed || [];
+
+  // Determine current active provider
+  const currentProvider = activeProvider?.provider;
+  console.log('currentProvider', currentProvider);
+  const selectedProvider = currentProvider as ProviderType;
+
+  const isStarting = startMutation.isPending;
+
+  return (
+    <>
+      <Card>
+        <CardHeader>
+          <CardTitle>TTS Provider</CardTitle>
+          <CardDescription>Choose how Voicebox generates speech.</CardDescription>
+        </CardHeader>
+        <CardContent className="relative">
+          {isStarting && (
+            <div className="absolute inset-0 bg-background/80 backdrop-blur-sm flex items-center justify-center z-10 rounded-lg">
+              <div className="flex items-center gap-2 text-muted-foreground">
+                <Icon icon="svg-spinners:ring-resize" className="h-5 w-5" />
+                <span>Starting provider...</span>
+              </div>
+            </div>
+          )}
+          <RadioGroup
+            value={selectedProvider}
+            onValueChange={(value) => handleStart(value)}
+            disabled={isStarting}
+          >
+            {/* PyTorch CUDA */}
+            <div className="flex items-center justify-between py-2">
+              <div className={`flex items-center space-x-3 flex-1 ${isMacOS() || !installedProviders.includes('pytorch-cuda') ? 'opacity-50' : ''}`}>
+                <RadioGroupItem value="pytorch-cuda" id="cuda" disabled={isMacOS() || isStarting || !installedProviders.includes('pytorch-cuda')} />
+                <Label
+                  htmlFor="cuda"
+                  className={`flex-1 ${isMacOS() || isStarting || !installedProviders.includes('pytorch-cuda') ? 'cursor-not-allowed' : 'cursor-pointer'}`}
+                >
+                  <div className="font-medium">PyTorch CUDA</div>
+                  <div className="text-sm text-muted-foreground">
+                    NVIDIA GPU-accelerated provider
+                  </div>
+                </Label>
+              </div>
+              <div className="flex items-center gap-2">
+                {isMacOS() && (
+                  <>
+                    <span className="text-xs text-muted-foreground">2.4GB</span>
+                    <Button size="sm" variant="secondary" disabled>
+                      Not Available on macOS
+                    </Button>
+                  </>
+                )}
+                {!isMacOS() && !installedProviders.includes('pytorch-cuda') && (
+                  <>
+                    <span className="text-xs text-muted-foreground">2.4GB</span>
+                    <Button
+                      onClick={() => handleDownload('pytorch-cuda')}
+                      size="sm"
+                      variant="outline"
+                      disabled={downloadingProvider === 'pytorch-cuda' || isStarting}
+                      className="shrink-0"
+                    >
+                      {downloadingProvider === 'pytorch-cuda' ? (
+                        <Icon icon="svg-spinners:ring-resize" className="h-4 w-4 animate-spin" />
+                      ) : (
+                        <>
+                          <HugeiconsIcon icon={Download01Icon} size={16} className="h-4 w-4 mr-2" />
+                          Download
+                        </>
+                      )}
+                    </Button>
+                  </>
+                )}
+                {installedProviders.includes('pytorch-cuda') && (
+                  <Button
+                    onClick={() => handleDelete('pytorch-cuda')}
+                    size="sm"
+                    variant="outline"
+                    disabled={isStarting}
+                    className="shrink-0"
+                  >
+                    <HugeiconsIcon icon={Delete01Icon} size={16} className="h-4 w-4 mr-2" />
+                    Uninstall
+                  </Button>
+                )}
+              </div>
+            </div>
+
+            {/* PyTorch CPU */}
+            <div className="flex items-center justify-between py-2">
+              <div className={`flex items-center space-x-3 flex-1 ${!installedProviders.includes('pytorch-cpu') ? 'opacity-50' : ''}`}>
+                <RadioGroupItem value="pytorch-cpu" id="cpu" disabled={isStarting || !installedProviders.includes('pytorch-cpu')} />
+                <Label
+                  htmlFor="cpu"
+                  className={`flex-1 ${isStarting || !installedProviders.includes('pytorch-cpu') ? 'cursor-not-allowed' : 'cursor-pointer'}`}
+                >
+                  <div className="font-medium">PyTorch CPU</div>
+                  <div className="text-sm text-muted-foreground">
+                    Works on any system, slower inference
+                  </div>
+                </Label>
+              </div>
+              <div className="flex items-center gap-2">
+                {!installedProviders.includes('pytorch-cpu') && (
+                  <>
+                    <span className="text-xs text-muted-foreground">242MB</span>
+                    <Button
+                      onClick={() => handleDownload('pytorch-cpu')}
+                      size="sm"
+                      variant="outline"
+                      disabled={downloadingProvider === 'pytorch-cpu' || isStarting}
+                      className="shrink-0"
+                    >
+                      {downloadingProvider === 'pytorch-cpu' ? (
+                        <Icon icon="svg-spinners:ring-resize" className="h-4 w-4 animate-spin" />
+                      ) : (
+                        <>
+                          <HugeiconsIcon icon={Download01Icon} size={16} className="h-4 w-4 mr-2" />
+                          Download
+                        </>
+                      )}
+                    </Button>
+                  </>
+                )}
+                {installedProviders.includes('pytorch-cpu') && (
+                  <Button
+                    onClick={() => handleDelete('pytorch-cpu')}
+                    size="sm"
+                    variant="outline"
+                    disabled={isStarting}
+                    className="shrink-0"
+                  >
+                    <HugeiconsIcon icon={Delete01Icon} size={16} className="h-4 w-4 mr-2" />
+                    Uninstall
+                  </Button>
+                )}
+              </div>
+            </div>
+
+            {/* MLX bundled (macOS Apple Silicon only) */}
+            <div className="flex items-center justify-between py-2">
+              <div className={`flex items-center space-x-3 flex-1 ${!isMacOS() ? 'opacity-50' : ''}`}>
+                <RadioGroupItem value="apple-mlx" id="mlx" disabled={isStarting || !isMacOS()} />
+                <Label
+                  htmlFor="mlx"
+                  className={`flex-1 ${isStarting || !isMacOS() ? 'cursor-not-allowed' : 'cursor-pointer'}`}
+                >
+                  <div className="font-medium">Apple MLX</div>
+                  <div className="text-sm text-muted-foreground">
+                    {isMacOS()
+                      ? 'Bundled with this version, optimized for Apple Silicon'
+                      : 'Only available on Apple Silicon'}
+                  </div>
+                </Label>
+              </div>
+              {!isMacOS() && (
+                <Button size="sm" variant="secondary" disabled>
+                  Not Available on {getPlatformName()}
+                </Button>
+              )}
+            </div>
+
+            {/* Remote */}
+            <div className="flex items-center justify-between py-2">
+              <div className="flex items-center space-x-3 flex-1 opacity-50">
+                <RadioGroupItem value="remote" id="remote" disabled />
+                <Label htmlFor="remote" className="flex-1 cursor-not-allowed">
+                  <div className="font-medium">Remote Server</div>
+                  <div className="text-sm text-muted-foreground">
+                    Connect to your own TTS server
+                  </div>
+                </Label>
+              </div>
+              <Button size="sm" variant="secondary" disabled>
+                Coming Soon
+              </Button>
+            </div>
+
+            {/* OpenAI */}
+            <div className="flex items-center justify-between py-2">
+              <div className="flex items-center space-x-3 flex-1 opacity-50">
+                <RadioGroupItem value="openai" id="openai" disabled />
+                <Label htmlFor="openai" className="flex-1 cursor-not-allowed">
+                  <div className="font-medium">OpenAI API</div>
+                  <div className="text-sm text-muted-foreground">Use OpenAI's TTS API</div>
+                </Label>
+              </div>
+              <Button size="sm" variant="secondary" disabled>
+                Coming Soon
+              </Button>
+            </div>
+          </RadioGroup>
+          <p className="text-xs text-muted-foreground mt-5">
+            Note: PyTorch and MLX use different versions of the same model. When switching between
+            them, you will need to redownload the model.
+          </p>
+        </CardContent>
+      </Card>
+
+      <AlertDialog open={deleteDialogOpen} onOpenChange={setDeleteDialogOpen}>
+        <AlertDialogContent>
+          <AlertDialogHeader>
+            <AlertDialogTitle>Delete Provider</AlertDialogTitle>
+            <AlertDialogDescription>
+              Are you sure you want to delete {providerToDelete}? This will remove the provider
+              binary from your system. You can download it again later if needed.
+            </AlertDialogDescription>
+          </AlertDialogHeader>
+          <AlertDialogFooter>
+            <AlertDialogCancel>Cancel</AlertDialogCancel>
+            <AlertDialogAction
+              onClick={confirmDelete}
+              className="bg-destructive text-destructive-foreground"
+            >
+              Delete
+            </AlertDialogAction>
+          </AlertDialogFooter>
+        </AlertDialogContent>
+      </AlertDialog>
+    </>
+  );
+}
@@ -1,4 +1,6 @@
-import { Loader2, XCircle } from 'lucide-react';
+import { CancelCircleIcon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Icon } from '@iconify/react';
 import { Badge } from '@/components/ui/badge';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
 import { useServerHealth } from '@/lib/hooks/useServer';
@@ -32,12 +34,12 @@ export function ServerStatus() {

        {isLoading ? (
          <div className="flex items-center gap-2">
-            <Loader2 className="h-4 w-4 animate-spin" />
+            <Icon icon="svg-spinners:ring-resize" className="h-4 w-4 animate-spin" />
            <span className="text-sm">Checking connection...</span>
          </div>
        ) : error ? (
          <div className="flex items-center gap-2">
-            <XCircle className="h-4 w-4 text-destructive" />
+            <HugeiconsIcon icon={CancelCircleIcon} size={16} className="h-4 w-4 text-destructive" />
            <span className="text-sm text-destructive">Connection failed: {error.message}</span>
          </div>
        ) : health ? (
@@ -1,21 +1,24 @@
-import { getVersion } from '@tauri-apps/api/app';
-import { AlertCircle, Download, RefreshCw } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { AlertCircleIcon, Download01Icon, Refresh01Icon } from '@hugeicons/core-free-icons';
 import { useEffect, useState } from 'react';
 import { Badge } from '@/components/ui/badge';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
 import { Progress } from '@/components/ui/progress';
 import { useAutoUpdater } from '@/hooks/useAutoUpdater';
+import { usePlatform } from '@/platform/PlatformContext';

 export function UpdateStatus() {
+  const platform = usePlatform();
  const { status, checkForUpdates, downloadAndInstall, restartAndInstall } = useAutoUpdater(false);
  const [currentVersion, setCurrentVersion] = useState<string>('');

  useEffect(() => {
-    getVersion()
+    platform.metadata
+      .getVersion()
      .then(setCurrentVersion)
-      .catch(() => setCurrentVersion('0.1.0'));
-  }, []);
+      .catch(() => setCurrentVersion('Unknown'));
+  }, [platform]);

  return (
    <Card>
@@ -34,21 +37,21 @@ export function UpdateStatus() {
            variant="outline"
            size="sm"
          >
-            <RefreshCw className={`h-4 w-4 mr-2 ${status.checking ? 'animate-spin' : ''}`} />
+            <HugeiconsIcon icon={Refresh01Icon} size={16} className={`h-4 w-4 mr-2 ${status.checking ? 'animate-spin' : ''}`} />
            Check for Updates
          </Button>
        </div>

        {status.checking && (
          <div className="flex items-center gap-2 text-sm text-muted-foreground">
-            <RefreshCw className="h-4 w-4 animate-spin" />
+            <HugeiconsIcon icon={Refresh01Icon} size={16} className="h-4 w-4 animate-spin" />
            Checking for updates...
          </div>
        )}

        {status.error && (
          <div className="flex items-center gap-2 text-sm text-destructive">
-            <AlertCircle className="h-4 w-4" />
+            <HugeiconsIcon icon={AlertCircleIcon} size={16} className="h-4 w-4" />
            {status.error}
          </div>
        )}
@@ -63,7 +66,7 @@ export function UpdateStatus() {
              <Badge>New</Badge>
            </div>
            <Button onClick={downloadAndInstall} className="w-full" size="sm">
-              <Download className="h-4 w-4 mr-2" />
+              <HugeiconsIcon icon={Download01Icon} size={16} className="h-4 w-4 mr-2" />
              Download Update
            </Button>
          </div>
@@ -73,7 +76,7 @@ export function UpdateStatus() {
          <div className="space-y-2">
            <div className="flex items-center justify-between text-sm">
              <div className="flex items-center gap-2">
-                <Download className="h-4 w-4" />
+                <HugeiconsIcon icon={Download01Icon} size={16} className="h-4 w-4" />
                Downloading update...
              </div>
              {status.downloadProgress !== undefined && (
@@ -107,7 +110,7 @@ export function UpdateStatus() {
              your convenience.
            </div>
            <Button onClick={restartAndInstall} className="w-full" size="sm">
-              <RefreshCw className="h-4 w-4 mr-2" />
+              <HugeiconsIcon icon={Refresh01Icon} size={16} className="h-4 w-4 mr-2" />
              Restart Now
            </Button>
          </div>
@@ -1,16 +1,21 @@
 import { ConnectionForm } from '@/components/ServerSettings/ConnectionForm';
+import { DataFolders } from '@/components/ServerSettings/DataFolders';
+import { ProviderSettings } from '@/components/ServerSettings/ProviderSettings';
 import { ServerStatus } from '@/components/ServerSettings/ServerStatus';
 import { UpdateStatus } from '@/components/ServerSettings/UpdateStatus';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';

 export function ServerTab() {
+  const platform = usePlatform();
  return (
    <div className="space-y-4 overflow-y-auto flex flex-col">
      <div className="grid gap-4 md:grid-cols-2">
        <ConnectionForm />
        <ServerStatus />
      </div>
-      {isTauri() && <UpdateStatus />}
+      <ProviderSettings />
+      <DataFolders />
+      {platform.metadata.isTauri && <UpdateStatus />}
      <div className="py-8 text-center text-sm text-muted-foreground">
        Created by{' '}
        <a
@@ -1,5 +1,14 @@
+import {
+  Book01Icon,
+  Mic01Icon,
+  PackageIcon,
+  ServerStack01Icon,
+  SpeakerIcon,
+  VolumeHighIcon,
+} from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Icon } from '@iconify/react';
 import { Link, useMatchRoute } from '@tanstack/react-router';
-import { Box, BookOpen, Loader2, Mic, Server, Speaker, Volume2 } from 'lucide-react';
 import voiceboxLogo from '@/assets/voicebox-logo.png';
 import { cn } from '@/lib/utils/cn';
 import { useGenerationStore } from '@/stores/generationStore';
@@ -10,12 +19,12 @@ interface SidebarProps {
 }

 const tabs = [
-  { id: 'main', path: '/', icon: Volume2, label: 'Generate' },
-  { id: 'stories', path: '/stories', icon: BookOpen, label: 'Stories' },
-  { id: 'voices', path: '/voices', icon: Mic, label: 'Voices' },
-  { id: 'audio', path: '/audio', icon: Speaker, label: 'Audio' },
-  { id: 'models', path: '/models', icon: Box, label: 'Models' },
-  { id: 'server', path: '/server', icon: Server, label: 'Server' },
+  { id: 'main', path: '/', icon: VolumeHighIcon, label: 'Generate' },
+  { id: 'stories', path: '/stories', icon: Book01Icon, label: 'Stories' },
+  { id: 'voices', path: '/voices', icon: Mic01Icon, label: 'Voices' },
+  { id: 'audio', path: '/audio', icon: SpeakerIcon, label: 'Audio' },
+  { id: 'models', path: '/models', icon: PackageIcon, label: 'Models' },
+  { id: 'server', path: '/server', icon: ServerStack01Icon, label: 'Server' },
 ];

 export function Sidebar({ isMacOS }: SidebarProps) {
@@ -42,9 +51,7 @@ export function Sidebar({ isMacOS }: SidebarProps) {
          const Icon = tab.icon;
          // For index route, use exact match; for others, use default matching
          const isActive =
-            tab.path === '/'
-              ? matchRoute({ to: '/', exact: true })
-              : matchRoute({ to: tab.path });
+            tab.path === '/' ? matchRoute({ to: '/' }) : matchRoute({ to: tab.path });

          return (
            <Link
@@ -58,7 +65,7 @@ export function Sidebar({ isMacOS }: SidebarProps) {
              title={tab.label}
              aria-label={tab.label}
            >
-              <Icon className="h-5 w-5" />
+              <HugeiconsIcon icon={Icon} size={20} className="h-5 w-5" />
            </Link>
          );
        })}
@@ -75,7 +82,7 @@ export function Sidebar({ isMacOS }: SidebarProps) {
            isPlayerVisible ? 'mb-[120px]' : 'mb-0',
          )}
        >
-          <Loader2 className="h-6 w-6 text-accent animate-spin" />
+          <Icon icon="svg-spinners:ring-resize" className="h-6 w-6 text-accent animate-spin" />
        </div>
      )}
    </div>
@@ -1,7 +1,7 @@
 import { useSortable } from '@dnd-kit/sortable';
 import { CSS } from '@dnd-kit/utilities';
-import { GripVertical, Mic, MoreHorizontal, Play, Trash2 } from 'lucide-react';
-import { useState } from 'react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { DragDropVerticalIcon, MoreHorizontalIcon, PlayIcon, Delete01Icon } from '@hugeicons/core-free-icons';
 import { Button } from '@/components/ui/button';
 import {
  DropdownMenu,
@@ -10,10 +10,10 @@ import {
  DropdownMenuTrigger,
 } from '@/components/ui/dropdown-menu';
 import { Textarea } from '@/components/ui/textarea';
+import { ProfileAvatar } from '@/components/VoiceProfiles/ProfileAvatar';
 import type { StoryItemDetail } from '@/lib/api/types';
 import { cn } from '@/lib/utils/cn';
 import { useStoryStore } from '@/stores/storyStore';
-import { useServerStore } from '@/stores/serverStore';

 interface StoryChatItemProps {
  item: StoryItemDetail;
@@ -35,10 +35,6 @@ export function StoryChatItem({
  isDragging,
 }: StoryChatItemProps) {
  const seek = useStoryStore((state) => state.seek);
-  const serverUrl = useServerStore((state) => state.serverUrl);
-  const [avatarError, setAvatarError] = useState(false);
-
-  const avatarUrl = `${serverUrl}/profiles/${item.profile_id}/avatar`;

  // Check if this item is currently playing based on timecode
  const itemStartMs = item.start_time_ms;
@@ -74,27 +70,18 @@ export function StoryChatItem({
          className="shrink-0 cursor-grab active:cursor-grabbing touch-none text-muted-foreground hover:text-foreground transition-colors"
          {...dragHandleProps}
        >
-          <GripVertical className="h-5 w-5" />
+          <HugeiconsIcon icon={DragDropVerticalIcon} size={20} className="h-5 w-5" />
        </button>
      )}

      {/* Voice Avatar */}
      <div className="shrink-0">
-        <div className="h-10 w-10 rounded-full bg-muted flex items-center justify-center overflow-hidden">
-          {!avatarError ? (
-            <img
-              src={avatarUrl}
-              alt={`${item.profile_name} avatar`}
-              className={cn(
-                'h-full w-full object-cover transition-all duration-200',
-                !isCurrentlyPlaying && 'grayscale'
-              )}
-              onError={() => setAvatarError(true)}
-            />
-          ) : (
-            <Mic className="h-5 w-5 text-muted-foreground" />
-          )}
-        </div>
+        <ProfileAvatar
+          profileId={item.profile_id}
+          size="lg"
+          grayscale={!isCurrentlyPlaying}
+          alt={`${item.profile_name} avatar`}
+        />
      </div>

      {/* Content */}
@@ -119,16 +106,16 @@ export function StoryChatItem({
        <DropdownMenu>
          <DropdownMenuTrigger asChild>
            <Button variant="ghost" size="icon" className="h-8 w-8" aria-label="Actions">
-              <MoreHorizontal className="h-4 w-4" />
+              <HugeiconsIcon icon={MoreHorizontalIcon} size={16} className="h-4 w-4" />
            </Button>
          </DropdownMenuTrigger>
          <DropdownMenuContent align="end">
            <DropdownMenuItem onClick={handlePlay}>
-              <Play className="mr-2 h-4 w-4" />
+              <HugeiconsIcon icon={PlayIcon} size={16} className="mr-2 h-4 w-4" />
              Play from here
            </DropdownMenuItem>
            <DropdownMenuItem onClick={onRemove} className="text-destructive focus:text-destructive">
-              <Trash2 className="mr-2 h-4 w-4" />
+              <HugeiconsIcon icon={Delete01Icon} size={16} className="mr-2 h-4 w-4" />
              Remove from Story
            </DropdownMenuItem>
          </DropdownMenuContent>
@@ -13,7 +13,8 @@ import {
  sortableKeyboardCoordinates,
  verticalListSortingStrategy,
 } from '@dnd-kit/sortable';
-import { Download, Plus } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Download01Icon, Add01Icon } from '@hugeicons/core-free-icons';
 import { useEffect, useMemo, useRef, useState } from 'react';
 import { Button } from '@/components/ui/button';
 import { Input } from '@/components/ui/input';
@@ -271,7 +272,7 @@ export function StoryContent() {
          <Popover open={isAddOpen} onOpenChange={setIsAddOpen}>
            <PopoverTrigger asChild>
              <Button variant="outline" size="sm">
-                <Plus className="mr-2 h-4 w-4" />
+                <HugeiconsIcon icon={Add01Icon} size={16} className="mr-2 h-4 w-4" />
                Add
              </Button>
            </PopoverTrigger>
@@ -316,7 +317,7 @@ export function StoryContent() {
              onClick={handleExportAudio}
              disabled={exportAudio.isPending}
            >
-              <Download className="mr-2 h-4 w-4" />
+              <HugeiconsIcon icon={Download01Icon} size={16} className="mr-2 h-4 w-4" />
              Export Audio
            </Button>
          )}
@@ -1,5 +1,6 @@
-import { Plus, BookOpen, MoreHorizontal, Pencil, Trash2 } from 'lucide-react';
-import { useState } from 'react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Add01Icon, Book01Icon, MoreHorizontalIcon, PencilIcon, Delete01Icon } from '@hugeicons/core-free-icons';
+import { useState, useMemo } from 'react';
 import {
  AlertDialog,
  AlertDialogAction,
@@ -29,7 +30,7 @@ import { Input } from '@/components/ui/input';
 import { Label } from '@/components/ui/label';
 import { Textarea } from '@/components/ui/textarea';
 import { useToast } from '@/components/ui/use-toast';
-import { useStories, useCreateStory, useUpdateStory, useDeleteStory } from '@/lib/hooks/useStories';
+import { useStories, useCreateStory, useUpdateStory, useDeleteStory, useStory } from '@/lib/hooks/useStories';
 import { cn } from '@/lib/utils/cn';
 import { formatDate } from '@/lib/utils/format';
 import { useStoryStore } from '@/stores/storyStore';
@@ -38,6 +39,8 @@ export function StoryList() {
  const { data: stories, isLoading } = useStories();
  const selectedStoryId = useStoryStore((state) => state.selectedStoryId);
  const setSelectedStoryId = useStoryStore((state) => state.setSelectedStoryId);
+  const trackEditorHeight = useStoryStore((state) => state.trackEditorHeight);
+  const { data: currentStory } = useStory(selectedStoryId);
  const createStory = useCreateStory();
  const updateStory = useUpdateStory();
  const deleteStory = useDeleteStory();
@@ -54,6 +57,16 @@ export function StoryList() {
  const [newStoryDescription, setNewStoryDescription] = useState('');
  const { toast } = useToast();

+  // Calculate bottom padding to account for FloatingGenerateBox and StoryTrackEditor
+  const hasTrackEditor = currentStory && currentStory.items.length > 0;
+  const bottomPadding = useMemo(() => {
+    // FloatingGenerateBox height (~100px) + gap (24px)
+    const generateBoxHeight = 124;
+    // Track editor height when visible
+    const editorHeight = hasTrackEditor ? trackEditorHeight + 24 : 0;
+    return generateBoxHeight + editorHeight;
+  }, [hasTrackEditor, trackEditorHeight]);
+
  const handleCreateStory = () => {
    if (!newStoryName.trim()) {
      toast({
@@ -177,16 +190,19 @@ export function StoryList() {
      <div className="flex items-center justify-between mb-4 px-1">
        <h2 className="text-2xl font-bold">Stories</h2>
        <Button onClick={() => setCreateDialogOpen(true)} size="sm">
-          <Plus className="mr-2 h-4 w-4" />
+          <HugeiconsIcon icon={Add01Icon} size={16} className="mr-2 h-4 w-4" />
          New Story
        </Button>
      </div>

      {/* Story List */}
-      <div className="flex-1 min-h-0 overflow-y-auto space-y-2">
+      <div 
+        className="flex-1 min-h-0 overflow-y-auto space-y-2"
+        style={{ paddingBottom: `${bottomPadding}px` }}
+      >
        {storyList.length === 0 ? (
          <div className="text-center py-12 px-5 border-2 border-dashed border-muted rounded-2xl text-muted-foreground">
-            <BookOpen className="h-12 w-12 mx-auto mb-4 opacity-50" />
+            <HugeiconsIcon icon={Book01Icon} size={48} className="h-12 w-12 mx-auto mb-4 opacity-50" />
            <p className="text-sm">No stories yet</p>
            <p className="text-xs mt-2">Create your first story to get started</p>
          </div>
@@ -227,19 +243,19 @@ export function StoryList() {
                      className="h-8 w-8 opacity-0 group-hover:opacity-100 transition-opacity"
                      onClick={(e) => e.stopPropagation()}
                    >
-                      <MoreHorizontal className="h-4 w-4" />
+                      <HugeiconsIcon icon={MoreHorizontalIcon} size={16} className="h-4 w-4" />
                    </Button>
                  </DropdownMenuTrigger>
                  <DropdownMenuContent align="end">
                    <DropdownMenuItem onClick={() => handleEditClick(story)}>
-                      <Pencil className="mr-2 h-4 w-4" />
+                      <HugeiconsIcon icon={PencilIcon} size={16} className="mr-2 h-4 w-4" />
                      Edit
                    </DropdownMenuItem>
                    <DropdownMenuItem
                      onClick={() => handleDeleteClick(story.id)}
                      className="text-destructive focus:text-destructive"
                    >
-                      <Trash2 className="mr-2 h-4 w-4" />
+                      <HugeiconsIcon icon={Delete01Icon} size={16} className="mr-2 h-4 w-4" />
                      Delete
                    </DropdownMenuItem>
                  </DropdownMenuContent>
@@ -1,14 +1,15 @@
+import { HugeiconsIcon } from '@hugeicons/react';
 import {
-  Copy,
-  GripHorizontal,
-  Minus,
-  Pause,
-  Play,
-  Plus,
-  Scissors,
-  Square,
-  Trash2,
-} from 'lucide-react';
+  Copy01Icon,
+  DragDropHorizontalIcon,
+  RemoveIcon,
+  PauseIcon,
+  PlayIcon,
+  Add01Icon,
+  Scissor01Icon,
+  SquareIcon,
+  Delete01Icon,
+} from '@hugeicons/core-free-icons';
 import { useCallback, useEffect, useMemo, useRef, useState } from 'react';
 import WaveSurfer from 'wavesurfer.js';
 import { Button } from '@/components/ui/button';
@@ -723,7 +724,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
          onMouseDown={handleResizeStart}
          aria-label="Resize track editor"
        >
-          <GripHorizontal className="h-3 w-3 text-muted-foreground/50 group-hover:text-muted-foreground" />
+          <HugeiconsIcon icon={DragDropHorizontalIcon} size={12} className="h-3 w-3 text-muted-foreground/50 group-hover:text-muted-foreground" />
        </button>

        {/* Toolbar */}
@@ -737,7 +738,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
              onClick={handlePlayPause}
              title="Play/Pause (Space)"
            >
-              {isCurrentlyPlaying ? <Pause className="h-4 w-4" /> : <Play className="h-4 w-4" />}
+              {isCurrentlyPlaying ? <HugeiconsIcon icon={PauseIcon} size={16} className="h-4 w-4" /> : <HugeiconsIcon icon={PlayIcon} size={16} className="h-4 w-4" />}
            </Button>
            <Button
              variant="ghost"
@@ -746,7 +747,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
              onClick={handleStop}
              disabled={!isCurrentlyPlaying}
            >
-              <Square className="h-3 w-3" />
+              <HugeiconsIcon icon={SquareIcon} size={12} className="h-3 w-3" />
            </Button>
            <span className="text-xs text-muted-foreground tabular-nums ml-2">
              {formatTime(currentTimeMs)} / {formatTime(totalDurationMs)}
@@ -763,7 +764,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
                onClick={handleSplit}
                title="Split at playhead (S)"
              >
-                <Scissors className="h-4 w-4" />
+                <HugeiconsIcon icon={Scissor01Icon} size={16} className="h-4 w-4" />
              </Button>
              <Button
                variant="ghost"
@@ -772,7 +773,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
                onClick={handleDuplicate}
                title="Duplicate (Cmd/Ctrl+D)"
              >
-                <Copy className="h-4 w-4" />
+                <HugeiconsIcon icon={Copy01Icon} size={16} className="h-4 w-4" />
              </Button>
              <Button
                variant="ghost"
@@ -781,7 +782,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
                onClick={handleDelete}
                title="Delete (Delete/Backspace)"
              >
-                <Trash2 className="h-4 w-4" />
+                <HugeiconsIcon icon={Delete01Icon} size={16} className="h-4 w-4" />
              </Button>
            </div>
          )}
@@ -790,10 +791,10 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
          <div className="flex items-center gap-2">
            <span className="text-xs text-muted-foreground">Zoom:</span>
            <Button variant="ghost" size="icon" className="h-6 w-6" onClick={handleZoomOut}>
-              <Minus className="h-3 w-3" />
+              <HugeiconsIcon icon={RemoveIcon} size={12} className="h-3 w-3" />
            </Button>
            <Button variant="ghost" size="icon" className="h-6 w-6" onClick={handleZoomIn}>
-              <Plus className="h-3 w-3" />
+              <HugeiconsIcon icon={Add01Icon} size={12} className="h-3 w-3" />
            </Button>
          </div>
        </div>
@@ -837,7 +838,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
              type="button"
              className="h-6 border-b bg-muted/20 sticky top-0 z-10 cursor-pointer text-left"
              style={{ width: `${timelineWidth}px` }}
-              onClick={handleTimelineClick}
+              onClick={(e) => handleTimelineClick(e as unknown as React.MouseEvent<HTMLDivElement>)}
              aria-label="Seek timeline"
            >
              {timeMarkers.map((ms) => (
@@ -878,7 +879,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
              <button
                type="button"
                className="absolute inset-0 z-0 cursor-pointer"
-                onClick={handleTimelineClick}
+                onClick={(e) => handleTimelineClick(e as unknown as React.MouseEvent<HTMLDivElement>)}
                aria-label="Seek timeline"
              />

@@ -1,4 +1,5 @@
-import { Mic, Pause, Play, Square } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Mic01Icon, PauseIcon, PlayIcon, SquareIcon } from '@hugeicons/core-free-icons';
 import { memo, useEffect, useState } from 'react';
 import { Visualizer } from 'react-sound-visualizer';
 import { Button } from '@/components/ui/button';
@@ -95,7 +96,7 @@ export function AudioSampleRecording({
                size="lg"
                className="relative z-10 flex items-center gap-2"
              >
-                <Mic className="h-5 w-5" />
+                <HugeiconsIcon icon={Mic01Icon} size={20} className="h-5 w-5" />
                Start Recording
              </Button>
              <p className="relative z-10 text-sm text-muted-foreground text-center">
@@ -122,7 +123,7 @@ export function AudioSampleRecording({
                onClick={onStop}
                className="relative z-10 flex items-center gap-2 bg-accent text-accent-foreground hover:bg-accent/90"
              >
-                <Square className="h-4 w-4" />
+                <HugeiconsIcon icon={SquareIcon} size={16} className="h-4 w-4" />
                Stop Recording
              </Button>
              <p className="relative z-10 text-sm text-muted-foreground text-center">
@@ -134,13 +135,13 @@ export function AudioSampleRecording({
          {file && !isRecording && (
            <div className="flex flex-col items-center justify-center gap-4 p-4 border-2 border-primary rounded-lg bg-primary/5 min-h-[180px]">
              <div className="flex items-center gap-2">
-                <Mic className="h-5 w-5 text-primary" />
+                <HugeiconsIcon icon={Mic01Icon} size={20} className="h-5 w-5 text-primary" />
                <span className="font-medium">Recording complete</span>
              </div>
              <p className="text-sm text-muted-foreground text-center">File: {file.name}</p>
              <div className="flex gap-2">
                <Button type="button" size="icon" variant="outline" onClick={onPlayPause}>
-                  {isPlaying ? <Pause className="h-4 w-4" /> : <Play className="h-4 w-4" />}
+                  {isPlaying ? <HugeiconsIcon icon={PauseIcon} size={16} className="h-4 w-4" /> : <HugeiconsIcon icon={PlayIcon} size={16} className="h-4 w-4" />}
                </Button>
                <Button
                  type="button"
@@ -149,7 +150,7 @@ export function AudioSampleRecording({
                  disabled={isTranscribing}
                  className="flex items-center gap-2"
                >
-                  <Mic className="h-4 w-4" />
+                  <HugeiconsIcon icon={Mic01Icon} size={16} className="h-4 w-4" />
                  {isTranscribing ? 'Transcribing...' : 'Transcribe'}
                </Button>
                <Button
@@ -1,4 +1,5 @@
-import { Mic, Monitor, Pause, Play, Square } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Mic01Icon, DeskIcon, PauseIcon, PlayIcon, SquareIcon } from '@hugeicons/core-free-icons';
 import { Button } from '@/components/ui/button';
 import { FormControl, FormItem, FormMessage } from '@/components/ui/form';
 import { formatAudioDuration } from '@/lib/utils/audio';
@@ -35,7 +36,7 @@ export function AudioSampleSystem({
          {!isRecording && !file && (
            <div className="flex flex-col items-center justify-center gap-4 p-4 border-2 border-dashed rounded-lg min-h-[180px]">
              <Button type="button" onClick={onStart} size="lg" className="flex items-center gap-2">
-                <Monitor className="h-5 w-5" />
+                <HugeiconsIcon icon={DeskIcon} size={20} className="h-5 w-5" />
                Start Capture
              </Button>
              <p className="text-sm text-muted-foreground text-center">
@@ -60,7 +61,7 @@ export function AudioSampleSystem({
                variant="destructive"
                className="flex items-center gap-2"
              >
-                <Square className="h-4 w-4" />
+                <HugeiconsIcon icon={SquareIcon} size={16} className="h-4 w-4" />
                Stop Capture
              </Button>
              <p className="text-sm text-muted-foreground text-center">
@@ -72,13 +73,13 @@ export function AudioSampleSystem({
          {file && !isRecording && (
            <div className="flex flex-col items-center justify-center gap-4 p-4 border-2 border-primary rounded-lg bg-primary/5 min-h-[180px]">
              <div className="flex items-center gap-2">
-                <Monitor className="h-5 w-5 text-primary" />
+                <HugeiconsIcon icon={DeskIcon} size={20} className="h-5 w-5 text-primary" />
                <span className="font-medium">Capture complete</span>
              </div>
              <p className="text-sm text-muted-foreground text-center">File: {file.name}</p>
              <div className="flex gap-2">
                <Button type="button" size="icon" variant="outline" onClick={onPlayPause}>
-                  {isPlaying ? <Pause className="h-4 w-4" /> : <Play className="h-4 w-4" />}
+                  {isPlaying ? <HugeiconsIcon icon={PauseIcon} size={16} className="h-4 w-4" /> : <HugeiconsIcon icon={PlayIcon} size={16} className="h-4 w-4" />}
                </Button>
                <Button
                  type="button"
@@ -87,7 +88,7 @@ export function AudioSampleSystem({
                  disabled={isTranscribing}
                  className="flex items-center gap-2"
                >
-                  <Mic className="h-4 w-4" />
+                  <HugeiconsIcon icon={Mic01Icon} size={16} className="h-4 w-4" />
                  {isTranscribing ? 'Transcribing...' : 'Transcribe'}
                </Button>
                <Button
@@ -1,4 +1,5 @@
-import { Mic, Pause, Play, Upload } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Mic01Icon, PauseIcon, PlayIcon, Upload01Icon } from '@hugeicons/core-free-icons';
 import { useRef, useState } from 'react';
 import { Button } from '@/components/ui/button';
 import { FormControl, FormItem, FormMessage } from '@/components/ui/form';
@@ -89,7 +90,7 @@ export function AudioSampleUpload({
                  onClick={() => fileInputRef.current?.click()}
                  className="flex items-center gap-2"
                >
-                  <Upload className="h-5 w-5" />
+                  <HugeiconsIcon icon={Upload01Icon} size={20} className="h-5 w-5" />
                  Choose File
                </Button>
                <p className="text-sm text-muted-foreground text-center">
@@ -99,7 +100,7 @@ export function AudioSampleUpload({
            ) : (
              <>
                <div className="flex items-center gap-2">
-                  <Upload className="h-5 w-5 text-primary" />
+                  <HugeiconsIcon icon={Upload01Icon} size={20} className="h-5 w-5 text-primary" />
                  <span className="font-medium">File uploaded</span>
                </div>
                <p className="text-sm text-muted-foreground text-center">File: {file.name}</p>
@@ -111,7 +112,7 @@ export function AudioSampleUpload({
                    onClick={onPlayPause}
                    disabled={isValidating}
                  >
-                    {isPlaying ? <Pause className="h-4 w-4" /> : <Play className="h-4 w-4" />}
+                    {isPlaying ? <HugeiconsIcon icon={PauseIcon} size={16} className="h-4 w-4" /> : <HugeiconsIcon icon={PlayIcon} size={16} className="h-4 w-4" />}
                  </Button>
                  <Button
                    type="button"
@@ -120,7 +121,7 @@ export function AudioSampleUpload({
                    disabled={isTranscribing || isValidating || isDisabled}
                    className="flex items-center gap-2"
                  >
-                    <Mic className="h-4 w-4" />
+                    <HugeiconsIcon icon={Mic01Icon} size={16} className="h-4 w-4" />
                    {isTranscribing ? 'Transcribing...' : 'Transcribe'}
                  </Button>
                  <Button
@@ -0,0 +1,80 @@
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Mic01Icon } from '@hugeicons/core-free-icons';
+import { useState } from 'react';
+import { cn } from '@/lib/utils/cn';
+import { useServerStore } from '@/stores/serverStore';
+
+interface ProfileAvatarProps {
+  profileId: string;
+  avatarPath?: string | null;
+  size?: 'sm' | 'md' | 'lg' | 'xl';
+  grayscale?: boolean;
+  className?: string;
+  alt?: string;
+}
+
+const sizeClasses = {
+  sm: 'h-6 w-6',
+  md: 'h-8 w-8',
+  lg: 'h-10 w-10',
+  xl: 'h-24 w-24',
+};
+
+const iconSizes = {
+  sm: 14,
+  md: 16,
+  lg: 20,
+  xl: 40,
+};
+
+const iconClassNames = {
+  sm: 'h-3.5 w-3.5',
+  md: 'h-4 w-4',
+  lg: 'h-5 w-5',
+  xl: 'h-10 w-10',
+};
+
+export function ProfileAvatar({
+  profileId,
+  avatarPath,
+  size = 'md',
+  grayscale = false,
+  className,
+  alt = 'Profile avatar',
+}: ProfileAvatarProps) {
+  const [avatarError, setAvatarError] = useState(false);
+  const serverUrl = useServerStore((state) => state.serverUrl);
+
+  // If avatarPath is explicitly null or empty string, don't try to load avatar
+  // Otherwise, always try to load (avatarPath might not be available in all contexts)
+  const avatarUrl =
+    avatarPath === null || avatarPath === '' ? null : `${serverUrl}/profiles/${profileId}/avatar`;
+
+  return (
+    <div
+      className={cn(
+        sizeClasses[size],
+        'rounded-full bg-muted flex items-center justify-center shrink-0 overflow-hidden',
+        className,
+      )}
+    >
+      {avatarUrl && !avatarError ? (
+        <img
+          src={avatarUrl}
+          alt={alt}
+          className={cn(
+            'h-full w-full object-cover transition-all duration-200',
+            grayscale && 'grayscale',
+          )}
+          onError={() => setAvatarError(true)}
+        />
+      ) : (
+        <HugeiconsIcon
+          icon={Mic01Icon}
+          size={iconSizes[size]}
+          className={cn(iconClassNames[size], 'text-muted-foreground')}
+        />
+      )}
+    </div>
+  );
+}
@@ -1,6 +1,6 @@
-import { Download, Edit, Mic, Trash2 } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Download01Icon, Edit01Icon, Delete01Icon } from '@hugeicons/core-free-icons';
 import { useState } from 'react';
-import { useServerStore } from '@/stores/serverStore';
 import { Badge } from '@/components/ui/badge';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
@@ -13,6 +13,7 @@ import {
  DialogHeader,
  DialogTitle,
 } from '@/components/ui/dialog';
+import { ProfileAvatar } from '@/components/VoiceProfiles/ProfileAvatar';
 import type { VoiceProfileResponse } from '@/lib/api/types';
 import { useDeleteProfile, useExportProfile } from '@/lib/hooks/useProfiles';
 import { cn } from '@/lib/utils/cn';
@@ -24,21 +25,15 @@ interface ProfileCardProps {

 export function ProfileCard({ profile }: ProfileCardProps) {
  const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
-  const [avatarError, setAvatarError] = useState(false);
  const deleteProfile = useDeleteProfile();
  const exportProfile = useExportProfile();
  const setEditingProfileId = useUIStore((state) => state.setEditingProfileId);
  const setProfileDialogOpen = useUIStore((state) => state.setProfileDialogOpen);
  const selectedProfileId = useUIStore((state) => state.selectedProfileId);
  const setSelectedProfileId = useUIStore((state) => state.setSelectedProfileId);
-  const serverUrl = useServerStore((state) => state.serverUrl);

  const isSelected = selectedProfileId === profile.id;

-  const avatarUrl = profile.avatar_path
-    ? `${serverUrl}/profiles/${profile.id}/avatar`
-    : null;
-
  const handleSelect = () => {
    setSelectedProfileId(isSelected ? null : profile.id);
  };
@@ -74,21 +69,13 @@ export function ProfileCard({ profile }: ProfileCardProps) {
      >
        <CardHeader className="p-3 pb-2">
          <CardTitle className="flex items-center gap-1.5 text-base font-medium">
-            <div className="h-6 w-6 rounded-full bg-muted flex items-center justify-center shrink-0 overflow-hidden">
-              {avatarUrl && !avatarError ? (
-                <img
-                  src={avatarUrl}
-                  alt={`${profile.name} avatar`}
-                  className={cn(
-                    'h-full w-full object-cover transition-all duration-200',
-                    !isSelected && 'grayscale'
-                  )}
-                  onError={() => setAvatarError(true)}
-                />
-              ) : (
-                <Mic className="h-3.5 w-3.5 text-muted-foreground" />
-              )}
-            </div>
+            <ProfileAvatar
+              profileId={profile.id}
+              avatarPath={profile.avatar_path}
+              size="sm"
+              grayscale={!isSelected}
+              alt={`${profile.name} avatar`}
+            />
            <span className="break-words">{profile.name}</span>
          </CardTitle>
        </CardHeader>
@@ -103,13 +90,13 @@ export function ProfileCard({ profile }: ProfileCardProps) {
          </div>
          <div className="flex gap-0.5 justify-end items-end mt-auto">
            <CircleButton
-              icon={Download}
+              icon={(props) => <HugeiconsIcon icon={Download01Icon} size={14} {...props} />}
              onClick={handleExport}
              disabled={exportProfile.isPending}
              aria-label="Export profile"
            />
            <CircleButton
-              icon={Edit}
+              icon={(props) => <HugeiconsIcon icon={Edit01Icon} size={14} {...props} />}
              onClick={(e) => {
                e.stopPropagation();
                handleEdit();
@@ -117,7 +104,7 @@ export function ProfileCard({ profile }: ProfileCardProps) {
              aria-label="Edit profile"
            />
            <CircleButton
-              icon={Trash2}
+              icon={(props) => <HugeiconsIcon icon={Delete01Icon} size={14} {...props} />}
              onClick={handleDeleteClick}
              disabled={deleteProfile.isPending}
              aria-label="Delete profile"
@@ -1,5 +1,6 @@
 import { zodResolver } from '@hookform/resolvers/zod';
-import { Edit2, Mic, Monitor, Upload, X } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Edit02Icon, Mic01Icon, DeskIcon, Upload01Icon, Cancel01Icon } from '@hugeicons/core-free-icons';
 import { useEffect, useRef, useState } from 'react';
 import { useForm } from 'react-hook-form';
 import * as z from 'zod';
@@ -43,10 +44,10 @@ import {
 } from '@/lib/hooks/useProfiles';
 import { useSystemAudioCapture } from '@/lib/hooks/useSystemAudioCapture';
 import { useTranscription } from '@/lib/hooks/useTranscription';
-import { isTauri } from '@/lib/tauri';
 import { formatAudioDuration, getAudioDuration } from '@/lib/utils/audio';
-import { type ProfileFormDraft, useUIStore } from '@/stores/uiStore';
+import { usePlatform } from '@/platform/PlatformContext';
 import { useServerStore } from '@/stores/serverStore';
+import { type ProfileFormDraft, useUIStore } from '@/stores/uiStore';
 import { AudioSampleRecording } from './AudioSampleRecording';
 import { AudioSampleSystem } from './AudioSampleSystem';
 import { AudioSampleUpload } from './AudioSampleUpload';
@@ -102,6 +103,7 @@ function base64ToFile(base64: string, fileName: string, fileType: string): File
 }

 export function ProfileForm() {
+  const platform = usePlatform();
  const open = useUIStore((state) => state.profileDialogOpen);
  const setOpen = useUIStore((state) => state.setProfileDialogOpen);
  const editingProfileId = useUIStore((state) => state.editingProfileId);
@@ -427,7 +429,8 @@ export function ProfileForm() {
          } catch (avatarError) {
            toast({
              title: 'Avatar upload failed',
-              description: avatarError instanceof Error ? avatarError.message : 'Failed to upload avatar',
+              description:
+                avatarError instanceof Error ? avatarError.message : 'Failed to upload avatar',
              variant: 'destructive',
            });
          }
@@ -520,7 +523,8 @@ export function ProfileForm() {
            } catch (avatarError) {
              toast({
                title: 'Avatar upload failed',
-                description: avatarError instanceof Error ? avatarError.message : 'Failed to upload avatar',
+                description:
+                  avatarError instanceof Error ? avatarError.message : 'Failed to upload avatar',
                variant: 'destructive',
              });
            }
@@ -632,7 +636,7 @@ export function ProfileForm() {
                    setSampleMode('record');
                  }}
                >
-                  <X className="h-3 w-3 mr-1" />
+                  <HugeiconsIcon icon={Cancel01Icon} size={12} className="h-3 w-3 mr-1" />
                  Discard
                </Button>
              </div>
@@ -662,19 +666,19 @@ export function ProfileForm() {
                        }}
                      >
                        <TabsList
-                          className={`grid w-full ${isTauri() && isSystemAudioSupported ? 'grid-cols-3' : 'grid-cols-2'}`}
+                          className={`grid w-full ${platform.metadata.isTauri && isSystemAudioSupported ? 'grid-cols-3' : 'grid-cols-2'}`}
                        >
                          <TabsTrigger value="upload" className="flex items-center gap-2">
-                            <Upload className="h-4 w-4 shrink-0" />
+                            <HugeiconsIcon icon={Upload01Icon} size={16} className="h-4 w-4 shrink-0" />
                            Upload
                          </TabsTrigger>
                          <TabsTrigger value="record" className="flex items-center gap-2">
-                            <Mic className="h-4 w-4 shrink-0" />
+                            <HugeiconsIcon icon={Mic01Icon} size={16} className="h-4 w-4 shrink-0" />
                            Record
                          </TabsTrigger>
-                          {isTauri() && isSystemAudioSupported && (
+                          {platform.metadata.isTauri && isSystemAudioSupported && (
                            <TabsTrigger value="system" className="flex items-center gap-2">
-                              <Monitor className="h-4 w-4 shrink-0" />
+                              <HugeiconsIcon icon={DeskIcon} size={16} className="h-4 w-4 shrink-0" />
                              System Audio
                            </TabsTrigger>
                          )}
@@ -724,7 +728,7 @@ export function ProfileForm() {
                          />
                        </TabsContent>

-                        {isTauri() && isSystemAudioSupported && (
+                        {platform.metadata.isTauri && isSystemAudioSupported && (
                          <TabsContent value="system" className="space-y-4">
                            <FormField
                              control={form.control}
@@ -795,7 +799,7 @@ export function ProfileForm() {
                                    className="h-full w-full object-cover"
                                  />
                                ) : (
-                                  <Mic className="h-10 w-10 text-muted-foreground" />
+                                  <HugeiconsIcon icon={Mic01Icon} size={40} className="h-10 w-10 text-muted-foreground" />
                                )}
                              </div>
                              <button
@@ -803,7 +807,7 @@ export function ProfileForm() {
                                onClick={() => avatarInputRef.current?.click()}
                                className="absolute inset-0 rounded-full bg-accent/60 opacity-0 group-hover:opacity-100 transition-opacity flex items-center justify-center cursor-pointer"
                              >
-                                <Edit2 className="h-6 w-6 text-accent-foreground" />
+                                <HugeiconsIcon icon={Edit02Icon} size={24} className="h-6 w-6 text-accent-foreground" />
                              </button>
                              {(avatarPreview || editingProfile?.avatar_path) && (
                                <button
@@ -812,7 +816,7 @@ export function ProfileForm() {
                                  disabled={deleteAvatar.isPending}
                                  className="absolute bottom-0 right-0 h-6 w-6 rounded-full bg-background/60 backdrop-blur-sm text-muted-foreground flex items-center justify-center hover:bg-background/80 hover:text-foreground transition-colors shadow-sm border border-border/50"
                                >
-                                  <X className="h-3.5 w-3.5" />
+                                  <HugeiconsIcon icon={Cancel01Icon} size={14} className="h-3.5 w-3.5" />
                                </button>
                              )}
                            </div>
@@ -1,4 +1,5 @@
-import { Mic, Sparkles } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Mic01Icon, SparklesIcon } from '@hugeicons/core-free-icons';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent } from '@/components/ui/card';
 import { useProfiles } from '@/lib/hooks/useProfiles';
@@ -30,12 +31,12 @@ export function ProfileList() {
        {allProfiles.length === 0 ? (
          <Card>
            <CardContent className="flex flex-col items-center justify-center py-12">
-              <Mic className="h-12 w-12 text-muted-foreground mb-4" />
+              <HugeiconsIcon icon={Mic01Icon} size={48} className="h-12 w-12 text-muted-foreground mb-4" />
              <p className="text-muted-foreground mb-4">
                No voice profiles yet. Create your first profile to get started.
              </p>
              <Button onClick={() => setDialogOpen(true)}>
-                <Sparkles className="mr-2 h-4 w-4" />
+                <HugeiconsIcon icon={SparklesIcon} size={16} className="mr-2 h-4 w-4" />
                Create Voice
              </Button>
            </CardContent>
@@ -1,9 +1,18 @@
-import { Plus, Trash2, Play, Edit, Check, X, Volume2, Pause } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { CheckmarkCircle01Icon, Edit01Icon, PauseIcon, PlayIcon, Add01Icon, Delete01Icon, VolumeHighIcon, Cancel01Icon } from '@hugeicons/core-free-icons';
 import { useEffect, useRef, useState } from 'react';
 import { Button } from '@/components/ui/button';
 import { CircleButton } from '@/components/ui/circle-button';
-import { Textarea } from '@/components/ui/textarea';
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from '@/components/ui/dialog';
 import { Slider } from '@/components/ui/slider';
+import { Textarea } from '@/components/ui/textarea';
 import { useToast } from '@/components/ui/use-toast';
 import { apiClient } from '@/lib/api/client';
 import { useDeleteSample, useProfileSamples, useUpdateSample } from '@/lib/hooks/useProfiles';
@@ -95,7 +104,7 @@ function MiniSamplePlayer({ audioUrl }: MiniSamplePlayerProps) {
          onClick={handlePlayPause}
          disabled={isLoading}
        >
-          {isPlaying ? <Pause className="h-3.5 w-3.5" /> : <Play className="h-3.5 w-3.5 ml-0.5" />}
+          {isPlaying ? <HugeiconsIcon icon={PauseIcon} size={14} className="h-3.5 w-3.5" /> : <HugeiconsIcon icon={PlayIcon} size={14} className="h-3.5 w-3.5 ml-0.5" />}
        </Button>

        <div className="flex-1 min-w-0 flex items-center gap-2">
@@ -121,7 +130,7 @@ function MiniSamplePlayer({ audioUrl }: MiniSamplePlayerProps) {
          onClick={handleStop}
          title="Stop"
        >
-          <X className="h-3.5 w-3.5" />
+          <HugeiconsIcon icon={Cancel01Icon} size={14} className="h-3.5 w-3.5" />
        </Button>
      </div>
    </div>
@@ -140,10 +149,19 @@ export function SampleList({ profileId }: SampleListProps) {
  const [uploadOpen, setUploadOpen] = useState(false);
  const [editingSampleId, setEditingSampleId] = useState<string | null>(null);
  const [editedText, setEditedText] = useState<string>('');
+  const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
+  const [sampleToDelete, setSampleToDelete] = useState<string | null>(null);

-  const handleDelete = (sampleId: string) => {
-    if (confirm('Are you sure you want to delete this sample?')) {
-      deleteSample.mutate(sampleId);
+  const handleDeleteClick = (sampleId: string) => {
+    setSampleToDelete(sampleId);
+    setDeleteDialogOpen(true);
+  };
+
+  const handleDeleteConfirm = () => {
+    if (sampleToDelete) {
+      deleteSample.mutate(sampleToDelete);
+      setDeleteDialogOpen(false);
+      setSampleToDelete(null);
    }
  };

@@ -192,9 +210,11 @@ export function SampleList({ profileId }: SampleListProps) {
    <div className="space-y-4 pt-4">
      {samples && samples.length === 0 ? (
        <div className="flex flex-col items-center justify-center py-8 text-center border border-dashed rounded-lg">
-          <Volume2 className="h-8 w-8 text-muted-foreground/50 mb-2" />
+          <HugeiconsIcon icon={VolumeHighIcon} size={32} className="h-8 w-8 text-muted-foreground/50 mb-2" />
          <p className="text-sm text-muted-foreground">No samples yet</p>
-          <p className="text-xs text-muted-foreground/70 mt-1">Add your first audio sample to get started</p>
+          <p className="text-xs text-muted-foreground/70 mt-1">
+            Add your first audio sample to get started
+          </p>
        </div>
      ) : (
        <div className="space-y-2">
@@ -206,14 +226,14 @@ export function SampleList({ profileId }: SampleListProps) {
                key={sample.id}
                className={cn(
                  'group relative rounded-lg border bg-card transition-all duration-200',
-                  isEditing ? 'ring-2 ring-primary/20' : 'hover:border-primary/30'
+                  isEditing ? 'ring-2 ring-primary/20' : 'hover:border-primary/30',
                )}
              >
                {isEditing ? (
                  /* Edit Mode */
                  <div className="p-4 space-y-3">
                    <div className="flex items-center gap-2 text-xs text-muted-foreground mb-2">
-                      <Edit className="h-3 w-3" />
+                      <HugeiconsIcon icon={Edit01Icon} size={12} className="h-3 w-3" />
                      <span>Editing transcription</span>
                    </div>
                    <Textarea
@@ -231,7 +251,7 @@ export function SampleList({ profileId }: SampleListProps) {
                        onClick={handleCancelEdit}
                        disabled={updateSample.isPending}
                      >
-                        <X className="h-4 w-4 mr-1" />
+                        <HugeiconsIcon icon={Cancel01Icon} size={16} className="h-4 w-4 mr-1" />
                        Cancel
                      </Button>
                      <Button
@@ -240,7 +260,7 @@ export function SampleList({ profileId }: SampleListProps) {
                        onClick={() => handleSaveEdit(sample.id)}
                        disabled={updateSample.isPending}
                      >
-                        <Check className="h-4 w-4 mr-1" />
+                        <HugeiconsIcon icon={CheckmarkCircle01Icon} size={16} className="h-4 w-4 mr-1" />
                        {updateSample.isPending ? 'Saving...' : 'Save'}
                      </Button>
                    </div>
@@ -259,14 +279,14 @@ export function SampleList({ profileId }: SampleListProps) {
                      {/* Action Buttons */}
                      <div className="shrink-0 flex items-center gap-0.5 opacity-0 group-hover:opacity-100 transition-opacity">
                        <CircleButton
-                          icon={Edit}
+                          icon={(props) => <HugeiconsIcon icon={Edit01Icon} size={14} {...props} />}
                          title="Edit transcription"
                          onClick={() => handleStartEdit(sample.id, sample.reference_text)}
                        />
                        <CircleButton
-                          icon={Trash2}
+                          icon={(props) => <HugeiconsIcon icon={Delete01Icon} size={14} {...props} />}
                          title="Delete sample"
-                          onClick={() => handleDelete(sample.id)}
+                          onClick={() => handleDeleteClick(sample.id)}
                          disabled={deleteSample.isPending}
                        />
                      </div>
@@ -287,12 +307,52 @@ export function SampleList({ profileId }: SampleListProps) {
        </div>
      )}

-      <Button type="button" variant="outline" className="w-full" onClick={() => setUploadOpen(true)}>
-        <Plus className="mr-2 h-4 w-4" />
+      <Button
+        type="button"
+        variant="outline"
+        className="w-full"
+        onClick={() => setUploadOpen(true)}
+      >
+        <HugeiconsIcon icon={Add01Icon} size={16} className="mr-2 h-4 w-4" />
        Add Sample
      </Button>

+      <p className="text-xs text-muted-foreground text-center px-2">
+        Note: A single 30-second sample is the sweet spot. Quality may decrease with multiple
+        samples. In a future update samples might be interchangeable and tagged for varying styles
+        of the same voice.
+      </p>
+
      <SampleUpload profileId={profileId} open={uploadOpen} onOpenChange={setUploadOpen} />
+
+      <Dialog open={deleteDialogOpen} onOpenChange={setDeleteDialogOpen}>
+        <DialogContent>
+          <DialogHeader>
+            <DialogTitle>Delete Sample</DialogTitle>
+            <DialogDescription>
+              Are you sure you want to delete this audio sample? This action cannot be undone.
+            </DialogDescription>
+          </DialogHeader>
+          <DialogFooter>
+            <Button
+              variant="outline"
+              onClick={() => {
+                setDeleteDialogOpen(false);
+                setSampleToDelete(null);
+              }}
+            >
+              Cancel
+            </Button>
+            <Button
+              variant="destructive"
+              onClick={handleDeleteConfirm}
+              disabled={deleteSample.isPending}
+            >
+              {deleteSample.isPending ? 'Deleting...' : 'Delete'}
+            </Button>
+          </DialogFooter>
+        </DialogContent>
+      </Dialog>
    </div>
  );
 }
@@ -1,5 +1,6 @@
 import { zodResolver } from '@hookform/resolvers/zod';
-import { Mic, Monitor, Upload } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Mic01Icon, DeskIcon, Upload01Icon } from '@hugeicons/core-free-icons';
 import { useEffect, useState } from 'react';
 import { useForm } from 'react-hook-form';
 import * as z from 'zod';
@@ -27,7 +28,7 @@ import { useAudioRecording } from '@/lib/hooks/useAudioRecording';
 import { useAddSample, useProfile } from '@/lib/hooks/useProfiles';
 import { useSystemAudioCapture } from '@/lib/hooks/useSystemAudioCapture';
 import { useTranscription } from '@/lib/hooks/useTranscription';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';
 import { AudioSampleRecording } from './AudioSampleRecording';
 import { AudioSampleSystem } from './AudioSampleSystem';
 import { AudioSampleUpload } from './AudioSampleUpload';
@@ -49,6 +50,7 @@ interface SampleUploadProps {
 }

 export function SampleUpload({ profileId, open, onOpenChange }: SampleUploadProps) {
+  const platform = usePlatform();
  const addSample = useAddSample();
  const transcribe = useTranscription();
  const { data: profile } = useProfile(profileId);
@@ -232,19 +234,19 @@ export function SampleUpload({ profileId, open, onOpenChange }: SampleUploadProp
          <form onSubmit={form.handleSubmit(onSubmit)} className="space-y-4">
            <Tabs value={mode} onValueChange={(v) => setMode(v as 'upload' | 'record' | 'system')}>
              <TabsList
-                className={`grid w-full ${isTauri() && isSystemAudioSupported ? 'grid-cols-3' : 'grid-cols-2'}`}
+                className={`grid w-full ${platform.metadata.isTauri && isSystemAudioSupported ? 'grid-cols-3' : 'grid-cols-2'}`}
              >
                <TabsTrigger value="upload" className="flex items-center gap-2">
-                  <Upload className="h-4 w-4 shrink-0" />
+                  <HugeiconsIcon icon={Upload01Icon} size={16} className="h-4 w-4 shrink-0" />
                  Upload
                </TabsTrigger>
                <TabsTrigger value="record" className="flex items-center gap-2">
-                  <Mic className="h-4 w-4 shrink-0" />
+                  <HugeiconsIcon icon={Mic01Icon} size={16} className="h-4 w-4 shrink-0" />
                  Record
                </TabsTrigger>
-                {isTauri() && isSystemAudioSupported && (
+                {platform.metadata.isTauri && isSystemAudioSupported && (
                  <TabsTrigger value="system" className="flex items-center gap-2">
-                    <Monitor className="h-4 w-4 shrink-0" />
+                    <HugeiconsIcon icon={DeskIcon} size={16} className="h-4 w-4 shrink-0" />
                    System Audio
                  </TabsTrigger>
                )}
@@ -289,7 +291,7 @@ export function SampleUpload({ profileId, open, onOpenChange }: SampleUploadProp
                />
              </TabsContent>

-              {isTauri() && isSystemAudioSupported && (
+              {platform.metadata.isTauri && isSystemAudioSupported && (
                <TabsContent value="system" className="space-y-4">
                  <FormField
                    control={form.control}
@@ -1,5 +1,6 @@
 import { useQuery, useQueryClient } from '@tanstack/react-query';
-import { Edit, MoreHorizontal, Plus, Trash2, Mic } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Edit01Icon, MoreHorizontalIcon, Add01Icon, Delete01Icon } from '@hugeicons/core-free-icons';
 import { useMemo, useRef } from 'react';
 import { Button } from '@/components/ui/button';
 import {
@@ -18,6 +19,7 @@ import {
  TableRow,
 } from '@/components/ui/table';
 import { ProfileForm } from '@/components/VoiceProfiles/ProfileForm';
+import { ProfileAvatar } from '@/components/VoiceProfiles/ProfileAvatar';
 import { apiClient } from '@/lib/api/client';
 import type { VoiceProfileResponse } from '@/lib/api/types';
 import { BOTTOM_SAFE_AREA_PADDING } from '@/lib/constants/ui';
@@ -112,7 +114,7 @@ export function VoicesTab() {
        <div className="flex items-center justify-between mb-6">
          <h1 className="text-2xl font-bold">Voices</h1>
          <Button onClick={() => setDialogOpen(true)}>
-            <Plus className="h-4 w-4 mr-2" />
+            <HugeiconsIcon icon={Add01Icon} size={16} className="h-4 w-4 mr-2" />
            New Voice
          </Button>
        </div>
@@ -184,9 +186,12 @@ function VoiceRow({
    <TableRow className="cursor-pointer" onClick={onEdit}>
      <TableCell>
        <div className="flex items-center gap-2">
-          <div className="h-8 w-8 rounded-lg bg-muted flex items-center justify-center shrink-0">
-            <Mic className="h-4 w-4 text-muted-foreground" />
-          </div>
+          <ProfileAvatar
+            profileId={profile.id}
+            avatarPath={profile.avatar_path}
+            size="md"
+            alt={`${profile.name} avatar`}
+          />
          <div>
            <div className="font-medium">{profile.name}</div>
            {profile.description && (
@@ -214,16 +219,16 @@ function VoiceRow({
        <DropdownMenu>
          <DropdownMenuTrigger asChild>
            <Button variant="ghost" size="icon">
-              <MoreHorizontal className="h-4 w-4" />
+              <HugeiconsIcon icon={MoreHorizontalIcon} size={16} className="h-4 w-4" />
            </Button>
          </DropdownMenuTrigger>
          <DropdownMenuContent>
            <DropdownMenuItem onClick={onEdit}>
-              <Edit className="h-4 w-4 mr-2" />
+              <HugeiconsIcon icon={Edit01Icon} size={16} className="h-4 w-4 mr-2" />
              Edit
            </DropdownMenuItem>
            <DropdownMenuItem onClick={onDelete} className="text-destructive">
-              <Trash2 className="h-4 w-4 mr-2" />
+              <HugeiconsIcon icon={Delete01Icon} size={16} className="h-4 w-4 mr-2" />
              Delete
            </DropdownMenuItem>
          </DropdownMenuContent>
@@ -1,5 +1,6 @@
 import * as React from 'react';
-import { Check } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { CheckmarkCircle01Icon } from '@hugeicons/core-free-icons';
 import { cn } from '@/lib/utils/cn';

 export interface CheckboxProps {
@@ -34,7 +35,7 @@ const Checkbox = React.forwardRef<HTMLButtonElement, CheckboxProps>(
        )}
        {...props}
      >
-        {checked && <Check className="h-3 w-3 text-accent-foreground" />}
+        {checked && <HugeiconsIcon icon={CheckmarkCircle01Icon} size={12} className="h-3 w-3 text-accent-foreground" />}
      </button>
    );
  },
@@ -6,10 +6,11 @@ export interface CircleButtonProps extends React.ButtonHTMLAttributes<HTMLButton
 }

 const CircleButton = React.forwardRef<HTMLButtonElement, CircleButtonProps>(
-  ({ className, icon: Icon, ...props }, ref) => {
+  ({ className, icon: Icon, type = 'button', ...props }, ref) => {
    return (
      <button
        ref={ref}
+        type={type}
        className={cn(
          'h-7 w-7 rounded-full flex items-center justify-center flex-shrink-0',
          'hover:bg-muted transition-colors',
@@ -1,5 +1,6 @@
 import * as DialogPrimitive from '@radix-ui/react-dialog';
-import { X } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Cancel01Icon } from '@hugeicons/core-free-icons';
 import * as React from 'react';
 import { cn } from '@/lib/utils/cn';

@@ -42,7 +43,7 @@ const DialogContent = React.forwardRef<
    >
      {children}
      <DialogPrimitive.Close className="absolute right-4 top-4 rounded-sm opacity-70 ring-offset-background transition-opacity hover:opacity-100 focus:outline-none focus:ring-2 focus:ring-ring focus:ring-offset-2 disabled:pointer-events-none data-[state=open]:bg-accent data-[state=open]:text-muted-foreground">
-        <X className="h-4 w-4" />
+        <HugeiconsIcon icon={Cancel01Icon} size={16} className="h-4 w-4" />
        <span className="sr-only">Close</span>
      </DialogPrimitive.Close>
    </DialogPrimitive.Content>
@@ -1,6 +1,7 @@
-import * as React from 'react';
+import { MoreHorizontalIcon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
 import * as DropdownMenuPrimitive from '@radix-ui/react-dropdown-menu';
-import { MoreHorizontal } from 'lucide-react';
+import * as React from 'react';
 import { cn } from '@/lib/utils/cn';

 const DropdownMenu = DropdownMenuPrimitive.Root;
@@ -26,7 +27,7 @@ const DropdownMenuSubTrigger = React.forwardRef<
    {...props}
  >
    {children}
-    <MoreHorizontal className="ml-auto h-4 w-4" />
+    <HugeiconsIcon icon={MoreHorizontalIcon} size={16} className="ml-auto h-4 w-4" />
  </DropdownMenuPrimitive.SubTrigger>
 ));
 DropdownMenuSubTrigger.displayName = DropdownMenuPrimitive.SubTrigger.displayName;
@@ -73,7 +74,7 @@ const DropdownMenuItem = React.forwardRef<
  <DropdownMenuPrimitive.Item
    ref={ref}
    className={cn(
-      'relative flex cursor-default select-none items-center rounded-sm px-2 py-1.5 text-sm outline-none transition-colors focus:bg-accent focus:text-accent-foreground data-[disabled]:pointer-events-none data-[disabled]:opacity-50',
+      'relative flex cursor-default select-none items-center rounded-sm px-2 py-1.5 text-sm outline-none focus:bg-accent focus:text-accent-foreground data-[disabled]:pointer-events-none data-[disabled]:opacity-50',
      inset && 'pl-8',
      className,
    )}
@@ -97,7 +98,7 @@ const DropdownMenuCheckboxItem = React.forwardRef<
  >
    <span className="absolute left-2 flex h-3.5 w-3.5 items-center justify-center">
      <DropdownMenuPrimitive.ItemIndicator>
-        <MoreHorizontal className="h-4 w-4" />
+        <HugeiconsIcon icon={MoreHorizontalIcon} size={16} className="h-4 w-4" />
      </DropdownMenuPrimitive.ItemIndicator>
    </span>
    {children}
@@ -119,7 +120,7 @@ const DropdownMenuRadioItem = React.forwardRef<
  >
    <span className="absolute left-2 flex h-3.5 w-3.5 items-center justify-center">
      <DropdownMenuPrimitive.ItemIndicator>
-        <MoreHorizontal className="h-2 w-2 fill-current" />
+        <HugeiconsIcon icon={MoreHorizontalIcon} size={8} className="h-2 w-2 fill-current" />
      </DropdownMenuPrimitive.ItemIndicator>
    </span>
    {children}
@@ -154,7 +155,9 @@ const DropdownMenuSeparator = React.forwardRef<
 DropdownMenuSeparator.displayName = DropdownMenuPrimitive.Separator.displayName;

 const DropdownMenuShortcut = ({ className, ...props }: React.HTMLAttributes<HTMLSpanElement>) => {
-  return <span className={cn('ml-auto text-xs tracking-widest opacity-60', className)} {...props} />;
+  return (
+    <span className={cn('ml-auto text-xs tracking-widest opacity-60', className)} {...props} />
+  );
 };
 DropdownMenuShortcut.displayName = 'DropdownMenuShortcut';

@@ -1,5 +1,6 @@
 import * as React from 'react';
-import { ChevronDown, Check } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { ArrowDown01Icon, CheckmarkCircle01Icon } from '@hugeicons/core-free-icons';
 import { cn } from '@/lib/utils/cn';
 import {
  DropdownMenu,
@@ -36,7 +37,7 @@ const MultiSelectCheckboxItem = React.forwardRef<
  >
    <span className="absolute left-2 flex h-3.5 w-3.5 items-center justify-center">
      <DropdownMenuPrimitive.ItemIndicator>
-        <Check className="h-4 w-4" />
+        <HugeiconsIcon icon={CheckmarkCircle01Icon} size={16} className="h-4 w-4" />
      </DropdownMenuPrimitive.ItemIndicator>
    </span>
    {children}
@@ -78,7 +79,7 @@ export function MultiSelect({
          )}
        >
          <span className="line-clamp-1">{displayText}</span>
-          <ChevronDown className="h-4 w-4 opacity-50" />
+          <HugeiconsIcon icon={ArrowDown01Icon} size={16} className="h-4 w-4 opacity-50" />
        </button>
      </DropdownMenuTrigger>
      <DropdownMenuContent
@@ -0,0 +1,43 @@
+'use client';
+
+import { CircleIcon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import * as RadioGroupPrimitive from '@radix-ui/react-radio-group';
+import * as React from 'react';
+
+import { cn } from '@/lib/utils/cn';
+
+const RadioGroup = React.forwardRef<
+  React.ElementRef<typeof RadioGroupPrimitive.Root>,
+  React.ComponentPropsWithoutRef<typeof RadioGroupPrimitive.Root>
+>(({ className, ...props }, ref) => {
+  return <RadioGroupPrimitive.Root className={cn('grid gap-2', className)} {...props} ref={ref} />;
+});
+RadioGroup.displayName = RadioGroupPrimitive.Root.displayName;
+
+const RadioGroupItem = React.forwardRef<
+  React.ElementRef<typeof RadioGroupPrimitive.Item>,
+  React.ComponentPropsWithoutRef<typeof RadioGroupPrimitive.Item>
+>(({ className, ...props }, ref) => {
+  return (
+    <RadioGroupPrimitive.Item
+      ref={ref}
+      className={cn(
+        'aspect-square h-4 w-4 rounded-full border border-accent text-accent ring-offset-background focus:outline-none focus-visible:ring-2 focus-visible:ring-ring focus-visible:ring-offset-2 disabled:cursor-not-allowed disabled:opacity-50',
+        className,
+      )}
+      {...props}
+    >
+      <RadioGroupPrimitive.Indicator className="flex items-center justify-center">
+        <HugeiconsIcon
+          icon={CircleIcon}
+          size={10}
+          className="h-2.5 w-2.5 fill-current text-current"
+        />
+      </RadioGroupPrimitive.Indicator>
+    </RadioGroupPrimitive.Item>
+  );
+});
+RadioGroupItem.displayName = RadioGroupPrimitive.Item.displayName;
+
+export { RadioGroup, RadioGroupItem };
@@ -1,5 +1,6 @@
 import * as SelectPrimitive from '@radix-ui/react-select';
-import { Check, ChevronDown, ChevronUp } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { CheckmarkCircle01Icon, ArrowDown01Icon, ArrowUp01Icon } from '@hugeicons/core-free-icons';
 import * as React from 'react';
 import { cn } from '@/lib/utils/cn';

@@ -23,7 +24,7 @@ const SelectTrigger = React.forwardRef<
  >
    {children}
    <SelectPrimitive.Icon asChild>
-      <ChevronDown className="h-4 w-4 opacity-50" />
+      <HugeiconsIcon icon={ArrowDown01Icon} size={16} className="h-4 w-4 opacity-50" />
    </SelectPrimitive.Icon>
  </SelectPrimitive.Trigger>
 ));
@@ -38,7 +39,7 @@ const SelectScrollUpButton = React.forwardRef<
    className={cn('flex cursor-default items-center justify-center py-1', className)}
    {...props}
  >
-    <ChevronUp className="h-4 w-4" />
+    <HugeiconsIcon icon={ArrowUp01Icon} size={16} className="h-4 w-4" />
  </SelectPrimitive.ScrollUpButton>
 ));
 SelectScrollUpButton.displayName = SelectPrimitive.ScrollUpButton.displayName;
@@ -52,7 +53,7 @@ const SelectScrollDownButton = React.forwardRef<
    className={cn('flex cursor-default items-center justify-center py-1', className)}
    {...props}
  >
-    <ChevronDown className="h-4 w-4" />
+    <HugeiconsIcon icon={ArrowDown01Icon} size={16} className="h-4 w-4" />
  </SelectPrimitive.ScrollDownButton>
 ));
 SelectScrollDownButton.displayName = SelectPrimitive.ScrollDownButton.displayName;
@@ -115,7 +116,7 @@ const SelectItem = React.forwardRef<
  >
    <span className="absolute left-2 flex h-3.5 w-3.5 items-center justify-center">
      <SelectPrimitive.ItemIndicator>
-        <Check className="h-4 w-4" />
+        <HugeiconsIcon icon={CheckmarkCircle01Icon} size={16} className="h-4 w-4" />
      </SelectPrimitive.ItemIndicator>
    </span>

@@ -1,6 +1,7 @@
 import * as ToastPrimitives from '@radix-ui/react-toast';
 import { cva, type VariantProps } from 'class-variance-authority';
-import { X } from 'lucide-react';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Cancel01Icon } from '@hugeicons/core-free-icons';
 import * as React from 'react';
 import { cn } from '@/lib/utils/cn';

@@ -79,7 +80,7 @@ const ToastClose = React.forwardRef<
    toast-close=""
    {...props}
  >
-    <X className="h-4 w-4" />
+    <HugeiconsIcon icon={Cancel01Icon} size={16} className="h-4 w-4" />
  </ToastPrimitives.Close>
 ));
 ToastClose.displayName = ToastPrimitives.Close.displayName;
@@ -0,0 +1,210 @@
+import { Download01Icon, Refresh01Icon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { useCallback, useEffect, useRef, useState } from 'react';
+import { Progress } from '@/components/ui/progress';
+import { ToastAction } from '@/components/ui/toast';
+import { useToast } from '@/components/ui/use-toast';
+import { usePlatform } from '@/platform/PlatformContext';
+import type { UpdateStatus } from '@/platform/types';
+
+// Re-export UpdateStatus for backwards compatibility
+export type { UpdateStatus };
+
+interface UseAutoUpdaterOptions {
+  checkOnMount?: boolean;
+  showToast?: boolean;
+}
+
+export function useAutoUpdater(options: boolean | UseAutoUpdaterOptions = false) {
+  // Support both old boolean API and new options object
+  const { checkOnMount, showToast } =
+    typeof options === 'boolean'
+      ? { checkOnMount: options, showToast: false }
+      : { checkOnMount: options.checkOnMount ?? false, showToast: options.showToast ?? false };
+
+  const platform = usePlatform();
+  const { toast } = useToast();
+  const [status, setStatus] = useState<UpdateStatus>(platform.updater.getStatus());
+  const hasCheckedRef = useRef(false);
+  const toastIdRef = useRef<string | null>(null);
+  const toastUpdateRef = useRef<
+    | ((props: {
+        title?: React.ReactNode;
+        description?: React.ReactNode;
+        duration?: number;
+        variant?: 'default' | 'destructive';
+        open?: boolean;
+        action?: React.ReactElement<typeof ToastAction>;
+      }) => void)
+    | null
+  >(null);
+
+  // Subscribe to updater status changes
+  useEffect(() => {
+    const unsubscribe = platform.updater.subscribe((newStatus) => {
+      setStatus(newStatus);
+    });
+    return unsubscribe;
+    // Empty dependency array - platform is stable from context
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.updater.subscribe]);
+
+  const checkForUpdates = useCallback(async () => {
+    await platform.updater.checkForUpdates();
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.updater.checkForUpdates]);
+
+  const downloadAndInstall = useCallback(async () => {
+    await platform.updater.downloadAndInstall();
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.updater.downloadAndInstall]);
+
+  const restartAndInstall = useCallback(async () => {
+    await platform.updater.restartAndInstall();
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.updater.restartAndInstall]);
+
+  // Check for updates on mount
+  useEffect(() => {
+    if (checkOnMount && platform.metadata.isTauri && !hasCheckedRef.current) {
+      hasCheckedRef.current = true;
+      checkForUpdates().catch((error) => {
+        console.error('Auto update check failed:', error);
+      });
+    }
+    // Empty dependency array - only run once on mount
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, [platform.metadata.isTauri, checkOnMount, checkForUpdates]);
+
+  // Show toast when update is available
+  useEffect(() => {
+    if (
+      !showToast ||
+      !status.available ||
+      status.downloading ||
+      status.readyToInstall ||
+      toastIdRef.current
+    ) {
+      return;
+    }
+
+    const handleUpdateNow = async () => {
+      await downloadAndInstall();
+    };
+
+    const toastResult = toast({
+      title: 'Update Available',
+      description: `Version ${status.version} is ready to download.`,
+      duration: Infinity,
+      action: (
+        <ToastAction altText="Update now" onClick={handleUpdateNow}>
+          Update Now
+        </ToastAction>
+      ),
+    });
+
+    toastIdRef.current = toastResult.id;
+    // Type assertion needed because update function has broader type than our ref
+    toastUpdateRef.current = toastResult.update as typeof toastUpdateRef.current;
+  }, [
+    showToast,
+    status.available,
+    status.downloading,
+    status.readyToInstall,
+    status.version,
+    downloadAndInstall,
+    toast,
+  ]);
+
+  // Update toast when downloading
+  useEffect(() => {
+    if (!showToast || !status.downloading || !toastIdRef.current || !toastUpdateRef.current) {
+      return;
+    }
+
+    const progressPercent = status.downloadProgress || 0;
+    const progressText =
+      status.downloadedBytes !== undefined &&
+      status.totalBytes !== undefined &&
+      status.totalBytes > 0
+        ? `${(status.downloadedBytes / 1024 / 1024).toFixed(1)} MB / ${(status.totalBytes / 1024 / 1024).toFixed(1)} MB`
+        : '';
+
+    toastUpdateRef.current({
+      title: (
+        <div className="flex items-center gap-2">
+          <HugeiconsIcon icon={Download01Icon} size={16} className="h-4 w-4 animate-pulse" />
+          <span>Downloading Update</span>
+        </div>
+      ),
+      description: (
+        <div className="space-y-2">
+          <div className="text-sm">Version {status.version}</div>
+          {progressPercent > 0 && (
+            <>
+              <Progress value={progressPercent} className="h-2" />
+              {progressText && <div className="text-xs text-muted-foreground">{progressText}</div>}
+            </>
+          )}
+        </div>
+      ),
+      duration: Infinity,
+    });
+  }, [
+    showToast,
+    status.downloading,
+    status.downloadProgress,
+    status.downloadedBytes,
+    status.totalBytes,
+    status.version,
+  ]);
+
+  // Update toast when ready to install
+  useEffect(() => {
+    if (!showToast || !status.readyToInstall || !toastIdRef.current || !toastUpdateRef.current) {
+      return;
+    }
+
+    const handleRestartNow = async () => {
+      await restartAndInstall();
+    };
+
+    toastUpdateRef.current({
+      title: 'Update Ready',
+      description: `Version ${status.version} has been downloaded and is ready to install.`,
+      duration: Infinity,
+      action: (
+        <ToastAction altText="Restart now" onClick={handleRestartNow}>
+          <HugeiconsIcon icon={Refresh01Icon} size={12} className="h-3 w-3 mr-1" />
+          Restart Now
+        </ToastAction>
+      ),
+    });
+  }, [showToast, status.readyToInstall, status.version, restartAndInstall]);
+
+  // Handle errors in toast
+  useEffect(() => {
+    if (!showToast || !status.error || !toastIdRef.current || !toastUpdateRef.current) {
+      return;
+    }
+
+    toastUpdateRef.current({
+      title: 'Update Failed',
+      description: status.error,
+      variant: 'destructive',
+      duration: 5000,
+    });
+
+    setTimeout(() => {
+      toastIdRef.current = null;
+      toastUpdateRef.current = null;
+    }, 5000);
+  }, [showToast, status.error]);
+
+  return {
+    status,
+    checkForUpdates,
+    downloadAndInstall,
+    restartAndInstall,
+  };
+}
@@ -1,29 +1,30 @@
-import { useServerStore } from '@/stores/serverStore';
 import type { LanguageCode } from '@/lib/constants/languages';
+import { useServerStore } from '@/stores/serverStore';
 import type {
-  VoiceProfileCreate,
-  VoiceProfileResponse,
-  ProfileSampleResponse,
+  ActiveTasksResponse,
+  FolderPathsResponse,
  GenerationRequest,
  GenerationResponse,
-  HistoryQuery,
-  HistoryListResponse,
-  HistoryResponse,
-  TranscriptionResponse,
  HealthResponse,
-  ModelStatusListResponse,
+  HistoryListResponse,
+  HistoryQuery,
+  HistoryResponse,
  ModelDownloadRequest,
-  ActiveTasksResponse,
+  ModelStatusListResponse,
+  ProfileSampleResponse,
  StoryCreate,
-  StoryResponse,
  StoryDetailResponse,
+  StoryItemBatchUpdate,
  StoryItemCreate,
  StoryItemDetail,
-  StoryItemBatchUpdate,
-  StoryItemReorder,
  StoryItemMove,
-  StoryItemTrim,
+  StoryItemReorder,
  StoryItemSplit,
+  StoryItemTrim,
+  StoryResponse,
+  TranscriptionResponse,
+  VoiceProfileCreate,
+  VoiceProfileResponse,
 } from './types';

 class ApiClient {
@@ -57,6 +58,11 @@ class ApiClient {
    return this.request<HealthResponse>('/health');
  }

+  // System
+  async getSystemFolders(): Promise<FolderPathsResponse> {
+    return this.request<FolderPathsResponse>('/system/folders');
+  }
+
  // Profiles
  async createProfile(data: VoiceProfileCreate): Promise<VoiceProfileResponse> {
    return this.request<VoiceProfileResponse>('/profiles', {
@@ -199,6 +205,77 @@ class ApiClient {
    });
  }

+  // Providers
+  async listProviders(): Promise<{
+    providers: Array<{
+      type: string;
+      name: string;
+      installed: boolean;
+      size_mb: number | null;
+    }>;
+    installed: string[];
+  }> {
+    return this.request('/providers');
+  }
+
+  async getActiveProvider(): Promise<{
+    provider: string;
+    health: {
+      status: string;
+      provider: string;
+      version: string | null;
+      model: string | null;
+      device: string | null;
+    };
+    status: {
+      model_loaded: boolean;
+      model_size: string | null;
+      available_sizes: string[];
+      gpu_available: boolean | null;
+      vram_used_mb: number | null;
+    };
+  }> {
+    return this.request('/providers/active');
+  }
+
+  async startProvider(providerType: string): Promise<{
+    message: string;
+    provider: {
+      status: string;
+      provider: string;
+      version: string | null;
+      model: string | null;
+      device: string | null;
+    };
+  }> {
+    return this.request('/providers/start', {
+      method: 'POST',
+      body: JSON.stringify({ provider_type: providerType }),
+    });
+  }
+
+  async stopProvider(): Promise<{ message: string }> {
+    return this.request('/providers/stop', {
+      method: 'POST',
+    });
+  }
+
+  async downloadProvider(providerType: string): Promise<{
+    message: string;
+    provider_type: string;
+  }> {
+    return this.request('/providers/download', {
+      method: 'POST',
+      body: JSON.stringify({ provider_type: providerType }),
+    });
+  }
+
+  async deleteProvider(providerType: string): Promise<{ message: string }> {
+    return this.request(`/providers/${providerType}`, {
+      method: 'DELETE',
+    });
+  }
+
  // History
  async listHistory(query?: HistoryQuery): Promise<HistoryListResponse> {
    const params = new URLSearchParams();
@@ -251,7 +328,15 @@ class ApiClient {
    return response.blob();
  }

-  async importGeneration(file: File): Promise<{ id: string; profile_id: string; profile_name: string; text: string; message: string }> {
+  async importGeneration(
+    file: File,
+  ): Promise<{
+    id: string;
+    profile_id: string;
+    profile_name: string;
+    text: string;
+    message: string;
+  }> {
    const url = `${this.getBaseUrl()}/history/import`;
    const formData = new FormData();
    formData.append('file', file);
@@ -310,10 +395,18 @@ class ApiClient {
  }

  async triggerModelDownload(modelName: string): Promise<{ message: string }> {
-    return this.request<{ message: string }>('/models/download', {
+    console.log(
+      '[API] triggerModelDownload called for:',
+      modelName,
+      'at',
+      new Date().toISOString(),
+    );
+    const result = await this.request<{ message: string }>('/models/download', {
      method: 'POST',
      body: JSON.stringify({ model_name: modelName } as ModelDownloadRequest),
    });
+    console.log('[API] triggerModelDownload response:', result);
+    return result;
  }

  async deleteModel(modelName: string): Promise<{ message: string }> {
@@ -340,10 +433,7 @@ class ApiClient {
    return this.request('/channels');
  }

-  async createChannel(data: {
-    name: string;
-    device_ids: string[];
-  }): Promise<{
+  async createChannel(data: { name: string; device_ids: string[] }): Promise<{
    id: string;
    name: string;
    is_default: boolean;
@@ -385,10 +475,7 @@ class ApiClient {
    return this.request(`/channels/${channelId}/voices`);
  }

-  async setChannelVoices(
-    channelId: string,
-    profileIds: string[],
-  ): Promise<{ message: string }> {
+  async setChannelVoices(channelId: string, profileIds: string[]): Promise<{ message: string }> {
    return this.request(`/channels/${channelId}/voices`, {
      method: 'PUT',
      body: JSON.stringify({ profile_ids: profileIds }),
@@ -399,10 +486,7 @@ class ApiClient {
    return this.request(`/profiles/${profileId}/channels`);
  }

-  async setProfileChannels(
-    profileId: string,
-    channelIds: string[],
-  ): Promise<{ message: string }> {
+  async setProfileChannels(profileId: string, channelIds: string[]): Promise<{ message: string }> {
    return this.request(`/profiles/${profileId}/channels`, {
      method: 'PUT',
      body: JSON.stringify({ channel_ids: channelIds }),
@@ -465,21 +549,33 @@ class ApiClient {
    });
  }

-  async moveStoryItem(storyId: string, itemId: string, data: StoryItemMove): Promise<StoryItemDetail> {
+  async moveStoryItem(
+    storyId: string,
+    itemId: string,
+    data: StoryItemMove,
+  ): Promise<StoryItemDetail> {
    return this.request<StoryItemDetail>(`/stories/${storyId}/items/${itemId}/move`, {
      method: 'PUT',
      body: JSON.stringify(data),
    });
  }

-  async trimStoryItem(storyId: string, itemId: string, data: StoryItemTrim): Promise<StoryItemDetail> {
+  async trimStoryItem(
+    storyId: string,
+    itemId: string,
+    data: StoryItemTrim,
+  ): Promise<StoryItemDetail> {
    return this.request<StoryItemDetail>(`/stories/${storyId}/items/${itemId}/trim`, {
      method: 'PUT',
      body: JSON.stringify(data),
    });
  }

-  async splitStoryItem(storyId: string, itemId: string, data: StoryItemSplit): Promise<StoryItemDetail[]> {
+  async splitStoryItem(
+    storyId: string,
+    itemId: string,
+    data: StoryItemSplit,
+  ): Promise<StoryItemDetail[]> {
    return this.request<StoryItemDetail[]>(`/stories/${storyId}/items/${itemId}/split`, {
      method: 'POST',
      body: JSON.stringify(data),
@@ -9,6 +9,7 @@ export type ModelStatus = {
  model_name: string;
  display_name: string;
  downloaded: boolean;
+  downloading?: boolean;  // True if download is in progress
  size_mb?: number | null;
  loaded?: boolean;
 };
@@ -34,6 +34,7 @@ export interface GenerationRequest {
  language: LanguageCode;
  seed?: number;
  model_size?: '1.7B' | '0.6B';
+  instruct?: string;
 }

 export interface GenerationResponse {
@@ -96,6 +97,7 @@ export interface ModelStatus {
  model_name: string;
  display_name: string;
  downloaded: boolean;
+  downloading: boolean;  // True if download is in progress
  size_mb?: number;
  loaded: boolean;
 }
@@ -126,6 +128,12 @@ export interface ActiveTasksResponse {
  generations: ActiveGenerationTask[];
 }

+export interface FolderPathsResponse {
+  data_dir: string;
+  models_dir: string;
+  providers_dir: string;
+}
+
 export interface StoryCreate {
  name: string;
  description?: string;
@@ -1,5 +1,5 @@
 import { useCallback, useEffect, useRef, useState } from 'react';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';
 import { convertToWav } from '@/lib/utils/audio';

 interface UseAudioRecordingOptions {
@@ -11,6 +11,7 @@ export function useAudioRecording({
  maxDurationSeconds = 29,
  onRecordingComplete,
 }: UseAudioRecordingOptions = {}) {
+  const platform = usePlatform();
  const [isRecording, setIsRecording] = useState(false);
  const [duration, setDuration] = useState(0);
  const [error, setError] = useState<string | null>(null);
@@ -40,15 +41,14 @@ export function useAudioRecording({
        await new Promise((resolve) => setTimeout(resolve, 100));

        if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
-          const isTauriEnv = isTauri();
          console.error('MediaDevices check:', {
            hasNavigator: typeof navigator !== 'undefined',
            hasMediaDevices: !!navigator?.mediaDevices,
            hasGetUserMedia: !!navigator?.mediaDevices?.getUserMedia,
-            isTauri: isTauriEnv,
+            isTauri: platform.metadata.isTauri,
          });

-          const errorMsg = isTauriEnv
+          const errorMsg = platform.metadata.isTauri
            ? 'Microphone access is not available. Please ensure:\n1. The app has microphone permissions in System Settings (macOS: System Settings > Privacy & Security > Microphone)\n2. You restart the app after granting permissions\n3. You are using Tauri v2 with a webview that supports getUserMedia'
            : 'Microphone access is not available. Please ensure you are using a secure context (HTTPS or localhost) and that your browser has microphone permissions enabled.';
          setError(errorMsg);
@@ -91,11 +91,6 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
        instruct: data.instruct || undefined,
      });

-      toast({
-        title: 'Generation complete!',
-        description: `Audio generated (${result.duration.toFixed(2)}s)`,
-      });
-
      const audioUrl = apiClient.getAudioUrl(result.id);
      setAudioWithAutoPlay(audioUrl, result.id, selectedProfileId, data.text.substring(0, 50));

@@ -1,7 +1,7 @@
 import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
 import { apiClient } from '@/lib/api/client';
 import type { HistoryQuery } from '@/lib/api/types';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';

 export function useHistory(query?: HistoryQuery) {
  return useQuery({
@@ -30,116 +30,52 @@ export function useDeleteGeneration() {
 }

 export function useExportGeneration() {
+  const platform = usePlatform();
+
  return useMutation({
    mutationFn: async ({ generationId, text }: { generationId: string; text: string }) => {
      const blob = await apiClient.exportGeneration(generationId);
-      
+
      // Create safe filename from text
-      const safeText = text.substring(0, 30).replace(/[^a-z0-9]/gi, '-').toLowerCase();
+      const safeText = text
+        .substring(0, 30)
+        .replace(/[^a-z0-9]/gi, '-')
+        .toLowerCase();
      const filename = `generation-${safeText}.voicebox.zip`;
-      
-      if (isTauri()) {
-        // Use Tauri's native save dialog
-        try {
-          const { save } = await import('@tauri-apps/plugin-dialog');
-          const filePath = await save({
-            defaultPath: filename,
-            filters: [
-              {
-                name: 'Voicebox Generation',
-                extensions: ['voicebox.zip', 'zip'],
-              },
-            ],
-          });
-          
-          if (filePath) {
-            // Write file using Tauri's filesystem API
-            const { writeBinaryFile } = await import('@tauri-apps/plugin-fs');
-            const arrayBuffer = await blob.arrayBuffer();
-            await writeBinaryFile(filePath, new Uint8Array(arrayBuffer));
-          }
-        } catch (error) {
-          console.error('Failed to use Tauri dialog, falling back to browser download:', error);
-          // Fall back to browser download if Tauri dialog fails
-          const url = window.URL.createObjectURL(blob);
-          const a = document.createElement('a');
-          a.href = url;
-          a.download = filename;
-          document.body.appendChild(a);
-          a.click();
-          window.URL.revokeObjectURL(url);
-          document.body.removeChild(a);
-        }
-      } else {
-        // Browser: trigger download
-        const url = window.URL.createObjectURL(blob);
-        const a = document.createElement('a');
-        a.href = url;
-        a.download = filename;
-        document.body.appendChild(a);
-        a.click();
-        window.URL.revokeObjectURL(url);
-        document.body.removeChild(a);
-      }
-      
+
+      await platform.filesystem.saveFile(filename, blob, [
+        {
+          name: 'Voicebox Generation',
+          extensions: ['zip'],
+        },
+      ]);
+
      return blob;
    },
  });
 }

 export function useExportGenerationAudio() {
+  const platform = usePlatform();
+
  return useMutation({
    mutationFn: async ({ generationId, text }: { generationId: string; text: string }) => {
      const blob = await apiClient.exportGenerationAudio(generationId);
-      
+
      // Create safe filename from text
-      const safeText = text.substring(0, 30).replace(/[^a-z0-9]/gi, '-').toLowerCase();
+      const safeText = text
+        .substring(0, 30)
+        .replace(/[^a-z0-9]/gi, '-')
+        .toLowerCase();
      const filename = `${safeText}.wav`;
-      
-      if (isTauri()) {
-        // Use Tauri's native save dialog
-        try {
-          const { save } = await import('@tauri-apps/plugin-dialog');
-          const filePath = await save({
-            defaultPath: filename,
-            filters: [
-              {
-                name: 'Audio File',
-                extensions: ['wav'],
-              },
-            ],
-          });
-          
-          if (filePath) {
-            // Write file using Tauri's filesystem API
-            const { writeBinaryFile } = await import('@tauri-apps/plugin-fs');
-            const arrayBuffer = await blob.arrayBuffer();
-            await writeBinaryFile(filePath, new Uint8Array(arrayBuffer));
-          }
-        } catch (error) {
-          console.error('Failed to use Tauri dialog, falling back to browser download:', error);
-          // Fall back to browser download if Tauri dialog fails
-          const url = window.URL.createObjectURL(blob);
-          const a = document.createElement('a');
-          a.href = url;
-          a.download = filename;
-          document.body.appendChild(a);
-          a.click();
-          window.URL.revokeObjectURL(url);
-          document.body.removeChild(a);
-        }
-      } else {
-        // Browser: trigger download
-        const url = window.URL.createObjectURL(blob);
-        const a = document.createElement('a');
-        a.href = url;
-        a.download = filename;
-        document.body.appendChild(a);
-        a.click();
-        window.URL.revokeObjectURL(url);
-        document.body.removeChild(a);
-      }
-      
+
+      await platform.filesystem.saveFile(filename, blob, [
+        {
+          name: 'Audio File',
+          extensions: ['wav'],
+        },
+      ]);
+
      return blob;
    },
  });
@@ -1,14 +1,18 @@
-import { useEffect, useRef } from 'react';
-import { useToast } from '@/components/ui/use-toast';
-import { useServerStore } from '@/stores/serverStore';
+import { CancelCircleIcon, CheckmarkCircle02Icon } from '@hugeicons/core-free-icons';
+import { HugeiconsIcon } from '@hugeicons/react';
+import { Icon } from '@iconify/react';
+import { useCallback, useEffect, useRef } from 'react';
 import { Progress } from '@/components/ui/progress';
-import { Loader2, CheckCircle2, XCircle } from 'lucide-react';
+import { useToast } from '@/components/ui/use-toast';
 import type { ModelProgress } from '@/lib/api/types';
+import { useServerStore } from '@/stores/serverStore';

 interface UseModelDownloadToastOptions {
  modelName: string;
  displayName: string;
  enabled?: boolean;
+  onComplete?: () => void;
+  onError?: () => void;
 }

 /**
@@ -19,47 +23,64 @@ export function useModelDownloadToast({
  modelName,
  displayName,
  enabled = false,
+  onComplete,
+  onError,
 }: UseModelDownloadToastOptions) {
  const { toast } = useToast();
  const serverUrl = useServerStore((state) => state.serverUrl);
  const toastIdRef = useRef<string | null>(null);
-  const toastUpdateRef = useRef<
-    ((props: {
-      title?: React.ReactNode;
-      description?: React.ReactNode;
-      duration?: number;
-      variant?: 'default' | 'destructive';
-      open?: boolean;
-    }) => void) | null
-  >(null);
+  // biome-ignore lint: Using any for toast update ref to handle complex toast types
+  const toastUpdateRef = useRef<any>(null);
  const eventSourceRef = useRef<EventSource | null>(null);

-  const formatBytes = (bytes: number): string => {
+  const formatBytes = useCallback((bytes: number): string => {
    if (bytes === 0) return '0 B';
    const k = 1024;
    const sizes = ['B', 'KB', 'MB', 'GB'];
    const i = Math.floor(Math.log(bytes) / Math.log(k));
-    return `${(bytes / Math.pow(k, i)).toFixed(1)} ${sizes[i]}`;
-  };
+    return `${(bytes / k ** i).toFixed(1)} ${sizes[i]}`;
+  }, []);

  useEffect(() => {
+    console.log('[useModelDownloadToast] useEffect triggered', {
+      enabled,
+      serverUrl,
+      modelName,
+      displayName,
+    });
+
    if (!enabled || !serverUrl || !modelName) {
+      console.log('[useModelDownloadToast] Not enabled, skipping');
      return;
    }

+    console.log('[useModelDownloadToast] Creating toast and EventSource for:', modelName);
+
    // Create initial toast
    const toastResult = toast({
      title: displayName,
-      description: 'Starting download...',
+      description: (
+        <div className="flex items-center gap-2">
+          <Icon icon="svg-spinners:ring-resize" className="h-4 w-4 animate-spin" />
+          <span>Connecting to download...</span>
+        </div>
+      ),
      duration: Infinity, // Don't auto-dismiss, we'll handle it manually
    });
    toastIdRef.current = toastResult.id;
    toastUpdateRef.current = toastResult.update;

    // Subscribe to progress updates via Server-Sent Events
-    const eventSource = new EventSource(`${serverUrl}/models/progress/${modelName}`);
+    const eventSourceUrl = `${serverUrl}/models/progress/${modelName}`;
+    console.log('[useModelDownloadToast] Creating EventSource to:', eventSourceUrl);
+    const eventSource = new EventSource(eventSourceUrl);
+
+    eventSource.onopen = () => {
+      console.log('[useModelDownloadToast] EventSource connection opened for:', modelName);
+    };

    eventSource.onmessage = (event) => {
+      console.log('[useModelDownloadToast] Received SSE message:', event.data);
      try {
        const progress = JSON.parse(event.data) as ModelProgress;

@@ -77,19 +98,35 @@ export function useModelDownloadToast({

          switch (progress.status) {
            case 'complete':
-              statusIcon = <CheckCircle2 className="h-4 w-4 text-green-500" />;
+              statusIcon = (
+                <HugeiconsIcon
+                  icon={CheckmarkCircle02Icon}
+                  size={16}
+                  className="h-4 w-4 text-green-500"
+                />
+              );
              statusText = 'Download complete';
              break;
            case 'error':
-              statusIcon = <XCircle className="h-4 w-4 text-destructive" />;
+              statusIcon = (
+                <HugeiconsIcon
+                  icon={CancelCircleIcon}
+                  size={16}
+                  className="h-4 w-4 text-destructive"
+                />
+              );
              statusText = `Error: ${progress.error || 'Unknown error'}`;
              break;
            case 'downloading':
-              statusIcon = <Loader2 className="h-4 w-4 animate-spin" />;
-              statusText = progress.filename ? `Downloading ${progress.filename}...` : 'Downloading...';
+              statusIcon = (
+                <Icon icon="svg-spinners:ring-resize" className="h-4 w-4 animate-spin" />
+              );
+              statusText = progress.filename || 'Downloading...';
              break;
            case 'extracting':
-              statusIcon = <Loader2 className="h-4 w-4 animate-spin" />;
+              statusIcon = (
+                <Icon icon="svg-spinners:ring-resize" className="h-4 w-4 animate-spin" />
+              );
              statusText = 'Extracting...';
              break;
          }
@@ -117,21 +154,44 @@ export function useModelDownloadToast({
          });

          // Close connection and dismiss toast on completion or error
-          if (progress.status === 'complete' || progress.status === 'error') {
+          // Also treat progress >= 100% as complete
+          const isComplete = progress.status === 'complete' || progress.progress >= 100;
+          const isError = progress.status === 'error';
+
+          if (isComplete || isError) {
+            console.log('[useModelDownloadToast] Download finished:', {
+              isComplete,
+              isError,
+              progress: progress.progress,
+            });
            eventSource.close();
            eventSourceRef.current = null;

-            // Auto-dismiss on completion after delay
-            if (progress.status === 'complete') {
-              setTimeout(() => {
-                if (toastIdRef.current && toastUpdateRef.current) {
-                  toastUpdateRef.current({
-                    open: false,
-                  });
-                  toastIdRef.current = null;
-                  toastUpdateRef.current = null;
-                }
-              }, 5000);
+            // Update toast to show completion state before callbacks
+            if (isComplete && toastUpdateRef.current) {
+              toastUpdateRef.current({
+                title: (
+                  <div className="flex items-center gap-2">
+                    <HugeiconsIcon
+                      icon={CheckmarkCircle02Icon}
+                      size={16}
+                      className="h-4 w-4 text-green-500"
+                    />
+                    <span>{displayName}</span>
+                  </div>
+                ),
+                description: 'Download complete',
+                duration: 3000,
+              });
+            }
+
+            // Call callbacks
+            if (isComplete && onComplete) {
+              console.log('[useModelDownloadToast] Download complete, calling onComplete callback');
+              onComplete();
+            } else if (isError && onError) {
+              console.log('[useModelDownloadToast] Download error, calling onError callback');
+              onError();
            }
          }
        }
@@ -141,7 +201,8 @@ export function useModelDownloadToast({
    };

    eventSource.onerror = (error) => {
-      console.error('SSE error:', error);
+      console.error('[useModelDownloadToast] SSE error for:', modelName, error);
+      console.log('[useModelDownloadToast] EventSource readyState:', eventSource.readyState);
      eventSource.close();
      eventSourceRef.current = null;

@@ -162,15 +223,16 @@ export function useModelDownloadToast({

    // Cleanup on unmount or when disabled
    return () => {
+      console.log('[useModelDownloadToast] Cleanup - closing EventSource for:', modelName);
      if (eventSourceRef.current) {
        eventSourceRef.current.close();
        eventSourceRef.current = null;
      }
      // Note: We don't dismiss the toast here as it might still be showing completion state
    };
-  }, [enabled, serverUrl, modelName, displayName, toast]);
+  }, [enabled, serverUrl, modelName, displayName, toast, formatBytes, onComplete, onError]);

  return {
    isTracking: enabled && eventSourceRef.current !== null,
  };
-}
+}
@@ -1,7 +1,7 @@
 import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
 import { apiClient } from '@/lib/api/client';
 import type { VoiceProfileCreate } from '@/lib/api/types';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';

 export function useProfiles() {
  return useQuery({
@@ -117,59 +117,24 @@ export function useUpdateSample() {
 }

 export function useExportProfile() {
+  const platform = usePlatform();
+
  return useMutation({
    mutationFn: async (profileId: string) => {
      const blob = await apiClient.exportProfile(profileId);
-      
+
      // Get profile name for filename
      const profile = await apiClient.getProfile(profileId);
      const safeName = profile.name.replace(/[^a-z0-9]/gi, '-').toLowerCase();
      const filename = `profile-${safeName}.voicebox.zip`;
-      
-      if (isTauri()) {
-        // Use Tauri's native save dialog
-        try {
-          const { save } = await import('@tauri-apps/plugin-dialog');
-          const filePath = await save({
-            defaultPath: filename,
-            filters: [
-              {
-                name: 'Voicebox Profile',
-                extensions: ['voicebox.zip', 'zip'],
-              },
-            ],
-          });
-          
-          if (filePath) {
-            // Write file using Tauri's filesystem API
-            const { writeBinaryFile } = await import('@tauri-apps/plugin-fs');
-            const arrayBuffer = await blob.arrayBuffer();
-            await writeBinaryFile(filePath, new Uint8Array(arrayBuffer));
-          }
-        } catch (error) {
-          console.error('Failed to use Tauri dialog, falling back to browser download:', error);
-          // Fall back to browser download if Tauri dialog fails
-          const url = window.URL.createObjectURL(blob);
-          const a = document.createElement('a');
-          a.href = url;
-          a.download = filename;
-          document.body.appendChild(a);
-          a.click();
-          window.URL.revokeObjectURL(url);
-          document.body.removeChild(a);
-        }
-      } else {
-        // Browser: trigger download
-        const url = window.URL.createObjectURL(blob);
-        const a = document.createElement('a');
-        a.href = url;
-        a.download = filename;
-        document.body.appendChild(a);
-        a.click();
-        window.URL.revokeObjectURL(url);
-        document.body.removeChild(a);
-      }
-      
+
+      await platform.filesystem.saveFile(filename, blob, [
+        {
+          name: 'Voicebox Profile',
+          extensions: ['zip'],
+        },
+      ]);
+
      return blob;
    },
  });
@@ -1,7 +1,7 @@
 import { useMutation, useQuery, useQueryClient } from '@tanstack/react-query';
 import { apiClient } from '@/lib/api/client';
 import type { StoryCreate, StoryItemCreate, StoryItemBatchUpdate, StoryItemReorder, StoryItemMove, StoryItemTrim, StoryItemSplit } from '@/lib/api/types';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';

 export function useStories() {
  return useQuery({
@@ -158,6 +158,8 @@ export function useDuplicateStoryItem() {
 }

 export function useExportStoryAudio() {
+  const platform = usePlatform();
+
  return useMutation({
    mutationFn: async ({ storyId, storyName }: { storyId: string; storyName: string }) => {
      const blob = await apiClient.exportStoryAudio(storyId);
@@ -166,49 +168,12 @@ export function useExportStoryAudio() {
      const safeName = storyName.substring(0, 50).replace(/[^a-z0-9]/gi, '-').toLowerCase();
      const filename = `${safeName || 'story'}.wav`;

-      if (isTauri()) {
-        // Use Tauri's native save dialog
-        try {
-          const { save } = await import('@tauri-apps/plugin-dialog');
-          const filePath = await save({
-            defaultPath: filename,
-            filters: [
-              {
-                name: 'Audio File',
-                extensions: ['wav'],
-              },
-            ],
-          });
-
-          if (filePath) {
-            // Write file using Tauri's filesystem API
-            const { writeBinaryFile } = await import('@tauri-apps/plugin-fs');
-            const arrayBuffer = await blob.arrayBuffer();
-            await writeBinaryFile(filePath, new Uint8Array(arrayBuffer));
-          }
-        } catch (error) {
-          console.error('Failed to use Tauri dialog, falling back to browser download:', error);
-          // Fall back to browser download if Tauri dialog fails
-          const url = window.URL.createObjectURL(blob);
-          const a = document.createElement('a');
-          a.href = url;
-          a.download = filename;
-          document.body.appendChild(a);
-          a.click();
-          window.URL.revokeObjectURL(url);
-          document.body.removeChild(a);
-        }
-      } else {
-        // Browser: trigger download
-        const url = window.URL.createObjectURL(blob);
-        const a = document.createElement('a');
-        a.href = url;
-        a.download = filename;
-        document.body.appendChild(a);
-        a.click();
-        window.URL.revokeObjectURL(url);
-        document.body.removeChild(a);
-      }
+      await platform.filesystem.saveFile(filename, blob, [
+        {
+          name: 'Audio File',
+          extensions: ['wav'],
+        },
+      ]);

      return blob;
    },
@@ -1,6 +1,5 @@
 import { useState, useRef, useCallback, useEffect } from 'react';
-import { invoke } from '@tauri-apps/api/core';
-import { isTauri } from '@/lib/tauri';
+import { usePlatform } from '@/platform/PlatformContext';

 interface UseSystemAudioCaptureOptions {
  maxDurationSeconds?: number;
@@ -15,6 +14,7 @@ export function useSystemAudioCapture({
  maxDurationSeconds = 29,
  onRecordingComplete,
 }: UseSystemAudioCaptureOptions = {}) {
+  const platform = usePlatform();
  const [isRecording, setIsRecording] = useState(false);
  const [duration, setDuration] = useState(0);
  const [error, setError] = useState<string | null>(null);
@@ -26,22 +26,12 @@ export function useSystemAudioCapture({

  // Check if system audio capture is supported
  useEffect(() => {
-    if (!isTauri()) {
-      setIsSupported(false);
-      return;
-    }
-
-    invoke<boolean>('is_system_audio_supported')
-      .then((supported) => {
-        setIsSupported(supported);
-      })
-      .catch(() => {
-        setIsSupported(false);
-      });
-  }, []);
+    const supported = platform.audio.isSystemAudioSupported();
+    setIsSupported(supported);
+  }, [platform]);

  const startRecording = useCallback(async () => {
-    if (!isTauri()) {
+    if (!platform.metadata.isTauri) {
      const errorMsg = 'System audio capture is only available in the desktop app.';
      setError(errorMsg);
      return;
@@ -58,9 +48,7 @@ export function useSystemAudioCapture({
      setDuration(0);

      // Start native capture
-      await invoke('start_system_audio_capture', {
-        maxDurationSecs: maxDurationSeconds,
-      });
+      await platform.audio.startSystemAudioCapture(maxDurationSeconds);

      setIsRecording(true);
      isRecordingRef.current = true;
@@ -86,10 +74,10 @@ export function useSystemAudioCapture({
      setError(errorMessage);
      setIsRecording(false);
    }
-  }, [maxDurationSeconds, isSupported]);
+  }, [maxDurationSeconds, isSupported, platform]);

  const stopRecording = useCallback(async () => {
-    if (!isRecording || !isTauri()) {
+    if (!isRecording || !platform.metadata.isTauri) {
      return;
    }

@@ -102,17 +90,9 @@ export function useSystemAudioCapture({
        timerRef.current = null;
      }

-      // Stop capture and get base64 WAV data
-      const base64Data = await invoke<string>('stop_system_audio_capture');
+      // Stop capture and get Blob
+      const blob = await platform.audio.stopSystemAudioCapture();

-      // Convert base64 to Blob
-      const binaryString = atob(base64Data);
-      const bytes = new Uint8Array(binaryString.length);
-      for (let i = 0; i < binaryString.length; i++) {
-        bytes[i] = binaryString.charCodeAt(i);
-      }
-
-      const blob = new Blob([bytes], { type: 'audio/wav' });
      // Pass the actual recorded duration
      const recordedDuration = startTimeRef.current 
        ? (Date.now() - startTimeRef.current) / 1000 
@@ -125,7 +105,7 @@ export function useSystemAudioCapture({
          : 'Failed to stop system audio capture.';
      setError(errorMessage);
    }
-  }, [isRecording, onRecordingComplete]);
+  }, [isRecording, onRecordingComplete, platform]);

  // Store stopRecording in ref for use in timer
  useEffect(() => {
@@ -155,15 +135,15 @@ export function useSystemAudioCapture({
        timerRef.current = null;
      }
      // Cancel recording on unmount if still recording
-      if (isRecordingRef.current && isTauri()) {
+      if (isRecordingRef.current && platform.metadata.isTauri) {
        // Call stop directly without the callback to avoid stale closure
-        invoke('stop_system_audio_capture').catch((err) => {
+        platform.audio.stopSystemAudioCapture().catch((err) => {
          console.error('Error stopping audio capture on unmount:', err);
        });
      }
    };
    // biome-ignore lint/correctness/useExhaustiveDependencies: Only run on unmount
-  }, []);
+  }, [platform]);

  return {
    isRecording,
@@ -0,0 +1,14 @@
+import { useQuery } from '@tanstack/react-query';
+import { apiClient } from '@/lib/api/client';
+import { useServerStore } from '@/stores/serverStore';
+
+export function useSystemFolders() {
+  const serverUrl = useServerStore((state) => state.serverUrl);
+
+  return useQuery({
+    queryKey: ['system', 'folders', serverUrl],
+    queryFn: () => apiClient.getSystemFolders(),
+    staleTime: 60000, // Cache for 1 minute - folder paths don't change often
+    retry: 1,
+  });
+}
@@ -1,108 +0,0 @@
-/**
- * Tauri integration utilities
- */
-
-import { invoke } from '@tauri-apps/api/core';
-import { listen, emit } from '@tauri-apps/api/event';
-
-/**
- * Check if running in Tauri environment
- */
-export function isTauri(): boolean {
-  return '__TAURI_INTERNALS__' in window;
-}
-
-/**
- * Check if running on macOS
- */
-export function isMacOS(): boolean {
-  return navigator.platform.toLowerCase().includes('mac');
-}
-
-/**
- * Start the bundled Python server (Tauri only)
- */
-export async function startServer(remote = false): Promise<string> {
-  if (!isTauri()) {
-    throw new Error('Not running in Tauri environment');
-  }
-
-  try {
-    const result = await invoke<string>('start_server', { remote });
-    console.log('Server started:', result);
-    return result;
-  } catch (error) {
-    console.error('Failed to start server:', error);
-    throw error;
-  }
-}
-
-/**
- * Stop the bundled Python server (Tauri only)
- */
-export async function stopServer(): Promise<void> {
-  if (!isTauri()) {
-    throw new Error('Not running in Tauri environment');
-  }
-
-  try {
-    await invoke('stop_server');
-    console.log('Server stopped');
-  } catch (error) {
-    console.error('Failed to stop server:', error);
-    throw error;
-  }
-}
-
-/**
- * Set whether the server should keep running when the app closes (Tauri only)
- */
-export async function setKeepServerRunning(keepRunning: boolean): Promise<void> {
-  if (!isTauri()) {
-    return;
-  }
-
-  try {
-    await invoke('set_keep_server_running', { keepRunning });
-  } catch (error) {
-    console.error('Failed to set keep server running setting:', error);
-  }
-}
-
-/**
- * Setup window close handler to check setting and stop server if needed
- */
-export async function setupWindowCloseHandler(): Promise<void> {
-  if (!isTauri()) {
-    return;
-  }
-
-  try {
-    // Listen for window close request from Rust
-    await listen<null>('window-close-requested', async () => {
-      // Import store here to avoid circular dependency
-      const { useServerStore } = await import('@/stores/serverStore');
-      const keepRunning = useServerStore.getState().keepServerRunningOnClose;
-
-      // Check if server was started by this app instance
-      // In dev mode, serverStartedByApp will be false, so we won't try to stop a separately-run server
-      // We need to access the module-level variable - this is a bit hacky but works
-      // @ts-expect-error - accessing module-level variable from another module
-      const serverStartedByApp = window.__voiceboxServerStartedByApp ?? false;
-
-      if (!keepRunning && serverStartedByApp) {
-        // Stop server before closing (only if we started it)
-        try {
-          await stopServer();
-        } catch (error) {
-          console.error('Failed to stop server on close:', error);
-        }
-      }
-
-      // Emit event back to Rust to allow close
-      await emit('window-close-allowed');
-    });
-  } catch (error) {
-    console.error('Failed to setup window close handler:', error);
-  }
-}
@@ -0,0 +1,25 @@
+import { createContext, useContext, type ReactNode } from 'react';
+import type { Platform } from './types';
+
+const PlatformContext = createContext<Platform | null>(null);
+
+export interface PlatformProviderProps {
+  platform: Platform;
+  children: ReactNode;
+}
+
+export function PlatformProvider({ platform, children }: PlatformProviderProps) {
+  return (
+    <PlatformContext.Provider value={platform}>
+      {children}
+    </PlatformContext.Provider>
+  );
+}
+
+export function usePlatform(): Platform {
+  const platform = useContext(PlatformContext);
+  if (!platform) {
+    throw new Error('usePlatform must be used within PlatformProvider');
+  }
+  return platform;
+}
@@ -0,0 +1,77 @@
+/**
+ * Platform abstraction types
+ * These interfaces define the contract that platform implementations must fulfill
+ */
+
+export interface FileFilter {
+  name: string;
+  extensions: string[];
+}
+
+export interface PlatformFilesystem {
+  saveFile(filename: string, blob: Blob, filters?: FileFilter[]): Promise<void>;
+  /**
+   * Open a folder in the native file explorer.
+   * On web, this is a no-op since browsers cannot open folders.
+   * @param path - The absolute path to the folder to open
+   * @returns true if the folder was opened, false if not supported
+   */
+  openFolder(path: string): Promise<boolean>;
+}
+
+export interface UpdateStatus {
+  checking: boolean;
+  available: boolean;
+  version?: string;
+  downloading: boolean;
+  installing: boolean;
+  readyToInstall: boolean;
+  error?: string;
+  downloadProgress?: number; // 0-100 percentage
+  downloadedBytes?: number;
+  totalBytes?: number;
+}
+
+export interface PlatformUpdater {
+  checkForUpdates(): Promise<void>;
+  downloadAndInstall(): Promise<void>;
+  restartAndInstall(): Promise<void>;
+  getStatus(): UpdateStatus;
+  subscribe(callback: (status: UpdateStatus) => void): () => void;
+}
+
+export interface AudioDevice {
+  id: string;
+  name: string;
+  is_default: boolean;
+}
+
+export interface PlatformAudio {
+  isSystemAudioSupported(): boolean;
+  startSystemAudioCapture(maxDurationSecs: number): Promise<void>;
+  stopSystemAudioCapture(): Promise<Blob>;
+  listOutputDevices(): Promise<AudioDevice[]>;
+  playToDevices(audioData: Uint8Array, deviceIds: string[]): Promise<void>;
+  stopPlayback(): void;
+}
+
+export interface PlatformLifecycle {
+  startServer(remote?: boolean): Promise<string>;
+  stopServer(): Promise<void>;
+  setKeepServerRunning(keep: boolean): Promise<void>;
+  setupWindowCloseHandler(): Promise<void>;
+  onServerReady?: () => void;
+}
+
+export interface PlatformMetadata {
+  getVersion(): Promise<string>;
+  isTauri: boolean;
+}
+
+export interface Platform {
+  filesystem: PlatformFilesystem;
+  updater: PlatformUpdater;
+  audio: PlatformAudio;
+  lifecycle: PlatformLifecycle;
+  metadata: PlatformMetadata;
+}
@@ -10,7 +10,8 @@ import { Toaster } from '@/components/ui/toaster';
 import { VoicesTab } from '@/components/VoicesTab/VoicesTab';
 import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
 import { MODEL_DISPLAY_NAMES, useRestoreActiveTasks } from '@/lib/hooks/useRestoreActiveTasks';
-import { isMacOS } from '@/lib/tauri';
+// Simple platform check that works in both web and Tauri
+const isMacOS = () => navigator.platform.toLowerCase().includes('mac');

 // Root layout component
 function RootLayout() {
@@ -1,3 +1,3 @@
 # Backend package

-__version__ = "0.1.10"
+__version__ = "0.1.13"
@@ -118,22 +118,37 @@ _stt_backend: Optional[STTBackend] = None
 def get_tts_backend() -> TTSBackend:
    """
    Get or create TTS backend instance based on platform.
-    
+
    Returns:
        TTS backend instance (MLX or PyTorch)
+
+    Raises:
+        ImportError: If required dependencies (mlx or torch) are not available
    """
    global _tts_backend
-    
+
    if _tts_backend is None:
        backend_type = get_backend_type()
-        
+
        if backend_type == "mlx":
-            from .mlx_backend import MLXTTSBackend
-            _tts_backend = MLXTTSBackend()
+            try:
+                from .mlx_backend import MLXTTSBackend
+                _tts_backend = MLXTTSBackend()
+            except ImportError as e:
+                raise ImportError(
+                    f"MLX backend dependencies not available. "
+                    f"Please install mlx and mlx_audio or download a provider. Error: {e}"
+                )
        else:
-            from .pytorch_backend import PyTorchTTSBackend
-            _tts_backend = PyTorchTTSBackend()
-    
+            try:
+                from .pytorch_backend import PyTorchTTSBackend
+                _tts_backend = PyTorchTTSBackend()
+            except ImportError as e:
+                raise ImportError(
+                    f"PyTorch backend dependencies not available. "
+                    f"Please download a TTS provider (pytorch-cpu or pytorch-cuda) from the Downloads page. Error: {e}"
+                )
+
    return _tts_backend


@@ -52,6 +52,47 @@ class MLXTTSBackend:
        
        return hf_model_id
    
+    def _is_model_cached(self, model_size: str) -> bool:
+        """
+        Check if the model is already cached locally AND fully downloaded.
+        
+        Args:
+            model_size: Model size to check
+            
+        Returns:
+            True if model is fully cached, False if missing or incomplete
+        """
+        try:
+            from huggingface_hub import constants as hf_constants
+            model_path = self._get_model_path(model_size)
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / ("models--" + model_path.replace("/", "--"))
+            
+            if not repo_cache.exists():
+                return False
+            
+            # Check for .incomplete files - if any exist, download is still in progress
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                print(f"[_is_model_cached] Found .incomplete files for {model_size}, treating as not cached")
+                return False
+            
+            # Check that actual model weight files exist in snapshots
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                has_weights = (
+                    any(snapshots_dir.rglob("*.safetensors")) or
+                    any(snapshots_dir.rglob("*.bin")) or
+                    any(snapshots_dir.rglob("*.npz"))
+                )
+                if not has_weights:
+                    print(f"[_is_model_cached] No model weights found for {model_size}, treating as not cached")
+                    return False
+            
+            return True
+        except Exception as e:
+            print(f"[_is_model_cached] Error checking cache for {model_size}: {e}")
+            return False
+    
    async def load_model_async(self, model_size: Optional[str] = None):
        """
        Lazy load the MLX TTS model.
@@ -79,46 +120,63 @@ class MLXTTSBackend:
    def _load_model_sync(self, model_size: str):
        """Synchronous model loading."""
        try:
-            from mlx_audio.tts import load
-            
-            # Get model path
+            # Get model path BEFORE importing mlx_audio
            model_path = self._get_model_path(model_size)
            
            # Set up progress tracking
            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
            model_name = f"qwen-tts-{model_size}"
            
-            # Start tracking download task
-            task_manager = get_task_manager()
-            task_manager.start_download(model_name)
+            # Check if model is already cached
+            is_cached = self._is_model_cached(model_size)
+            
+            # Set up progress callback
+            # If cached: filter out non-download progress
+            # If not cached: report all progress (we're actually downloading)
+            progress_callback = create_hf_progress_callback(model_name, progress_manager)
+            tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
            
            print(f"Loading MLX TTS model {model_size}...")
            
-            # Initialize progress state
-            progress_manager.update_progress(
-                model_name=model_name,
-                current=0,
-                total=1,
-                filename="",
-                status="downloading",
-            )
+            # Only track download progress if model is NOT cached
+            if not is_cached:
+                # Start tracking download task
+                task_manager.start_download(model_name)
+                
+                # Initialize progress state so SSE endpoint has initial data to send
+                # This provides immediate feedback while HuggingFace fetches metadata
+                progress_manager.update_progress(
+                    model_name=model_name,
+                    current=0,
+                    total=0,  # Will be updated once actual total is known
+                    filename="Connecting to HuggingFace...",
+                    status="downloading",
+                )
            
-            # Set up progress callback
-            progress_callback = create_hf_progress_callback(model_name, progress_manager)
-            tracker = HFProgressTracker(progress_callback)
+            # IMPORTANT: Patch tqdm BEFORE importing mlx_audio
+            # Otherwise mlx_audio caches reference to original tqdm
+            tracker_context = tracker.patch_download()
+            tracker_context.__enter__()
            
-            # Use progress tracker during download
-            with tracker.patch_download():
-                # Load MLX model (downloads automatically)
+            # Import mlx_audio AFTER patching tqdm
+            from mlx_audio.tts import load
+            
+            # Load MLX model (downloads automatically)
+            try:
                self.model = load(model_path)
+            finally:
+                # Exit the patch context
+                tracker_context.__exit__(None, None, None)
+            
+            # Only mark download as complete if we were tracking it
+            if not is_cached:
+                progress_manager.mark_complete(model_name)
+                task_manager.complete_download(model_name)
            
            self._current_model_size = model_size
            self.model_size = model_size
            
-            # Mark as complete
-            progress_manager.mark_complete(model_name)
-            task_manager.complete_download(model_name)
-            
            print(f"MLX TTS model {model_size} loaded successfully")
            
        except ImportError as e:
@@ -175,7 +233,13 @@ class MLXTTSBackend:
            if cached_prompt is not None:
                # Return cached prompt (should be dict format)
                if isinstance(cached_prompt, dict):
-                    return cached_prompt, True
+                    # Validate that the cached audio file still exists
+                    cached_audio_path = cached_prompt.get("ref_audio") or cached_prompt.get("ref_audio_path")
+                    if cached_audio_path and Path(cached_audio_path).exists():
+                        return cached_prompt, True
+                    else:
+                        # Cached file no longer exists, invalidate cache
+                        print(f"Cached audio file not found: {cached_audio_path}, regenerating prompt")
        
        # MLX voice prompt format - store audio path and text
        # The model will process this during generation
@@ -263,6 +327,13 @@ class MLXTTSBackend:
            ref_audio = voice_prompt.get("ref_audio") or voice_prompt.get("ref_audio_path")
            ref_text = voice_prompt.get("ref_text", "")
            
+            # Validate that the audio file exists
+            if ref_audio and not Path(ref_audio).exists():
+                print(f"Warning: Audio file not found: {ref_audio}")
+                print("This may be due to a cached voice prompt referencing a deleted temp file.")
+                print("Regenerating without voice prompt.")
+                ref_audio = None
+            
            # Check if model supports voice cloning via generate method
            # MLX API may support ref_audio parameter directly
            try:
@@ -319,6 +390,47 @@ class MLXSTTBackend:
        """Check if model is loaded."""
        return self.model is not None
    
+    def _is_model_cached(self, model_size: str) -> bool:
+        """
+        Check if the Whisper model is already cached locally AND fully downloaded.
+        
+        Args:
+            model_size: Model size to check
+            
+        Returns:
+            True if model is fully cached, False if missing or incomplete
+        """
+        try:
+            from huggingface_hub import constants as hf_constants
+            model_name = f"openai/whisper-{model_size}"
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / ("models--" + model_name.replace("/", "--"))
+            
+            if not repo_cache.exists():
+                return False
+            
+            # Check for .incomplete files - if any exist, download is still in progress
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                print(f"[_is_model_cached] Found .incomplete files for whisper-{model_size}, treating as not cached")
+                return False
+            
+            # Check that actual model weight files exist in snapshots
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                has_weights = (
+                    any(snapshots_dir.rglob("*.safetensors")) or
+                    any(snapshots_dir.rglob("*.bin")) or
+                    any(snapshots_dir.rglob("*.npz"))
+                )
+                if not has_weights:
+                    print(f"[_is_model_cached] No model weights found for whisper-{model_size}, treating as not cached")
+                    return False
+            
+            return True
+        except Exception as e:
+            print(f"[_is_model_cached] Error checking cache for whisper-{model_size}: {e}")
+            return False
+    
    async def load_model_async(self, model_size: Optional[str] = None):
        """
        Lazy load the MLX Whisper model.
@@ -341,44 +453,59 @@ class MLXSTTBackend:
    def _load_model_sync(self, model_size: str):
        """Synchronous model loading."""
        try:
-            from mlx_audio.asr import load
-            
-            # MLX Whisper model naming
-            model_name = f"mlx-community/whisper-{model_size}"
-            
-            # Set up progress tracking
            progress_manager = get_progress_manager()
-            progress_model_name = f"whisper-{model_size}"
-            
-            # Start tracking download task
            task_manager = get_task_manager()
-            task_manager.start_download(progress_model_name)
-            
-            print(f"Loading MLX Whisper model {model_size}...")
-            
-            # Initialize progress state
-            progress_manager.update_progress(
-                model_name=progress_model_name,
-                current=0,
-                total=1,
-                filename="",
-                status="downloading",
-            )
-            
-            # Set up progress callback
+            progress_model_name = f"whisper-{model_size}"
+
+            # Check if model is already cached
+            is_cached = self._is_model_cached(model_size)
+
+            # Set up progress callback and tracker
+            # If cached: filter out non-download progress
+            # If not cached: report all progress (we're actually downloading)
            progress_callback = create_hf_progress_callback(progress_model_name, progress_manager)
-            tracker = HFProgressTracker(progress_callback)
-            
-            # Use progress tracker during download
-            with tracker.patch_download():
+            tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
+
+            # Patch tqdm BEFORE importing mlx_audio
+            tracker_context = tracker.patch_download()
+            tracker_context.__enter__()
+
+            # Import mlx_audio
+            from mlx_audio.stt import load
+
+            # MLX Whisper uses the standard OpenAI models
+            model_name = f"openai/whisper-{model_size}"
+
+            print(f"Loading MLX Whisper model {model_size}...")
+
+            # Only track download progress if model is NOT cached
+            if not is_cached:
+                # Start tracking download task
+                task_manager.start_download(progress_model_name)
+                
+                # Initialize progress state so SSE endpoint has initial data to send
+                progress_manager.update_progress(
+                    model_name=progress_model_name,
+                    current=0,
+                    total=0,
+                    filename="Connecting to HuggingFace...",
+                    status="downloading",
+                )
+
+            # Load the model (tqdm is patched, but filters out non-download progress)
+            try:
                self.model = load(model_name)
+            finally:
+                # Exit the patch context
+                tracker_context.__exit__(None, None, None)
+            
+            # Only mark download as complete if we were tracking it
+            if not is_cached:
+                progress_manager.mark_complete(progress_model_name)
+                task_manager.complete_download(progress_model_name)
            
            self.model_size = model_size
            
-            # Mark as complete
-            progress_manager.mark_complete(progress_model_name)
-            task_manager.complete_download(progress_model_name)
-            
            print(f"MLX Whisper model {model_size} loaded successfully")
            
        except ImportError as e:
@@ -412,34 +539,35 @@ class MLXSTTBackend:
    ) -> str:
        """
        Transcribe audio to text.
-        
+
        Args:
            audio_path: Path to audio file
            language: Optional language hint (en or zh)
-            
+
        Returns:
            Transcribed text
        """
        await self.load_model_async(None)
-        
+
        def _transcribe_sync():
            """Run synchronous transcription in thread pool."""
-            # Load audio
-            audio, sr = load_audio(audio_path, sample_rate=16000)
-            
-            # MLX Whisper transcription
-            # The API may vary - check mlx-audio documentation
-            # For now, assuming similar API to PyTorch Whisper
-            result = self.model.transcribe(audio, language=language)
-            
-            # Extract text from result (format may vary)
+            # MLX Whisper transcription using generate method
+            # The generate method accepts audio path directly
+            decode_options = {}
+            if language:
+                decode_options["language"] = language
+
+            result = self.model.generate(str(audio_path), **decode_options)
+
+            # Extract text from result
            if isinstance(result, str):
                return result.strip()
            elif isinstance(result, dict):
                return result.get("text", "").strip()
+            elif hasattr(result, "text"):
+                return result.text.strip()
            else:
-                # Try to get text attribute
                return str(result).strip()
-        
+
        # Run blocking transcription in thread pool
        return await asyncio.to_thread(_transcribe_sync)
@@ -58,6 +58,46 @@ class PyTorchTTSBackend:
        
        return hf_model_map[model_size]
    
+    def _is_model_cached(self, model_size: str) -> bool:
+        """
+        Check if the model is already cached locally AND fully downloaded.
+        
+        Args:
+            model_size: Model size to check
+            
+        Returns:
+            True if model is fully cached, False if missing or incomplete
+        """
+        try:
+            from huggingface_hub import constants as hf_constants
+            model_path = self._get_model_path(model_size)
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / ("models--" + model_path.replace("/", "--"))
+            
+            if not repo_cache.exists():
+                return False
+            
+            # Check for .incomplete files - if any exist, download is still in progress
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                print(f"[_is_model_cached] Found .incomplete files for {model_size}, treating as not cached")
+                return False
+            
+            # Check that actual model weight files exist in snapshots
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                has_weights = (
+                    any(snapshots_dir.rglob("*.safetensors")) or
+                    any(snapshots_dir.rglob("*.bin"))
+                )
+                if not has_weights:
+                    print(f"[_is_model_cached] No model weights found for {model_size}, treating as not cached")
+                    return False
+            
+            return True
+        except Exception as e:
+            print(f"[_is_model_cached] Error checking cache for {model_size}: {e}")
+            return False
+    
    async def load_model_async(self, model_size: Optional[str] = None):
        """
        Lazy load the TTS model with automatic downloading from HuggingFace Hub.
@@ -85,46 +125,60 @@ class PyTorchTTSBackend:
    def _load_model_sync(self, model_size: str):
        """Synchronous model loading."""
        try:
+            progress_manager = get_progress_manager()
+            task_manager = get_task_manager()
+            model_name = f"qwen-tts-{model_size}"
+
+            # Check if model is already cached
+            is_cached = self._is_model_cached(model_size)
+
+            # Set up progress callback and tracker
+            # If cached: filter out non-download progress (like "Segment 1/1" during generation)
+            # If not cached: report all progress (we're actually downloading)
+            progress_callback = create_hf_progress_callback(model_name, progress_manager)
+            tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
+
+            # Patch tqdm BEFORE importing qwen_tts
+            tracker_context = tracker.patch_download()
+            tracker_context.__enter__()
+
+            # Import qwen_tts
            from qwen_tts import Qwen3TTSModel
-            
+
            # Get model path (local or HuggingFace Hub ID)
            model_path = self._get_model_path(model_size)
-            
-            # Set up progress tracking
-            progress_manager = get_progress_manager()
-            model_name = f"qwen-tts-{model_size}"
-            
+
            print(f"Loading TTS model {model_size} on {self.device}...")
-            
-            # Start tracking download task
-            task_manager = get_task_manager()
-            task_manager.start_download(model_name)
-            
-            # Initialize progress state to show download has started
-            progress_manager.update_progress(
-                model_name=model_name,
-                current=0,
-                total=1,  # Set to 1 initially, will be updated by callback
-                filename="",
-                status="downloading",
-            )
-            
-            # Set up progress callback
-            progress_callback = create_hf_progress_callback(model_name, progress_manager)
-            tracker = HFProgressTracker(progress_callback)
-            
-            # Use progress tracker during download
-            with tracker.patch_download():
-                # Load the model - downloads will happen automatically with progress tracking
+
+            # Only track download progress if model is NOT cached
+            if not is_cached:
+                # Start tracking download task
+                task_manager.start_download(model_name)
+
+                # Initialize progress state so SSE endpoint has initial data to send
+                progress_manager.update_progress(
+                    model_name=model_name,
+                    current=0,
+                    total=0,  # Will be updated once actual total is known
+                    filename="Connecting to HuggingFace...",
+                    status="downloading",
+                )
+
+            # Load the model (tqdm is patched, but filters out non-download progress)
+            try:
                self.model = Qwen3TTSModel.from_pretrained(
                    model_path,
                    device_map=self.device,
                    torch_dtype=torch.float32 if self.device == "cpu" else torch.bfloat16,
                )
+            finally:
+                # Exit the patch context
+                tracker_context.__exit__(None, None, None)
            
-            # Mark as complete
-            progress_manager.mark_complete(model_name)
-            task_manager.complete_download(model_name)
+            # Only mark download as complete if we were tracking it
+            if not is_cached:
+                progress_manager.mark_complete(model_name)
+                task_manager.complete_download(model_name)
            
            self._current_model_size = model_size
            self.model_size = model_size
@@ -188,6 +242,8 @@ class PyTorchTTSBackend:
                # Cache stores as torch.Tensor but actual prompt is dict
                # Convert if needed
                if isinstance(cached_prompt, dict):
+                    # For PyTorch backend, the dict should contain tensors, not file paths
+                    # So we can safely return it
                    return cached_prompt, True
                elif isinstance(cached_prompt, torch.Tensor):
                    # Legacy cache format - convert to dict
@@ -311,67 +367,131 @@ class PyTorchSTTBackend:
        """Check if model is loaded."""
        return self.model is not None
    
+    def _is_model_cached(self, model_size: str) -> bool:
+        """
+        Check if the Whisper model is already cached locally AND fully downloaded.
+        
+        Args:
+            model_size: Model size to check
+            
+        Returns:
+            True if model is fully cached, False if missing or incomplete
+        """
+        try:
+            from huggingface_hub import constants as hf_constants
+            model_name = f"openai/whisper-{model_size}"
+            repo_cache = Path(hf_constants.HF_HUB_CACHE) / ("models--" + model_name.replace("/", "--"))
+            
+            if not repo_cache.exists():
+                return False
+            
+            # Check for .incomplete files - if any exist, download is still in progress
+            blobs_dir = repo_cache / "blobs"
+            if blobs_dir.exists() and any(blobs_dir.glob("*.incomplete")):
+                print(f"[_is_model_cached] Found .incomplete files for whisper-{model_size}, treating as not cached")
+                return False
+            
+            # Check that actual model weight files exist in snapshots
+            snapshots_dir = repo_cache / "snapshots"
+            if snapshots_dir.exists():
+                has_weights = (
+                    any(snapshots_dir.rglob("*.safetensors")) or
+                    any(snapshots_dir.rglob("*.bin"))
+                )
+                if not has_weights:
+                    print(f"[_is_model_cached] No model weights found for whisper-{model_size}, treating as not cached")
+                    return False
+            
+            return True
+        except Exception as e:
+            print(f"[_is_model_cached] Error checking cache for whisper-{model_size}: {e}")
+            return False
+    
    async def load_model_async(self, model_size: Optional[str] = None):
        """
        Lazy load the Whisper model.
-        
+
        Args:
            model_size: Model size (tiny, base, small, medium, large)
        """
+        print(f"[DEBUG] load_model_async called with size: {model_size}")
        if model_size is None:
            model_size = self.model_size
-        
+
+        print(f"[DEBUG] Model already loaded? {self.model is not None}, current size: {self.model_size}, requested: {model_size}")
        if self.model is not None and self.model_size == model_size:
+            print(f"[DEBUG] Early return - model already loaded")
            return
-        
+
+        print(f"[DEBUG] Calling asyncio.to_thread for _load_model_sync")
        # Run blocking load in thread pool
        await asyncio.to_thread(self._load_model_sync, model_size)
+        print(f"[DEBUG] asyncio.to_thread completed")
    
    # Alias for compatibility
    load_model = load_model_async
    
    def _load_model_sync(self, model_size: str):
        """Synchronous model loading."""
+        print(f"[DEBUG] _load_model_sync called for Whisper {model_size}")
        try:
-            from transformers import WhisperProcessor, WhisperForConditionalGeneration
-            
-            model_name = f"openai/whisper-{model_size}"
-            
-            # Set up progress tracking
            progress_manager = get_progress_manager()
-            progress_model_name = f"whisper-{model_size}"
-            
-            # Start tracking download task
            task_manager = get_task_manager()
-            task_manager.start_download(progress_model_name)
-            
-            print(f"Loading Whisper model {model_size} on {self.device}...")
-            
-            # Initialize progress state to show download has started
-            progress_manager.update_progress(
-                model_name=progress_model_name,
-                current=0,
-                total=1,  # Set to 1 initially, will be updated by callback
-                filename="",
-                status="downloading",
-            )
-            
-            # Set up progress callback
+            progress_model_name = f"whisper-{model_size}"
+
+            # Check if model is already cached
+            is_cached = self._is_model_cached(model_size)
+
+            # Set up progress callback and tracker
+            # If cached: filter out non-download progress
+            # If not cached: report all progress (we're actually downloading)
            progress_callback = create_hf_progress_callback(progress_model_name, progress_manager)
-            tracker = HFProgressTracker(progress_callback)
-            
-            # Use progress tracker during download
-            with tracker.patch_download():
+            tracker = HFProgressTracker(progress_callback, filter_non_downloads=is_cached)
+
+            # Patch tqdm BEFORE importing transformers
+            print("[DEBUG] Starting tqdm patch BEFORE transformers import")
+            tracker_context = tracker.patch_download()
+            tracker_context.__enter__()
+            print("[DEBUG] tqdm patched, now importing transformers")
+
+            # Import transformers
+            from transformers import WhisperProcessor, WhisperForConditionalGeneration
+
+            model_name = f"openai/whisper-{model_size}"
+            print(f"[DEBUG] Model name: {model_name}")
+
+            print(f"Loading Whisper model {model_size} on {self.device}...")
+
+            # Only track download progress if model is NOT cached
+            if not is_cached:
+                # Start tracking download task
+                task_manager.start_download(progress_model_name)
+
+                # Initialize progress state so SSE endpoint has initial data to send
+                progress_manager.update_progress(
+                    model_name=progress_model_name,
+                    current=0,
+                    total=0,  # Will be updated once actual total is known
+                    filename="Connecting to HuggingFace...",
+                    status="downloading",
+                )
+
+            # Load models (tqdm is patched, but filters out non-download progress)
+            try:
                self.processor = WhisperProcessor.from_pretrained(model_name)
                self.model = WhisperForConditionalGeneration.from_pretrained(model_name)
+            finally:
+                # Exit the patch context
+                tracker_context.__exit__(None, None, None)
+            
+            # Only mark download as complete if we were tracking it
+            if not is_cached:
+                progress_manager.mark_complete(progress_model_name)
+                task_manager.complete_download(progress_model_name)
            
            self.model.to(self.device)
            self.model_size = model_size
            
-            # Mark as complete
-            progress_manager.mark_complete(progress_model_name)
-            task_manager.complete_download(progress_model_name)
-            
            print(f"Whisper model {model_size} loaded successfully")
            
        except Exception as e:
@@ -30,7 +30,7 @@ def build_server():
        args.extend(['--paths', str(qwen_tts_path)])
        print(f"Using local qwen_tts source from: {qwen_tts_path}")

-    # Add common hidden imports
+    # Add common hidden imports (always included)
    args.extend([
        '--hidden-import', 'backend',
        '--hidden-import', 'backend.main',
@@ -42,53 +42,80 @@ def build_server():
        '--hidden-import', 'backend.tts',
        '--hidden-import', 'backend.transcribe',
        '--hidden-import', 'backend.platform_detect',
-        '--hidden-import', 'backend.backends',
-        '--hidden-import', 'backend.backends.pytorch_backend',
+        '--hidden-import', 'backend.providers',
+        '--hidden-import', 'backend.providers.base',
+        '--hidden-import', 'backend.providers.bundled',
+        '--hidden-import', 'backend.providers.types',
        '--hidden-import', 'backend.utils.audio',
        '--hidden-import', 'backend.utils.cache',
        '--hidden-import', 'backend.utils.progress',
        '--hidden-import', 'backend.utils.hf_progress',
        '--hidden-import', 'backend.utils.validation',
-        '--hidden-import', 'torch',
-        '--hidden-import', 'transformers',
+        '--hidden-import', 'numpy',
+        '--hidden-import', 'numpy.core',
+        '--hidden-import', 'numpy.core._multiarray_umath',
+        '--hidden-import', 'scipy',
+        '--hidden-import', 'scipy.signal',
        '--hidden-import', 'fastapi',
        '--hidden-import', 'uvicorn',
        '--hidden-import', 'sqlalchemy',
        '--hidden-import', 'librosa',
        '--hidden-import', 'soundfile',
-        '--hidden-import', 'qwen_tts',
-        '--hidden-import', 'qwen_tts.inference',
-        '--hidden-import', 'qwen_tts.inference.qwen3_tts_model',
-        '--hidden-import', 'qwen_tts.inference.qwen3_tts_tokenizer',
-        '--hidden-import', 'qwen_tts.core',
-        '--hidden-import', 'qwen_tts.cli',
-        '--copy-metadata', 'qwen-tts',
-        '--collect-submodules', 'qwen_tts',
-        '--collect-data', 'qwen_tts',
        # Fix for pkg_resources and jaraco namespace packages
        '--hidden-import', 'pkg_resources.extern',
        '--collect-submodules', 'jaraco',
+        # Asyncio and threading support for PyInstaller
+        '--hidden-import', 'asyncio',
+        '--hidden-import', 'asyncio.subprocess',
+        '--hidden-import', 'concurrent.futures',
+        '--hidden-import', 'concurrent.futures.thread',
    ])

-    # Add MLX-specific imports if building on Apple Silicon
+    # Platform-specific TTS backend handling
+    system = platform.system()
+
    if is_apple_silicon():
-        print("Building for Apple Silicon - including MLX dependencies")
+        print("Building for Apple Silicon - including MLX dependencies (bundled)")
        args.extend([
+            '--hidden-import', 'backend.backends',
            '--hidden-import', 'backend.backends.mlx_backend',
            '--hidden-import', 'mlx',
            '--hidden-import', 'mlx.core',
            '--hidden-import', 'mlx.nn',
            '--hidden-import', 'mlx_audio',
            '--hidden-import', 'mlx_audio.tts',
-            '--hidden-import', 'mlx_audio.asr',
+            '--hidden-import', 'mlx_audio.stt',
            '--collect-submodules', 'mlx',
            '--collect-submodules', 'mlx_audio',
            # Collect MLX data files including Metal shader libraries (.metallib)
            '--collect-data', 'mlx',
            '--collect-data', 'mlx_audio',
        ])
+    elif system == "Windows" or (system == "Darwin" and not is_apple_silicon()):
+        # Windows and Intel macOS: Bundle PyTorch CPU provider
+        print(f"Building for {system} - including PyTorch CPU provider (bundled)")
+        args.extend([
+            '--hidden-import', 'backend.backends',
+            '--hidden-import', 'backend.backends.pytorch_backend',
+            '--hidden-import', 'torch',
+            '--hidden-import', 'transformers',
+            '--hidden-import', 'qwen_tts',
+            '--hidden-import', 'qwen_tts.inference',
+            '--hidden-import', 'qwen_tts.inference.qwen3_tts_model',
+            '--hidden-import', 'qwen_tts.inference.qwen3_tts_tokenizer',
+            '--hidden-import', 'qwen_tts.core',
+            '--hidden-import', 'qwen_tts.cli',
+            '--copy-metadata', 'qwen-tts',
+            '--collect-submodules', 'qwen_tts',
+            '--collect-data', 'qwen_tts',
+        ])
    else:
-        print("Building for non-Apple Silicon platform - PyTorch only")
+        # Linux: No bundled provider - users download providers separately
+        print("Building for Linux - no bundled provider (users download separately)")
+        args.extend([
+            '--hidden-import', 'backend.backends',
+            '--hidden-import', 'backend.backends.pytorch_backend',
+        ])

    args.extend([
        '--noconfirm',
@@ -14,7 +14,6 @@ from datetime import datetime
 import asyncio
 import uvicorn
 import argparse
-import torch
 import tempfile
 import io
 from pathlib import Path
@@ -23,11 +22,22 @@ import asyncio
 import signal
 import os

+# Optional torch import - not available on all platforms (e.g. Windows/Linux without bundled provider)
+try:
+    import torch
+    TORCH_AVAILABLE = True
+except ImportError:
+    torch = None  # type: ignore
+    TORCH_AVAILABLE = False
+
 from . import database, models, profiles, history, tts, transcribe, config, export_import, channels, stories, __version__
 from .database import get_db, Generation as DBGeneration, VoiceProfile as DBVoiceProfile
 from .utils.progress import get_progress_manager
 from .utils.tasks import get_task_manager
+from .utils.cache import clear_voice_prompt_cache
 from .platform_detect import get_backend_type
+from .providers import get_provider_manager
+from .providers.types import ProviderType

 app = FastAPI(
    title="voicebox API",
@@ -49,10 +59,8 @@ app.add_middleware(
 # ROOT & HEALTH ENDPOINTS
 # ============================================

-@app.get("/")
-async def root():
-    """Root endpoint."""
-    return {"message": "voicebox API", "version": __version__}
+# Root endpoint removed - web UI served at / instead
+# API info available at /health


@app.post("/shutdown")
@@ -66,23 +74,48 @@ async def shutdown():
    return {"message": "Shutting down..."}


+@app.get("/system/folders", response_model=models.FolderPathsResponse)
+async def get_system_folders():
+    """Get system folder paths for data, models, and providers."""
+    from huggingface_hub import constants as hf_constants
+    from .providers.installer import _get_providers_dir
+    
+    return models.FolderPathsResponse(
+        data_dir=str(config.get_data_dir().absolute()),
+        models_dir=str(Path(hf_constants.HF_HUB_CACHE).absolute()),
+        providers_dir=str(_get_providers_dir().absolute()),
+    )
+
+
@app.get("/health", response_model=models.HealthResponse)
 async def health():
    """Health check endpoint."""
-    from huggingface_hub import hf_hub_download, constants as hf_constants
+    from huggingface_hub import constants as hf_constants
    from pathlib import Path
-    import os

-    tts_model = tts.get_tts_model()
+    # Try to get TTS model provider, but it may not be available if dependencies aren't installed
+    tts_model = None
+    try:
+        tts_model = await tts.get_tts_model_async()
+    except ImportError as e:
+        # Provider dependencies not available (e.g., PyTorch not bundled on this platform)
+        # This is expected on Windows/Linux builds without a bundled provider
+        print(f"Provider not available: {e}")
+
    backend_type = get_backend_type()

    # Check for GPU availability (CUDA or MPS)
-    has_cuda = torch.cuda.is_available()
-    has_mps = hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()
+    # PyTorch might not be available if no provider is bundled
+    has_cuda = False
+    has_mps = False
+    if TORCH_AVAILABLE and torch is not None:
+        has_cuda = torch.cuda.is_available()
+        has_mps = hasattr(torch.backends, 'mps') and torch.backends.mps.is_available()
+
    gpu_available = has_cuda or has_mps

    gpu_type = None
-    if has_cuda:
+    if has_cuda and torch is not None:
        gpu_type = f"CUDA ({torch.cuda.get_device_name(0)})"
    elif has_mps:
        gpu_type = "MPS (Apple Silicon)"
@@ -90,26 +123,27 @@ async def health():
        gpu_type = "Metal (Apple Silicon via MLX)"

    vram_used = None
-    if has_cuda:
+    if has_cuda and torch is not None:
        vram_used = torch.cuda.memory_allocated() / 1024 / 1024  # MB
-    
+
    # Check if model is loaded - use the same logic as model status endpoint
    model_loaded = False
    model_size = None
-    try:
-        # Use the same check as model status endpoint
-        if tts_model.is_loaded():
-            model_loaded = True
-            # Get the actual loaded model size
-            # Check _current_model_size first (more reliable for actually loaded models)
-            model_size = getattr(tts_model, '_current_model_size', None)
-            if not model_size:
-                # Fallback to model_size attribute (which should be set when model loads)
-                model_size = getattr(tts_model, 'model_size', None)
-    except Exception:
-        # If there's an error checking, assume not loaded
-        model_loaded = False
-        model_size = None
+    if tts_model is not None:
+        try:
+            # Use the same check as model status endpoint
+            if tts_model.is_loaded():
+                model_loaded = True
+                # Get the actual loaded model size
+                # Check _current_model_size first (more reliable for actually loaded models)
+                model_size = getattr(tts_model, '_current_model_size', None)
+                if not model_size:
+                    # Fallback to model_size attribute (which should be set when model loads)
+                    model_size = getattr(tts_model, 'model_size', None)
+        except Exception:
+            # If there's an error checking, assume not loaded
+            model_loaded = False
+            model_size = None
    
    # Check if default model is downloaded (cached)
    model_downloaded = None
@@ -548,7 +582,7 @@ async def generate_speech(
        )
        
        # Generate audio
-        tts_model = tts.get_tts_model()
+        tts_model = await tts.get_tts_model_async()
        # Load the requested model size if different from current (async to not block)
        model_size = data.model_size or "1.7B"

@@ -1112,8 +1146,8 @@ async def get_sample_audio(sample_id: str, db: Session = Depends(get_db)):
 async def load_model(model_size: str = "1.7B"):
    """Manually load TTS model."""
    try:
-        tts_model = tts.get_tts_model()
-        await tts_model.load_model_async(model_size)
+        tts_model = await tts.get_tts_model_async()
+        await tts_model.load_model(model_size)
        return {"message": f"Model {model_size} loaded successfully"}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
@@ -1155,11 +1189,14 @@ async def get_model_progress(model_name: str):
@app.get("/models/status", response_model=models.ModelStatusListResponse)
 async def get_model_status():
    """Get status of all available models."""
-    from huggingface_hub import hf_hub_download, constants as hf_constants
+    from huggingface_hub import constants as hf_constants
    from pathlib import Path
-    import os
    
    backend_type = get_backend_type()
+    task_manager = get_task_manager()
+    
+    # Get set of currently downloading model names
+    active_download_names = {task.model_name for task in task_manager.get_active_downloads()}
    
    # Try to import scan_cache_dir (might not be available in older versions)
    try:
@@ -1168,10 +1205,10 @@ async def get_model_status():
    except ImportError:
        use_scan_cache = False
    
-    def check_tts_loaded(model_size: str):
+    async def check_tts_loaded(model_size: str):
        """Check if TTS model is loaded with specific size."""
        try:
-            tts_model = tts.get_tts_model()
+            tts_model = await tts.get_tts_model_async()
            return tts_model.is_loaded() and getattr(tts_model, 'model_size', None) == model_size
        except Exception:
            return False
@@ -1188,10 +1225,11 @@ async def get_model_status():
    if backend_type == "mlx":
        tts_1_7b_id = "mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16"
        tts_0_6b_id = "mlx-community/Qwen3-TTS-12Hz-1.7B-Base-bf16"  # Fallback to 1.7B
-        whisper_base_id = "mlx-community/whisper-base"
-        whisper_small_id = "mlx-community/whisper-small"
-        whisper_medium_id = "mlx-community/whisper-medium"
-        whisper_large_id = "mlx-community/whisper-large"
+        # MLX backend uses openai/whisper-* models, not mlx-community
+        whisper_base_id = "openai/whisper-base"
+        whisper_small_id = "openai/whisper-small"
+        whisper_medium_id = "openai/whisper-medium"
+        whisper_large_id = "openai/whisper-large"
    else:
        tts_1_7b_id = "Qwen/Qwen3-TTS-12Hz-1.7B-Base"
        tts_0_6b_id = "Qwen/Qwen3-TTS-12Hz-0.6B-Base"
@@ -1206,14 +1244,14 @@ async def get_model_status():
            "display_name": "Qwen TTS 1.7B",
            "hf_repo_id": tts_1_7b_id,
            "model_size": "1.7B",
-            "check_loaded": lambda: check_tts_loaded("1.7B"),
+            "check_loaded": lambda: check_tts_loaded("1.7B"),  # Async function
        },
        {
            "model_name": "qwen-tts-0.6B",
            "display_name": "Qwen TTS 0.6B",
            "hf_repo_id": tts_0_6b_id,
            "model_size": "0.6B",
-            "check_loaded": lambda: check_tts_loaded("0.6B"),
+            "check_loaded": lambda: check_tts_loaded("0.6B"),  # Async function
        },
        {
            "model_name": "whisper-base",
@@ -1245,6 +1283,13 @@ async def get_model_status():
        },
    ]
    
+    # Build a mapping of model_name -> hf_repo_id so we can check if shared repos are downloading
+    model_to_repo = {cfg["model_name"]: cfg["hf_repo_id"] for cfg in model_configs}
+    
+    # Get the set of hf_repo_ids that are currently being downloaded
+    # This handles the case where multiple models share the same repo (e.g., 0.6B and 1.7B on MLX)
+    active_download_repos = {model_to_repo.get(name) for name in active_download_names if name in model_to_repo}
+    
    # Get HuggingFace cache info (if available)
    cache_info = None
    if use_scan_cache:
@@ -1267,13 +1312,37 @@ async def get_model_status():
                repo_id = config["hf_repo_id"]
                for repo in cache_info.repos:
                    if repo.repo_id == repo_id:
-                        downloaded = True
-                        # Calculate size from cache info
+                        # Check if actual model weight files exist (not just config files)
+                        # scan_cache_dir only shows completed files, so check if any are model weights
+                        has_model_weights = False
+                        for rev in repo.revisions:
+                            for f in rev.files:
+                                fname = f.file_name.lower()
+                                if fname.endswith(('.safetensors', '.bin', '.pt', '.pth', '.npz')):
+                                    has_model_weights = True
+                                    break
+                            if has_model_weights:
+                                break
+                        
+                        # Also check for .incomplete files in blobs directory (downloads in progress)
+                        has_incomplete = False
                        try:
-                            total_size = sum(revision.size_on_disk for revision in repo.revisions)
-                            size_mb = total_size / (1024 * 1024)
+                            cache_dir = hf_constants.HF_HUB_CACHE
+                            blobs_dir = Path(cache_dir) / ("models--" + repo_id.replace("/", "--")) / "blobs"
+                            if blobs_dir.exists():
+                                has_incomplete = any(blobs_dir.glob("*.incomplete"))
                        except Exception:
                            pass
+                        
+                        # Only mark as downloaded if we have model weights AND no incomplete files
+                        if has_model_weights and not has_incomplete:
+                            downloaded = True
+                            # Calculate size from cache info
+                            try:
+                                total_size = sum(revision.size_on_disk for revision in repo.revisions)
+                                size_mb = total_size / (1024 * 1024)
+                            except Exception:
+                                pass
                        break
            
            # Method 2: Fallback to checking cache directory directly (using HuggingFace's OS-specific cache location)
@@ -1283,67 +1352,96 @@ async def get_model_status():
                    repo_cache = Path(cache_dir) / ("models--" + config["hf_repo_id"].replace("/", "--"))
                    
                    if repo_cache.exists():
-                        # Check for model files (bin, safetensors, or other common model files)
-                        # MLX models may use .npz or .safetensors
-                        has_model_files = (
-                            any(repo_cache.rglob("*.bin")) or
-                            any(repo_cache.rglob("*.safetensors")) or
-                            any(repo_cache.rglob("*.pt")) or
-                            any(repo_cache.rglob("*.pth")) or
-                            any(repo_cache.rglob("*.npz")) or
-                            any(repo_cache.rglob("model.safetensors.index.json")) or
-                            any(repo_cache.rglob("pytorch_model.bin.index.json"))
-                        )
+                        # Check for .incomplete files - if any exist, download is still in progress
+                        blobs_dir = repo_cache / "blobs"
+                        has_incomplete = blobs_dir.exists() and any(blobs_dir.glob("*.incomplete"))
                        
-                        if has_model_files:
-                            downloaded = True
-                            # Calculate size
-                            try:
-                                total_size = sum(f.stat().st_size for f in repo_cache.rglob("*") if f.is_file())
-                                size_mb = total_size / (1024 * 1024)
-                            except Exception:
-                                pass
+                        if not has_incomplete:
+                            # Check for actual model weight files (not just index files)
+                            # in the snapshots directory (symlinks to completed blobs)
+                            snapshots_dir = repo_cache / "snapshots"
+                            has_model_files = False
+                            if snapshots_dir.exists():
+                                has_model_files = (
+                                    any(snapshots_dir.rglob("*.bin")) or
+                                    any(snapshots_dir.rglob("*.safetensors")) or
+                                    any(snapshots_dir.rglob("*.pt")) or
+                                    any(snapshots_dir.rglob("*.pth")) or
+                                    any(snapshots_dir.rglob("*.npz"))
+                                )
+                            
+                            if has_model_files:
+                                downloaded = True
+                                # Calculate size (exclude .incomplete files)
+                                try:
+                                    total_size = sum(
+                                        f.stat().st_size for f in repo_cache.rglob("*") 
+                                        if f.is_file() and not f.name.endswith('.incomplete')
+                                    )
+                                    size_mb = total_size / (1024 * 1024)
+                                except Exception:
+                                    pass
                except Exception:
                    pass
            
-            # Method 3: Try to check if model can be loaded locally (last resort)
-            if not downloaded:
-                try:
-                    # Try to download with local_files_only=True to check if cached
-                    hf_hub_download(
-                        repo_id=config["hf_repo_id"],
-                        filename="config.json",  # Try a common file
-                        local_files_only=True,
-                    )
-                    downloaded = True
-                except Exception:
-                    # File not found locally, model not downloaded
-                    pass
+            # Method 3 removed - checking for config.json is too lenient
+            # Methods 1 and 2 properly verify that model weight files exist
            
            # Check if loaded in memory
            try:
-                loaded = config["check_loaded"]()
+                check_func = config["check_loaded"]
+                if asyncio.iscoroutinefunction(check_func):
+                    loaded = await check_func()
+                else:
+                    result = check_func()
+                    # Handle lambdas that return coroutines
+                    if asyncio.iscoroutine(result):
+                        loaded = await result
+                    else:
+                        loaded = result
            except Exception:
                loaded = False
            
+            # Check if this model (or its shared repo) is currently being downloaded
+            is_downloading = config["hf_repo_id"] in active_download_repos
+            
+            # If downloading, don't report as downloaded (partial files exist)
+            if is_downloading:
+                downloaded = False
+                size_mb = None  # Don't show partial size during download
+            
            statuses.append(models.ModelStatus(
                model_name=config["model_name"],
                display_name=config["display_name"],
                downloaded=downloaded,
+                downloading=is_downloading,
                size_mb=size_mb,
                loaded=loaded,
            ))
        except Exception as e:
            # If check fails, try to at least check if loaded
            try:
-                loaded = config["check_loaded"]()
+                check_func = config["check_loaded"]
+                if asyncio.iscoroutinefunction(check_func):
+                    loaded = await check_func()
+                else:
+                    result = check_func()
+                    # Handle lambdas that return coroutines
+                    if asyncio.iscoroutine(result):
+                        loaded = await result
+                    else:
+                        loaded = result
            except Exception:
                loaded = False
            
+            # Check if this model (or its shared repo) is currently being downloaded
+            is_downloading = config["hf_repo_id"] in active_download_repos
+            
            statuses.append(models.ModelStatus(
                model_name=config["model_name"],
                display_name=config["display_name"],
                downloaded=False,  # Assume not downloaded if check failed
+                downloading=is_downloading,
                size_mb=None,
                loaded=loaded,
            ))
@@ -1357,15 +1455,26 @@ async def trigger_model_download(request: models.ModelDownloadRequest):
    import asyncio
    
    task_manager = get_task_manager()
+    progress_manager = get_progress_manager()
+    
+    async def load_tts_model_1_7b():
+        """Load 1.7B TTS model."""
+        tts_model = await tts.get_tts_model_async()
+        await tts_model.load_model("1.7B")
+    
+    async def load_tts_model_0_6b():
+        """Load 0.6B TTS model."""
+        tts_model = await tts.get_tts_model_async()
+        await tts_model.load_model("0.6B")
    
    model_configs = {
        "qwen-tts-1.7B": {
            "model_size": "1.7B",
-            "load_func": lambda: tts.get_tts_model().load_model("1.7B"),
+            "load_func": load_tts_model_1_7b,
        },
        "qwen-tts-0.6B": {
            "model_size": "0.6B",
-            "load_func": lambda: tts.get_tts_model().load_model("0.6B"),
+            "load_func": load_tts_model_0_6b,
        },
        "whisper-base": {
            "model_size": "base",
@@ -1393,13 +1502,29 @@ async def trigger_model_download(request: models.ModelDownloadRequest):
    async def download_in_background():
        """Download model in background without blocking the HTTP request."""
        try:
-            await asyncio.to_thread(config["load_func"])
+            # Call the load function (which may be async)
+            result = config["load_func"]()
+            # If it's a coroutine, await it
+            if asyncio.iscoroutine(result):
+                await result
            task_manager.complete_download(request.model_name)
        except Exception as e:
            task_manager.error_download(request.model_name, str(e))

    # Start tracking download
    task_manager.start_download(request.model_name)
+    
+    # Initialize progress state so SSE endpoint has initial data to send.
+    # This fixes a race condition where the frontend connects to SSE before
+    # any progress callbacks have fired (especially for large models like Qwen
+    # where huggingface_hub takes time to fetch metadata for all files).
+    progress_manager.update_progress(
+        model_name=request.model_name,
+        current=0,
+        total=0,  # Will be updated once actual total is known
+        filename="Connecting to HuggingFace...",
+        status="downloading",
+    )

    # Start download in background task (don't await)
    asyncio.create_task(download_in_background())
@@ -1408,6 +1533,171 @@ async def trigger_model_download(request: models.ModelDownloadRequest):
    return {"message": f"Model {request.model_name} download started"}


+# ============================================
+# PROVIDER ENDPOINTS
+# ============================================
+
+@app.get("/providers")
+async def list_providers():
+    """List all available provider types."""
+    manager = get_provider_manager()
+    installed = await manager.list_installed()
+    
+    # Get info for all known provider types
+    all_providers = [
+        "apple-mlx",
+        "bundled-pytorch",
+        "pytorch-cpu",
+        "pytorch-cuda",
+        "remote",
+        "openai",
+    ]
+    
+    providers_info = []
+    for provider_type in all_providers:
+        info = await manager.get_provider_info(provider_type)
+        providers_info.append(info)
+    
+    return {
+        "providers": providers_info,
+        "installed": installed,
+    }
+
+
+@app.get("/providers/installed")
+async def list_installed_providers():
+    """List installed provider types."""
+    manager = get_provider_manager()
+    installed = await manager.list_installed()
+    return {"installed": installed}
+
+
+@app.get("/providers/active")
+async def get_active_provider():
+    """Get information about the currently active provider."""
+    manager = get_provider_manager()
+    provider = await manager.get_active_provider()
+    
+    health = await provider.health()
+    status = await provider.status()
+    
+    return {
+        "provider": health["provider"],
+        "health": health,
+        "status": status,
+    }
+
+
+@app.post("/providers/start")
+async def start_provider(data: dict):
+    """Start a specific provider."""
+    provider_type = data.get("provider_type")
+    if not provider_type:
+        raise HTTPException(status_code=400, detail="provider_type is required")
+    
+    manager = get_provider_manager()
+    try:
+        await manager.start_provider(provider_type)
+        provider = await manager.get_active_provider()
+        health = await provider.health()
+        return {
+            "message": f"Provider {provider_type} started",
+            "provider": health,
+        }
+    except NotImplementedError as e:
+        raise HTTPException(status_code=501, detail=str(e))
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.post("/providers/stop")
+async def stop_provider():
+    """Stop the currently active provider."""
+    manager = get_provider_manager()
+    await manager.stop_provider()
+    return {"message": "Provider stopped"}
+
+
+@app.post("/providers/download")
+async def download_provider_endpoint(data: dict):
+    """Download a provider binary."""
+    from .providers.installer import download_provider
+    
+    provider_type = data.get("provider_type")
+    if not provider_type:
+        raise HTTPException(status_code=400, detail="provider_type is required")
+    
+    if provider_type not in ["pytorch-cpu", "pytorch-cuda"]:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Provider type {provider_type} cannot be downloaded"
+        )
+    
+    try:
+        # Start download in background
+        asyncio.create_task(download_provider(provider_type))
+        return {
+            "message": f"Provider {provider_type} download started",
+            "provider_type": provider_type,
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@app.get("/providers/download/progress/{provider_type}")
+async def get_provider_download_progress(provider_type: str):
+    """Get provider download progress via Server-Sent Events."""
+    from fastapi.responses import StreamingResponse
+    from .utils.progress import get_progress_manager
+    
+    progress_manager = get_progress_manager()
+    
+    async def event_generator():
+        """Generate SSE events for provider download progress."""
+        import asyncio
+        import json
+        
+        last_progress = None
+        
+        while True:
+            progress = progress_manager.get_progress(provider_type)
+            
+            if progress and progress != last_progress:
+                yield f"data: {json.dumps(progress)}\n\n"
+                last_progress = progress
+                
+                if progress.get("status") in ["complete", "error"]:
+                    break
+            
+            await asyncio.sleep(0.5)
+    
+    return StreamingResponse(event_generator(), media_type="text/event-stream")
+
+
+@app.delete("/providers/{provider_type}")
+async def delete_provider_endpoint(provider_type: str):
+    """Delete an installed provider."""
+    from .providers.installer import delete_provider
+    
+    if provider_type not in ["pytorch-cpu", "pytorch-cuda"]:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Provider type {provider_type} cannot be deleted"
+        )
+    
+    deleted = delete_provider(provider_type)
+    
+    if deleted:
+        return {"message": f"Provider {provider_type} deleted successfully"}
+    else:
+        raise HTTPException(
+            status_code=404,
+            detail=f"Provider {provider_type} not found"
+        )
+
+
@app.delete("/models/{model_name}")
 async def delete_model(model_name: str):
    """Delete a downloaded model from the HuggingFace cache."""
@@ -1458,9 +1748,9 @@ async def delete_model(model_name: str):
    try:
        # Check if model is loaded and unload it first
        if config["model_type"] == "tts":
-            tts_model = tts.get_tts_model()
-            if tts_model.is_loaded() and tts_model.model_size == config["model_size"]:
-                tts.unload_tts_model()
+            tts_model = await tts.get_tts_model_async()
+            if tts_model.is_loaded() and getattr(tts_model, 'model_size', None) == config["model_size"]:
+                tts_model.unload_model()
        elif config["model_type"] == "whisper":
            whisper_model = transcribe.get_whisper_model()
            if whisper_model.is_loaded() and whisper_model.model_size == config["model_size"]:
@@ -1491,6 +1781,19 @@ async def delete_model(model_name: str):
        raise HTTPException(status_code=500, detail=f"Failed to delete model: {str(e)}")


+@app.post("/cache/clear")
+async def clear_cache():
+    """Clear all voice prompt caches (memory and disk)."""
+    try:
+        deleted_count = clear_voice_prompt_cache()
+        return {
+            "message": f"Voice prompt cache cleared successfully",
+            "files_deleted": deleted_count,
+        }
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=f"Failed to clear cache: {str(e)}")
+
+
 # ============================================
 # TASK MANAGEMENT
 # ============================================
@@ -1557,6 +1860,16 @@ async def get_active_tasks():
    )


+# ============================================
+# WEB UI STATIC FILES
+# ============================================
+
+# Serve web UI at root if dist directory exists
+_web_dist_path = Path(__file__).parent.parent / "web" / "dist"
+if _web_dist_path.exists():
+    app.mount("/", StaticFiles(directory=str(_web_dist_path), html=True), name="web")
+
+
 # ============================================
 # STARTUP & SHUTDOWN
 # ============================================
@@ -1564,11 +1877,12 @@ async def get_active_tasks():
 def _get_gpu_status() -> str:
    """Get GPU availability status."""
    backend_type = get_backend_type()
-    if torch.cuda.is_available():
-        return f"CUDA ({torch.cuda.get_device_name(0)})"
-    elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
-        return "MPS (Apple Silicon)"
-    elif backend_type == "mlx":
+    if TORCH_AVAILABLE and torch is not None:
+        if torch.cuda.is_available():
+            return f"CUDA ({torch.cuda.get_device_name(0)})"
+        elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
+            return "MPS (Apple Silicon)"
+    if backend_type == "mlx":
        return "Metal (Apple Silicon via MLX)"
    return "None (CPU only)"

@@ -1607,8 +1921,14 @@ async def shutdown_event():
    """Run on application shutdown."""
    print("voicebox API shutting down...")
    # Unload models to free memory
-    tts.unload_tts_model()
-    transcribe.unload_whisper_model()
+    try:
+        tts.unload_tts_model()
+    except Exception as e:
+        print(f"Warning: Failed to unload TTS model: {e}")
+    try:
+        transcribe.unload_whisper_model()
+    except Exception as e:
+        print(f"Warning: Failed to unload Whisper model: {e}")


 # ============================================
@@ -134,6 +134,7 @@ class ModelStatus(BaseModel):
    model_name: str
    display_name: str
    downloaded: bool
+    downloading: bool = False  # True if download is in progress
    size_mb: Optional[float] = None
    loaded: bool = False

@@ -169,6 +170,13 @@ class ActiveTasksResponse(BaseModel):
    generations: List[ActiveGenerationTask]


+class FolderPathsResponse(BaseModel):
+    """Response model for system folder paths."""
+    data_dir: str
+    models_dir: str
+    providers_dir: str
+
+
 class AudioChannelCreate(BaseModel):
    """Request model for creating an audio channel."""
    name: str = Field(..., min_length=1, max_length=100)
@@ -22,6 +22,7 @@ from .database import (
 )
 from .utils.audio import validate_reference_audio, load_audio, save_audio
 from .utils.images import validate_image, process_avatar
+from .utils.cache import _get_cache_dir, clear_profile_cache
 from .tts import get_tts_model
 from . import config

@@ -120,6 +121,10 @@ async def add_profile_sample(
    db.commit()
    db.refresh(db_sample)
    
+    # Invalidate combined audio cache for this profile
+    # Since a new sample was added, any cached combined audio is now stale
+    clear_profile_cache(profile_id)
+    
    return ProfileSampleResponse.model_validate(db_sample)


@@ -241,6 +246,9 @@ async def delete_profile(
    if profile_dir.exists():
        shutil.rmtree(profile_dir)
    
+    # Clean up combined audio cache files for this profile
+    clear_profile_cache(profile_id)
+    
    return True


@@ -262,6 +270,9 @@ async def delete_profile_sample(
    if not sample:
        return False
    
+    # Store profile_id before deleting
+    profile_id = sample.profile_id
+    
    # Delete audio file
    audio_path = Path(sample.audio_path)
    if audio_path.exists():
@@ -271,6 +282,10 @@ async def delete_profile_sample(
    db.delete(sample)
    db.commit()
    
+    # Invalidate combined audio cache for this profile
+    # Since the sample set changed, any cached combined audio is now stale
+    clear_profile_cache(profile_id)
+    
    return True


@@ -294,10 +309,17 @@ async def update_profile_sample(
    if not sample:
        return None
    
+    # Store profile_id before updating
+    profile_id = sample.profile_id
+    
    sample.reference_text = reference_text
    db.commit()
    db.refresh(sample)
    
+    # Invalidate combined audio cache for this profile
+    # Since the reference text changed, cache keys and combined text are now stale
+    clear_profile_cache(profile_id)
+    
    return ProfileSampleResponse.model_validate(sample)


@@ -345,23 +367,27 @@ async def create_voice_prompt_for_profile(
            reference_texts,
        )

-        # Save combined audio temporarily
-        import tempfile
-        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp:
-            save_audio(combined_audio, tmp.name, 24000)
-            tmp_path = tmp.name
+        # Save combined audio to cache directory (persistent)
+        # Create a hash of sample IDs to identify this specific combination
+        import hashlib
+        sample_ids_str = "-".join(sorted([s.id for s in samples]))
+        combination_hash = hashlib.md5(sample_ids_str.encode()).hexdigest()[:12]
+        
+        # Store in cache directory
+        cache_dir = _get_cache_dir()
+        cache_dir.mkdir(parents=True, exist_ok=True)
+        combined_path = cache_dir / f"combined_{profile_id}_{combination_hash}.wav"
+        
+        # Save combined audio
+        save_audio(combined_audio, str(combined_path), 24000)

-        try:
-            # Create prompt from combined audio
-            voice_prompt, _ = await tts_model.create_voice_prompt(
-                tmp_path,
-                combined_text,
-                use_cache=use_cache,
-            )
-            return voice_prompt
-        finally:
-            # Clean up temp file
-            Path(tmp_path).unlink(missing_ok=True)
+        # Create prompt from combined audio
+        voice_prompt, _ = await tts_model.create_voice_prompt(
+            str(combined_path),
+            combined_text,
+            use_cache=use_cache,
+        )
+        return voice_prompt


 async def upload_avatar(
@@ -0,0 +1,327 @@
+"""
+Provider management system for TTS providers.
+"""
+
+from typing import Optional
+import asyncio
+import platform
+from pathlib import Path
+
+from .base import TTSProvider
+from .types import ProviderType
+from .bundled import BundledProvider
+from .local import LocalProvider
+from .installer import get_provider_binary_path, _get_providers_dir
+from ..config import get_data_dir
+import subprocess
+import socket
+
+
+class ProviderManager:
+    """Manages TTS provider lifecycle."""
+    
+    def __init__(self):
+        self.active_provider: Optional[TTSProvider] = None
+        self._default_provider: Optional[TTSProvider] = None
+        self._provider_process: Optional[subprocess.Popen] = None
+        self._provider_port: Optional[int] = None
+    
+    def _get_default_provider(self) -> TTSProvider:
+        """Get the default bundled provider."""
+        if self._default_provider is None:
+            self._default_provider = BundledProvider()
+        return self._default_provider
+    
+    async def get_active_provider(self) -> TTSProvider:
+        """
+        Get the currently active provider.
+        
+        Returns:
+            Active TTS provider instance
+        """
+        if self.active_provider is None:
+            # Default to bundled provider
+            self.active_provider = self._get_default_provider()
+        return self.active_provider
+    
+    async def start_provider(self, provider_type: str) -> None:
+        """
+        Start a TTS provider.
+        
+        Args:
+            provider_type: Type of provider to start
+        """
+        if provider_type == "apple-mlx":
+            # Use bundled MLX provider
+            self.active_provider = self._get_default_provider()
+        elif provider_type in ["pytorch-cpu", "pytorch-cuda"]:
+            # Try to start external provider subprocess if binary exists
+            provider_path = get_provider_binary_path(provider_type)
+            if provider_path and provider_path.exists():
+                # External downloaded provider exists, start it
+                # Find a free port
+                port = self._get_free_port()
+
+                # Start provider subprocess with stdout/stderr capture
+                from ..config import get_data_dir
+                import logging
+                logger = logging.getLogger(__name__)
+
+                logger.info(f"Starting provider {provider_type} on port {port}")
+                logger.info(f"Provider binary: {provider_path}")
+                logger.info(f"Data directory: {get_data_dir()}")
+
+                # Create log files for provider output (easier debugging on Windows)
+                logs_dir = get_data_dir() / "logs"
+                logs_dir.mkdir(exist_ok=True)
+                stdout_log = logs_dir / f"{provider_type}-stdout.log"
+                stderr_log = logs_dir / f"{provider_type}-stderr.log"
+
+                logger.info(f"Provider logs will be written to: {logs_dir}")
+
+                process = subprocess.Popen(
+                    [
+                        str(provider_path),
+                        "--port", str(port),
+                        "--data-dir", str(get_data_dir()),
+                    ],
+                    stdout=open(stdout_log, 'w'),
+                    stderr=open(stderr_log, 'w'),
+                    text=True,
+                    bufsize=1,
+                )
+
+                # Wait for provider to be ready
+                base_url = f"http://127.0.0.1:{port}"
+                try:
+                    await self._wait_for_provider_health(base_url, timeout=30)
+                except TimeoutError as e:
+                    # Read log files for debugging (works on all platforms unlike select)
+                    stdout_content = ""
+                    stderr_content = ""
+
+                    # Try to read available output (works on Windows and Unix)
+                    try:
+                        # Use non-blocking read with timeout
+                        import threading
+                        import queue
+
+                        def enqueue_output(stream, queue):
+                            try:
+                                for line in iter(stream.readline, ''):
+                                    queue.put(line)
+                            except:
+                                pass
+
+                        stdout_queue = queue.Queue()
+                        stderr_queue = queue.Queue()
+
+                        if process.stdout:
+                            t = threading.Thread(target=enqueue_output, args=(process.stdout, stdout_queue))
+                            t.daemon = True
+                            t.start()
+
+                        if process.stderr:
+                            t2 = threading.Thread(target=enqueue_output, args=(process.stderr, stderr_queue))
+                            t2.daemon = True
+                            t2.start()
+
+                        # Give threads a moment to read
+                        import time
+                        time.sleep(0.5)
+
+                        # Collect output
+                        while not stdout_queue.empty():
+                            stdout_lines.append(stdout_queue.get_nowait())
+                        while not stderr_queue.empty():
+                            stderr_lines.append(stderr_queue.get_nowait())
+                    except Exception as ex:
+                        logger.warning(f"Could not capture subprocess output: {ex}")
+
+                    logger.error(f"Provider failed to start within 30 seconds")
+                    logger.error(f"Check logs at: {logs_dir}")
+                    if stdout_content:
+                        logger.error(f"Stdout: {stdout_content[-2000:]}")  # Last 2000 chars
+                    if stderr_content:
+                        logger.error(f"Stderr: {stderr_content[-2000:]}")  # Last 2000 chars
+
+                    # Terminate the process
+                    process.terminate()
+                    try:
+                        process.wait(timeout=5)
+                    except subprocess.TimeoutExpired:
+                        process.kill()
+
+                    # Raise with log file location for user
+                    raise TimeoutError(
+                        f"Provider {provider_type} failed to start. Check logs at: {logs_dir}"
+                    )
+
+                # Create LocalProvider instance
+                self.active_provider = LocalProvider(base_url)
+                self._provider_process = process
+                self._provider_port = port
+
+                # Logs are written directly to files (stdout_log, stderr_log)
+                # No need for background task - users can check {logs_dir} for debugging
+            else:
+                # No external binary, use bundled provider (if available)
+                if provider_type == "pytorch-cpu":
+                    # PyTorch CPU can use bundled backend
+                    self.active_provider = self._get_default_provider()
+                else:
+                    raise ValueError(f"Provider {provider_type} is not installed. Please download it first.")
+        elif provider_type == "remote":
+            # Remote provider - will be implemented in Phase 5
+            raise NotImplementedError("Remote provider not yet implemented")
+        elif provider_type == "openai":
+            # OpenAI provider - will be implemented in Phase 5
+            raise NotImplementedError("OpenAI provider not yet implemented")
+        else:
+            raise ValueError(f"Unknown provider type: {provider_type}")
+    
+    async def stop_provider(self) -> None:
+        """Stop the active provider."""
+        if self.active_provider:
+            # Only stop if it's not the default bundled provider
+            if self.active_provider is not self._default_provider:
+                if hasattr(self.active_provider, 'stop'):
+                    await self.active_provider.stop()
+                self.active_provider = None
+            
+            # Stop subprocess if running
+            if self._provider_process:
+                self._provider_process.terminate()
+                try:
+                    self._provider_process.wait(timeout=5)
+                except subprocess.TimeoutExpired:
+                    self._provider_process.kill()
+                self._provider_process = None
+                self._provider_port = None
+    
+    async def list_installed(self) -> list[str]:
+        """
+        List installed provider types.
+        
+        Returns:
+            List of installed provider type strings
+        """
+        installed = []
+        
+        # Bundled providers are always available
+        system = platform.system()
+        machine = platform.machine()
+
+        if system == "Darwin" and machine == "arm64":
+            # Apple Silicon gets MLX bundled
+            installed.append("apple-mlx")
+        elif system == "Windows" or (system == "Darwin" and machine != "arm64"):
+            # Windows and Intel macOS get PyTorch CPU bundled
+            installed.append("pytorch-cpu")
+        # Linux: no bundled provider - users must download
+        
+        # Check for downloaded providers by checking if binary path exists
+        for provider_type in ["pytorch-cpu", "pytorch-cuda"]:
+            binary_path = get_provider_binary_path(provider_type)
+            if binary_path and binary_path.exists() and provider_type not in installed:
+                installed.append(provider_type)
+        
+        return installed
+    
+    async def get_provider_info(self, provider_type: str) -> dict:
+        """
+        Get information about a provider.
+        
+        Args:
+            provider_type: Type of provider
+            
+        Returns:
+            Provider information dictionary
+        """
+        if provider_type in ["apple-mlx", "bundled-pytorch"]:
+            return {
+                "type": provider_type,
+                "name": "Bundled Provider",
+                "installed": True,
+                "size_mb": None,  # Bundled, no separate size
+            }
+        elif provider_type == "pytorch-cpu":
+            return {
+                "type": provider_type,
+                "name": "PyTorch CPU",
+                "installed": provider_type in await self.list_installed(),
+                "size_mb": 300,
+            }
+        elif provider_type == "pytorch-cuda":
+            return {
+                "type": provider_type,
+                "name": "PyTorch CUDA",
+                "installed": provider_type in await self.list_installed(),
+                "size_mb": 2400,
+            }
+        else:
+            return {
+                "type": provider_type,
+                "name": provider_type,
+                "installed": False,
+                "size_mb": None,
+            }
+
+
+    def _get_free_port(self) -> int:
+        """Get a free port for the provider server."""
+        with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
+            s.bind(('', 0))
+            return s.getsockname()[1]
+    
+    async def _wait_for_provider_health(self, base_url: str, timeout: int = 30) -> None:
+        """Wait for provider to become healthy."""
+        import httpx
+        import asyncio
+
+        start_time = asyncio.get_event_loop().time()
+        while True:
+            try:
+                async with httpx.AsyncClient(timeout=2.0) as client:
+                    response = await client.get(f"{base_url}/tts/health")
+                    if response.status_code == 200:
+                        return
+            except Exception:
+                pass
+
+            if asyncio.get_event_loop().time() - start_time > timeout:
+                raise TimeoutError(f"Provider did not become healthy within {timeout} seconds")
+
+            await asyncio.sleep(0.5)
+
+    async def _log_subprocess_output(self, process: subprocess.Popen) -> None:
+        """Log subprocess stdout and stderr."""
+        import logging
+        logger = logging.getLogger(__name__)
+
+        async def read_stream(stream, prefix):
+            if stream:
+                loop = asyncio.get_event_loop()
+                while True:
+                    line = await loop.run_in_executor(None, stream.readline)
+                    if not line:
+                        break
+                    logger.info(f"{prefix}: {line.rstrip()}")
+
+        await asyncio.gather(
+            read_stream(process.stdout, "Provider stdout"),
+            read_stream(process.stderr, "Provider stderr"),
+            return_exceptions=True,
+        )
+
+
+# Global provider manager instance
+_provider_manager: Optional[ProviderManager] = None
+
+
+def get_provider_manager() -> ProviderManager:
+    """Get the global provider manager instance."""
+    global _provider_manager
+    if _provider_manager is None:
+        _provider_manager = ProviderManager()
+    return _provider_manager
@@ -0,0 +1,97 @@
+"""
+Base protocol for TTS providers.
+"""
+
+from typing import Protocol, Optional, Tuple
+from typing_extensions import runtime_checkable
+import numpy as np
+
+from .types import ProviderHealth, ProviderStatus
+
+
+@runtime_checkable
+class TTSProvider(Protocol):
+    """Protocol for TTS provider implementations."""
+    
+    async def generate(
+        self,
+        text: str,
+        voice_prompt: dict,
+        language: str = "en",
+        seed: Optional[int] = None,
+        instruct: Optional[str] = None,
+    ) -> Tuple[np.ndarray, int]:
+        """
+        Generate speech audio from text.
+        
+        Args:
+            text: Text to synthesize
+            voice_prompt: Voice prompt dictionary
+            language: Language code
+            seed: Random seed for reproducibility
+            instruct: Delivery instructions
+            
+        Returns:
+            Tuple of (audio_array, sample_rate)
+        """
+        ...
+    
+    async def create_voice_prompt(
+        self,
+        audio_path: str,
+        reference_text: str,
+        use_cache: bool = True,
+    ) -> Tuple[dict, bool]:
+        """
+        Create voice prompt from reference audio.
+        
+        Args:
+            audio_path: Path to reference audio file
+            reference_text: Transcript of the audio
+            use_cache: Whether to use cached prompts
+            
+        Returns:
+            Tuple of (voice_prompt_dict, was_cached)
+        """
+        ...
+    
+    async def combine_voice_prompts(
+        self,
+        audio_paths: list[str],
+        reference_texts: list[str],
+    ) -> Tuple[np.ndarray, str]:
+        """
+        Combine multiple voice prompts.
+        
+        Args:
+            audio_paths: List of audio file paths
+            reference_texts: List of reference texts
+            
+        Returns:
+            Tuple of (combined_audio_array, combined_text)
+        """
+        ...
+    
+    async def load_model_async(self, model_size: str) -> None:
+        """Load TTS model."""
+        ...
+    
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        ...
+    
+    def is_loaded(self) -> bool:
+        """Check if model is loaded."""
+        ...
+    
+    def _get_model_path(self, model_size: str) -> str:
+        """Get model path for a given size."""
+        ...
+    
+    async def health(self) -> ProviderHealth:
+        """Get provider health status."""
+        ...
+    
+    async def status(self) -> ProviderStatus:
+        """Get provider model status."""
+        ...
@@ -0,0 +1,144 @@
+"""
+Bundled provider that wraps existing MLX/PyTorch backends.
+"""
+
+from typing import Optional, Tuple
+import numpy as np
+import platform
+
+from .base import TTSProvider
+from .types import ProviderHealth, ProviderStatus
+from ..backends import get_tts_backend, TTSBackend
+from ..platform_detect import get_backend_type
+
+
+class BundledProvider:
+    """Provider that wraps the existing bundled TTS backend."""
+    
+    def __init__(self):
+        self._backend: Optional[TTSBackend] = None
+    
+    def _get_backend(self) -> TTSBackend:
+        """Get or create backend instance."""
+        if self._backend is None:
+            self._backend = get_tts_backend()
+        return self._backend
+    
+    async def generate(
+        self,
+        text: str,
+        voice_prompt: dict,
+        language: str = "en",
+        seed: Optional[int] = None,
+        instruct: Optional[str] = None,
+    ) -> Tuple[np.ndarray, int]:
+        """Generate speech audio."""
+        backend = self._get_backend()
+        return await backend.generate(text, voice_prompt, language, seed, instruct)
+    
+    async def create_voice_prompt(
+        self,
+        audio_path: str,
+        reference_text: str,
+        use_cache: bool = True,
+    ) -> Tuple[dict, bool]:
+        """Create voice prompt from reference audio."""
+        backend = self._get_backend()
+        return await backend.create_voice_prompt(audio_path, reference_text, use_cache)
+    
+    async def combine_voice_prompts(
+        self,
+        audio_paths: list[str],
+        reference_texts: list[str],
+    ) -> Tuple[np.ndarray, str]:
+        """Combine multiple voice prompts."""
+        backend = self._get_backend()
+        return await backend.combine_voice_prompts(audio_paths, reference_texts)
+    
+    async def load_model_async(self, model_size: str) -> None:
+        """Load TTS model."""
+        backend = self._get_backend()
+        if hasattr(backend, 'load_model_async'):
+            await backend.load_model_async(model_size)
+        else:
+            await backend.load_model(model_size)
+
+    # Alias for compatibility
+    load_model = load_model_async
+    
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        backend = self._get_backend()
+        backend.unload_model()
+    
+    def is_loaded(self) -> bool:
+        """Check if model is loaded."""
+        backend = self._get_backend()
+        return backend.is_loaded()
+    
+    def _get_model_path(self, model_size: str) -> str:
+        """Get model path for a given size."""
+        backend = self._get_backend()
+        return backend._get_model_path(model_size)
+    
+    async def health(self) -> ProviderHealth:
+        """Get provider health status."""
+        backend = self._get_backend()
+        backend_type = get_backend_type()
+
+        model_size = None
+        if backend.is_loaded():
+            # Try to get current model size from backend
+            if hasattr(backend, '_current_model_size') and backend._current_model_size:
+                model_size = backend._current_model_size
+
+        device = None
+        if backend_type == "mlx":
+            device = "metal"
+        elif hasattr(backend, 'device'):
+            device = backend.device
+
+        # Use apple-mlx for MLX backend, pytorch-cpu for PyTorch
+        provider_name = "apple-mlx" if backend_type == "mlx" else "pytorch-cpu"
+
+        return ProviderHealth(
+            status="healthy",
+            provider=provider_name,
+            version=None,  # Provider versioning not implemented yet
+            model=model_size,
+            device=device,
+        )
+    
+    async def status(self) -> ProviderStatus:
+        """Get provider model status."""
+        backend = self._get_backend()
+        backend_type = get_backend_type()
+        
+        model_size = None
+        if backend.is_loaded():
+            if hasattr(backend, '_current_model_size') and backend._current_model_size:
+                model_size = backend._current_model_size
+        
+        available_sizes = ["1.7B"]
+        if backend_type == "pytorch":
+            available_sizes.append("0.6B")
+        
+        gpu_available = None
+        vram_used_mb = None
+        
+        if backend_type == "pytorch":
+            try:
+                import torch
+                gpu_available = torch.cuda.is_available()
+                if gpu_available:
+                    vram_used_mb = torch.cuda.memory_allocated() / 1024 / 1024
+            except ImportError:
+                pass
+        
+        return ProviderStatus(
+            model_loaded=backend.is_loaded(),
+            model_size=model_size,
+            available_sizes=available_sizes,
+            gpu_available=gpu_available,
+            vram_used_mb=int(vram_used_mb) if vram_used_mb else None,
+        )
@@ -0,0 +1,11 @@
+# Provider checksums - embedded at build time for security
+# This file is auto-generated during CI builds
+# In development, checksums are empty (verification is skipped)
+
+PROVIDER_CHECKSUMS = {
+    # Populated during release builds with SHA256 checksums of provider binaries
+    # Example:
+    # "tts-provider-pytorch-cpu-windows.exe": "abc123...",
+    # "tts-provider-pytorch-cuda-windows.exe": "def456...",
+    # "tts-provider-pytorch-cuda-linux": "789xyz...",
+}
@@ -0,0 +1,262 @@
+"""
+Provider download and installation manager.
+"""
+
+import asyncio
+import httpx
+import platform
+from pathlib import Path
+from typing import Optional
+
+from .types import ProviderType
+from ..utils.progress import get_progress_manager
+from ..utils.tasks import get_task_manager
+
+
+# Provider version (independent of app version)
+PROVIDER_VERSION = "1.0.0"
+
+# Base URL for provider downloads (Cloudflare R2)
+PROVIDER_DOWNLOAD_BASE_URL = "https://downloads.voicebox.sh/providers"
+
+
+def _get_providers_dir() -> Path:
+    """Get the directory where providers are stored."""
+    system = platform.system()
+    
+    if system == "Windows":
+        appdata = Path.home() / "AppData" / "Roaming"
+    elif system == "Darwin":
+        appdata = Path.home() / "Library" / "Application Support"
+    else:  # Linux
+        appdata = Path.home() / ".local" / "share"
+    
+    providers_dir = appdata / "voicebox" / "providers"
+    providers_dir.mkdir(parents=True, exist_ok=True)
+    return providers_dir
+
+
+def _get_provider_binary_name(provider_type: str) -> str:
+    """Get the local binary filename for a provider type."""
+    system = platform.system()
+    ext = ".exe" if system == "Windows" else ""
+    
+    binary_map = {
+        "pytorch-cpu": f"tts-provider-pytorch-cpu{ext}",
+        "pytorch-cuda": f"tts-provider-pytorch-cuda{ext}",
+    }
+    
+    if provider_type not in binary_map:
+        raise ValueError(f"Unknown provider type: {provider_type}")
+    
+    return binary_map[provider_type]
+
+
+def _get_provider_download_name(provider_type: str) -> str:
+    """Get the remote download filename for a provider type (includes platform suffix)."""
+    system = platform.system()
+
+    if system == "Windows":
+        platform_suffix = "windows"
+        ext = ".zip"
+    elif system == "Linux":
+        platform_suffix = "linux"
+        ext = ".tar.gz"
+    elif system == "Darwin":
+        # Detect macOS architecture
+        machine = platform.machine()
+        if machine == "arm64":
+            platform_suffix = "macos-arm64"
+        else:
+            platform_suffix = "macos-x64"
+        ext = ".tar.gz"
+    else:
+        raise ValueError(f"Provider downloads not supported on {system}")
+
+    return f"tts-provider-{provider_type}-{platform_suffix}{ext}"
+
+
+def _get_provider_download_url(provider_type: str) -> str:
+    """Get the download URL for a provider."""
+    download_name = _get_provider_download_name(provider_type)
+    return f"{PROVIDER_DOWNLOAD_BASE_URL}/v{PROVIDER_VERSION}/{download_name}"
+
+
+async def download_provider(provider_type: str) -> Path:
+    """
+    Download and extract a provider archive from Cloudflare R2.
+
+    Args:
+        provider_type: Type of provider to download (e.g., "pytorch-cpu")
+
+    Returns:
+        Path to the extracted provider binary
+
+    Raises:
+        ValueError: If provider_type is invalid
+        httpx.HTTPError: If download fails
+    """
+    if provider_type not in ["pytorch-cpu", "pytorch-cuda"]:
+        raise ValueError(f"Provider type {provider_type} cannot be downloaded")
+
+    progress_manager = get_progress_manager()
+    task_manager = get_task_manager()
+
+    archive_name = _get_provider_download_name(provider_type)
+    download_url = _get_provider_download_url(provider_type)
+    providers_dir = _get_providers_dir()
+    archive_path = providers_dir / archive_name
+
+    # Start tracking download
+    task_manager.start_download(provider_type)
+
+    # Initialize progress state
+    progress_manager.update_progress(
+        model_name=provider_type,
+        current=0,
+        total=0,  # Will be updated once we get Content-Length
+        filename=archive_name,
+        status="downloading",
+    )
+
+    try:
+        # Download archive
+        async with httpx.AsyncClient(timeout=300.0) as client:
+            async with client.stream("GET", download_url) as response:
+                response.raise_for_status()
+
+                # Get total size from Content-Length header
+                total_size = int(response.headers.get("Content-Length", 0))
+
+                if total_size > 0:
+                    progress_manager.update_progress(
+                        model_name=provider_type,
+                        current=0,
+                        total=total_size,
+                        filename=archive_name,
+                        status="downloading",
+                    )
+
+                # Download with progress tracking
+                downloaded = 0
+                with open(archive_path, "wb") as f:
+                    async for chunk in response.aiter_bytes(chunk_size=8192):
+                        f.write(chunk)
+                        downloaded += len(chunk)
+
+                        # Update progress
+                        progress_manager.update_progress(
+                            model_name=provider_type,
+                            current=downloaded,
+                            total=total_size if total_size > 0 else downloaded,
+                            filename=archive_name,
+                            status="downloading",
+                        )
+
+        # Extract archive
+        progress_manager.update_progress(
+            model_name=provider_type,
+            current=downloaded,
+            total=downloaded,
+            filename="Extracting...",
+            status="downloading",
+        )
+
+        import zipfile
+        import tarfile
+
+        if archive_name.endswith('.zip'):
+            with zipfile.ZipFile(archive_path, 'r') as zip_ref:
+                zip_ref.extractall(providers_dir)
+        elif archive_name.endswith('.tar.gz'):
+            with tarfile.open(archive_path, 'r:gz') as tar_ref:
+                tar_ref.extractall(providers_dir)
+        else:
+            raise ValueError(f"Unsupported archive format: {archive_name}")
+
+        # Remove archive after extraction
+        archive_path.unlink()
+
+        # Get path to extracted binary
+        binary_path = get_provider_binary_path(provider_type)
+        if not binary_path:
+            raise ValueError(f"Provider binary not found after extraction")
+
+        # Make executable on Unix systems
+        if platform.system() != "Windows":
+            binary_path.chmod(0o755)
+
+        # Mark as complete
+        progress_manager.update_progress(
+            model_name=provider_type,
+            current=downloaded,
+            total=downloaded,
+            filename=_get_provider_binary_name(provider_type),
+            status="complete",
+        )
+        task_manager.complete_download(provider_type)
+
+        return binary_path
+
+    except Exception as e:
+        # Clean up archive if it exists
+        if archive_path.exists():
+            archive_path.unlink()
+
+        # Mark as error
+        progress_manager.update_progress(
+            model_name=provider_type,
+            current=0,
+            total=0,
+            filename=archive_name,
+            status="error",
+        )
+        task_manager.error_download(provider_type, str(e))
+        raise
+
+
+def get_provider_binary_path(provider_type: str) -> Optional[Path]:
+    """
+    Get the path to an installed provider binary.
+
+    Args:
+        provider_type: Type of provider
+
+    Returns:
+        Path to provider binary, or None if not installed
+    """
+    providers_dir = _get_providers_dir()
+    binary_name = _get_provider_binary_name(provider_type)
+
+    # Check for --onedir structure (directory with binary inside)
+    provider_dir = providers_dir / f"tts-provider-{provider_type}"
+    if provider_dir.exists() and provider_dir.is_dir():
+        binary_path = provider_dir / binary_name
+        if binary_path.exists() and binary_path.is_file():
+            return binary_path
+
+    # Fallback: check for direct binary (legacy)
+    provider_path = providers_dir / binary_name
+    if provider_path.exists() and provider_path.is_file():
+        return provider_path
+
+    return None
+
+
+def delete_provider(provider_type: str) -> bool:
+    """
+    Delete an installed provider binary.
+    
+    Args:
+        provider_type: Type of provider to delete
+        
+    Returns:
+        True if deleted, False if not found
+    """
+    provider_path = get_provider_binary_path(provider_type)
+    
+    if provider_path and provider_path.exists():
+        provider_path.unlink()
+        return True
+    
+    return False
@@ -0,0 +1,191 @@
+"""
+Local provider that communicates with standalone provider servers via HTTP.
+"""
+
+from typing import Optional, Tuple
+import base64
+import io
+import numpy as np
+import httpx
+import soundfile as sf
+
+from .base import TTSProvider
+from .types import ProviderHealth, ProviderStatus
+
+
+class LocalProvider:
+    """Provider that communicates with local subprocess via HTTP."""
+    
+    def __init__(self, base_url: str):
+        """
+        Initialize local provider.
+        
+        Args:
+            base_url: Base URL of the provider server (e.g., "http://localhost:8000")
+        """
+        self.base_url = base_url.rstrip('/')
+        self.client = httpx.AsyncClient(timeout=300.0)  # 5 minute timeout for generation
+        self._current_model_size = "1.7B"  # Default model size
+    
+    async def generate(
+        self,
+        text: str,
+        voice_prompt: dict,
+        language: str = "en",
+        seed: Optional[int] = None,
+        instruct: Optional[str] = None,
+    ) -> Tuple[np.ndarray, int]:
+        """Generate speech audio."""
+        response = await self.client.post(
+            f"{self.base_url}/tts/generate",
+            json={
+                "text": text,
+                "voice_prompt": voice_prompt,
+                "language": language,
+                "seed": seed,
+                "model_size": self._current_model_size,
+            }
+        )
+        response.raise_for_status()
+        data = response.json()
+        
+        # Decode base64 audio
+        audio_bytes = base64.b64decode(data["audio"])
+        audio_buffer = io.BytesIO(audio_bytes)
+        audio, sample_rate = sf.read(audio_buffer)
+        
+        return audio, data["sample_rate"]
+    
+    async def create_voice_prompt(
+        self,
+        audio_path: str,
+        reference_text: str,
+        use_cache: bool = True,
+    ) -> Tuple[dict, bool]:
+        """Create voice prompt from reference audio."""
+        # Read audio file
+        with open(audio_path, 'rb') as f:
+            audio_data = f.read()
+        
+        # Send multipart form data
+        files = {
+            "audio": ("audio.wav", audio_data, "audio/wav")
+        }
+        data = {
+            "reference_text": reference_text,
+            "use_cache": str(use_cache).lower(),
+        }
+        
+        response = await self.client.post(
+            f"{self.base_url}/tts/create_voice_prompt",
+            files=files,
+            data=data,
+        )
+        response.raise_for_status()
+        result = response.json()
+        
+        return result["voice_prompt"], result.get("was_cached", False)
+    
+    async def combine_voice_prompts(
+        self,
+        audio_paths: list[str],
+        reference_texts: list[str],
+    ) -> Tuple[np.ndarray, str]:
+        """
+        Combine multiple voice prompts.
+        
+        Note: This is not implemented in the provider API yet.
+        For now, we'll combine locally by concatenating audio.
+        """
+        import numpy as np
+        from ..utils.audio import load_audio, normalize_audio
+        
+        combined_audio = []
+        for audio_path in audio_paths:
+            audio, sr = load_audio(audio_path)
+            audio = normalize_audio(audio)
+            combined_audio.append(audio)
+        
+        # Concatenate audio
+        mixed = np.concatenate(combined_audio)
+        mixed = normalize_audio(mixed)
+        
+        # Combine texts
+        combined_text = " ".join(reference_texts)
+        
+        return mixed, combined_text
+    
+    async def load_model_async(self, model_size: str) -> None:
+        """Load TTS model."""
+        # Track the requested model size - the provider server will load it
+        # when generate() is called with this size
+        self._current_model_size = model_size
+
+    # Alias for compatibility
+    load_model = load_model_async
+    
+    def unload_model(self) -> None:
+        """Unload model to free memory."""
+        # Model unloading is handled by the provider server
+        # This is a no-op for local providers
+        pass
+    
+    def is_loaded(self) -> bool:
+        """Check if model is loaded."""
+        # We can't know this without querying the provider
+        # Return True optimistically
+        return True
+    
+    def _get_model_path(self, model_size: str) -> str:
+        """Get model path for a given size."""
+        # For local providers, model paths are handled by the provider server
+        # Return a placeholder
+        return f"Qwen/Qwen3-TTS-12Hz-{model_size}-Base"
+    
+    async def health(self) -> ProviderHealth:
+        """Get provider health status."""
+        try:
+            response = await self.client.get(f"{self.base_url}/tts/health")
+            response.raise_for_status()
+            data = response.json()
+            return ProviderHealth(
+                status=data["status"],
+                provider=data["provider"],
+                version=data.get("version"),
+                model=data.get("model"),
+                device=data.get("device"),
+            )
+        except Exception as e:
+            return ProviderHealth(
+                status="unhealthy",
+                provider="local",
+                version=None,
+                model=None,
+                device=None,
+            )
+    
+    async def status(self) -> ProviderStatus:
+        """Get provider model status."""
+        try:
+            response = await self.client.get(f"{self.base_url}/tts/status")
+            response.raise_for_status()
+            data = response.json()
+            return ProviderStatus(
+                model_loaded=data["model_loaded"],
+                model_size=data.get("model_size"),
+                available_sizes=data.get("available_sizes", []),
+                gpu_available=data.get("gpu_available"),
+                vram_used_mb=data.get("vram_used_mb"),
+            )
+        except Exception as e:
+            return ProviderStatus(
+                model_loaded=False,
+                model_size=None,
+                available_sizes=[],
+                gpu_available=None,
+                vram_used_mb=None,
+            )
+    
+    async def stop(self) -> None:
+        """Stop the provider (close HTTP client)."""
+        await self.client.aclose()
@@ -0,0 +1,34 @@
+"""
+Shared types for TTS providers.
+"""
+
+from typing import Optional, TypedDict
+from enum import Enum
+
+
+class ProviderType(str, Enum):
+    """Available provider types."""
+    BUNDLED_MLX = "apple-mlx"
+    BUNDLED_PYTORCH = "bundled-pytorch"
+    PYTORCH_CPU = "pytorch-cpu"
+    PYTORCH_CUDA = "pytorch-cuda"
+    REMOTE = "remote"
+    OPENAI = "openai"
+
+
+class ProviderHealth(TypedDict):
+    """Provider health status."""
+    status: str  # "healthy", "unhealthy", "starting"
+    provider: str
+    version: Optional[str]
+    model: Optional[str]
+    device: Optional[str]
+
+
+class ProviderStatus(TypedDict):
+    """Provider model status."""
+    model_loaded: bool
+    model_size: Optional[str]
+    available_sizes: list[str]
+    gpu_available: Optional[bool]
+    vram_used_mb: Optional[int]
@@ -0,0 +1,58 @@
+# Backend Tests
+
+Manual test scripts for debugging and validating backend functionality.
+
+## Test Files
+
+### `test_generation_progress.py`
+Tests TTS generation with SSE progress monitoring to identify UX issues where users see download progress even when the model is already cached.
+
+**Usage:**
+```bash
+cd backend
+python tests/test_generation_progress.py
+```
+
+**Prerequisites:**
+- Server must be running (`python main.py`)
+- At least one voice profile must exist
+
+### `test_real_download.py`
+Tests real model download with SSE progress monitoring.
+
+**Usage:**
+```bash
+cd backend
+# Delete cache first to force fresh download
+rm -rf ~/.cache/huggingface/hub/models--openai--whisper-base
+python tests/test_real_download.py
+```
+
+**Prerequisites:**
+- Server must be running (`python main.py`)
+
+### `test_progress.py`
+Unit tests for ProgressManager and HFProgressTracker functionality.
+
+**Usage:**
+```bash
+cd backend
+python tests/test_progress.py
+```
+
+### `test_check_progress_state.py`
+Debugging script to inspect the internal state of ProgressManager and TaskManager.
+
+**Usage:**
+```bash
+cd backend
+python tests/test_check_progress_state.py
+```
+
+## Notes
+
+These are manual test scripts, not automated unit tests. They're designed for:
+- Debugging progress tracking issues
+- Validating SSE event streams
+- Monitoring real-time download behavior
+- Inspecting internal state during development
@@ -0,0 +1,6 @@
+"""
+Test suite for Voicebox backend.
+
+This directory contains manual test scripts for debugging and validating
+progress tracking, model downloads, and generation functionality.
+"""
@@ -0,0 +1,321 @@
+"""
+Test TTS generation with SSE progress monitoring.
+This test captures the exact SSE events triggered during generation
+to identify UX issues where users see download progress even when
+the model is already cached.
+"""
+
+import asyncio
+import json
+import httpx
+from typing import List, Dict, Optional
+from datetime import datetime
+
+
+async def monitor_sse_stream(model_name: str, timeout: int = 120):
+    """Monitor SSE stream for a model during generation."""
+    events: List[Dict] = []
+    url = f"http://localhost:8000/models/progress/{model_name}"
+
+    print(f"[{_timestamp()}] Connecting to SSE endpoint: {url}")
+
+    try:
+        async with httpx.AsyncClient(timeout=timeout) as client:
+            async with client.stream("GET", url) as response:
+                print(f"[{_timestamp()}] SSE connected, status: {response.status_code}")
+
+                if response.status_code != 200:
+                    print(f"[{_timestamp()}] Error: SSE endpoint returned {response.status_code}")
+                    return events
+
+                async for line in response.aiter_lines():
+                    if not line:
+                        continue
+
+                    timestamp = _timestamp()
+
+                    if line.startswith("data: "):
+                        try:
+                            data = json.loads(line[6:])
+                            print(f"[{timestamp}] → SSE Event: {data['status']:12} {data.get('progress', 0):6.1f}% {data.get('filename', '')}")
+                            events.append({
+                                **data,
+                                "_timestamp": timestamp
+                            })
+
+                            # Stop if complete or error
+                            if data.get("status") in ("complete", "error"):
+                                print(f"[{timestamp}] → Model {data['status']}!")
+                                break
+
+                        except json.JSONDecodeError as e:
+                            print(f"[{timestamp}] Error parsing JSON: {e}")
+                            print(f"  Line was: {line}")
+
+                    elif line.startswith(": heartbeat"):
+                        print(f"[{timestamp}] ♥ heartbeat")
+
+    except asyncio.TimeoutError:
+        print(f"[{_timestamp()}] SSE monitoring timed out")
+    except Exception as e:
+        print(f"[{_timestamp()}] SSE error: {e}")
+
+    return events
+
+
+async def trigger_generation(profile_id: str, text: str, model_size: str = "1.7B"):
+    """Trigger TTS generation via the API."""
+    url = "http://localhost:8000/generate"
+
+    print(f"\n[{_timestamp()}] Triggering generation...")
+    print(f"  Profile: {profile_id}")
+    print(f"  Text: {text[:50]}...")
+    print(f"  Model: {model_size}")
+
+    try:
+        async with httpx.AsyncClient(timeout=120) as client:
+            response = await client.post(url, json={
+                "profile_id": profile_id,
+                "text": text,
+                "language": "en",
+                "model_size": model_size,
+            })
+
+            print(f"[{_timestamp()}] Response: {response.status_code}")
+
+            if response.status_code == 200:
+                result = response.json()
+                print(f"[{_timestamp()}] ✓ Generation successful!")
+                print(f"  Generation ID: {result.get('id')}")
+                print(f"  Duration: {result.get('duration', 0):.2f}s")
+                return True, result
+            elif response.status_code == 202:
+                # Model is being downloaded
+                result = response.json()
+                print(f"[{_timestamp()}] → Model download in progress")
+                print(f"  Detail: {result}")
+                return False, result
+            else:
+                print(f"[{_timestamp()}] ✗ Error: {response.text}")
+                return False, None
+
+    except Exception as e:
+        print(f"[{_timestamp()}] ✗ Exception: {e}")
+        return False, None
+
+
+async def get_first_profile():
+    """Get the first available voice profile."""
+    url = "http://localhost:8000/profiles"
+
+    try:
+        async with httpx.AsyncClient(timeout=10) as client:
+            response = await client.get(url)
+            if response.status_code == 200:
+                profiles = response.json()
+                if profiles:
+                    return profiles[0]["id"]
+    except Exception as e:
+        print(f"Error getting profiles: {e}")
+
+    return None
+
+
+async def check_server():
+    """Check if the server is running."""
+    try:
+        async with httpx.AsyncClient(timeout=5) as client:
+            response = await client.get("http://localhost:8000/health")
+            return response.status_code == 200
+    except Exception as e:
+        print(f"Server not running: {e}")
+        return False
+
+
+def _timestamp():
+    """Get current timestamp for logging."""
+    return datetime.now().strftime("%H:%M:%S.%f")[:-3]
+
+
+async def test_generation_with_cached_model():
+    """
+    Test Case 1: Generation when model is already cached.
+    
+    This should NOT show any download progress events.
+    If it does, that's the UX bug we're trying to fix.
+    """
+    print("\n" + "=" * 80)
+    print("TEST CASE 1: Generation with Cached Model")
+    print("=" * 80)
+    print("Expected: No download progress events (or minimal/instant completion)")
+    print("Actual UX Issue: Users see 'started' and 'finished' events even for cached models")
+    print("=" * 80)
+
+    model_size = "1.7B"
+    model_name = f"qwen-tts-{model_size}"
+
+    # Get a profile
+    profile_id = await get_first_profile()
+    if not profile_id:
+        print("✗ No voice profiles found. Please create a profile first.")
+        return False
+
+    print(f"\nUsing profile: {profile_id}")
+
+    # Start SSE monitor BEFORE triggering generation
+    monitor_task = asyncio.create_task(monitor_sse_stream(model_name, timeout=30))
+
+    # Wait for SSE to connect
+    await asyncio.sleep(1)
+
+    # Trigger generation
+    test_text = "Hello, this is a test of the voice generation system."
+    success, result = await trigger_generation(profile_id, test_text, model_size)
+
+    if not success and result and result.get("downloading"):
+        print("\n⚠ Model is being downloaded. Waiting for download to complete...")
+        # Wait for SSE monitor to capture download events
+        events = await monitor_task
+        return events
+
+    # Wait a bit more to catch any progress events
+    await asyncio.sleep(3)
+
+    # Cancel SSE monitor
+    monitor_task.cancel()
+    try:
+        events = await monitor_task
+    except asyncio.CancelledError:
+        events = []
+
+    return events
+
+
+async def test_generation_with_fresh_download():
+    """
+    Test Case 2: Generation when model needs to be downloaded.
+    
+    This SHOULD show download progress events.
+    """
+    print("\n" + "=" * 80)
+    print("TEST CASE 2: Generation with Model Download")
+    print("=" * 80)
+    print("Expected: Download progress events from 0% to 100%")
+    print("=" * 80)
+
+    # Use a different model size to force download
+    model_size = "0.6B"  # Smaller model for faster testing
+    model_name = f"qwen-tts-{model_size}"
+
+    # Get a profile
+    profile_id = await get_first_profile()
+    if not profile_id:
+        print("✗ No voice profiles found. Please create a profile first.")
+        return False
+
+    print(f"\nUsing profile: {profile_id}")
+    print("Note: This will download the model if not cached")
+
+    # Start SSE monitor BEFORE triggering generation
+    monitor_task = asyncio.create_task(monitor_sse_stream(model_name, timeout=300))
+
+    # Wait for SSE to connect
+    await asyncio.sleep(1)
+
+    # Trigger generation
+    test_text = "This should trigger a model download if the model is not cached."
+    success, result = await trigger_generation(profile_id, test_text, model_size)
+
+    if not success and result and result.get("downloading"):
+        print("\n→ Model download initiated. Monitoring progress...")
+        # Wait for download to complete
+        events = await monitor_task
+
+        # Try generation again
+        print(f"\n[{_timestamp()}] Retrying generation after download...")
+        await asyncio.sleep(2)
+        success, result = await trigger_generation(profile_id, test_text, model_size)
+
+        if success:
+            print("✓ Generation successful after download")
+
+        return events
+
+    # If model was already cached
+    await asyncio.sleep(3)
+    monitor_task.cancel()
+    try:
+        events = await monitor_task
+    except asyncio.CancelledError:
+        events = []
+
+    return events
+
+
+async def main():
+    print("=" * 80)
+    print("TTS Generation Progress Test")
+    print("=" * 80)
+    print("Purpose: Capture exact SSE events during generation to identify UX issues")
+    print("=" * 80)
+
+    # Check if server is running
+    print(f"\n[{_timestamp()}] Checking if server is running...")
+    if not await check_server():
+        print("✗ Server is not running on http://localhost:8000")
+        print("\nPlease start the server first:")
+        print("  cd backend && python main.py")
+        return False
+
+    print("✓ Server is running")
+
+    # Test Case 1: Cached model
+    print("\n" + "🧪 " * 20)
+    events_cached = await test_generation_with_cached_model()
+
+    # Results for Test Case 1
+    print("\n" + "=" * 80)
+    print("TEST CASE 1 RESULTS: Generation with Cached Model")
+    print("=" * 80)
+
+    if not events_cached:
+        print("✓ GOOD: No SSE progress events received")
+        print("  This is the expected behavior for a cached model.")
+    else:
+        print(f"⚠ ISSUE FOUND: Received {len(events_cached)} SSE events:")
+        print("\nEvent Timeline:")
+        for i, event in enumerate(events_cached, 1):
+            timestamp = event.pop("_timestamp", "??:??:??.???")
+            print(f"  {i}. [{timestamp}] {event}")
+
+        print("\n⚠ This explains the UX issue!")
+        print("  Users see progress events even when the model is already cached,")
+        print("  making them think the model is downloading again.")
+
+    # Test Case 2: Fresh download (optional, commented out by default)
+    # Uncomment if you want to test download progress
+    # print("\n" + "🧪 " * 20)
+    # events_download = await test_generation_with_fresh_download()
+    #
+    # print("\n" + "=" * 80)
+    # print("TEST CASE 2 RESULTS: Generation with Model Download")
+    # print("=" * 80)
+    #
+    # if not events_download:
+    #     print("ℹ Model was already cached, no download occurred")
+    # else:
+    #     print(f"✓ Received {len(events_download)} download progress events")
+    #     print("\nDownload Timeline:")
+    #     for i, event in enumerate(events_download, 1):
+    #         timestamp = event.pop("_timestamp", "??:??:??.???")
+    #         print(f"  {i}. [{timestamp}] {event}")
+
+    print("\n" + "=" * 80)
+    print("Test Complete!")
+    print("=" * 80)
+
+    return True
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,313 @@
+"""
+Test script to debug model download progress tracking.
+"""
+
+import asyncio
+import json
+import time
+from typing import List, Dict
+import logging
+
+# Set up logging to see what's happening
+logging.basicConfig(
+    level=logging.DEBUG,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+)
+
+from utils.progress import ProgressManager, get_progress_manager
+from utils.hf_progress import HFProgressTracker, create_hf_progress_callback
+
+
+def test_progress_manager_basic():
+    """Test 1: Basic ProgressManager functionality."""
+    print("\n" + "=" * 60)
+    print("Test 1: ProgressManager Basic Operations")
+    print("=" * 60)
+
+    pm = ProgressManager()
+
+    # Test update_progress
+    pm.update_progress(
+        model_name="test-model",
+        current=50,
+        total=100,
+        filename="test.bin",
+        status="downloading"
+    )
+
+    # Test get_progress
+    progress = pm.get_progress("test-model")
+    print(f"✓ Progress stored: {progress}")
+    assert progress is not None
+    assert progress["progress"] == 50.0
+    assert progress["filename"] == "test.bin"
+    assert progress["status"] == "downloading"
+
+    # Test mark_complete
+    pm.mark_complete("test-model")
+    progress = pm.get_progress("test-model")
+    print(f"✓ Marked complete: {progress}")
+    assert progress["status"] == "complete"
+    assert progress["progress"] == 100.0
+
+    print("✓ Test 1 PASSED\n")
+    return True
+
+
+async def test_progress_manager_sse():
+    """Test 2: ProgressManager SSE streaming."""
+    print("\n" + "=" * 60)
+    print("Test 2: ProgressManager SSE Streaming")
+    print("=" * 60)
+
+    pm = ProgressManager()
+    collected_events: List[Dict] = []
+
+    # Simulate SSE client
+    async def sse_client():
+        """Simulates a frontend SSE connection."""
+        print("  SSE client: Subscribing to test-model-sse...")
+        async for event in pm.subscribe("test-model-sse"):
+            # Parse SSE event
+            if event.startswith("data: "):
+                data = json.loads(event[6:])
+                print(f"  SSE client: Received event: {data['status']} - {data.get('progress', 0):.1f}%")
+                collected_events.append(data)
+
+                # Stop when complete
+                if data.get("status") in ("complete", "error"):
+                    break
+            elif event.startswith(": heartbeat"):
+                print("  SSE client: Received heartbeat")
+
+    # Simulate download progress updates (from backend thread)
+    async def simulate_download():
+        """Simulates backend sending progress updates."""
+        print("  Backend: Starting simulated download...")
+        await asyncio.sleep(0.2)  # Let SSE client subscribe first
+
+        # Send progress updates
+        for i in range(0, 101, 20):
+            print(f"  Backend: Updating progress to {i}%")
+            pm.update_progress(
+                model_name="test-model-sse",
+                current=i,
+                total=100,
+                filename=f"file_{i}.bin",
+                status="downloading" if i < 100 else "downloading"
+            )
+            await asyncio.sleep(0.1)
+
+        # Mark complete
+        print("  Backend: Marking download complete")
+        pm.mark_complete("test-model-sse")
+
+    # Run SSE client and download simulation concurrently
+    await asyncio.gather(
+        sse_client(),
+        simulate_download()
+    )
+
+    # Verify we got events
+    print(f"\n  Collected {len(collected_events)} events")
+    assert len(collected_events) > 0, "Should have received at least one event"
+    assert collected_events[-1]["status"] == "complete", "Last event should be 'complete'"
+
+    print("✓ Test 2 PASSED\n")
+    return True
+
+
+def test_hf_progress_tracker():
+    """Test 3: HFProgressTracker tqdm patching."""
+    print("\n" + "=" * 60)
+    print("Test 3: HFProgressTracker tqdm Patching")
+    print("=" * 60)
+
+    captured_progress: List[tuple] = []
+
+    def progress_callback(downloaded: int, total: int, filename: str):
+        """Capture progress updates."""
+        captured_progress.append((downloaded, total, filename))
+        print(f"  Progress callback: {downloaded}/{total} bytes ({filename})")
+
+    tracker = HFProgressTracker(progress_callback)
+
+    # Simulate a download with tqdm
+    with tracker.patch_download():
+        try:
+            from tqdm import tqdm
+
+            # Simulate downloading a file
+            print("  Simulating download with tqdm...")
+            total_size = 1000
+            with tqdm(total=total_size, desc="model.bin", unit="B", unit_scale=True) as pbar:
+                for chunk in range(0, total_size, 100):
+                    pbar.update(100)
+                    time.sleep(0.01)
+
+            print(f"  Captured {len(captured_progress)} progress updates")
+            assert len(captured_progress) > 0, "Should have captured progress updates"
+
+            # Verify progress increases
+            last_downloaded = 0
+            for downloaded, total, filename in captured_progress:
+                assert downloaded >= last_downloaded, "Downloaded bytes should increase"
+                assert total == total_size, "Total should be consistent"
+                last_downloaded = downloaded
+
+            print("✓ Test 3 PASSED\n")
+            return True
+
+        except ImportError:
+            print("✗ tqdm not available, skipping test\n")
+            return None
+
+
+async def test_full_integration():
+    """Test 4: Full integration test."""
+    print("\n" + "=" * 60)
+    print("Test 4: Full Integration (ProgressManager + HFProgressTracker)")
+    print("=" * 60)
+
+    pm = get_progress_manager()
+    collected_events: List[Dict] = []
+
+    # SSE client
+    async def sse_client():
+        print("  SSE client: Subscribing...")
+        async for event in pm.subscribe("integration-test"):
+            if event.startswith("data: "):
+                data = json.loads(event[6:])
+                print(f"  SSE client: {data['status']} - {data.get('progress', 0):.1f}% - {data.get('filename', '')}")
+                collected_events.append(data)
+                if data.get("status") in ("complete", "error"):
+                    break
+
+    # Simulate backend download with HFProgressTracker
+    async def simulate_real_download():
+        await asyncio.sleep(0.2)  # Let SSE subscribe
+
+        print("  Backend: Starting download with HFProgressTracker...")
+
+        # Set up tracking (like the real backend does)
+        progress_callback = create_hf_progress_callback("integration-test", pm)
+        tracker = HFProgressTracker(progress_callback)
+
+        # Initialize progress
+        pm.update_progress(
+            model_name="integration-test",
+            current=0,
+            total=1,
+            filename="",
+            status="downloading"
+        )
+
+        # Simulate download with tqdm patching
+        with tracker.patch_download():
+            try:
+                from tqdm import tqdm
+
+                # Simulate multi-file download (like HuggingFace does)
+                files = [
+                    ("model.safetensors", 5000),
+                    ("config.json", 1000),
+                    ("tokenizer.json", 500),
+                ]
+
+                for filename, size in files:
+                    print(f"  Backend: Downloading {filename}...")
+                    with tqdm(total=size, desc=filename, unit="B") as pbar:
+                        for chunk in range(0, size, 500):
+                            chunk_size = min(500, size - chunk)
+                            pbar.update(chunk_size)
+                            await asyncio.sleep(0.05)
+
+                # Mark complete
+                print("  Backend: Download complete")
+                pm.mark_complete("integration-test")
+
+            except ImportError:
+                print("  ✗ tqdm not available")
+                pm.mark_error("integration-test", "tqdm not available")
+
+    # Run both
+    await asyncio.gather(
+        sse_client(),
+        simulate_real_download()
+    )
+
+    # Verify
+    print(f"\n  Collected {len(collected_events)} events")
+    if len(collected_events) > 0:
+        print(f"  First event: {collected_events[0]}")
+        print(f"  Last event: {collected_events[-1]}")
+        assert collected_events[-1]["status"] == "complete", "Should end with 'complete'"
+        print("✓ Test 4 PASSED\n")
+        return True
+    else:
+        print("✗ Test 4 FAILED - No events received\n")
+        return False
+
+
+async def main():
+    """Run all tests."""
+    print("\n" + "=" * 60)
+    print("Voicebox Progress Tracking Test Suite")
+    print("=" * 60)
+
+    results = []
+
+    # Test 1: Basic operations
+    try:
+        results.append(("Basic Operations", test_progress_manager_basic()))
+    except Exception as e:
+        print(f"✗ Test 1 FAILED: {e}\n")
+        results.append(("Basic Operations", False))
+
+    # Test 2: SSE streaming
+    try:
+        results.append(("SSE Streaming", await test_progress_manager_sse()))
+    except Exception as e:
+        print(f"✗ Test 2 FAILED: {e}\n")
+        results.append(("SSE Streaming", False))
+
+    # Test 3: tqdm patching
+    try:
+        results.append(("tqdm Patching", test_hf_progress_tracker()))
+    except Exception as e:
+        print(f"✗ Test 3 FAILED: {e}\n")
+        results.append(("tqdm Patching", False))
+
+    # Test 4: Full integration
+    try:
+        results.append(("Full Integration", await test_full_integration()))
+    except Exception as e:
+        print(f"✗ Test 4 FAILED: {e}\n")
+        results.append(("Full Integration", False))
+
+    # Summary
+    print("\n" + "=" * 60)
+    print("Test Results Summary")
+    print("=" * 60)
+
+    for name, result in results:
+        status = "✓ PASS" if result else ("⊘ SKIP" if result is None else "✗ FAIL")
+        print(f"  {status:8} {name}")
+
+    passed = sum(1 for _, r in results if r is True)
+    failed = sum(1 for _, r in results if r is False)
+    skipped = sum(1 for _, r in results if r is None)
+
+    print()
+    print(f"  Total: {len(results)} tests")
+    print(f"  Passed: {passed}")
+    print(f"  Failed: {failed}")
+    print(f"  Skipped: {skipped}")
+    print("=" * 60 + "\n")
+
+    return failed == 0
+
+
+if __name__ == "__main__":
+    success = asyncio.run(main())
+    exit(0 if success else 1)
@@ -0,0 +1,317 @@
+"""
+Test Qwen TTS model download with SSE progress monitoring.
+
+This specifically tests the MLX TTS backend download progress tracking,
+which requires tqdm to be patched BEFORE mlx_audio is imported.
+
+Usage:
+    cd backend && python -m tests.test_qwen_download
+
+Prerequisites:
+    - Server must be running: cd backend && python main.py
+    - Delete model first for fresh download test:
+      curl -X DELETE http://localhost:8000/models/qwen-tts-0.6B
+"""
+
+import asyncio
+import json
+import httpx
+import time
+from typing import List, Dict, Optional
+
+
+async def monitor_sse_stream(model_name: str, timeout: int = 600) -> List[Dict]:
+    """
+    Monitor SSE stream for a model download.
+    
+    Args:
+        model_name: Name of the model to monitor
+        timeout: Maximum time to wait for download (seconds)
+        
+    Returns:
+        List of SSE events received
+    """
+    events: List[Dict] = []
+    url = f"http://localhost:8000/models/progress/{model_name}"
+    last_progress = -1
+    
+    print(f"\n📡 Connecting to SSE endpoint: {url}")
+
+    try:
+        async with httpx.AsyncClient(timeout=timeout) as client:
+            async with client.stream("GET", url) as response:
+                print(f"   SSE connected, status: {response.status_code}")
+
+                if response.status_code != 200:
+                    print(f"   ❌ Error: SSE endpoint returned {response.status_code}")
+                    return events
+
+                async for line in response.aiter_lines():
+                    if not line:
+                        continue
+
+                    if line.startswith("data: "):
+                        try:
+                            data = json.loads(line[6:])
+                            events.append(data)
+                            
+                            # Print progress (only when it changes significantly)
+                            progress = data.get('progress', 0)
+                            status = data.get('status', 'unknown')
+                            filename = data.get('filename', '')
+                            current = data.get('current', 0)
+                            total = data.get('total', 0)
+                            
+                            # Print every 5% change or status change
+                            if abs(progress - last_progress) >= 5 or status in ('complete', 'error'):
+                                current_mb = current / (1024 * 1024)
+                                total_mb = total / (1024 * 1024)
+                                print(f"   📊 {status:12} {progress:6.1f}% ({current_mb:.1f}MB / {total_mb:.1f}MB) {filename[:50]}")
+                                last_progress = progress
+
+                            # Stop if complete or error
+                            if status in ("complete", "error"):
+                                if status == "complete":
+                                    print(f"   ✅ Download complete!")
+                                else:
+                                    print(f"   ❌ Download error: {data.get('error', 'unknown')}")
+                                break
+
+                        except json.JSONDecodeError as e:
+                            print(f"   ⚠️  Error parsing JSON: {e}")
+
+                    elif line.startswith(": heartbeat"):
+                        # Heartbeat every 1 second, don't spam
+                        pass
+
+    except asyncio.CancelledError:
+        print("   ⏹️  SSE monitor cancelled")
+    except Exception as e:
+        print(f"   ❌ SSE error: {e}")
+
+    return events
+
+
+async def trigger_download(model_name: str) -> bool:
+    """Trigger a model download via the API."""
+    url = "http://localhost:8000/models/download"
+
+    print(f"\n🚀 Triggering download for: {model_name}")
+
+    try:
+        async with httpx.AsyncClient(timeout=30) as client:
+            response = await client.post(url, json={"model_name": model_name})
+            result = response.json()
+            print(f"   Response: {response.status_code} - {result}")
+            return response.status_code == 200
+    except Exception as e:
+        print(f"   ❌ Error triggering download: {e}")
+        return False
+
+
+async def delete_model(model_name: str) -> bool:
+    """Delete a model from cache."""
+    url = f"http://localhost:8000/models/{model_name}"
+
+    print(f"\n🗑️  Deleting model: {model_name}")
+
+    try:
+        async with httpx.AsyncClient(timeout=30) as client:
+            response = await client.delete(url)
+            if response.status_code == 200:
+                print(f"   ✅ Model deleted")
+                return True
+            elif response.status_code == 404:
+                print(f"   ℹ️  Model not found (already deleted)")
+                return True
+            else:
+                print(f"   ⚠️  Delete response: {response.status_code} - {response.text}")
+                return False
+    except Exception as e:
+        print(f"   ❌ Error deleting model: {e}")
+        return False
+
+
+async def check_model_status(model_name: str) -> Optional[Dict]:
+    """Check the status of a model."""
+    try:
+        async with httpx.AsyncClient(timeout=10) as client:
+            response = await client.get("http://localhost:8000/models/status")
+            if response.status_code == 200:
+                data = response.json()
+                for model in data.get("models", []):
+                    if model["model_name"] == model_name:
+                        return model
+    except Exception as e:
+        print(f"   ⚠️  Error checking model status: {e}")
+    return None
+
+
+async def check_server() -> bool:
+    """Check if the server is running."""
+    try:
+        async with httpx.AsyncClient(timeout=5) as client:
+            response = await client.get("http://localhost:8000/health")
+            return response.status_code == 200
+    except Exception:
+        return False
+
+
+async def main():
+    print("=" * 70)
+    print("🧪 Qwen TTS Model Download Progress Test")
+    print("=" * 70)
+    print("\nThis test verifies that MLX TTS download progress tracking works.")
+    print("It specifically tests the tqdm patching for mlx_audio.tts imports.")
+
+    # Check if server is running
+    print("\n📡 Checking if server is running...")
+    if not await check_server():
+        print("   ❌ Server is not running on http://localhost:8000")
+        print("\n   Please start the server first:")
+        print("   cd backend && python main.py")
+        return False
+
+    print("   ✅ Server is running")
+
+    # Test model
+    model_name = "qwen-tts-0.6B"  # Note: 0.6B currently maps to 1.7B on MLX
+    
+    # Check current status
+    print(f"\n📊 Checking status of {model_name}...")
+    status = await check_model_status(model_name)
+    if status:
+        print(f"   Downloaded: {status.get('downloaded', False)}")
+        print(f"   Downloading: {status.get('downloading', False)}")
+        print(f"   Loaded: {status.get('loaded', False)}")
+        if status.get('size_mb'):
+            print(f"   Size: {status['size_mb']:.1f} MB")
+    else:
+        print("   ⚠️  Could not get model status")
+
+    # Ask if user wants to delete first
+    print("\n" + "-" * 70)
+    if status and status.get('downloaded'):
+        print("⚠️  Model is already downloaded. Delete it for a fresh download test?")
+        print("   [y] Yes, delete and download fresh")
+        print("   [n] No, just test SSE connection")
+        print("   [q] Quit")
+        
+        choice = input("\nChoice [y/n/q]: ").strip().lower()
+        
+        if choice == 'q':
+            print("Exiting...")
+            return True
+        
+        if choice == 'y':
+            if not await delete_model(model_name):
+                print("Failed to delete model. Continue anyway? [y/n]")
+                if input().strip().lower() != 'y':
+                    return False
+    else:
+        print("Model not downloaded. Will perform fresh download test.")
+        input("Press Enter to continue...")
+
+    # Run the test
+    print("\n" + "=" * 70)
+    print("🏃 Starting Download Test")
+    print("=" * 70)
+
+    async def run_test():
+        # Start SSE monitor in background FIRST
+        monitor_task = asyncio.create_task(monitor_sse_stream(model_name, timeout=600))
+
+        # Wait for SSE to connect
+        await asyncio.sleep(1)
+
+        # Trigger download
+        success = await trigger_download(model_name)
+
+        if not success:
+            print("   ❌ Failed to trigger download")
+            monitor_task.cancel()
+            try:
+                await monitor_task
+            except asyncio.CancelledError:
+                pass
+            return []
+
+        # Wait for SSE monitor to complete
+        print("\n⏳ Waiting for download to complete (this may take several minutes)...")
+        events = await monitor_task
+
+        return events
+
+    start_time = time.time()
+    events = await run_test()
+    elapsed = time.time() - start_time
+
+    # Results
+    print("\n" + "=" * 70)
+    print("📋 Test Results")
+    print("=" * 70)
+
+    print(f"\n⏱️  Elapsed time: {elapsed:.1f} seconds")
+    print(f"📨 Total SSE events received: {len(events)}")
+
+    if not events:
+        print("\n❌ FAILED - No SSE events received!")
+        print("\nPossible causes:")
+        print("  1. SSE endpoint not working")
+        print("  2. tqdm not patched before mlx_audio import")
+        print("  3. Progress callbacks not firing")
+        print("  4. Model already fully downloaded")
+        print("\nDebug steps:")
+        print("  1. Check server logs for [DEBUG] messages")
+        print("  2. Look for 'tqdm patched' before 'mlx_audio.tts import'")
+        print(f"  3. Delete model: curl -X DELETE http://localhost:8000/models/{model_name}")
+        return False
+
+    # Analyze events
+    first_event = events[0]
+    last_event = events[-1]
+    
+    print(f"\n📊 First event:")
+    print(f"   Status: {first_event.get('status')}")
+    print(f"   Progress: {first_event.get('progress', 0):.1f}%")
+    
+    print(f"\n📊 Last event:")
+    print(f"   Status: {last_event.get('status')}")
+    print(f"   Progress: {last_event.get('progress', 0):.1f}%")
+
+    # Check for expected behaviors
+    has_progress_updates = len(events) > 2
+    has_increasing_progress = False
+    has_complete = any(e.get('status') == 'complete' for e in events)
+    has_100_percent = any(e.get('progress', 0) >= 100 for e in events)
+    
+    # Check if progress increased over time
+    if len(events) >= 2:
+        progress_values = [e.get('progress', 0) for e in events]
+        has_increasing_progress = progress_values[-1] > progress_values[0]
+
+    print("\n📋 Checks:")
+    print(f"   {'✅' if has_progress_updates else '❌'} Multiple progress updates received ({len(events)} events)")
+    print(f"   {'✅' if has_increasing_progress else '❌'} Progress increased over time")
+    print(f"   {'✅' if has_100_percent else '❌'} Reached 100% progress")
+    print(f"   {'✅' if has_complete else '❌'} Received 'complete' status")
+
+    # Overall result
+    success = has_progress_updates and has_complete
+    
+    if success:
+        print("\n" + "=" * 70)
+        print("✅ TEST PASSED - Qwen TTS download progress tracking works!")
+        print("=" * 70)
+    else:
+        print("\n" + "=" * 70)
+        print("❌ TEST FAILED - Progress tracking has issues")
+        print("=" * 70)
+        print("\nCheck the server logs for debug output.")
+
+    return success
+
+
+if __name__ == "__main__":
+    result = asyncio.run(main())
+    exit(0 if result else 1)
@@ -0,0 +1,178 @@
+"""
+Test real model download with SSE progress monitoring.
+"""
+
+import asyncio
+import json
+import httpx
+import time
+from typing import List, Dict
+
+async def monitor_sse_stream(model_name: str, timeout: int = 300):
+    """Monitor SSE stream for a model download."""
+    events: List[Dict] = []
+    url = f"http://localhost:8000/models/progress/{model_name}"
+
+    print(f"Connecting to SSE endpoint: {url}")
+
+    async with httpx.AsyncClient(timeout=timeout) as client:
+        async with client.stream("GET", url) as response:
+            print(f"SSE connected, status: {response.status_code}")
+
+            if response.status_code != 200:
+                print(f"Error: SSE endpoint returned {response.status_code}")
+                return events
+
+            async for line in response.aiter_lines():
+                if not line:
+                    continue
+
+                print(f"  Raw SSE: {line[:100]}...")  # Print first 100 chars
+
+                if line.startswith("data: "):
+                    try:
+                        data = json.loads(line[6:])
+                        print(f"  → {data['status']:12} {data.get('progress', 0):6.1f}% {data.get('filename', '')}")
+                        events.append(data)
+
+                        # Stop if complete or error
+                        if data.get("status") in ("complete", "error"):
+                            print(f"  Download {data['status']}!")
+                            break
+
+                    except json.JSONDecodeError as e:
+                        print(f"  Error parsing JSON: {e}")
+                        print(f"  Line was: {line}")
+
+                elif line.startswith(": heartbeat"):
+                    print("  ♥ heartbeat")
+
+    return events
+
+
+async def trigger_download(model_name: str):
+    """Trigger a model download via the API."""
+    url = "http://localhost:8000/models/download"
+
+    print(f"\nTriggering download for: {model_name}")
+
+    async with httpx.AsyncClient(timeout=300) as client:
+        response = await client.post(url, json={"model_name": model_name})
+        print(f"Response: {response.status_code} - {response.json()}")
+        return response.status_code == 200
+
+
+async def check_server():
+    """Check if the server is running."""
+    try:
+        async with httpx.AsyncClient(timeout=5) as client:
+            response = await client.get("http://localhost:8000/health")
+            return response.status_code == 200
+    except Exception as e:
+        print(f"Server not running: {e}")
+        return False
+
+
+async def main():
+    print("=" * 60)
+    print("Real Model Download Progress Test")
+    print("=" * 60)
+
+    # Check if server is running
+    print("\nChecking if server is running...")
+    if not await check_server():
+        print("✗ Server is not running on http://localhost:8000")
+        print("\nPlease start the server first:")
+        print("  cd backend && python main.py")
+        return False
+
+    print("✓ Server is running")
+
+    # Choose a small model for testing
+    model_name = "whisper-base"  # ~150MB, faster to download
+    print(f"\nUsing model: {model_name}")
+
+    # Option to delete model first if it exists
+    print("\nDo you want to delete the model first to force a fresh download? (y/n)")
+    # For automated testing, skip deletion prompt
+    # delete_first = input().strip().lower() == 'y'
+    delete_first = False
+
+    if delete_first:
+        print(f"Deleting {model_name}...")
+        async with httpx.AsyncClient(timeout=30) as client:
+            response = await client.delete(f"http://localhost:8000/models/{model_name}")
+            print(f"Delete response: {response.status_code}")
+
+    print("\n" + "=" * 60)
+    print("Starting Test")
+    print("=" * 60)
+
+    # Start monitoring SSE stream BEFORE triggering download
+    async def run_test():
+        # Start SSE monitor in background
+        monitor_task = asyncio.create_task(monitor_sse_stream(model_name))
+
+        # Wait a bit to ensure SSE is connected
+        await asyncio.sleep(1)
+
+        # Trigger download
+        success = await trigger_download(model_name)
+
+        if not success:
+            print("✗ Failed to trigger download")
+            monitor_task.cancel()
+            return False
+
+        # Wait for SSE monitor to complete
+        events = await monitor_task
+
+        return events
+
+    events = await run_test()
+
+    # Results
+    print("\n" + "=" * 60)
+    print("Test Results")
+    print("=" * 60)
+
+    if not events:
+        print("✗ FAILED - No SSE events received!")
+        print("\nPossible causes:")
+        print("  1. SSE endpoint not working")
+        print("  2. Progress updates not being sent")
+        print("  3. Model already downloaded (no progress to report)")
+        print("\nTry deleting the model first to force a fresh download:")
+        print(f"  curl -X DELETE http://localhost:8000/models/{model_name}")
+        return False
+
+    print(f"✓ Received {len(events)} SSE events")
+    print(f"\nFirst event: {events[0]}")
+    print(f"Last event: {events[-1]}")
+
+    # Check if we got meaningful progress
+    has_progress = any(e.get('progress', 0) > 0 for e in events)
+    has_complete = any(e.get('status') == 'complete' for e in events)
+
+    if has_progress:
+        print("✓ Progress updates received")
+    else:
+        print("✗ No progress updates (might be already downloaded)")
+
+    if has_complete:
+        print("✓ Download completed successfully")
+    else:
+        print("✗ Download did not complete")
+
+    success = has_progress and has_complete
+
+    if success:
+        print("\n✓ TEST PASSED - Progress tracking works!")
+    else:
+        print("\n⊘ TEST INCONCLUSIVE - Try with a fresh download")
+
+    return success
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -1,5 +1,5 @@
 """
-TTS inference module - delegates to backend abstraction layer.
+TTS inference module - delegates to provider abstraction layer.
 """

 from typing import Optional
@@ -7,31 +7,51 @@ import numpy as np
 import io
 import soundfile as sf

-from .backends import get_tts_backend, TTSBackend
+from .backends import TTSBackend
+from .providers import get_provider_manager
+from .providers.base import TTSProvider


-def get_tts_model() -> TTSBackend:
+def get_tts_model() -> TTSProvider:
    """
-    Get TTS backend instance (MLX or PyTorch based on platform).
+    Get TTS provider instance (via ProviderManager).
    
    Returns:
-        TTS backend instance
+        TTS provider instance
    """
-    return get_tts_backend()
+    manager = get_provider_manager()
+    # Note: This is async but we need sync interface for backward compatibility
+    # In practice, this will be called from async contexts
+    import asyncio
+    try:
+        loop = asyncio.get_event_loop()
+        if loop.is_running():
+            # We're in an async context, but can't await here
+            # Return a wrapper that will use the provider manager
+            return manager._get_default_provider()
+        else:
+            return loop.run_until_complete(manager.get_active_provider())
+    except RuntimeError:
+        # No event loop, return default
+        return manager._get_default_provider()
+
+
+async def get_tts_model_async() -> TTSProvider:
+    """
+    Get TTS provider instance asynchronously.
+    
+    Returns:
+        TTS provider instance
+    """
+    manager = get_provider_manager()
+    return await manager.get_active_provider()


 def unload_tts_model():
    """Unload TTS model to free memory."""
-    backend = get_tts_backend()
-    backend.unload_model()
-
-
-def audio_to_wav_bytes(audio: np.ndarray, sample_rate: int) -> bytes:
-    """Convert audio array to WAV bytes."""
-    buffer = io.BytesIO()
-    sf.write(buffer, audio, sample_rate, format="WAV")
-    buffer.seek(0)
-    return buffer.read()
+    manager = get_provider_manager()
+    provider = manager._get_default_provider()
+    provider.unload_model()


 def audio_to_wav_bytes(audio: np.ndarray, sample_rate: int) -> bytes:
@@ -88,3 +88,63 @@ def cache_voice_prompt(
    # Store on disk (torch.save can handle both dicts and tensors)
    cache_file = _get_cache_dir() / f"{cache_key}.prompt"
    torch.save(voice_prompt, cache_file)
+
+
+def clear_voice_prompt_cache() -> int:
+    """
+    Clear all voice prompt caches (memory and disk).
+    
+    Returns:
+        Number of cache files deleted
+    """
+    # Clear memory cache
+    _memory_cache.clear()
+    
+    # Clear disk cache
+    cache_dir = _get_cache_dir()
+    deleted_count = 0
+    
+    if cache_dir.exists():
+        # Delete prompt cache files
+        for cache_file in cache_dir.glob("*.prompt"):
+            try:
+                cache_file.unlink()
+                deleted_count += 1
+            except Exception as e:
+                print(f"Failed to delete cache file {cache_file}: {e}")
+        
+        # Delete combined audio files
+        for audio_file in cache_dir.glob("combined_*.wav"):
+            try:
+                audio_file.unlink()
+                deleted_count += 1
+            except Exception as e:
+                print(f"Failed to delete combined audio file {audio_file}: {e}")
+    
+    return deleted_count
+
+
+def clear_profile_cache(profile_id: str) -> int:
+    """
+    Clear cache files for a specific profile.
+    
+    Args:
+        profile_id: Profile ID
+    
+    Returns:
+        Number of cache files deleted
+    """
+    cache_dir = _get_cache_dir()
+    deleted_count = 0
+    
+    if cache_dir.exists():
+        # Delete combined audio files for this profile
+        pattern = f"combined_{profile_id}_*.wav"
+        for audio_file in cache_dir.glob(pattern):
+            try:
+                audio_file.unlink()
+                deleted_count += 1
+            except Exception as e:
+                print(f"Failed to delete combined audio file {audio_file}: {e}")
+    
+    return deleted_count
@@ -11,8 +11,9 @@ import sys
 class HFProgressTracker:
    """Tracks HuggingFace Hub download progress by intercepting tqdm."""
    
-    def __init__(self, progress_callback: Optional[Callable] = None):
+    def __init__(self, progress_callback: Optional[Callable] = None, filter_non_downloads: bool = False):
        self.progress_callback = progress_callback
+        self.filter_non_downloads = filter_non_downloads  # Only filter if True
        self._original_tqdm_class = None
        self._lock = threading.Lock()
        self._total_downloaded = 0
@@ -21,6 +22,7 @@ class HFProgressTracker:
        self._file_downloaded = {}  # Track downloaded bytes per file
        self._current_filename = ""
        self._active_tqdms = {}  # Track active tqdm instances
+        self._hf_tqdm_original_update = None  # For monkey-patching hf's tqdm
    
    def _create_tracked_tqdm_class(self):
        """Create a tqdm subclass that tracks progress."""
@@ -29,7 +31,7 @@ class HFProgressTracker:
        
        class TrackedTqdm(original_tqdm):
            """A tqdm subclass that reports progress to our tracker."""
-            
+
            def __init__(self, *args, **kwargs):
                # Extract filename from desc before passing to parent
                desc = kwargs.get("desc", "")
@@ -80,7 +82,7 @@ class HFProgressTracker:
            
            def update(self, n=1):
                result = super().update(n)
-                
+
                # Report progress
                with tracker._lock:
                    if id(self) in tracker._active_tqdms:
@@ -89,6 +91,16 @@ class HFProgressTracker:
                        total = getattr(self, "total", 0)
                        
                        if total and total > 0:
+                            # Always filter out non-byte progress bars (e.g., "Fetching 12 files")
+                            # These cause crazy percentages because they're counting files, not bytes
+                            if self._is_non_byte_progress(filename):
+                                return result
+                            
+                            # When model is cached, also filter out generation-related progress
+                            if tracker.filter_non_downloads:
+                                if not self._is_download_progress(filename):
+                                    return result
+                            
                            # Update per-file tracking
                            tracker._file_sizes[filename] = total
                            tracker._file_downloaded[filename] = current
@@ -97,6 +109,13 @@ class HFProgressTracker:
                            tracker._total_size = sum(tracker._file_sizes.values())
                            tracker._total_downloaded = sum(tracker._file_downloaded.values())
                            
+                            # Only report progress once we have a meaningful total (at least 1MB)
+                            # This avoids the "100% at 0MB" issue when small config
+                            # files are counted before the real model files
+                            MIN_TOTAL_BYTES = 1_000_000  # 1MB
+                            if tracker._total_size < MIN_TOTAL_BYTES:
+                                return result
+                            
                            # Call progress callback
                            if tracker.progress_callback:
                                tracker.progress_callback(
@@ -107,6 +126,50 @@ class HFProgressTracker:
                
                return result
            
+            def _is_non_byte_progress(self, filename: str) -> bool:
+                """Check if this progress bar should be SKIPPED (returns True to skip).
+                
+                We want to track byte-based progress bars. This method identifies
+                progress bars that count files/items instead of bytes, which would
+                cause crazy percentages if mixed with our byte counting.
+                
+                Returns:
+                    True = SKIP this bar (it's not byte-based)
+                    False = TRACK this bar (it counts bytes)
+                """
+                if not filename:
+                    return False
+                
+                filename_lower = filename.lower()
+                
+                # Skip "Fetching X files" - it counts files (total=12), not bytes
+                # Don't skip "Downloading (incomplete total...)" - that IS byte-based
+                skip_patterns = [
+                    'fetching',  # "Fetching 12 files" has total=12 files, not bytes
+                ]
+                return any(pattern in filename_lower for pattern in skip_patterns)
+            
+            def _is_download_progress(self, filename: str) -> bool:
+                """Check if this is a real file download progress bar vs internal processing."""
+                if not filename or filename == "unknown":
+                    return False
+                
+                # Real downloads have file extensions
+                download_extensions = [
+                    '.safetensors', '.bin', '.pt', '.pth',  # Model weights
+                    '.json', '.txt', '.py',  # Config files
+                    '.msgpack', '.h5',  # Other formats
+                ]
+                
+                filename_lower = filename.lower()
+                has_extension = any(filename_lower.endswith(ext) for ext in download_extensions)
+                
+                # Skip generation-related progress indicators
+                skip_patterns = ['segment', 'processing', 'generating', 'loading']
+                has_skip_pattern = any(pattern in filename_lower for pattern in skip_patterns)
+                
+                return has_extension and not has_skip_pattern
+            
            def close(self):
                with tracker._lock:
                    if id(self) in tracker._active_tqdms:
@@ -120,7 +183,7 @@ class HFProgressTracker:
        """Context manager to patch tqdm for progress tracking."""
        try:
            import tqdm as tqdm_module
-            
+
            # Store original tqdm class
            self._original_tqdm_class = tqdm_module.tqdm
            
@@ -135,10 +198,10 @@ class HFProgressTracker:
            
            # Create our tracked tqdm class
            tracked_tqdm = self._create_tracked_tqdm_class()
-            
+
            # Patch tqdm.tqdm
            tqdm_module.tqdm = tracked_tqdm
-            
+
            # Also patch tqdm.auto.tqdm if it exists (used by huggingface_hub)
            self._original_tqdm_auto = None
            if hasattr(tqdm_module, "auto") and hasattr(tqdm_module.auto, "tqdm"):
@@ -146,22 +209,79 @@ class HFProgressTracker:
                tqdm_module.auto.tqdm = tracked_tqdm
            
            # Patch in sys.modules to catch already-imported references
+            # huggingface_hub uses: from tqdm.auto import tqdm as base_tqdm
+            # So we need to patch both 'tqdm' and 'base_tqdm' attributes
            self._patched_modules = {}
+            tqdm_attr_names = ['tqdm', 'base_tqdm', 'old_tqdm']  # Various names used
+            
+            patched_count = 0
            for module_name in list(sys.modules.keys()):
                if "huggingface" in module_name or module_name.startswith("tqdm"):
                    try:
                        module = sys.modules[module_name]
-                        if hasattr(module, "tqdm"):
-                            attr = getattr(module, "tqdm")
-                            # Only patch if it's the original tqdm class (not already patched)
-                            if attr is self._original_tqdm_class or (
-                                hasattr(attr, "__name__") and attr.__name__ == "tqdm"
-                            ):
-                                self._patched_modules[module_name] = attr
-                                setattr(module, "tqdm", tracked_tqdm)
+                        for attr_name in tqdm_attr_names:
+                            if hasattr(module, attr_name):
+                                attr = getattr(module, attr_name)
+                                # Only patch if it's a tqdm class (not already patched)
+                                is_tqdm_class = (
+                                    attr is self._original_tqdm_class or 
+                                    (self._original_tqdm_auto and attr is self._original_tqdm_auto) or
+                                    (hasattr(attr, "__name__") and attr.__name__ == "tqdm" and 
+                                     hasattr(attr, "update"))  # tqdm classes have update method
+                                )
+                                if is_tqdm_class:
+                                    key = f"{module_name}.{attr_name}"
+                                    self._patched_modules[key] = (module, attr_name, attr)
+                                    setattr(module, attr_name, tracked_tqdm)
+                                    patched_count += 1
                    except (AttributeError, TypeError):
                        pass
            
+            # ALSO monkey-patch the update method on huggingface_hub's tqdm class
+            # This is needed because the class was already defined at import time
+            self._hf_tqdm_original_update = None
+            try:
+                from huggingface_hub.utils import tqdm as hf_tqdm_module
+                if hasattr(hf_tqdm_module, 'tqdm'):
+                    hf_tqdm_class = hf_tqdm_module.tqdm
+                    self._hf_tqdm_original_update = hf_tqdm_class.update
+                    
+                    # Create a wrapper that calls our tracking
+                    tracker = self  # Reference to HFProgressTracker instance
+                    def patched_update(tqdm_self, n=1):
+                        result = tracker._hf_tqdm_original_update(tqdm_self, n)
+                        
+                        # Track this progress
+                        with tracker._lock:
+                            desc = getattr(tqdm_self, 'desc', '') or ''
+                            current = getattr(tqdm_self, 'n', 0)
+                            total = getattr(tqdm_self, 'total', 0) or 0
+                            
+                            # Skip non-byte progress bars
+                            if 'fetching' in desc.lower():
+                                return result
+                            
+                            # Skip until we have a meaningful total (at least 1MB)
+                            # This avoids the "100% at 0MB" issue when small config
+                            # files are counted before the real model files
+                            MIN_TOTAL_BYTES = 1_000_000  # 1MB
+                            if total >= MIN_TOTAL_BYTES:
+                                tracker._total_downloaded = current
+                                tracker._total_size = total
+                                
+                                if tracker.progress_callback:
+                                    tracker.progress_callback(current, total, desc)
+                        
+                        return result
+                    
+                    hf_tqdm_class.update = patched_update
+                    patched_count += 1
+                    print(f"[HFProgressTracker] Monkey-patched huggingface_hub.utils.tqdm.tqdm.update")
+            except (ImportError, AttributeError) as e:
+                print(f"[HFProgressTracker] Could not monkey-patch hf_tqdm: {e}")
+            
+            print(f"[HFProgressTracker] Patched {patched_count} tqdm references")
+            
            yield
            
        except ImportError:
@@ -178,15 +298,24 @@ class HFProgressTracker:
                        tqdm_module.auto.tqdm = self._original_tqdm_auto
                    
                    # Restore patched modules
-                    for module_name, original in self._patched_modules.items():
+                    for key, (module, attr_name, original) in self._patched_modules.items():
                        try:
-                            module = sys.modules.get(module_name)
                            if module and original:
-                                setattr(module, "tqdm", original)
+                                setattr(module, attr_name, original)
                        except (AttributeError, TypeError):
                            pass
                    self._patched_modules = {}
                    
+                    # Restore hf_tqdm's original update method
+                    if self._hf_tqdm_original_update:
+                        try:
+                            from huggingface_hub.utils import tqdm as hf_tqdm_module
+                            if hasattr(hf_tqdm_module, 'tqdm'):
+                                hf_tqdm_module.tqdm.update = self._hf_tqdm_original_update
+                        except (ImportError, AttributeError):
+                            pass
+                        self._hf_tqdm_original_update = None
+                    
                except (ImportError, AttributeError):
                    pass

@@ -194,13 +323,17 @@ class HFProgressTracker:
 def create_hf_progress_callback(model_name: str, progress_manager):
    """Create a progress callback for HuggingFace downloads."""
    def callback(downloaded: int, total: int, filename: str = ""):
-        """Progress callback."""
-        if total > 0:
-            progress_manager.update_progress(
-                model_name=model_name,
-                current=downloaded,
-                total=total,
-                filename=filename or "",
-                status="downloading",
-            )
+        """Progress callback.
+        
+        Note: We send updates even when total=0 (unknown) to provide feedback
+        during the "incomplete total" phase of huggingface_hub downloads.
+        The frontend handles total=0 gracefully.
+        """
+        progress_manager.update_progress(
+            model_name=model_name,
+            current=downloaded,
+            total=total,
+            filename=filename or "",
+            status="downloading",
+        )
    return callback
@@ -16,11 +16,17 @@ class ProgressManager:
    Thread-safe: can be called from background threads (e.g., via asyncio.to_thread).
    """
    
+    # Throttle settings to prevent overwhelming SSE clients
+    THROTTLE_INTERVAL_SECONDS = 0.5  # Minimum time between updates
+    THROTTLE_PROGRESS_DELTA = 1.0    # Minimum progress change (%) to force update
+    
    def __init__(self):
        self._progress: Dict[str, Dict] = {}
        self._listeners: Dict[str, list] = {}
        self._lock = threading.Lock()  # Thread-safe lock for progress dict
        self._main_loop: Optional[asyncio.AbstractEventLoop] = None
+        self._last_notify_time: Dict[str, float] = {}  # Last notification time per model
+        self._last_notify_progress: Dict[str, float] = {}  # Last notified progress per model
    
    def _set_main_loop(self, loop: asyncio.AbstractEventLoop):
        """Set the main event loop for thread-safe operations."""
@@ -43,11 +49,17 @@ class ProgressManager:
                    queue.put_nowait(progress_data.copy())
                except RuntimeError:
                    # Not in async context (running in background thread)
-                    # Use call_soon_threadsafe to safely put on queue
+                    # Use asyncio.run_coroutine_threadsafe for better PyInstaller compatibility
                    if self._main_loop and self._main_loop.is_running():
-                        self._main_loop.call_soon_threadsafe(
-                            lambda q=queue, d=progress_data.copy(): q.put_nowait(d) if not q.full() else None
-                        )
+                        async def put_data_async():
+                            try:
+                                queue.put_nowait(progress_data.copy())
+                            except asyncio.QueueFull:
+                                pass  # Queue full, drop update
+                        try:
+                            asyncio.run_coroutine_threadsafe(put_data_async(), self._main_loop)
+                        except Exception as e:
+                            logger.warning(f"Failed to schedule progress update: {e}")
                    else:
                        logger.debug(f"No main loop available for {model_name}, skipping notification")
            except asyncio.QueueFull:
@@ -65,8 +77,12 @@ class ProgressManager:
    ):
        """
        Update progress for a model download.
-        
+
        Thread-safe: can be called from background threads.
+        
+        Progress updates are throttled to prevent overwhelming SSE clients.
+        Updates are sent at most every THROTTLE_INTERVAL_SECONDS, or when
+        progress changes by at least THROTTLE_PROGRESS_DELTA percent.

        Args:
            model_name: Name of the model (e.g., "qwen-tts-1.7B", "whisper-base")
@@ -76,9 +92,17 @@ class ProgressManager:
            status: Status string (downloading, extracting, complete, error)
        """
        import logging
+        import time
        logger = logging.getLogger(__name__)

-        progress_pct = (current / total * 100) if total > 0 else 0
+        # Calculate progress percentage, clamped to 0-100 range
+        # This prevents crazy percentages from edge cases like:
+        # - current > total temporarily during aggregation
+        # - mixing file-count progress with byte-count progress
+        if total > 0:
+            progress_pct = min(100.0, max(0.0, (current / total * 100)))
+        else:
+            progress_pct = 0

        progress_data = {
            "model_name": model_name,
@@ -89,13 +113,36 @@ class ProgressManager:
            "status": status,
            "timestamp": datetime.now().isoformat(),
        }
-        
-        # Thread-safe update of progress dict
+
+        # Thread-safe update of progress dict (always update internal state)
        with self._lock:
            self._progress[model_name] = progress_data

+        # Check if we should notify listeners (throttling)
+        current_time = time.time()
+        last_time = self._last_notify_time.get(model_name, 0)
+        last_progress = self._last_notify_progress.get(model_name, -100)
+        
+        time_delta = current_time - last_time
+        progress_delta = abs(progress_pct - last_progress)
+        
+        # Always notify for complete/error status, or if throttle conditions are met
+        should_notify = (
+            status in ("complete", "error") or
+            time_delta >= self.THROTTLE_INTERVAL_SECONDS or
+            progress_delta >= self.THROTTLE_PROGRESS_DELTA
+        )
+        
+        if not should_notify:
+            return  # Skip this update (throttled)
+        
+        # Update throttle tracking
+        self._last_notify_time[model_name] = current_time
+        self._last_notify_progress[model_name] = progress_pct
+
        # Notify all listeners (thread-safe)
        listener_count = len(self._listeners.get(model_name, []))
+
        if listener_count > 0:
            logger.debug(f"Notifying {listener_count} listeners for {model_name}: {progress_pct:.1f}% ({filename})")
            self._notify_listeners_threadsafe(model_name, progress_data)
@@ -1,15 +1,11 @@
 # -*- mode: python ; coding: utf-8 -*-
 from PyInstaller.utils.hooks import collect_data_files
 from PyInstaller.utils.hooks import collect_submodules
-from PyInstaller.utils.hooks import copy_metadata

 datas = []
-hiddenimports = ['backend', 'backend.main', 'backend.config', 'backend.database', 'backend.models', 'backend.profiles', 'backend.history', 'backend.tts', 'backend.transcribe', 'backend.platform_detect', 'backend.backends', 'backend.backends.pytorch_backend', 'backend.utils.audio', 'backend.utils.cache', 'backend.utils.progress', 'backend.utils.hf_progress', 'backend.utils.validation', 'torch', 'transformers', 'fastapi', 'uvicorn', 'sqlalchemy', 'librosa', 'soundfile', 'qwen_tts', 'qwen_tts.inference', 'qwen_tts.inference.qwen3_tts_model', 'qwen_tts.inference.qwen3_tts_tokenizer', 'qwen_tts.core', 'qwen_tts.cli', 'pkg_resources.extern', 'backend.backends.mlx_backend', 'mlx', 'mlx.core', 'mlx.nn', 'mlx_audio', 'mlx_audio.tts', 'mlx_audio.asr']
-datas += collect_data_files('qwen_tts')
+hiddenimports = ['backend', 'backend.main', 'backend.config', 'backend.database', 'backend.models', 'backend.profiles', 'backend.history', 'backend.tts', 'backend.transcribe', 'backend.platform_detect', 'backend.providers', 'backend.providers.base', 'backend.providers.bundled', 'backend.providers.types', 'backend.utils.audio', 'backend.utils.cache', 'backend.utils.progress', 'backend.utils.hf_progress', 'backend.utils.validation', 'fastapi', 'uvicorn', 'sqlalchemy', 'librosa', 'soundfile', 'pkg_resources.extern', 'asyncio', 'asyncio.subprocess', 'concurrent.futures', 'concurrent.futures.thread', 'backend.backends', 'backend.backends.mlx_backend', 'mlx', 'mlx.core', 'mlx.nn', 'mlx_audio', 'mlx_audio.tts', 'mlx_audio.stt']
 datas += collect_data_files('mlx')
 datas += collect_data_files('mlx_audio')
-datas += copy_metadata('qwen-tts')
-hiddenimports += collect_submodules('qwen_tts')
 hiddenimports += collect_submodules('jaraco')
 hiddenimports += collect_submodules('mlx')
 hiddenimports += collect_submodules('mlx_audio')
@@ -13,12 +13,16 @@
    },
    "app": {
      "name": "@voicebox/app",
-      "version": "0.1.9",
+      "version": "0.1.13",
      "dependencies": {
        "@dnd-kit/core": "^6.3.1",
        "@dnd-kit/sortable": "^10.0.0",
        "@dnd-kit/utilities": "^3.2.2",
        "@hookform/resolvers": "^3.9.0",
+        "@hugeicons/core-free-icons": "^3.1.1",
+        "@hugeicons/react": "^1.1.4",
+        "@iconify-json/svg-spinners": "^1.2.4",
+        "@iconify/react": "^6.0.2",
        "@radix-ui/react-alert-dialog": "^1.1.1",
        "@radix-ui/react-avatar": "^1.1.0",
        "@radix-ui/react-dialog": "^1.1.1",
@@ -26,6 +30,7 @@
        "@radix-ui/react-label": "^2.1.0",
        "@radix-ui/react-popover": "^1.1.1",
        "@radix-ui/react-progress": "^1.1.0",
+        "@radix-ui/react-radio-group": "^1.2.0",
        "@radix-ui/react-scroll-area": "^1.1.0",
        "@radix-ui/react-select": "^2.1.1",
        "@radix-ui/react-separator": "^1.1.0",
@@ -45,7 +50,6 @@
        "clsx": "^2.1.1",
        "date-fns": "^3.6.0",
        "framer-motion": "^12.29.0",
-        "lucide-react": "^0.454.0",
        "motion": "^12.29.0",
        "react": "^18.3.0",
        "react-dom": "^18.3.0",
@@ -68,7 +72,7 @@
    },
    "landing": {
      "name": "@voicebox/landing",
-      "version": "0.1.9",
+      "version": "0.1.13",
      "dependencies": {
        "@radix-ui/react-separator": "^1.1.8",
        "@radix-ui/react-slot": "^1.2.4",
@@ -93,10 +97,14 @@
    },
    "tauri": {
      "name": "@voicebox/tauri",
-      "version": "0.1.9",
+      "version": "0.1.13",
      "dependencies": {
        "@tauri-apps/api": "^2.0.0",
+        "@tauri-apps/plugin-dialog": "^2.0.0",
+        "@tauri-apps/plugin-fs": "^2.0.0",
+        "@tauri-apps/plugin-process": "^2.0.0",
        "@tauri-apps/plugin-shell": "^2.0.0",
+        "@tauri-apps/plugin-updater": "^2.0.0",
      },
      "devDependencies": {
        "@tailwindcss/vite": "^4.1.18",
@@ -112,7 +120,7 @@
    },
    "web": {
      "name": "@voicebox/web",
-      "version": "0.1.9",
+      "version": "0.1.13",
      "dependencies": {
        "@tanstack/react-query": "^5.0.0",
        "react": "^18.3.0",
@@ -121,6 +129,7 @@
        "zustand": "^4.5.0",
      },
      "devDependencies": {
+        "@tailwindcss/vite": "^4.1.18",
        "@types/react": "^18.3.0",
        "@types/react-dom": "^18.3.0",
        "@typescript-eslint/eslint-plugin": "^7.0.0",
@@ -129,6 +138,7 @@
        "eslint": "^8.57.0",
        "eslint-plugin-react-hooks": "^4.6.0",
        "eslint-plugin-react-refresh": "^0.4.0",
+        "tailwindcss": "^4.1.0",
        "typescript": "^5.6.0",
        "vite": "^5.4.0",
      },
@@ -267,12 +277,22 @@

    "@hookform/resolvers": ["@hookform/[email protected]", "", { "peerDependencies": { "react-hook-form": "^7.0.0" } }, "sha512-79Dv+3mDF7i+2ajj7SkypSKHhl1cbln1OGavqrsF7p6mbUv11xpqpacPsGDCTRvCSjEEIez2ef1NveSVL3b0Ag=="],

+    "@hugeicons/core-free-icons": ["@hugeicons/[email protected]", "", {}, "sha512-UpS2lUQFi5sKyJSWwM6rO+BnPLvVz1gsyCpPHeZyVuZqi89YH8ksliza4cwaODqKOZyeXmG8juo1ty4QtQofkg=="],
+
+    "@hugeicons/react": ["@hugeicons/[email protected]", "", { "peerDependencies": { "react": ">=16.0.0" } }, "sha512-gsc3eZyd2fGqRUThW9+lfjxxsOkz6KNVmRXRgJjP32GL0OnnLJnl3hytKt47CBbiQj2xE2kCw+rnP3UQCThcKw=="],
+
    "@humanwhocodes/config-array": ["@humanwhocodes/[email protected]", "", { "dependencies": { "@humanwhocodes/object-schema": "^2.0.3", "debug": "^4.3.1", "minimatch": "^3.0.5" } }, "sha512-DZLEEqFWQFiyK6h5YIeynKx7JlvCYWL0cImfSRXZ9l4Sg2efkFGTuFf6vzXjK1cq6IYkU+Eg/JizXw+TD2vRNw=="],

    "@humanwhocodes/module-importer": ["@humanwhocodes/[email protected]", "", {}, "sha512-bxveV4V8v5Yb4ncFTT3rPSgZBOpCkjfK0y4oVVVJwIuDVBRMDXrPyXRL988i5ap9m9bnyEEjWfm5WkBmtffLfA=="],

    "@humanwhocodes/object-schema": ["@humanwhocodes/[email protected]", "", {}, "sha512-93zYdMES/c1D69yZiKDBj0V24vqNzB/koF26KPaagAfd3P/4gUlh3Dys5ogAK+Exi9QyzlD8x/08Zt7wIKcDcA=="],

+    "@iconify-json/svg-spinners": ["@iconify-json/[email protected]", "", { "dependencies": { "@iconify/types": "*" } }, "sha512-ayn0pogFPwJA1WFZpDnoq9/hjDxN+keeCMyThaX4d3gSJ3y0mdKUxIA/b1YXWGtY9wVtZmxwcvOIeEieG4+JNg=="],
+
+    "@iconify/react": ["@iconify/[email protected]", "", { "dependencies": { "@iconify/types": "^2.0.0" }, "peerDependencies": { "react": ">=16" } }, "sha512-SMmC2sactfpJD427WJEDN6PMyznTFMhByK9yLW0gOTtnjzzbsi/Ke/XqsumsavFPwNiXs8jSiYeZTmLCLwO+Fg=="],
+
+    "@iconify/types": ["@iconify/[email protected]", "", {}, "sha512-+wluvCrRhXrhyOmRDJ3q8mux9JkKy5SJ/v8ol2tu4FVjyYvtEzkc/3pK15ET6RKg4b4w4BmTk1+gsCUhf21Ykg=="],
+
    "@img/colour": ["@img/[email protected]", "", {}, "sha512-A5P/LfWGFSl6nsckYtjw9da+19jB8hkJ6ACTGcDfEJ0aE+l2n2El7dsVM7UVHZQ9s2lmYMWlrS21YLy2IR1LUw=="],

    "@img/sharp-darwin-arm64": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-darwin-arm64": "1.2.4" }, "os": "darwin", "cpu": "arm64" }, "sha512-imtQ3WMJXbMY4fxb/Ndp6HBTNVtWCUI0WdobyheGf5+ad6xX8VIDO8u2xE4qc/fr08CKG/7dDseFtn6M6g/r3w=="],
@@ -403,6 +423,8 @@

    "@radix-ui/react-progress": ["@radix-ui/[email protected]", "", { "dependencies": { "@radix-ui/react-context": "1.1.3", "@radix-ui/react-primitive": "2.1.4" }, "peerDependencies": { "@types/react": "*", "@types/react-dom": "*", "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc", "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react", "@types/react-dom"] }, "sha512-+gISHcSPUJ7ktBy9RnTqbdKW78bcGke3t6taawyZ71pio1JewwGSJizycs7rLhGTvMJYCQB1DBK4KQsxs7U8dA=="],

+    "@radix-ui/react-radio-group": ["@radix-ui/[email protected]", "", { "dependencies": { "@radix-ui/primitive": "1.1.3", "@radix-ui/react-compose-refs": "1.1.2", "@radix-ui/react-context": "1.1.2", "@radix-ui/react-direction": "1.1.1", "@radix-ui/react-presence": "1.1.5", "@radix-ui/react-primitive": "2.1.3", "@radix-ui/react-roving-focus": "1.1.11", "@radix-ui/react-use-controllable-state": "1.2.2", "@radix-ui/react-use-previous": "1.1.1", "@radix-ui/react-use-size": "1.1.1" }, "peerDependencies": { "@types/react": "*", "@types/react-dom": "*", "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc", "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react", "@types/react-dom"] }, "sha512-VBKYIYImA5zsxACdisNQ3BjCBfmbGH3kQlnFVqlWU4tXwjy7cGX8ta80BcrO+WJXIn5iBylEH3K6ZTlee//lgQ=="],
+
    "@radix-ui/react-roving-focus": ["@radix-ui/[email protected]", "", { "dependencies": { "@radix-ui/primitive": "1.1.3", "@radix-ui/react-collection": "1.1.7", "@radix-ui/react-compose-refs": "1.1.2", "@radix-ui/react-context": "1.1.2", "@radix-ui/react-direction": "1.1.1", "@radix-ui/react-id": "1.1.1", "@radix-ui/react-primitive": "2.1.3", "@radix-ui/react-use-callback-ref": "1.1.1", "@radix-ui/react-use-controllable-state": "1.2.2" }, "peerDependencies": { "@types/react": "*", "@types/react-dom": "*", "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc", "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react", "@types/react-dom"] }, "sha512-7A6S9jSgm/S+7MdtNDSb+IU859vQqJ/QAtcYQcfFC6W8RS4IxIZDldLR0xqCFZ6DCyrQLjLPsxtTNch5jVA4lA=="],

    "@radix-ui/react-scroll-area": ["@radix-ui/[email protected]", "", { "dependencies": { "@radix-ui/number": "1.1.1", "@radix-ui/primitive": "1.1.3", "@radix-ui/react-compose-refs": "1.1.2", "@radix-ui/react-context": "1.1.2", "@radix-ui/react-direction": "1.1.1", "@radix-ui/react-presence": "1.1.5", "@radix-ui/react-primitive": "2.1.3", "@radix-ui/react-use-callback-ref": "1.1.1", "@radix-ui/react-use-layout-effect": "1.1.1" }, "peerDependencies": { "@types/react": "*", "@types/react-dom": "*", "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc", "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react", "@types/react-dom"] }, "sha512-tAXIa1g3sM5CGpVT0uIbUx/U3Gs5N8T52IICuCtObaos1S8fzsrPXG5WObkQN3S6NVl6wKgPhAIiBGbWnvc97A=="],
@@ -877,7 +899,7 @@

    "lru-cache": ["[email protected]", "", { "dependencies": { "yallist": "^3.0.2" } }, "sha512-KpNARQA3Iwv+jTA0utUVVbrh+Jlrr1Fv0e56GGzAFOXN7dk/FviaDW8LHmK52DlcH4WP2n6gI8vN1aesBFgo9w=="],

-    "lucide-react": ["lucide-react@0.454.0", "", { "peerDependencies": { "react": "^16.5.1 || ^17.0.0 || ^18.0.0 || ^19.0.0-rc" } }, "sha512-hw7zMDwykCLnEzgncEEjHeA6+45aeEzRYuKHuyRSOPkhko+J3ySGjGIzu+mmMfDFG1vazHepMaYFYHbTFAZAAQ=="],
+    "lucide-react": ["lucide-react@0.316.0", "", { "peerDependencies": { "react": "^16.5.1 || ^17.0.0 || ^18.0.0" } }, "sha512-dTmYX1H4IXsRfVcj/KUxworV6814ApTl7iXaS21AimK2RUEl4j4AfOmqD3VR8phe5V91m4vEJ8tCK4uT1jE5nA=="],

    "magic-string": ["[email protected]", "", { "dependencies": { "@jridgewell/sourcemap-codec": "^1.5.5" } }, "sha512-vd2F4YUyEXKGcLHoq+TEyCjxueSeHnFxyyjNp80yg0XV4vUhnDer/lvvlqM/arB5bXQN5K2/3oinyCRyx8T2CQ=="],

@@ -1133,8 +1155,6 @@

    "@typescript-eslint/typescript-estree/semver": ["[email protected]", "", { "bin": { "semver": "bin/semver.js" } }, "sha512-SdsKMrI9TdgjdweUSR9MweHA4EJ8YxHn8DFaDisvhVlUOe4BF1tLD7GAj0lIqWVl+dPb/rExr0Btby5loQm20Q=="],

-    "@voicebox/landing/lucide-react": ["[email protected]", "", { "peerDependencies": { "react": "^16.5.1 || ^17.0.0 || ^18.0.0" } }, "sha512-dTmYX1H4IXsRfVcj/KUxworV6814ApTl7iXaS21AimK2RUEl4j4AfOmqD3VR8phe5V91m4vEJ8tCK4uT1jE5nA=="],
-
    "@voicebox/landing/tailwind-merge": ["[email protected]", "", {}, "sha512-uSaO4gnW+b3Y2aWoWfFpX62vn2sR3skfhbjsEnaBI81WD1wBLlHZe5sWf0AqjksNdYTbGBEd0UasQMT3SNV15g=="],

    "@voicebox/landing/tailwindcss": ["[email protected]", "", { "dependencies": { "@alloc/quick-lru": "^5.2.0", "arg": "^5.0.2", "chokidar": "^3.6.0", "didyoumean": "^1.2.2", "dlv": "^1.1.3", "fast-glob": "^3.3.2", "glob-parent": "^6.0.2", "is-glob": "^4.0.3", "jiti": "^1.21.7", "lilconfig": "^3.1.3", "micromatch": "^4.0.8", "normalize-path": "^3.0.0", "object-hash": "^3.0.0", "picocolors": "^1.1.1", "postcss": "^8.4.47", "postcss-import": "^15.1.0", "postcss-js": "^4.0.1", "postcss-load-config": "^4.0.2 || ^5.0 || ^6.0", "postcss-nested": "^6.2.0", "postcss-selector-parser": "^6.1.2", "resolve": "^1.22.8", "sucrase": "^3.35.0" }, "bin": { "tailwind": "lib/cli.js", "tailwindcss": "lib/cli.js" } }, "sha512-3ofp+LL8E+pK/JuPLPggVAIaEuhvIz4qNcf3nA1Xn2o/7fb7s/TYpHhwGDv1ZU3PkBluUVaF8PyCHcm48cKLWQ=="],
@@ -1,7 +0,0 @@
-# User data directory
-# This directory contains:
-# - profiles/ - Voice profile audio files
-# - generations/ - Generated audio files
-# - projects/ - Audio studio project files
-# - voicebox.db - SQLite database
-# - cache/ - Voice prompt cache files
@@ -1 +0,0 @@
-# Voice prompt cache files
@@ -0,0 +1,26 @@
+version: '3.8'
+
+services:
+  voicebox:
+    image: ghcr.io/jamiepine/voicebox:latest
+    container_name: voicebox
+    restart: unless-stopped
+    ports:
+      - "8000:8000"
+    volumes:
+      - voicebox-data:/app/data
+      - huggingface-cache:/root/.cache/huggingface
+    environment:
+      - LOG_LEVEL=info
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 40s
+
+volumes:
+  voicebox-data:
+    driver: local
+  huggingface-cache:
+    driver: local
@@ -0,0 +1,34 @@
+version: '3.8'
+
+services:
+  voicebox:
+    image: ghcr.io/jamiepine/voicebox:latest-cuda
+    container_name: voicebox
+    restart: unless-stopped
+    ports:
+      - "8000:8000"
+    volumes:
+      - voicebox-data:/app/data
+      - huggingface-cache:/root/.cache/huggingface
+    environment:
+      - GPU_MEMORY_FRACTION=0.8
+      - LOG_LEVEL=info
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+    healthcheck:
+      test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 40s
+
+volumes:
+  voicebox-data:
+    driver: local
+  huggingface-cache:
+    driver: local
@@ -40,7 +40,7 @@
    {
      "group": "Getting Started",
      "icon": "rocket",
-      "pages": ["overview/introduction", "overview/installation", "overview/quick-start"]
+      "pages": ["overview/introduction", "overview/installation", "overview/docker", "overview/quick-start"]
    },
    {
      "group": "Features",
@@ -0,0 +1,403 @@
+---
+title: "Docker Deployment"
+description: "Run Voicebox in Docker with the web UI for server deployments"
+---
+
+## Overview
+
+Voicebox is available as Docker images that include both the backend API and web UI. Run the full Voicebox experience in a container with a single command.
+
+**What's included:**
+- FastAPI backend with all TTS/Whisper capabilities
+- Complete web UI (same React app as the desktop version)
+- Provider download system (downloads PyTorch on first use)
+- Multi-architecture support (amd64, arm64)
+
+## Quick Start
+
+<Tabs>
+  <Tab title="NVIDIA GPU">
+    ```bash
+    docker run --gpus all -p 8000:8000 \
+      -v voicebox-data:/app/data \
+      ghcr.io/jamiepine/voicebox:latest-cuda
+    ```
+
+    Then open http://localhost:8000 to access the web UI.
+  </Tab>
+
+  <Tab title="CPU Only">
+    ```bash
+    docker run -p 8000:8000 \
+      -v voicebox-data:/app/data \
+      ghcr.io/jamiepine/voicebox:latest
+    ```
+
+    Then open http://localhost:8000 to access the web UI.
+  </Tab>
+
+  <Tab title="Docker Compose">
+    Clone the repo or download `docker-compose.yml`:
+
+    ```bash
+    # CUDA variant (default)
+    docker compose up -d
+
+    # CPU-only variant
+    docker compose -f docker-compose-cpu.yml up -d
+    ```
+
+    Then open http://localhost:8000 to access the web UI.
+  </Tab>
+</Tabs>
+
+<Note>
+  On first launch, you'll be prompted to download a TTS provider (PyTorch CPU ~300MB or PyTorch CUDA ~2.4GB). This happens once and is cached in the `huggingface-cache` volume.
+</Note>
+
+## Available Images
+
+Images are automatically built and published to GitHub Container Registry on each release.
+
+| Image | Description | Platforms |
+|-------|-------------|-----------|
+| `ghcr.io/jamiepine/voicebox:latest` | Latest CPU-only release | linux/amd64, linux/arm64 |
+| `ghcr.io/jamiepine/voicebox:0.1.13` | Specific version (CPU) | linux/amd64, linux/arm64 |
+| `ghcr.io/jamiepine/voicebox:latest-cuda` | Latest with NVIDIA GPU support | linux/amd64 |
+| `ghcr.io/jamiepine/voicebox:0.1.13-cuda` | Specific version (CUDA) | linux/amd64 |
+
+<Tip>
+  Pin to a specific version in production to avoid unexpected updates:
+  ```yaml
+  image: ghcr.io/jamiepine/voicebox:0.1.13-cuda
+  ```
+</Tip>
+
+## Docker Compose Examples
+
+### GPU Deployment (Recommended)
+
+```yaml
+version: '3.8'
+
+services:
+  voicebox:
+    image: ghcr.io/jamiepine/voicebox:latest-cuda
+    container_name: voicebox
+    restart: unless-stopped
+    ports:
+      - "8000:8000"
+    volumes:
+      - voicebox-data:/app/data
+      - huggingface-cache:/root/.cache/huggingface
+    environment:
+      - GPU_MEMORY_FRACTION=0.8
+      - LOG_LEVEL=info
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              count: 1
+              capabilities: [gpu]
+
+volumes:
+  voicebox-data:
+  huggingface-cache:
+```
+
+### CPU Deployment
+
+```yaml
+version: '3.8'
+
+services:
+  voicebox:
+    image: ghcr.io/jamiepine/voicebox:latest
+    container_name: voicebox
+    restart: unless-stopped
+    ports:
+      - "8000:8000"
+    volumes:
+      - voicebox-data:/app/data
+      - huggingface-cache:/root/.cache/huggingface
+    environment:
+      - LOG_LEVEL=info
+
+volumes:
+  voicebox-data:
+  huggingface-cache:
+```
+
+## Volume Mounts
+
+<CardGroup cols={2}>
+  <Card title="voicebox-data" icon="database">
+    Stores voice profiles, generated audio, and database
+  </Card>
+  <Card title="huggingface-cache" icon="download">
+    Caches downloaded TTS/Whisper models (saves re-downloading)
+  </Card>
+</CardGroup>
+
+<Warning>
+  Always mount `/app/data` to preserve your voice profiles and generations across container restarts.
+</Warning>
+
+## Environment Variables
+
+Configure Voicebox behavior with environment variables:
+
+| Variable | Default | Description |
+|----------|---------|-------------|
+| `GPU_MEMORY_FRACTION` | `0.9` | Fraction of GPU memory to use (0.0-1.0) |
+| `LOG_LEVEL` | `info` | Logging level: `debug`, `info`, `warning`, `error` |
+| `DATA_DIR` | `/app/data` | Directory for profiles and generations |
+
+Example:
+```bash
+docker run -e GPU_MEMORY_FRACTION=0.8 \
+           -e LOG_LEVEL=debug \
+           -p 8000:8000 \
+           ghcr.io/jamiepine/voicebox:latest-cuda
+```
+
+## Cloud Deployment
+
+### AWS EC2
+
+<Steps>
+  <Step title="Launch GPU Instance">
+    Use g4dn.xlarge or p3.2xlarge with NVIDIA GPU
+  </Step>
+
+  <Step title="Install Docker & NVIDIA Container Toolkit">
+    ```bash
+    # Install Docker
+    curl -fsSL https://get.docker.com -o get-docker.sh
+    sudo sh get-docker.sh
+
+    # Install NVIDIA Container Toolkit
+    distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
+    curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
+    curl -s -L https://nvidia.github.io/libnvidia-container/$distribution/libnvidia-container.list | \
+      sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
+      sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
+    sudo apt-get update
+    sudo apt-get install -y nvidia-container-toolkit
+    sudo systemctl restart docker
+    ```
+  </Step>
+
+  <Step title="Deploy">
+    ```bash
+    docker run -d --gpus all -p 8000:8000 \
+      -v voicebox-data:/app/data \
+      --restart unless-stopped \
+      ghcr.io/jamiepine/voicebox:latest-cuda
+    ```
+  </Step>
+</Steps>
+
+### DigitalOcean
+
+<Steps>
+  <Step title="Create GPU Droplet">
+    ```bash
+    doctl compute droplet create voicebox \
+      --size gpu-h100x1-80gb \
+      --image ubuntu-22-04-x64 \
+      --region nyc3
+    ```
+  </Step>
+
+  <Step title="SSH and Deploy">
+    ```bash
+    ssh root@<droplet-ip>
+    curl -fsSL https://get.docker.com | sh
+    docker run -d --gpus all -p 80:8000 \
+      ghcr.io/jamiepine/voicebox:latest-cuda
+    ```
+  </Step>
+</Steps>
+
+### Fly.io
+
+Create `fly.toml`:
+
+```toml
+app = "voicebox"
+
+[build]
+  image = "ghcr.io/jamiepine/voicebox:latest"
+
+[[services]]
+  http_checks = []
+  internal_port = 8000
+  protocol = "tcp"
+
+  [[services.ports]]
+    port = 80
+    handlers = ["http"]
+
+  [[services.ports]]
+    port = 443
+    handlers = ["tls", "http"]
+
+[mounts]
+  source = "voicebox_data"
+  destination = "/app/data"
+```
+
+Deploy:
+```bash
+fly launch
+fly deploy
+```
+
+## Updates
+
+Docker images are automatically built and published on each GitHub release.
+
+<Tabs>
+  <Tab title="Latest Tag">
+    Always get the newest version:
+
+    ```bash
+    docker pull ghcr.io/jamiepine/voicebox:latest
+    docker compose up -d
+    ```
+  </Tab>
+
+  <Tab title="Pinned Version">
+    Update to a specific version:
+
+    ```yaml
+    services:
+      voicebox:
+        image: ghcr.io/jamiepine/voicebox:0.1.13-cuda
+    ```
+
+    ```bash
+    docker compose pull
+    docker compose up -d
+    ```
+  </Tab>
+
+  <Tab title="Automatic Updates">
+    Use Watchtower for automatic updates:
+
+    ```yaml
+    services:
+      voicebox:
+        image: ghcr.io/jamiepine/voicebox:latest-cuda
+        # ... other config ...
+
+      watchtower:
+        image: containrrr/watchtower
+        volumes:
+          - /var/run/docker.sock:/var/run/docker.sock
+        command: --interval 3600 # Check hourly
+    ```
+  </Tab>
+</Tabs>
+
+## GPU Requirements
+
+### NVIDIA GPU
+
+Requires:
+- **Docker version:** 19.03+
+- **NVIDIA Driver:** 450.80.02+
+- **NVIDIA Container Toolkit:** Installed and configured
+
+Verify GPU access:
+```bash
+docker run --rm --gpus all nvidia/cuda:12.1.1-base-ubuntu22.04 nvidia-smi
+```
+
+If this works, Voicebox will detect and use your GPU automatically.
+
+### AMD GPU (ROCm)
+
+AMD GPU support via ROCm is not currently available in pre-built images. If you need ROCm support, build a custom image using the ROCm base.
+
+## Troubleshooting
+
+### GPU Not Detected
+
+<Accordion title="Check NVIDIA Docker">
+  ```bash
+  # Verify NVIDIA Container Toolkit is installed
+  docker run --rm --gpus all nvidia/cuda:12.1.1-base-ubuntu22.04 nvidia-smi
+  ```
+
+  If this fails, reinstall NVIDIA Container Toolkit.
+</Accordion>
+
+<Accordion title="Insufficient GPU Memory">
+  Reduce GPU memory usage:
+
+  ```bash
+  docker run -e GPU_MEMORY_FRACTION=0.5 \
+    --gpus all -p 8000:8000 \
+    ghcr.io/jamiepine/voicebox:latest-cuda
+  ```
+
+  Or use CPU-only mode:
+  ```bash
+  docker run -p 8000:8000 \
+    ghcr.io/jamiepine/voicebox:latest
+  ```
+</Accordion>
+
+<Accordion title="Port Already in Use">
+  Change the host port:
+
+  ```bash
+  docker run -p 8080:8000 ghcr.io/jamiepine/voicebox:latest
+  ```
+
+  Then open http://localhost:8080
+</Accordion>
+
+<Accordion title="Permission Errors">
+  Run with specific user:
+
+  ```bash
+  docker run --user $(id -u):$(id -g) \
+    -v $(pwd)/data:/app/data \
+    ghcr.io/jamiepine/voicebox:latest
+  ```
+</Accordion>
+
+## Building From Source
+
+If you need to customize the Docker image:
+
+```bash
+# Clone the repo
+git clone https://github.com/jamiepine/voicebox.git
+cd voicebox
+
+# Build web UI
+bun install
+cd web && bun run build && cd ..
+
+# Build Docker image
+docker build -t voicebox:custom .
+
+# Or CUDA variant
+docker build -f Dockerfile.cuda -t voicebox:custom-cuda .
+```
+
+## Next Steps
+
+<CardGroup cols={2}>
+  <Card title="API Reference" icon="code" href="/api/overview">
+    Integrate Voicebox into your applications
+  </Card>
+  <Card title="Remote Mode" icon="server" href="/overview/remote-mode">
+    Connect desktop app to Docker backend
+  </Card>
+</CardGroup>
@@ -5,15 +5,21 @@ description: "Download and install Voicebox on macOS, Windows, or Linux"

 ## Download

-Voicebox is available for macOS and Windows, with Linux builds coming soon.
+Voicebox is available for macOS, Windows, and Linux.

-<CardGroup cols={2}>
+<CardGroup cols={4}>
  <Card title="macOS" icon="apple">
    Download for Apple Silicon or Intel Macs
  </Card>
  <Card title="Windows" icon="windows">
    Download MSI installer or Setup executable
  </Card>
+  <Card title="Linux" icon="linux">
+    Download AppImage or Deb package
+  </Card>
+  <Card title="Docker" icon="docker" href="/overview/docker">
+    Run with web UI in a container
+  </Card>
 </CardGroup>

 ### macOS
@@ -60,8 +66,33 @@ Voicebox is available for macOS and Windows, with Linux builds coming soon.

 ### Linux

+<Tabs>
+  <Tab title="AppImage">
+    Download: [voicebox_x86_64.AppImage](https://github.com/jamiepine/voicebox/releases/latest)
+
+    ```bash
+    # Make executable
+    chmod +x voicebox_x86_64.AppImage
+
+    # Run
+    ./voicebox_x86_64.AppImage
+    ```
+  </Tab>
+  <Tab title="Debian/Ubuntu">
+    Download: [voicebox_amd64.deb](https://github.com/jamiepine/voicebox/releases/latest)
+
+    ```bash
+    # Install
+    sudo dpkg -i voicebox_amd64.deb
+
+    # Run
+    voicebox
+    ```
+  </Tab>
+</Tabs>
+
 <Note>
-  Linux builds are coming soon. Currently blocked by GitHub runner disk space limitations.
+  For headless server deployments, use [Docker](/overview/docker) instead of the desktop app.
 </Note>

 ## First Launch
@@ -5,7 +5,7 @@ description: "Welcome to Voicebox - the open-source voice synthesis studio"

 ## What is Voicebox?

-Voicebox is a **local-first voice cloning studio** with DAW-like features for professional voice synthesis. Think of it as the **Ollama for voice** — download models, clone voices, and generate speech entirely on your machine.
+Voicebox is a **local-first voice cloning studio** with DAW-like features for professional voice synthesis. Think of it as a **local, free and open-source alternative to ElevenLabs** — download models, clone voices, and generate speech entirely on your machine.

 <Frame>
  <img src="/images/app-screenshot-1.webp" alt="Voicebox App Screenshot" />
@@ -1,24 +1,31 @@
 # Docker Deployment Guide

-**Status:** In Development for v0.2.0
-**Requested By:** Reddit community ([thread](https://reddit.com/r/LocalLLaMA/...))
+**Status:** Implemented
+**Images:** `ghcr.io/jamiepine/voicebox`

 ## Overview

-Docker support makes Voicebox easier to deploy, especially for:
+Voicebox is available as Docker images with the full web UI included. Images are automatically built and published to GitHub Container Registry on each release.

- **Consistent Environments**: Same setup across dev/staging/prod
- **GPU Passthrough**: Easy NVIDIA/AMD GPU access
+**What's included:**
+- FastAPI backend with all TTS/Whisper capabilities
+- Complete web UI (same React app as the Tauri desktop version)
+- Provider download system (downloads TTS providers on first use, just like desktop)
+- Multi-architecture support (amd64, arm64 for CPU variant)
+
+Docker support is ideal for:
 - **Server Deployments**: Run on headless Linux servers
- **Multi-User Setups**: Isolate instances per user/team
+- **GPU Passthrough**: Easy NVIDIA GPU access
+- **Consistent Environments**: Same setup across dev/staging/prod
 - **Cloud Platforms**: Deploy to AWS, GCP, Azure, DigitalOcean
+- **Multi-User Setups**: Isolate instances per user/team

 ## Quick Start

 ### Using Pre-Built Images (Recommended)

 ```bash
-# CPU-only version
+# CPU-only version (supports amd64 and arm64)
 docker run -p 8000:8000 -v voicebox-data:/app/data \
  ghcr.io/jamiepine/voicebox:latest

@@ -26,184 +33,80 @@ docker run -p 8000:8000 -v voicebox-data:/app/data \
 docker run --gpus all -p 8000:8000 -v voicebox-data:/app/data \
  ghcr.io/jamiepine/voicebox:latest-cuda

-# AMD GPU version (experimental)
-docker run --device=/dev/kfd --device=/dev/dri -p 8000:8000 \
-  -v voicebox-data:/app/data \
-  ghcr.io/jamiepine/voicebox:latest-rocm
+# Specific version (pinned for stability)
+docker run -p 8000:8000 -v voicebox-data:/app/data \
+  ghcr.io/jamiepine/voicebox:0.1.13
 ```

 Then open: `http://localhost:8000`

+The web UI will load automatically. On first use, you'll be prompted to download a TTS provider (PyTorch CPU ~300MB or PyTorch CUDA ~2.4GB).
+
 ### Using Docker Compose (Easiest)

-Create `docker-compose.yml`:
+Use the provided `docker-compose.yml` (CUDA) or `docker-compose.cpu.yml` in the repository root:

-```yaml
-version: '3.8'
+```bash
+# CUDA (default)
+docker compose up -d

-services:
-  voicebox:
-    image: ghcr.io/jamiepine/voicebox:latest-cuda
-    ports:
-      - "8000:8000"
-    volumes:
-      - voicebox-data:/app/data
-      - huggingface-cache:/root/.cache/huggingface
-    environment:
-      - GPU_MEMORY_FRACTION=0.8  # Use 80% of GPU memory
-      - TTS_MODE=local
-      - WHISPER_MODE=local
-    deploy:
-      resources:
-        reservations:
-          devices:
-            - driver: nvidia
-              count: 1
-              capabilities: [gpu]
-
-volumes:
-  voicebox-data:
-  huggingface-cache:
+# Or CPU-only
+docker compose -f docker-compose.cpu.yml up -d
 ```

-Run:
-```bash
-docker compose up -d
+To pin to a specific version, edit the compose file:
+```yaml
+services:
+  voicebox:
+    image: ghcr.io/jamiepine/voicebox:0.1.13-cuda  # Pinned version
 ```

 ## Building From Source

-### Basic Dockerfile
-
-```dockerfile
-# Dockerfile
-FROM python:3.11-slim
-
-WORKDIR /app
-
-# Install system dependencies
-RUN apt-get update && apt-get install -y \
-    git \
-    build-essential \
-    ffmpeg \
-    && rm -rf /var/lib/apt/lists/*
-
-# Copy application
-COPY backend/ /app/backend/
-COPY requirements.txt /app/
-
-# Install Python dependencies
-RUN pip install --no-cache-dir -r requirements.txt
-RUN pip install --no-cache-dir git+https://github.com/QwenLM/Qwen3-TTS.git
-
-# Create data directory
-RUN mkdir -p /app/data
-
-# Expose port
-EXPOSE 8000
-
-# Run server
-CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]
-```
+See `Dockerfile` and `Dockerfile.cuda` in the repository root.

 Build and run:
 ```bash
+# Build web UI first
+bun install
+cd web && bun run build && cd ..
+
+# Build CPU image
 docker build -t voicebox .
-docker run -p 8000:8000 -v $(pwd)/data:/app/data voicebox
+docker run -p 8000:8000 -v voicebox-data:/app/data voicebox
+
+# Or build CUDA image
+docker build -f Dockerfile.cuda -t voicebox:cuda .
+docker run --gpus all -p 8000:8000 -v voicebox-data:/app/data voicebox:cuda
 ```

-### Multi-Stage Build (Optimized)
+### Architecture

-Smaller image size by separating build and runtime:
+The Docker images include:
+- **Backend**: FastAPI server with TTS/Whisper endpoints
+- **Web UI**: Pre-built React app served as static files from the backend
+- **Provider System**: Downloads PyTorch CPU/CUDA providers on first use (same UX as desktop app)

-```dockerfile
-# Dockerfile.optimized
-# Stage 1: Build dependencies
-FROM python:3.11-slim AS builder
-
-WORKDIR /build
-
-RUN apt-get update && apt-get install -y \
-    git build-essential && \
-    rm -rf /var/lib/apt/lists/*
-
-COPY backend/requirements.txt .
-RUN pip install --no-cache-dir --target=/build/packages \
-    -r requirements.txt
-
-RUN pip install --no-cache-dir --target=/build/packages \
-    git+https://github.com/QwenLM/Qwen3-TTS.git
-
-# Stage 2: Runtime
-FROM python:3.11-slim
-
-WORKDIR /app
-
-# Install only runtime dependencies
-RUN apt-get update && apt-get install -y \
-    ffmpeg \
-    && rm -rf /var/lib/apt/lists/*
-
-# Copy installed packages from builder
-COPY --from=builder /build/packages /usr/local/lib/python3.11/site-packages/
-
-# Copy application code
-COPY backend/ /app/backend/
-
-# Create data directory
-RUN mkdir -p /app/data
-
-EXPOSE 8000
-
-CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]
-```
-
-Build:
-```bash
-docker build -f Dockerfile.optimized -t voicebox:slim .
-```
+Images are automatically built on release and tagged with both version number and `latest`.

 ## GPU Support

 ### NVIDIA GPUs (CUDA)

-**Dockerfile:**
-```dockerfile
-FROM nvidia/cuda:12.1.0-runtime-ubuntu22.04
-
-# Install Python
-RUN apt-get update && apt-get install -y \
-    python3.11 python3-pip git ffmpeg && \
-    rm -rf /var/lib/apt/lists/*
-
-WORKDIR /app
-
-# Install PyTorch with CUDA support
-COPY backend/requirements.txt .
-RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121
-
-# Install other dependencies
-RUN pip3 install -r requirements.txt
-RUN pip3 install git+https://github.com/QwenLM/Qwen3-TTS.git
-
-COPY backend/ /app/backend/
-
-EXPOSE 8000
-CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]
-```
+The CUDA image includes PyTorch with CUDA 12.1 support:

 **Run with GPU:**
 ```bash
 docker run --gpus all -p 8000:8000 \
  -v voicebox-data:/app/data \
-  voicebox:cuda
+  ghcr.io/jamiepine/voicebox:latest-cuda
 ```

 **Docker Compose with GPU:**
 ```yaml
 services:
  voicebox:
-    image: voicebox:cuda
+    image: ghcr.io/jamiepine/voicebox:latest-cuda
    deploy:
      resources:
        reservations:
@@ -213,47 +116,9 @@ services:
              capabilities: [gpu]
 ```

-### AMD GPUs (ROCm) - Experimental
+### AMD GPUs (ROCm)

-**Dockerfile:**
-```dockerfile
-FROM rocm/dev-ubuntu-22.04:6.0
-
-# Install Python
-RUN apt-get update && apt-get install -y \
-    python3.11 python3-pip git ffmpeg && \
-    rm -rf /var/lib/apt/lists/*
-
-WORKDIR /app
-
-# Install PyTorch with ROCm support
-COPY backend/requirements.txt .
-RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.0
-
-# Install other dependencies
-RUN pip3 install -r requirements.txt
-RUN pip3 install git+https://github.com/QwenLM/Qwen3-TTS.git
-
-# Set ROCm environment variables
-ENV HSA_OVERRIDE_GFX_VERSION=10.3.0
-ENV ROCM_PATH=/opt/rocm
-
-COPY backend/ /app/backend/
-
-EXPOSE 8000
-CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]
-```
-
-**Run with AMD GPU:**
-```bash
-docker run --device=/dev/kfd --device=/dev/dri \
-  --group-add video --ipc=host --cap-add=SYS_PTRACE \
-  --security-opt seccomp=unconfined \
-  -p 8000:8000 -v voicebox-data:/app/data \
-  voicebox:rocm
-```
-
-**Note:** ROCm support varies by GPU model. Works best on Linux. See [AMD ROCm docs](https://rocm.docs.amd.com) for compatibility.
+ROCm support is not currently available in pre-built images. If you need ROCm, build a custom image using the ROCm base and PyTorch ROCm builds.

 ## Volume Mounts

@@ -734,13 +599,27 @@ docker logs -f voicebox
 docker compose logs -f voicebox
 ```

-## Next Steps
+## Updates

- [ ] Publish official images to GitHub Container Registry
- [ ] Add Kubernetes Helm charts
- [ ] Create Docker Desktop extension
- [ ] Add automated vulnerability scanning
- [ ] Support ARM64 builds for Raspberry Pi / Apple Silicon
+Docker images are automatically built and published on each GitHub release. To update:
+
+```bash
+# Pull latest
+docker pull ghcr.io/jamiepine/voicebox:latest
+docker compose up -d
+
+# Or pin to a specific version
+docker pull ghcr.io/jamiepine/voicebox:0.1.13
+```
+
+For automatic updates, use [Watchtower](https://containrrr.dev/watchtower/).
+
+## Future Enhancements
+
+- Kubernetes Helm charts
+- Docker Desktop extension
+- Automated vulnerability scanning
+- ROCm image variant

 ## Contributing

--- a/Show More
+++ b/Show More